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Digital Health
Number of Followers: 11  Open Access journalISSN (Print) 2055-2076 - ISSN (Online) 2055-2076 Published by Sage Publications  [1176 journals]
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- Fast bilateral weighted least square for the detail enhancement of
COVID-19 chest X-rays
Authors: Wenyan Bian, Yang Yang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundX-ray is an effective measure in the diagnosis of coronavirus disease 2019. However, it suffers from low visibility and poor details. A plausible solution is to decompose the captured images and enhance the details. The bilateral weighted least square model can be an effective tool for this task. However, it is highly computationally expensive.MethodIn this article, we propose an efficient algorithm for the bilateral weighted least square model. We approximate the bilateral weight with the bilateral grid and then incorporate it into the optimization model. This significantly reduces the number of variables in the linear system. Therefore, the model can be efficiently solved. We employ the proposed algorithm to decompose the input X-rays into base and detail layers. The detail layers are then boosted and added back to the input to derive the detail-enhanced results.ResultsThe subjective results indicate that our method achieves higher contrast than the best-performing method ([math], [math], [math]). Furthermore, our method is highly efficient. It takes 0.92 s to process a 720P color image on an Intel i7-6700 CPU. The objective results derive from the chi-square test indicate that subjects hold more positive attitudes toward our detail-enhanced images than the original X-ray images ([math], [math], [math]).ConclusionWe have conducted extensive experiments to evaluate the proposed image detail enhancement method. It can be concluded that (1) our method could significantly improve the visibility of the X-ray images. (2) our method is fast and effective, thus facilitating real applications.
Citation: DIGITAL HEALTH
PubDate: 2023-09-12T06:48:20Z
DOI: 10.1177/20552076231200981
Issue No: Vol. 9 (2023)
- A web-based care assistant for caregivers of the elderly: Development and
pilot study
Authors: Hwawoo Jeon, Yong Suk Choi, Yoonseob Lim
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe aging population in Korea has driven a surge in demand for elderly care services, leading to significant growth in elderly welfare facilities, particularly Adult Daycare Centers (ADCs). However, despite advancements in care facilities, caregivers continue to face challenges in providing suitable elderly care due to difficulties arising from gaps in the latest information on the elderly and their coping abilities.ObjectiveThe objective of this study is to develop and evaluate the effectiveness of the elderly care assistant system, which facilitates the sharing of information and knowledge necessary for elderly care among caregivers.MethodsThe ECA system was designed to support knowledge sharing through a knowledge management system based on an ontological knowledge model, with a web-based user interface for improved accessibility. A field trial was conducted at ADC in Seoul from August 17 to September 21, with eight caregivers participating. A mixed-methods approach, involving both surveys and interviews, was employed to gauge the ECA system's effectiveness.ResultsThe study found that the use of the ECA was beneficial in promoting knowledge sharing among caregivers. Additionally, caregivers noted the potential benefits of using the ECA in conjunction with family caregivers, who can offer additional information and perspectives on elderly care.ConclusionsThis study presents preliminary evidence of the potential benefits of a care knowledge sharing system among various caregivers in elderly care. Although the elderly care assistant effectively promotes knowledge sharing, more research is needed to fully understand its impact on elderly care outcomes.
Citation: DIGITAL HEALTH
PubDate: 2023-09-11T08:54:41Z
DOI: 10.1177/20552076231200976
Issue No: Vol. 9 (2023)
- Performance evaluation for medical alliance in China based on a novel
multi-attribute group decision-making technique with Archimedean
copulas-based Hamy operators and extended best-worst method
Authors: Yuping Xing, Jun Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundMedical alliance plays an important role in promoting resource sharing, optimizing the allocation of medical resources, establishing a hierarchical diagnosis and treatment system featuring primary diagnosis at the grassroots level, a two-way referral system, separated treatment for acute and chronic diseases, and dynamic cooperation. Thus, comprehensive performance evaluation for medical alliance is a necessary research that involves a multi-attribute group decision-making problem.ObjectiveThe aim of this paper is to develop a new multi-attribute group decision-making evaluation framework and new weight method to better efficaciously resolve the issues of evaluation for the medical alliance.MethodsFirstly, Archimedean copula and co-copula operational rules, called Archimedean co-copula, and the form of q-rung orthopair fuzzy Hamy mean aggregation operator based on Archimedean co-copula operational rules are also developed. Secondly, an extended q-rung orthopair fuzzy extended best-worst method satisfying multiplicative consistency is developed to originate the weight information of the attributes. The new weight method can integrate the membership and non-membership of assessment information, improve constancy for group decision making and get an extremely reliable weight consequence. Finally, a novel multi-attribute group decision-making framework is presented based on the proposed q-rung orthopair fuzzy Archimedean copula and co-copula Hamy mean aggregation operator and q-rung orthopair fuzzy Euclidean best-worst method. Furthermore, the new multi-attribute group decision-making method is applied to comprehensive performance evaluation for medical alliance in Shanghai, and the effectiveness of the new method is also demonstrated.ResultsThe results show that the proposed multi-attribute group decision-making method with Archimedean copulas-based Hamy operators and extended best-worst in this paper outperforms some existing methods and provides support for policymakers seeking the use of patient- and community-centered health evaluations to improve health services.ConclusionThe proposed method is a theoretical guidance method and a good reference for the evaluation of medical alliances of other regions in China.
Citation: DIGITAL HEALTH
PubDate: 2023-09-06T10:21:18Z
DOI: 10.1177/20552076231196997
Issue No: Vol. 9 (2023)
- The facilitators and barriers of mHealth adoption and use among people
with a low socio-economic position: A scoping review
Authors: Tessi M Hengst, Lilian Lechner, Daan Dohmen, Catherine AW Bolman
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundDespite the fact that 95% of the global population has a mobile phone, the adoption of mHealth lags among people with a low socio-economic position (SEP). As they face health risks and many barriers in the traditional offline healthcare system, mHealth has an important role. Therefore, it is important to understand the factors that promote and impede mHealth adoption among people with a lower SEP.ObjectiveThe current study aims to provide an overview of what is known about the facilitators and barriers to the adoption and use of autonomous mHealth applications among people with low SEP.MethodsA PRISMA scoping review in which the scientific databases PubMed, Web of Science, PsychInfo and SocINDEX were searched in the period of March 2017 to March 2022.ResultsOf the 1827 indexed papers, 13 papers were included in the review. In these papers, 30 factors have been identified as promoting or hindering the adoption of autonomous mHealth applications among low SEP people. ConclusionsThirty factors were found to facilitate or impede mHealth adoption among people with a low SEP, categorised into intrapersonal, interpersonal, community, ecological and app specific levels. Factors are assumed to be interrelated. The relationship between traditional (offline) care and digital care appeared to be of particular interest as the current study revealed that face-to-face contact is a prerequisite of mHealth adoption among people with low SEP. Therefore, a well-structured cosmopolitan system of stakeholders has been recommended.Trial registrationThis study was registered in OSF (https://doi.org/10.17605/OSF.IO/ATU9D).
Citation: DIGITAL HEALTH
PubDate: 2023-09-06T06:01:47Z
DOI: 10.1177/20552076231198702
Issue No: Vol. 9 (2023)
- Nurses’ view of benefits, enablers and constraints to the use of digital
health tools with patients: A cross-sectional study
Authors: Olga Navarro Martínez, Jorge Igual García, Vicente Traver Salcedo
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionDigital literacy helps patients to be more informed in order to make decisions about their health. Patient empowerment in the digital realm is a duty for all healthcare professionals, but nurses are the most numerous professionals in all healthcare systems worldwide. In addition, they have an important role in health education and patient follow-up. Therefore, the use of digital tools, by nurses to empower and help patients know more about their health, is crucial.ObjectiveThis study was conducted to identify nurses’ views on the benefits as well as constraints nurses encounter when using digital resources to empower and educate their patients. We sought to identify enablers that could help nurses use technology with their patients as a means to reinforce the care and advice they offer them.MethodsAn online ad hoc questionnaire was answered by 848 currently employed Spanish nurses on the benefits of using digital media with their patients, as well as on the constraints and enablers during implementation.ResultsThe majority of the nurses considered that reliable digital information would reduce unnecessary consultations. In addition, they think that at least 50% of their patients could benefit from consulting information online. Among the constraints, nurses mainly pointed out the older age and low educational level of their patients. Younger nurses are the most likely nurses to see patient age as a problem. As for enablers, nurses pointed out the training offered to patients as well as digital tools being user-friendly for patients.ConclusionsIt is crucial to work while following a lifelong learning strategy, with training from university education as well as training from healthcare institutions to reduce the digital gap that affects patients’ digital empowerment.
Citation: DIGITAL HEALTH
PubDate: 2023-09-04T08:19:00Z
DOI: 10.1177/20552076231197339
Issue No: Vol. 9 (2023)
- Safety considerations for assessing the quality of apps used during
pregnancy: A scoping review
Authors: Alayna Carrandi, Melanie Hayman, Cheryce L Harrison
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivePregnant women are increasingly turning to apps targeting knowledge and behaviour change for supporting healthy lifestyles and managing medical conditions. Yet, there is growing concern over the credibility and safety of content within mobile health (mHealth) apps. This scoping review aimed to systematically and thematically consolidate safety considerations described in reviews evaluating pregnancy-specific apps.MethodsPubMed, Ovid MEDLINE® and EPub, CINAHL, Web of Science, Cochrane Libraries, and SCOPUS were systematically searched to identify reviews that assessed apps targeting pregnant women. Data related to safety were extracted and thematically analysed to establish a set of relevant safety considerations.ResultsSixteen reviews met the inclusion criteria. The included reviews assessed an average of 27 apps each and targeted pregnancy topics, such as nutrition and physical activity. Five major and 20 minor themes were identified, including information, transparency, credibility, privacy and security, and app tailoring. Information, transparency, and credibility relate to the evidence base of information within the app, privacy and security of apps relate to the protection of personal information and data, and app tailoring relates to the consideration of contextual factors, such as local guidelines and digital health literacy.ConclusionsResults present possible safety considerations when evaluating pregnancy-specific apps and emphasise a clear need for consumer guidance on how to make informed decisions around engagement and use of mHealth apps during pregnancy.
Citation: DIGITAL HEALTH
PubDate: 2023-09-04T07:39:29Z
DOI: 10.1177/20552076231198683
Issue No: Vol. 9 (2023)
- Using video consultations for clinical assessment and decision of
treatment readiness before chemotherapy: A mixed-methods study among
patients with gastrointestinal cancer and oncology nurses
Authors: Karin Brochstedt Dieperink, Lene Vedel Vestergaard, Pia Krause Møller, Lærke Kjær Tolstrup
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo investigate the feasibility of clinical assessment and decision of treatment readiness before chemotherapy using video consultations, as perceived by gastrointestinal cancer patients and oncology nurses. In addition, to estimate reductions in travel time for patients and environmental carbon dioxide (CO2) emissions.MethodsIn a mixed-method study, patients with gastrointestinal cancer who participated in at least one video consultation during April–October 2019 completed a questionnaire on socioeconomic status, time and kilometers saved on travel. Kilometers saved were converted into reduced CO2 emissions. Descriptive statistics were used for analysis. Patients (n = 15) participated in semi-structured individual interviews, and five oncology nurses participated in a focus group interview.ResultsA total of 84/119 patients (71%) consented to video consultation and responded to the questionnaire. 69% were male, with a mean age of 66 years. For 46% of patients, a video consultation saved more than an hour of travel time. Avoiding a median travel distance of 120 km per patient (range, 2–450 km) reduced CO2 emissions by 7018 lb. Video consultations had other positive effects on patients, including avoiding waiting rooms, having more energy, and experiencing more focused interactions with nurses. Technical issues occurred rarely. Nurses found technical issues more troublesome, sometimes precluding complete assessments. They reported a need to rethink nursing practice to effectively provide care during video consultations.ConclusionsVideo consultations reduced CO2 emissions. In addition, they were beneficial for patients with gastrointestinal cancer. However, providing an optimal clinical assessment and decision of treatment readiness before chemotherapy requires testing patient equipment, technical skills and new oncology nursing competencies.
Citation: DIGITAL HEALTH
PubDate: 2023-09-04T05:54:26Z
DOI: 10.1177/20552076231197415
Issue No: Vol. 9 (2023)
- Can digital finance mitigate trust issues for chronically ill patients
because of relative deprivation of income'
Authors: Jiao Lu, Yanping Li, Lijing Cao, Zhongliang Zhou
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe relative deprivation of income among chronically ill patients may create a perception of inequity in their access to quality healthcare, which may lead to a decline in patients’ trust and further increases the burden of chronic diseases. Digital finance could be the antidote. To promote equity in healthcare delivery, this study explores the mitigating effect of digital finance by elucidating the relationship between relative deprivation of income and chronically ill patients’ trust.MethodsUsing data from the China Family Panel Study, a Poisson regression model was applied to assess the effect of relative deprivation of income on chronically ill patients’ trust. A marginal effect analysis was used to verify the effect and a two-stage least squares method was used to test robustness.ResultsChronically ill patients’ trust was at a medium level (5.98 ± 2.05). Relative deprivation of income significantly reduced patients’ trust (β=−0.056, p
Citation: DIGITAL HEALTH
PubDate: 2023-09-04T05:53:19Z
DOI: 10.1177/20552076231197327
Issue No: Vol. 9 (2023)
- Chronic disease diagnosis model based on convolutional neural network and
ensemble learning method
Authors: Huan Zhou, Pei-Ying Zhang, Xiao Zou, Jia Liu, Wen-Jie Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionChronic diseases have become one of the main causes of premature death all around the world in recent years. The diagnosis of chronic diseases is time-consuming and costly. Therefore, timely diagnosis and prediction of chronic diseases are very necessary.MethodsIn this paper, a new method for chronic disease diagnosis is proposed by combining convolutional neural network (CNN) and ensemble learning. This method utilizes random forest (RF) as the base classifier to improve classification performance and diagnostic accuracy, and then combines AdaBoost to successfully replace the Softmax layer of CNN to generate multiple accurate base classifiers while determining their optimal attributes, achieving high-quality classification and prediction of chronic diseases.ResultsTo verify the effectiveness of the proposed method, real-world Electronic Medical Records dataset (C-EMRs) was used for experimental analysis. The results show that compared with other traditional machine learning methods such as CNN, K-Nearest Neighbor, and RF, the proposed method can effectively improve the accuracy of diagnosis and reduce the occurrence of missed diagnosis and misdiagnosis.ConclusionsThis study will provide effective information for the diagnosis of chronic diseases, assist doctors in making clinical decisions, develop targeted intervention measures, and reduce the probability of misdiagnosis.
Citation: DIGITAL HEALTH
PubDate: 2023-09-01T06:16:14Z
DOI: 10.1177/20552076231198643
Issue No: Vol. 9 (2023)
- Accuracy of smartphone camera urine photo colorimetry as indicators of
dehydration
Authors: Aida Bustam, Khadijah Poh, Siew Shuin Soo, Fathmath Sausan Naseem, Mohd Hafyzuddin Md Yusuf, Naseeha Ubaidi Hishamudin, Muhaimin Noor Azhar
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDirect urine color assessment has been shown to correlate with hydration status. However, this method is subject to inter- and intra-observer variability. Digital image colorimetry provides a more objective method. This study evaluated the diagnostic accuracy of urine photo colorimetry using different smartphones under different lighting conditions, and determined the optimal cut-off value to predict clinical dehydration.MethodsThe urine samples were photographed in a customized photo box, under five simulated lighting conditions, using five smartphones. The images were analyzed using Adobe Photoshop to obtain Red, Green, and Blue (RGB) values. The correlation between RGB values and urine laboratory parameters were determined. The optimal cut-off value to predict dehydration was determined using area under the receiver operating characteristic curve.ResultsA total of 56 patients were included in the data analysis. Images captured using five different smartphones under five lighting conditions produced a dataset of 1400 images. The study found a statistically significant correlation between Blue and Green values with urine osmolality, sodium, urine specific gravity, protein, and ketones. The diagnostic accuracy of the Blue value for predicting dehydration were “good” to “excellent” across all phones under all lighting conditions with sensitivity>90% at cut-off Blue value of 170.ConclusionsSmartphone-based urine colorimetry is a highly sensitive tool in predicting dehydration.
Citation: DIGITAL HEALTH
PubDate: 2023-08-31T06:43:58Z
DOI: 10.1177/20552076231197961
Issue No: Vol. 9 (2023)
- Crossing boundaries in the delivery of healthcare – a qualitative study
of an eHealth intervention in relation to boundary object theory
Authors: Trust Saidi, Erlend Mork, Sofie Aminoff, Fiona Lobban, Kristin Lie Romm
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
With the increasing trend of digitalisation in the health sector, eHealth is being deployed to facilitate interaction between health professionals and service users without physical contact or close proximity. It became prominent during the COVID-19 era when mobility for physical meetings was restricted. Focusing on a video-supported digital toolkit, REACT-NOR, this study explored the experiences of caregivers and supporters in relation to the notion of boundary object. In-depth semi-structured interviews were conducted with 10 supporters and 11 caregivers to gather first-hand experience on the use of the digital tool. It emerged from the study that the use of REACT-NOR made a huge difference for the involved parties by bridging the knowledge gap between supporters and caregivers. The use of the video in particular was useful in engaging and emotionally connecting the supporters and caregivers, resulting in an exciting digital experience. The effectiveness of the digital tool can be explained in the context of a boundary object in that it facilitated the processes of transferring, translating and transforming knowledge. The tool exhibited the attributes of dynamism, flexibility, standardisation and shared structure, which resonates with the notion of a boundary object. An understanding of how boundary objects work is crucial especially with remote care, as depicted in this study, due to the fact that the transfer of knowledge involves multiple processes such as sharing of new and existing knowledge, translation to make it accessible to others and transformation to render it usable across different boundaries.
Citation: DIGITAL HEALTH
PubDate: 2023-08-31T06:42:56Z
DOI: 10.1177/20552076231196970
Issue No: Vol. 9 (2023)
- Diagnostic validation of smart wearable device embedded with single-lead
electrocardiogram for arrhythmia detection
Authors: Yonghong Niu, Hao Wang, Hong Wang, Hui Zhang, Zhigeng Jin, Yutao Guo
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo validate a single-lead electrocardiogram algorithm for identifying atrial fibrillation, atrial premature beats, ventricular premature beats, and sinus rhythm.MethodsA total of 656 subjects aged 19 to 94 years were enrolled. Participants were simultaneously tested with a wristwatch (Huawei Watch GT2 Pro, Huawei Technologies Co., Ltd, Shenzhen, China) and a 12-lead electrocardiogram for 3 minutes. A total of 1926 electrocardiogram signals from 628 subjects (282 men and 346 women) aged 19 to 94 years (median 64 years) were analyzed using an algorithm.ResultsThe numbers of subjects with atrial fibrillation, atrial premature beats, ventricular premature beats, and sinus rhythm were 129, 141, 107, and 251, respectively, and together they had a total of 1926 electrocardiogram signals. For the three-class classification system, the recall, precision, and F1 score were 97.6%, 96.5%, 97.0% for sinus rhythm; 96.7%, 96.9%, 96.8% for atrial fibrillation; and 92.8%, 94.2%, 93.5% for ectopic beats, respectively. The macro-F1 score of the three-class classification system was 95.8%. For the four-class classification system, the recall, precision, and F1 score were 97.6%, 96.5%, 97.0% for sinus rhythm; 96.7%, 96.9%, 96.8% for atrial fibrillation; 90.5%, 89.4%, 89.9% for atrial premature beats; and 86.1%, 89.6%, 87.8% for ventricular premature beats, respectively. The macro-F1 score of the four-class classification system was 92.9%.ConclusionsThe single-lead electrocardiogram algorithm embedded into smart wearables demonstrated good performance in detecting atrial fibrillation, atrial/ventricular premature beats, and sinus rhythm, and thus would facilitate atrial fibrillation screening and management.
Citation: DIGITAL HEALTH
PubDate: 2023-08-31T05:55:54Z
DOI: 10.1177/20552076231198682
Issue No: Vol. 9 (2023)
- Understanding the impact of digital technology on the well-being of older
immigrants and refugees: A scoping review
Authors: Prince Chiagozie Ekoh, Tochukwu Jonathan Okolie, Fidel Bethel Nnadi, Oluwagbemiga Oyinlola, Christine A Walsh
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe fast-paced development of digital technologies in the areas of social media, pet robots, smart homes, and artificial intelligence, among others, profoundly influence the daily lives of older adults. Digital technology can improve the well-being and quality of life of older adults, older immigrants and refugees who suffer migration-associated stress, loneliness, health and psychosocial challenges.AimsThe aim of this scoping review is to map out extant empirical literature that has examined the implication of digital technology among older refugees and immigrants.MethodsUsing a five-stage framework, we conducted a scoping review of peer-reviewed empirical studies published in English with no time restrictions. We searched nine databases for the reviews, and abstracts were reviewed using Rayyan QCRi(c) before the full-text review. The comprehensive database search yielded 4134 articles, of which 15 met the inclusion criteria.ResultsThe results of the review suggest that digital technology is essential to the well-being, quality of life of older immigrants and refugees, especially for maintaining and building new social support networks, navigating opportunities, coping with migration-induced stress through e-leisure, and staying connected to their culture. The literature also revealed poor utilisation of digital technologies amongst older immigrants and refugees, suggesting barriers to access.ConclusionThe study concluded by highlighting the need for more research and interventions that focus on multiple strategies, including education for increased access to and utilisation of digital technology to ensure that more older migrants can benefit from the advantages of digital technology in a safe way.
Citation: DIGITAL HEALTH
PubDate: 2023-08-31T05:54:47Z
DOI: 10.1177/20552076231194947
Issue No: Vol. 9 (2023)
- Describing and visualizing the patient and caregiver experience of cancer
pain in the home context using ecological momentary assessments
Authors: Virginia LeBaron, Nutta Homdee, Emmanuel Ogunjirin, Nyota Patel, Leslie Blackhall, John Lach
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundPain continues to be a difficult and pervasive problem for patients with cancer, and those who care for them. Remote health monitoring systems (RHMS), such as the Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), can utilize Ecological Momentary Assessments (EMAs) to provide a more holistic understanding of the patient and family experience of cancer pain within the home context.MethodsParticipants used the BESI-C system for 2-weeks which collected data via EMAs deployed on wearable devices (smartwatches) worn by both patients with cancer and their primary family caregiver. We developed three unique EMA schemas that allowed patients and caregivers to describe patient pain events and perceived impact on quality of life from their own perspective. EMA data were analyzed to provide a descriptive summary of pain events and explore different types of data visualizations.ResultsData were collected from five (n = 5) patient-caregiver dyads (total 10 individual participants, 5 patients, 5 caregivers). A total of 283 user-initiated pain event EMAs were recorded (198 by patients; 85 by caregivers) over all 5 deployments with an average severity score of 5.4/10 for patients and 4.6/10 for caregivers’ assessments of patient pain. Average self-reported overall distress and pain interference levels (1 = least distress; 4 = most distress) were higher for caregivers ([math] 3.02, [math]) compared to patients ([math] 2.82, [math] 2.25, respectively) while perceived burden of partner distress was higher for patients (i.e., patients perceived caregivers to be more distressed, [math] 3.21, than caregivers perceived patients to be distressed, [math]). Data visualizations were created using time wheels, bubble charts, box plots and line graphs to graphically represent EMA findings.ConclusionCollecting data via EMAs is a viable RHMS strategy to capture longitudinal cancer pain event data from patients and caregivers that can inform personalized pain management and distress-alleviating interventions.
Citation: DIGITAL HEALTH
PubDate: 2023-08-30T06:56:15Z
DOI: 10.1177/20552076231194936
Issue No: Vol. 9 (2023)
- Digital pathology world tour
Authors: Paola Chiara Rizzo, Alessandro Caputo, Eddy Maddalena, Nicolò Caldonazzi, Ilaria Girolami, Angelo Paolo Dei Tos, Aldo Scarpa, Marta Sbaraglia, Matteo Brunelli, Stefano Gobbo, Stefano Marletta, Liron Pantanowitz, Vincenzo Della Mea, Albino Eccher
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDigital pathology (DP) is currently in the spotlight and is rapidly gaining ground, even though the history of this field spans decades. Despite great technological progress, the adoption of DP for routine clinical diagnostic use remains limited.MethodsA systematic search was conducted in the electronic databases Pubmed-MEDLINE and Embase. Inclusion criteria were all published studies that encompassed any application of DP.ResultsOf 4888 articles retrieved, 4041 were included. Relevant articles were categorized as “diagnostic” (147/4041, 4%) where DP was utilized for routine diagnostic workflow and “non-diagnostic” (3894/4041, 96%) for all other applications. The “non-diagnostic” articles were further categorized according to DP application including “artificial intelligence” (33%), “education” (5%), “narrative” (17%) for reviews and editorials, and “technical” (45%) for pure research publications.ConclusionThis manuscript provided temporal and geographical insight into the global adoption of DP by analyzing the published scientific literature.
Citation: DIGITAL HEALTH
PubDate: 2023-08-30T06:54:41Z
DOI: 10.1177/20552076231194551
Issue No: Vol. 9 (2023)
- How to promote the healthy development of continuous participation in
smart medical and elderly care systems: The dual perspective of perceived
value and risk
Authors: Cong Cao, Huangyi Dai, Dan Li
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveIn an environment with an ageing population, elderly care has become a focus of social attention. The combination of smart medical care with elderly care and how to encourage the elderly to participate in the systems and enjoy a higher quality of life have become social priorities. We aimed to analyse the perceived risk and value associations of self-health management-conscious older adults regarding smart medical and elderly care systems (SMECS) and to explore the mechanisms of SMECS affecting them.MethodsUsing a Likert scale, we conducted a questionnaire-based survey and collected 387 valid responses. This was a cross-sectional study, and various key data were collected relating to the continued participation of older users in SMECS. Partial least squares structural equation modelling was used to explore the data.ResultsAccording to the data analysis, price, operability and personalisation all have significant correlations with perceived value and perceived risk. Perceptions of value and risk influence the continuous participation of the elderly, and this has a potentially positive effect on their mental and physical health.ConclusionsUnder the home-based care model, economic factors and technological accessibility were important factors affecting the elderly's continuous participation in SMECS. A personalised programme for the elderly warrants attention. In addition, the effect of perceived risk from the health-related systems was stronger than their perceived value. This research can help elderly users bridge the digital divide and enjoy smart health and medical care.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T04:36:08Z
DOI: 10.1177/20552076231197425
Issue No: Vol. 9 (2023)
- Telerehabilitation and telemonitoring interventions programs used to
improving quality of life in people with cystic fibrosis: A systematic
review
Authors: Lucía Ortiz Ortigosa, María Jesús Vinolo-Gil, José-Manuel Pastora Bernal, María Jesús Casuso-Holgado, Manuel Rodriguez-Huguet, Rocío Martín-Valero
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundCystic fibrosis causes mucus to build up in the lungs, digestive tract, and other areas. It is the most common chronic lung disease in children and young adults. It requires daily medical care. Before the COVID-19 pandemic, telerehabilitation and telehealth were used, but it was after this that there was a boom in these types of assistance in order to continue caring for cystic fibrosis patients.ObjectiveThe objective is to evaluate the effect of telemedicine programs in people with cystic fibrosis.MethodsFor the search, the PubMed, Scopus, Web of Science, PEDro, Cochrane, and CINAHL databases were used. Randomized controlled trials, pilot studies, and clinical trials have been included. The exclusion criteria have considered that the population did not have another active disease or that telemedicine was not used as the main intervention. This study follows the PRISMA statement and has been registered in the PROSPERO database (CRD42021257647).ResultsA total of 11 articles have been included in the systematic review. No improvements have been found in quality of life, forced expiratory volume, and forced vital capacity. Good results have been found in increasing physical activity and early detection of exacerbations. Adherence and satisfaction are very positive and promising.ConclusionsDespite not obtaining significant improvements in some of the variables, it should be noted that the adherence and satisfaction of both patients and workers reinforce the use of this type of care. Future studies are recommended in which to continue investigating this topic.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T04:35:08Z
DOI: 10.1177/20552076231197023
Issue No: Vol. 9 (2023)
- Evaluating an advance care planning website for people with dementia and
their caregivers: Protocol for a mixed method study
Authors: Charlèss Dupont, Fanny Monnet, Lara Pivodic, Aline De Vleminck, Chantal Van Audenhove, Lieve Van den Block, Tinne Smets
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundWeb-based tools (e.g., websites, apps) for people with dementia and their family caregivers may be useful in supporting advance care planning (ACP). Using a user-centred design approach, we developed an ACP website for people with dementia and their families. This protocol describes how we will test and evaluate the ACP website. Publishing a study protocol can guide others who want to evaluate web-based tools. Moreover, the data collection methods used in this study are very innovative since they aim to involve people living with dementia without overburdening them.MethodsWe will conduct an evaluation study of the ACP website in Flanders, Belgium, using a convergent parallel mixed methods pre-post-test design with continuous follow-up. Thirty eligible dyads of people with mild to moderate dementia (both early and late onset) and their family caregivers will use the website in their everyday life for 8 weeks. We will evaluate the usage, usability, acceptability, and feasibility of the website, as well as the experiences of users. Additionally, we evaluate the effects of using the website on ACP readiness, ACP knowledge, attitudes, perceived barriers to engage in ACP, self-efficacy and skills to engage in ACPResultsRecruitment and data collection is foreseen between end of 2022 and 2023.ConclusionThis evaluation study of an ACP website for people with dementia and their family caregivers will be the first to evaluate how a web-based tool can support people living with dementia and their families in ACP. The strength of this study lies in the combination of interviews, surveys, and ongoing data logging, which provide insights into the use of support tools in people's daily context. We expect that recruiting people with dementia and their families will be difficult so we have set up a thorough strategy to reach the anticipated sample size.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T04:34:48Z
DOI: 10.1177/20552076231197021
Issue No: Vol. 9 (2023)
- Sustainable adoption of noninvasive telemonitoring for chronic heart
failure: A qualitative study in the Netherlands
Authors: Stefan L. Auener, Simone A. van Dulmen, R van Kimmenade, Gert P Westert, Patrick PJ Jeurissen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveNoninvasive telemonitoring aims to improve healthcare for patients with chronic heart failure (HF) by reducing hospitalizations and improving patient experiences. Yet, sustainable adoption seems to be limited. Therefore, the goal of our study is to gain insight in the processes that support sustainable adoption of telemonitoring for patients with HF.MethodsWe conducted semi-structured interviews with 25 stakeholders that were involved with the adoption of telemonitoring, such as healthcare professionals, policymakers and healthcare insurers. We analyzed the interviews by using a combination of open-coding and the themes of the Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability framework.ResultsWe found that telemonitoring projects have moved beyond initial pilot phases despite a high level of complexity on multiple topics. The patient selection, the business case, the evidence, the aims of telemonitoring, integration of telemonitoring in the care pathway, reimbursement, and future centralization were items that yielded different and sometimes contradictory opinions.ConclusionsThis study showed that the sustainable adoption of telemonitoring for HF is a complex endeavor. Different aims and perspectives play an important role in the patient selection, design, evaluations and envisioned futures of telemonitoring. High conviction among participants of the added value that telemonitoring may support further adoption of telemonitoring. Structural evaluations will be needed to guide cyclical improvement and adapt programs to employ telemonitoring in such a manner that it contributes to collectively supported aims.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T04:34:31Z
DOI: 10.1177/20552076231196998
Issue No: Vol. 9 (2023)
- Digital literacy among Korean older adults: A scoping review of
quantitative studies
Authors: Hun Kang, Jiwon Baek, Sang Hui Chu, JiYeon Choi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundWhile digital literacy has become an essential competency for individuals across generations and sectors of society, supporting digital literacy in older adults is particularly challenging. South Korea is among the many countries undergoing rapid digitalization and population aging. Therefore, it is timely to identify the current understanding of digital literacy among older adults in South Korea.AimTo identify prior studies that quantitatively measure digital literacy among older adults in South Korea and to identify and evaluate how digital literacy was measured in the reviewed studies.MethodsThe study followed Arksey and O’Malley's scoping review framework, searching through four international (PubMed, CINAHL, Embase, and Cochrane Library) and four Korean (RISS, KISS, KCI, and KMBase) databases.ResultsAmong 42 studies included in the final analysis, 38 were cross-sectional studies, and 21 employed primary data. Digital literacy was assessed in various scopes, including digital literacy, e-health literacy, Internet use, and smartphone use. Of the 25 identified measures, three were validated; the rest varied greatly, from using a few items from large surveys to employing investigator-developed measures. Based on the European Commission's Digital Competence Framework, the most commonly addressed components were “information and data literacy” and “communication and collaboration.”ConclusionsIn recent years, attention toward digital literacy among South Korean older adults has grown rapidly. However, the level of digital literacy among older adults in South Korea remains inconclusive given measurement heterogeneity. Developing and validating more robust measures are warranted to evaluate digital literacy among older adults with diverse functions and circumstances.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T03:39:04Z
DOI: 10.1177/20552076231197334
Issue No: Vol. 9 (2023)
- Using machine learning to detect sarcopenia from electronic health records
Authors: Xiao Luo, Haoran Ding, Andrea Broyles, Stuart J Warden, Ranjani N Moorthi, Erik A Imel
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionSarcopenia (low muscle mass and strength) causes dysmobility and loss of independence. Sarcopenia is often not directly coded or described in electronic health records (EHR). The objective was to improve sarcopenia detection using structured data from EHR.MethodsAdults undergoing musculoskeletal testing (December 2017–March 2020) were classified as meeting sarcopenia thresholds for 0 (controls), ≥1 (Sarcopenia-1), or ≥2 (Sarcopenia-2) tests. Electronic health record diagnoses, medications, and laboratory testing were extracted from the Indiana Network for Patient Care. Five machine learning models were applied to EHR data for predicting sarcopenia.ResultsOf 1304 participants, 1055 were controls, 249 met Sarcopenia-1 and 76 met Sarcopenia-2. Sarcopenic participants were older, with higher fat mass, Charlson Comorbidity Index, and more chronic diseases. All models performed better for Sarcopenia-2 than Sarcopenia-1. The top performing models for Sarcopenia-1 were Logistic Regression [area under the curve (AUC) 71.59 (95% confidence interval [CI], 71.51–71.66)] and Multi-Layer Perceptron [AUC 71.48 (95%CI, 71.00–71.97)]. The top performing models for Sarcopenia-2 were Logistic Regression [AUC 91.44 (95%CI, 91.28–91.60)] and Support Vector Machine [AUC 90.81 (95%CI, 88.41–93.20)]. For the best Logistic Regression Model, important sarcopenia predictors included diabetes mellitus, digestive system complaints, signs and symptoms involving the nervous, musculoskeletal and respiratory systems, metabolic disorders, and kidney or urinary tract disorders. Opioids, corticosteroids, and antihyperlipidemic drugs were also more common among sarcopenic participants.ConclusionsApplying machine learning models, sarcopenia can be predicted from structured data in EHR, which may be developed through future studies to facilitate large-scale early detection and intervention in clinical populations.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T03:38:04Z
DOI: 10.1177/20552076231197098
Issue No: Vol. 9 (2023)
- Optimizing the predictive power of depression screenings using machine
learning
Authors: Yannik Terhorst, Lasse B Sander, David D Ebert, Harald Baumeister
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveMental health self-report and clinician-rating scales with diagnoses defined by sum-score cut-offs are often used for depression screening. This study investigates whether machine learning (ML) can detect major depressive episodes (MDE) based on screening scales with higher accuracy than best-practice clinical sum-score approaches.MethodsPrimary data was obtained from two RCTs on the treatment of depression. Ground truth were DSM 5 MDE diagnoses based on structured clinical interviews (SCID) and PHQ-9 self-report, clinician-rated QIDS-16, and HAM-D-17 were predictors. ML models were trained using 10-fold cross-validation. Performance was compared against best-practice sum-score cut-offs. Primary outcome was the Area Under the Curve (AUC) of the Receiver Operating Characteristic curve. DeLong's test with bootstrapping was used to test for differences in AUC. Secondary outcomes were balanced accuracy, precision, recall, F1-score, and number needed to diagnose (NND).ResultsA total of k = 1030 diagnoses (no diagnosis: k = 775; MDE: k = 255) were included. ML models achieved an AUCQIDS-16 = 0.94, AUCHAM-D-17 = 0.88, and AUCPHQ-9 = 0.83 in the testing set. ML AUC was significantly higher than sum-score cut-offs for QIDS-16 and PHQ-9 (ps ≤ 0.01; HAM_D-17: p = 0.847). Applying optimal prediction thresholds, QIDS-16 classifier achieved clinically relevant improvements (Δbalanced accuracy = 8%, ΔF1-score = 14%, ΔNND = 21%). Differences for PHQ_9 and HAM-D-17 were marginal.ConclusionsML augmented depression screenings could potentially make a major contribution to improving MDE diagnosis depending on questionnaire (e.g., QIDS-16). Confirmatory studies are needed before ML enhanced screening can be implemented into routine care practice.
Citation: DIGITAL HEALTH
PubDate: 2023-08-29T03:37:43Z
DOI: 10.1177/20552076231194939
Issue No: Vol. 9 (2023)
- Measuring efficiency of the global fight against the COVID-19 pandemic
Authors: Jih-Shong Wu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThe ongoing COVID-19 pandemic has led to an unprecedented loss of life and a severe economic downturn across the globe. Countries have adopted various social distancing and vaccination policies to reduce the spread of the disease and lessen the impact on healthcare systems. The world should work together to confront the disaster and challenge of COVID-19.MethodsThis study uses stochastic frontier analysis to measure the efficiency and influencing factors of the global response to COVID-19 epidemics and to provide follow-up strategies and reference guidelines.ResultsThe results of this study show that (1) the average efficiency of the global response to COVID-19 is not good, with significant space for improvement of up to 60%; (2) adequate medical supplies and equipment can reduce mortality; (3) the initial implementation of social distancing policies and wearing masks can effectively reduce the infection rate; and (4) as infection rates and vaccination rates increase so that most people have basic immunity to COVID-19, the epidemic will gradually be reduced.ConclusionsAs the world becomes more aware of the COVID-19 disease, humans will gradually return to normal social interaction and lifestyles. The results of this study are expected to provide a reference for the future direction of the global fight against epidemics and the improvement of public health policies.
Citation: DIGITAL HEALTH
PubDate: 2023-08-28T04:50:41Z
DOI: 10.1177/20552076231197528
Issue No: Vol. 9 (2023)
- Feasibility of a smartphone app for prescribed exercise tutoring in
patients with stable coronary heart disease
Authors: Kun Xia, Changhao Bai, Rongjing Ding, Yue Kong, Xiaomian Fan, Yefa Liu, Bo Liu, Xi Chen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundDigital health technologies have potential to address the challenges associated with traditional cardiac rehabilitation (CR). However, it is not complete enough for prescribed exercise guidance and remote monitoring.ObjectiveWe aimed to evaluate the feasibility of a smartphone app for prescribed exercise tutoring by exercise videos combined with wearable devices to monitor heart rate in patients with stable coronary heart disease (CHD).MethodsThe study is a quasi-experimental design study with a single group. A total of 31 patients were included with an average age of 56.2 years (SD 13.4). They participated in a 12-week remote digital CR program. We employed a wearable heart rate monitoring device connected with an app to monitor the patients’ exercise intensity. The app can display the videos corresponding to an exercise prescription to guide the exercise. Cardiorespiratory endurance, blood pressure, blood glucose, cholesterol, blood uric acid, left ventricular ejection fraction and quality of life (QoL) were assessed at the beginning and end of the intervention. Compliance and safety events were recorded as well.ResultsCompletion rate reached 90.3%. Average daily effective exercise time was 39.4 min (SD 17.8), and 92.9% of the patients could exercise in the prescribed intensity for at least 20 min per day. Average effective exercise days per week were 4.6 days (SD 2.2), and 67.9% of the patients could exercise in the prescribed intensity for at least 3 days per week. Patients’ peak VO2 (P = 0.041) and peak metabolic equivalents (P = 0.018) were significantly increased, low-density lipoprotein (P = 0.036) and diastolic blood pressure at rest (P = 0.044) were significantly decreased, and depression (GAD-7, P = 0.014) and anxiety (PHQ-9, P = 0.013) were significantly improved.ConclusionsIt is feasible, safe, and helpful for stable CHD patients to use the app for prescribed exercise tutoring with videos combined with wearable devices to monitor heart rate.Trial RegistrationChiCTR1800019144.
Citation: DIGITAL HEALTH
PubDate: 2023-08-28T04:49:11Z
DOI: 10.1177/20552076231197424
Issue No: Vol. 9 (2023)
- Has smart city transition elevated the provision of healthcare services'
Evidence from China's Smart City Pilot Policy
Authors: Lin Guo, Yulin Chai, Chunxiao Yang, Linlin Zhang, Hongwei Guo, Honglv Yang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
This paper endeavors to identify the causal effects between the smart city transition and the provision of healthcare services while uncovering potential pathways of influence. This study first constructs a logical analytical framework and posits five hypotheses for examination. Subsequently, leveraging the quasi-natural experiment of the China Smart City Pilot Policy (CSCPP), empirical tests are conducted utilizing a Difference-in-Differences (DD) two-way fixed effects model. The findings suggest that the CSCPP has significantly enhanced the provision of healthcare services. Even after addressing the formidable challenges of endogeneity, sample self-selection, and spatial spillovers, the conclusion remains robust. Mechanism tests indicate that the CSCPP primarily operates through two avenues: augmenting human resources and institutional services. Heterogeneity tests reveal that the efficacy of CSCPP is heightened in cities boasting administrative approval service centers, experiencing diminished financial constraints, and exhibiting elevated healthcare provision levels and situated in the eastern region. The theoretical and empirical analysis of this paper demonstrates that smart city transitions can facilitate the enhancement of healthcare services. The potential contribution of this paper is to enrich the conceptualization of governance frameworks for smart city transition while providing empirical evidence from China.
Citation: DIGITAL HEALTH
PubDate: 2023-08-28T04:48:13Z
DOI: 10.1177/20552076231197335
Issue No: Vol. 9 (2023)
- ‘I understood the texting process well’. Participant perspectives on
usability and acceptability of SMS-based telehealth follow-up after
voluntary medical male circumcision in South Africa
Authors: Jacqueline Pienaar, Sarah Day, Geoffrey Setswe, Beatrice Wasunna, Vuyolwethu Ncube, Felex Ndebele, Femi Oni, Evelyn Waweru, Calsile Khumalo, Hannock Tweya, Kenneth Sherr, Yanfang Su, Caryl Feldacker
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundVoluntary medical male circumcision (MC) is a biomedical HIV prevention method that requires post-operative follow-up for healing confirmation. Recent research found that a two-way texting (2wT) app providing SMS-based telehealth for MC patients was safe and reduced provider workload. We evaluated 2wT usability among MC clients in South Africa assigned the 2wT intervention within a larger randomized controlled trial (RCT) of 2wT safety and workload.MethodsThis quantitative usability study is within an RCT where 547 men used 2wT to interact with an MC provider via SMS. The sub-study involved the first 100 men assigned to 2wT who completed a usability survey 14 days after surgery. Acceptability was assessed through 2wT response rates of the 547 men. Regression models analyzed associations between age, wage, location, potential adverse events (AEs), and 2wT responses.ResultsMen assigned to 2wT found it safe, comfortable, and convenient, reporting time and cost savings. High response rates (88%) to daily messages indicated acceptability. Age, wage, and location didn't affect text responses or potential AEs.Conclusion2wT for post-MC follow-up was highly usable and acceptable, suggesting its viability as an alternative to in-person visits. It enhanced confidence in wound self-management. This SMS-based telehealth can enhance MC care quality and be adapted to similar contexts for independent healing support, particularly for men.
Citation: DIGITAL HEALTH
PubDate: 2023-08-28T04:46:35Z
DOI: 10.1177/20552076231194924
Issue No: Vol. 9 (2023)
- Effectiveness of the non-face-to-face comprehensive elderly care
application “smart silver care” for community-dwelling elderly: A
randomized controlled trial
Authors: Dahye Hong, Seon Heui Lee
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundQuality of life for the elderly has become an important issue, and services aimed at improving it have typically been provided face-to-face. However, coronavirus disease 2019 has limited the use of face-to-face services, and the need to convert such systems to online interfaces has emerged.ObjectiveThis study evaluates the effectiveness of a non-face-to-face comprehensive elderly care application called “Smart Silver Care.”MethodsThis study was designed as a randomized controlled trial. Sixty community-dwelling elderly individuals were randomly assigned to experimental and control groups in a 1:1 ratio. The participants participated in the “Smart Silver Care” intervention using a tablet and smartwatch based on the programs we provided. The participants performed five tasks, five days a week, consisting of physical, emotional, and cognitive programs. Participants could communicate with the researchers in real-time from their homes, and the researchers could remotely supervise their performance.ResultsWe found positive effects on the relevant scales testing fall risk (Activities-Specific Balance Confidence [ABC] Scale, p = 0.028; Timed Up and Go [TUG] test, p = 0.001). However, there was no time × group interaction between the experimental and control groups on the relevant scales for depression and quality of life (Short Form-Geriatric Depression Scale [SGDS]-K: p = 0.225; EuroQol five-dimension five-level [EQ-5D-5L], p = 0.172). While the SGDS-K and EQ-5D-5L did not show statistical significance, we found improvement trends in the experimental group.ConclusionsThe findings of this study show that Smart Silver Care significantly improved the participants’ TUG and ABC scores in community-dwelling elderly, and a qualitative evaluation confirmed that it could be conveniently used by the elderly. Thus, Smart Silver Care offers a feasible intervention to improve the quality of life of the elderly, including physical aspects.
Citation: DIGITAL HEALTH
PubDate: 2023-08-24T09:50:52Z
DOI: 10.1177/20552076231197340
Issue No: Vol. 9 (2023)
- A new early warning method for mild cognitive impairment due to
Alzheimer's disease based on dynamic evaluation of the “spatial
executive process”
Authors: Kai Li, Xiaowen Ma, Tong Chen, Junyi Xin, Chen Wang, Bo Wu, Atsushi Ogihara, Siyu Zhou, Jiakang Liu, Shouqiang Huang, Yujia Wang, Shuwu Li, Zeyuan Chen, Runlong Xu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveMild cognitive impairment (MCI) due to Alzheimer's disease (AD), as an early stage of AD, is an important point for early warning of AD. Neuropathological studies have shown that AD pathology in pre-dementia patients involves the hippocampus and caudate nucleus, which are responsible for controlling cognitive mechanisms such as the spatial executive process (SEP). The aim of this study is to design a new method for early warning of MCI due to AD by dynamically evaluating SEP.MethodsWe designed fingertip interaction handwriting digital evaluation paradigms and analyzed the dynamic trajectory of fingertip interaction and image data during “clock drawing” and “repetitive writing” tasks. Extracted fingertip interaction digital biomarkers were used to assess participants’ SEP disorders, ultimately enabling intelligent diagnosis of MCI due to AD. A cross-sectional study demonstrated the predictive performance of this new method.ResultsWe enrolled 30 normal cognitive (NC) elderly and 30 MCI due to AD patients, and clinical research results showed that there may be neurobehavioral differences between the two groups in digital biomarkers captured during SEP. The early warning performance for MCI due to AD of this new method (areas under the curve (AUC) = 0.880) is better than that of the Minimum Mental State Examination (MMSE) neuropsychological scale (AUC = 0.856) assessed by physicians.ConclusionPatients with MCI due to AD may have SEP disorders, and this new method based on dynamic evaluation of SEP will provide a novel human–computer interaction and intelligent early warning method for home and community screening of MCI due to AD.
Citation: DIGITAL HEALTH
PubDate: 2023-08-24T09:50:40Z
DOI: 10.1177/20552076231194938
Issue No: Vol. 9 (2023)
- Development of the Tool to Empower Parental Telling and Talking (TELL
Tool): A digital decision aid intervention about children's origins from
donated gametes or embryos
Authors: Patricia E. Hershberger, Agatha M. Gallo, Kirby Adlam, Martha Driessnack, Harold D. Grotevant, Susan C. Klock, Lauri Pasch, Valerie Gruss
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study aimed to create and develop a well-designed, theoretically driven, evidence-based, digital, decision Tool to Empower Parental Telling and Talking (TELL Tool) prototype.MethodsThis developmental study used an inclusive, systematic, and iterative process to formulate a prototype TELL Tool: the first digital decision aid for parents who have children 1 to 16 years of age and used donated gametes or embryos to establish their families. Recommendations from the International Patient Decision Aids Standards Collaboration and from experts in decision aid development, digital health interventions, design thinking, and instructional design guided the process.ResultsThe extensive developmental process incorporated researchers, clinicians, parents, children, and other stakeholders, including donor-conceived adults. We determined the scope and target audience of the decision aid and formed a steering group. During design work, we used the decision-making process model as the guiding framework for selecting content. Parents’ views and decisional needs were incorporated into the prototype through empirical research and review, appraisal, and synthesis of the literature. Clinicians’ perspectives and insights were also incorporated. We used the experiential learning theory to guide the delivery of the content through a digital distribution plan. Following creation of initial content, including storyboards and scripts, an early prototype was redrafted and redesigned based on feedback from the steering group. A final TELL Tool prototype was then developed for alpha testing.ConclusionsDetailing our early developmental processes provides transparency that can benefit the donor-conceived community as well as clinicians and researchers, especially those designing digital decision aids. Future research to evaluate the efficacy of the TELL Tool is planned.
Citation: DIGITAL HEALTH
PubDate: 2023-08-24T06:47:20Z
DOI: 10.1177/20552076231194934
Issue No: Vol. 9 (2023)
- Digital technologies in dentistry in Saudi Arabia: Perceptions, practices
and challenges
Authors: Hawazen A Radwan, Alla T Alsharif, Maha T Alsharif, Mohammed R Aloufi, Bassam S Alshammari
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe aim of this study was to assess practicing dentists’ characteristics and professional aspects that influence users to adopt Digital Technologies in Dentistry (DTD) in Saudi Arabia (SA). Moreover, we aimed to identify dentists’ perceived barriers and challenges and to anticipate future potential developments towards implementing DTDs in their practices in SA.MethodsThis analytical cross-sectional study based on a validated questionnaire was conducted using a snowball sampling technique to include a conveniently selected sample of dentists from all dental specialties currently working in SA.ResultsThe response rate was 64% completed and returned. A statistically significantly large share of Gen X (10.1%) used digital technologies (DTs) in dental practice compared with non-digital users. 40% received sufficient postgraduate education on DT, 92% agreed that DT should be included in the undergraduate dental curriculum. However, 79% actually gained skills or knowledge on DT through workshops and formal courses. ‘Lack of practitioners’ awareness’, ‘lack of education and pioneers’ and ‘lack of clinical evidence’ were highlighted as the foremost barriers. Lower-frequency DT users believed that treating patients with DT makes treatment more predictable. Together, clinical trials and hands-on training courses can help overcome the barriers to the adoption of new dental technologies.ConclusionsExploring technology adoption and usage amongst practicing dentists allows healthcare stakeholders and policymakers to set a clear direction towards the digitalisation of the healthcare system and within healthcare organisations. The study also highlighted the foremost barriers, challenges and actions towards the adoption of DTDs.
Citation: DIGITAL HEALTH
PubDate: 2023-08-23T08:20:59Z
DOI: 10.1177/20552076231197095
Issue No: Vol. 9 (2023)
- A blockchain-based computerized network infrastructure for the
transparent, immutable calculation and dissemination of quantitative,
measurable parameters of academic and medical research publications
Authors: Gad Segal, Yonatan Martsiano, Alina Markinzon, Amit Mayer, Avner Halperin, Eyal Zimlichman
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Digital transformation of healthcare systems should rely on decentralized computer networks and take advantage of the unique characteristics of blockchain technology. Decentralization ensures process transparency and data transparency for all relevant stakeholders. These values are essential in the realms of populations’ healthcare information communications and processing, control and tracking of medical logistics supply chains, clinical research management, and control of certified healthcare services organizations. Mounting decentralized processes onto a blockchain-based computerized network will endow the values of immutability, improved cybersecurity, and potential for incentivizing stakeholders for relevant, pre-determined activities. One of the most relevant processes that would benefit from a decentralized, blockchain-based architecture is the submission, review, and publishing of scientific manuscripts. Current structures and processes in this world are non-transparent, poorly incentivizing significant stakeholders such as manuscripts’ reviewers, and many are potentially corrupted. In this review, we suggest a blockchain-based architecture for such systems and advocate further research and development in several domains of modern healthcare systems—offering medicine to become “the new guy on the block (chain).”
Citation: DIGITAL HEALTH
PubDate: 2023-08-22T06:08:43Z
DOI: 10.1177/20552076231194851
Issue No: Vol. 9 (2023)
- Utilization of remote e-prescription (Anat) in Saudi Arabia during
COVID-19: Factors associated with primary adherence and antibiotic
prescription
Authors: Roaa Khaled Alhassoun, Sharifah Abdullah AlDossary
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe COVID-19 pandemic has affected healthcare systems globally. Various health care technologies have been used to mitigate the risk of disease transmission. Telemedicine is one such technology, and remote consulting and prescribing comprise one of its key aspects. In Saudi Arabia, telephone health services have been widely used through the free Medical Consultation Call Center (937). This platform facilitates medical consultations for all citizens, residents, and visitors. After consultations, healthcare providers are able to issue authenticated e-prescriptions using the Anat platform.ObjectivesTo explore the utilization of the Anat remote prescription system in Saudi Arabia during the COVID-19 pandemic and to identify the factors associated with antibiotic prescription and primary medication adherence.MethodsThis retrospective analysis included data from the Anat e‑prescription system using a stratified random sample of 25000 prescriptions issued in Saudi Arabia in 2020. Predictive factors related to the patients, practitioners, and prescriptions were identified through bivariate and multivariate logistic regression analyses.ResultsOut of 25,000 e-prescriptions, 8885 were dispensed, resulting in a 35.5% primary medication adherence rate. The significant predictors of primary adherence were children, respiratory diseases, and antibacterial drugs. In addition, antibiotics made up 32.1% of the e-prescriptions. The prescription of antibiotics was significantly associated with male sex, children, genitourinary system diseases, and being treated by radiologists.ConclusionsAlmost two thirds 62.2% of e-prescriptions were undispensed, with antibiotic eprescriptions at 32.1%. Findings emphasize the need to enhance primary medication adherence and antibiotic prescription interventions. These findings could aid decision-makers in improving patient-centered e-prescribing practices.
Citation: DIGITAL HEALTH
PubDate: 2023-08-21T09:23:27Z
DOI: 10.1177/20552076231194925
Issue No: Vol. 9 (2023)
- How suitable are clinical vignettes for the evaluation of symptom checker
apps' A test theoretical perspective
Authors: Marvin Kopka, Markus A Feufel, Eta S Berner, Malte L Schmieding
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo evaluate the ability of case vignettes to assess the performance of symptom checker applications and to suggest refinements to the methodology used in case vignette-based audit studies.MethodsWe re-analyzed the publicly available data of two prominent case vignette-based symptom checker audit studies by calculating common metrics of test theory. Furthermore, we developed a new metric, the Capability Comparison Score (CCS), which compares symptom checker capability while controlling for the difficulty of the set of cases each symptom checker evaluated. We then scrutinized whether applying test theory and the CCS altered the performance ranking of the investigated symptom checkers.ResultsIn both studies, most symptom checkers changed their rank order when adjusting the triage capability for item difficulty (ID) with the CCS. The previously reported triage accuracies commonly overestimated the capability of symptom checkers because they did not account for the fact that symptom checkers tend to selectively appraise easier cases (i.e., with high ID values). Also, many case vignettes in both studies showed insufficient (very low and even negative) values of item-total correlation (ITC), suggesting that individual items or the composition of item sets are of low quality.ConclusionsA test–theoretic perspective helps identify previously undetected threats to the validity of case vignette-based symptom checker assessments and provides guidance and specific metrics to improve the quality of case vignettes, in particular by controlling for the difficulty of the vignettes an app was (not) able to evaluate correctly. Such measures might prove more meaningful than accuracy alone for the competitive assessment of symptom checkers. Our approach helps elaborate and standardize the methodology used for appraising symptom checker capability, which, ultimately, may yield more reliable results.
Citation: DIGITAL HEALTH
PubDate: 2023-08-21T03:11:03Z
DOI: 10.1177/20552076231194929
Issue No: Vol. 9 (2023)
- A framework for design and usability testing of telerehabilitation system
for adults with chronic diseases: A panoramic scoping review
Authors: Suad J Ghaben, Arimi Fitri Mat Ludin, Nazlena Mohamad Ali, Kok Beng Gan, Devinder Kaur Ajit Singh
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis scoping review aimed to identify the design and usability testing of a telerehabilitation (TR) system, and its characteristics and functionalities that are best-suited for rehabilitating adults with chronic diseases.MethodsSearches were conducted in PubMed, EBSCO, Web of Science, and Cochrane library for studies published between January 2017 and December 2022. We followed the Joanna Briggs Institute guidelines and the framework by Arksey and O’Malley. Screening was undertaken by two reviewers, and data extraction was undertaken by the first author. Then, the data were further reviewed and discussed thoroughly with the team members.ResultsA total of 31 results were identified, with the core criteria of developing and testing a telerehabilitation system, including a mobile app for cardiovascular diseases, cancer, diabetes, and chronic respiratory disorders. All developed systems resulted from multidisciplinary teams and employed mixed-methods research. We proposed the “input-process-output” framework that identified phases of both system design and usability testing. Through system design, we reported the use of user-centered design, iterative design, users’ needs and characteristics, theory underpinning development, and the expert panel in 64%, 75%, 86%, 82%, and 71% of the studies, respectively. We recorded the application of moderated usability testing, unmoderated testing (1), and unmoderated testing (2) in 74%, 63%, and 15% of the studies, respectively. The identified design and testing activities produced a matured system, a high-fidelity prototype, and a released system in 81.5%, 15%, and 3.5%, respectively.ConclusionThis review provides a framework for TR system design and testing for a wide range of chronic diseases that require prolonged management through remote monitoring using a mobile app. The identified “input-process-output” framework highlights the inputs, design, development, and improvement as components of the system design. It also identifies the “moderated-unmoderated” model for conducting usability testing. This review illustrates characteristics and functionalities of the TR systems and healthcare professional roles.
Citation: DIGITAL HEALTH
PubDate: 2023-08-17T07:29:22Z
DOI: 10.1177/20552076231191014
Issue No: Vol. 9 (2023)
- Modeling the intention and usage of medicine vending machine: Using
partial least squares-structural equation modelling and necessary
condition analysis
Authors: Qing Yang, Abdullah Al Mamun, Jingzu Gao, Zafir Khan Mohamed Makhbul
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study aimed to investigate the factors influencing the intention to use and actual usage of medicine vending machines (MVMs) in China and to close the existing literature gap by examining the relationship between perceived convenience (PC), perceived trust, performance expectancy, effort expectancy, and social influence, on the intention to use MVM in a comprehensive manner. The impact of facilitating conditions on MVM adoption was also examined. Finally, customer age was tested as a moderator.MethodsThis was a cross-sectional study that used data collected through a self-administered questionnaire. A combination of partial least squares-structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) technique was used to analyze and discuss the 308 valid questionnaires, test the hypotheses, and conduct an in-depth analysis.ResultsThe results showed that PC, perceived trust, and performance expectancy were significantly related to the intention to use MVM. Effort expectancy was a non-significant predictor of intention to use MVM. Social influence was a significant negative predictor of the intention to use MVM. More importantly, performance expectancy was found to be a necessary factor for MVM intention, providing new marketing ideas for MVM owners. Age had a significant moderating effect on the facilitating conditions and intention to use vending machines. The relatively young population is more conscious of the facilitating conditions.ConclusionsThe findings of this study are of considerable importance as a guide for the main user group of vending machines. The combined analysis and discussion of PLS-SEM and NCA provide a sound theoretical basis for the practical implications of this study. In the future, we will attempt to use this technique in other areas of study. In terms of theoretical implications, this study provides technical references for future research.
Citation: DIGITAL HEALTH
PubDate: 2023-08-16T07:10:46Z
DOI: 10.1177/20552076231194935
Issue No: Vol. 9 (2023)
- Feasibility and acceptability to use a smartphone-based manikin for daily
longitudinal self-reporting of chronic pain
Authors: Syed Mustafa Ali, David A Selby, Darryl Bourke, Ramiro D Bravo Santisteban, Alessandro Chiarotto, Jill Firth, Ben James, Ben Parker, William G Dixon, Sabine N van der Veer
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAs management of chronic pain continues to be suboptimal, there is a need for tools that support frequent, longitudinal pain self-reporting to improve our understanding of pain. This study aimed to assess the feasibility and acceptability of daily pain self-reporting using a smartphone-based pain manikin.MethodsFor this prospective feasibility study, we recruited adults with lived experience of painful musculoskeletal condition. They were asked to complete daily pain self-reports via an app for 30 days. We assessed feasibility by calculating pain report completion levels, and investigated differences in completion levels between subgroups. We assessed acceptability via an end-of-study questionnaire, which we analysed descriptively.ResultsOf the 104 participants, the majority were female (n = 87; 84%), aged 45-64 (n = 59; 57%), and of white ethnic background (n = 89; 86%). The mean completion levels was 21 (± 7.7) pain self-reports. People who were not working (odds ratio (OR) = 1.84; 95% confidence interval (CI), 1.52-2.23) were more likely, and people living in less deprived areas (OR = 0.77; 95% CI, 0.62-0.97) and of non-white ethnicity (OR = 0.45; 95% CI, 0.36-0.57) were less likely to complete pain self-reports than their employed, more deprived and white counterparts, respectively. Of the 96 participants completing the end-of-study questionnaire, almost all participants agreed that it was easy to complete a pain drawing (n = 89; 93%).ConclusionIt is feasible and acceptable to self–report pain using a smartphone–based manikin over a month. For its wider adoption for pain self–reporting, the feasibility and acceptability should be further explored among people with diverse socio–economic and ethnic backgrounds.
Citation: DIGITAL HEALTH
PubDate: 2023-08-16T07:09:26Z
DOI: 10.1177/20552076231194544
Issue No: Vol. 9 (2023)
- Dynamic consent, communication and return of results in large-scale health
data reuse: Survey of public preferences
Authors: Sam HA Muller, Ghislaine JMW van Thiel, Menno Mostert, Johannes JM van Delden
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Dynamic consent forms a comprehensive, tailored approach for interacting with research participants. We conducted a survey study to inquire how research participants evaluate the elements of consent, information provision, communication and return of results within dynamic consent in a hypothetical health data reuse scenario. We distributed a digital questionnaire among a purposive sample of patient panel members. Data were analysed using descriptive and nonparametric inferential statistics. Respondents favoured the potential to manage changing consent preferences over time. There was much agreement between people favouring closer and more specific control over data reuse approval and those in favour of broader approval, facilitated by an opt-out system or an independent data reuse committee. People want to receive more information about reuse, outcomes and return of results. Respondents supported an interactive model of research participation, welcoming regular, diverse and interactive forms of communication, like a digital communication platform. Approval for reuse and providing meaningful information, including meaningful return of results, are intricately related to facilitating better communication. Respondents favoured return of actionable research results. These findings emphasize the potential of dynamic consent for enabling participants to maintain control over how their data are being used for which purposes by whom. Allowing different options to shape a dynamic consent interface in health data reuse in a personalized manner is pivotal to accommodate plurality in a flexible though robust manner. Interaction via dynamic consent enables participants to tailor the elements of participation they deem relevant to their own preferences, engaging diverse perspectives, interests and preferences.
Citation: DIGITAL HEALTH
PubDate: 2023-08-16T07:07:48Z
DOI: 10.1177/20552076231190997
Issue No: Vol. 9 (2023)
- Digital screening method using social media advertising for the remote
assessment of trigeminal neuralgia
Authors: Fu-Yu B Chen, Daniel AN Barbosa
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveGlobal trends, such as improving accessibility to healthcare services through the Internet, and the COVID-19 pandemic are among the driving factors in the adoption of digital health. This study hypothesized that digital solutions can reach and gather data from a large number of patients with trigeminal neuralgia (TN), a commonly misdiagnosed neuropathic facial pain syndrome, and quickly and fast-track their diagnosis by suggesting them to consult a neurologist. We developed an accessible digital screening tool based on patient symptoms and history to test this hypothesis and used social media advertisement to screen a general population for TN.MethodsThe standard diagnostic criteria, International Classification of Orofacial Pain, for facial pain is digitized as a web-based questionnaire that allows easy access to the evaluation for patients with suspected TN symptoms. Targeted search with relevant keywords and display campaigns on Google search engine and Facebook social media platform were used to reach large numbers of subjects. A report was autogenerated, which included a summary of a subject's symptoms, likely or likely not TN diagnosis, and information to seek appropriate medical assistance.ResultsThe website was live for seven weeks and generated 240 screening questionnaire submissions, with a total spending of $2482. Forty-four subjects (18.3%) that reported typical symptoms of TN experienced unilateral and episodic pain in one of the trigeminal nerve regions.ConclusionsWe have demonstrated the feasibility of social media advertisement and digitally screening a general population for TN, gathering valuable clinical data, such as pain characteristics, through a web-based questionnaire. Based on these data, patients with similar symptoms of TN are suggested to consult a neurologist for diagnosis. This study provides a framework for using digital screening tools to improve the healthcare experience of patients who would spend several months before finding appropriate diagnosis for their specific conditions.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T07:29:30Z
DOI: 10.1177/20552076231194913
Issue No: Vol. 9 (2023)
- Chronic disease IMPACT (chronic disease early detection and improved
management in primary care project): An Australian stepped wedge cluster
randomised trial
Authors: Julia L Jones, Koen Simons, Jo-Anne Manski-Nankervis, Natalie G Lumsden, Sanduni Fernando, Maximilian P de Courten, Nicholas Cox, Peter Shane Hamblin, Edward D Janus, Craig L Nelson
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundInterrelated chronic vascular diseases (chronic kidney disease (CKD), type 2 diabetes (T2D) and cardiovascular disease (CVD)) are common with high morbidity and mortality. This study aimed to assess if an electronic-technology-based quality improvement intervention in primary care could improve detection and management of people with and at risk of these diseases.MethodsStepped-wedge trial with practices randomised to commence intervention in one of five 16-week periods. Intervention included (1) electronic-technology tool extracting data from general practice electronic medical records and generating graphs and lists for audit; (2) education regarding chronic disease and the electronic-technology tool; (3) assistance with quality improvement audit plan development, benchmarking, monitoring and support. De-identified data analysis using R 3.5.1 conducted using Bayesian generalised linear mixed model with practice and time-specific random intercepts.ResultsAt baseline, eight included practices had 37,946 active patients (attending practice ≥3 times within 2 years) aged ≥18 years. Intervention was associated with increased OR (95% CI) for: kidney health checks (estimated glomerular filtration rate, urine albumin:creatinine ratio (uACR) and blood pressure) in those at risk 1.34 (1.26–1.42); coded diagnosis of CKD 1.18 (1.09–1.27); T2D diagnostic testing (fasting glucose or HbA1c) in those at risk 1.15 (1.08–1.23); uACR in patients with T2D 1.78 (1.56–2.05). Documented eye checks within recommended frequency in patients with T2D decreased 0.85 (0.77–0.96). There were no significant changes in other assessed variables.ConclusionsThis electronic-technology-based intervention in primary care has potential to help translate guidelines into practice but requires further refining to achieve widespread improvements across the interrelated chronic vascular diseases.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T07:05:17Z
DOI: 10.1177/20552076231194948
Issue No: Vol. 9 (2023)
- Psychometric properties of the German revised version of the eHealth
literacy scale in individuals with cardiac diseases: Validation and test
of measurement invariance
Authors: Alexander Bäuerle, Matthias Marsall, Lisa Maria Jahre, Christos Rammos, Charlotta Mallien, Eva-Maria Skoda, Tienush Rassaf, Julia Lortz, Martin Teufel
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe internet is most people's primary source of (health) information. However, no validated instrument exists to assess eHealth literacy in the group of patient with cardiac diseases.ObjectiveThe objective of this study was the evaluation of the psychometric properties of the German revised version of the eHealth literacy scale (GR-eHEALS) in individuals with coronary artery disease (CAD) and congestive heart failure (CHF).MethodsA cross-sectional study was conducted. N = 455 were included in the statistical analyses. The assessment compromised the GR-eHEALS, medical history, sociodemographic data, and technology-related data. Confirmatory factor analyses, correlational analyses, and tests of measurement invariance were performed.ResultsThe two-factorial model reached a good model fit. The sub-scales information seeking and information appraisal, as well as the eHealth literacy total score, reached high reliability coefficients. Construct and criterion validity was fully confirmed For the two-factorial model, measurement invariance up to the scalar level could be confirmed regarding the sociodemographic characteristics sex, age, and educational level.ConclusionsThis study confirmed the two-factor structure, construct, and criterion validity as well as measurement invariance at the scalar level for sex, age, and educational level of the GR-eHEALS scale in a sample of individuals with CAD and CHF.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T07:04:09Z
DOI: 10.1177/20552076231194915
Issue No: Vol. 9 (2023)
- Usability of a continuous oxygen saturation device for home telemonitoring
Authors: Francesco Bonometti, Palmira Bernocchi, Andrea Vitali, Anna Savoldelli, Caterina Rizzi, Simonetta Scalvini
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe emergency for the COVID-19 pandemic has led to greater use of home telemonitoring devices. The aim of this study was to assess the usability of continuous home-monitoring care with an oxygen saturation device on post-COVID-19 patients.MethodThe system consists of a digital continuous pulse oximeter and a smartphone with an App, which were provided to patients. A survey composed of a standard Post-Study System Usability Questionnaire, and a satisfaction questionnaire was exploited to conduct a usability and feasibility analysis of the service.ResultsA total of 29 patients (17.2% female) with a mean age of 65 ± 11.5 years were enrolled: 20 patients were smartphone users (69%) with a mean age of 60.2 ± 9.5 years, and 9 patients (31%) did not own a smartphone (mean age 76.8 ± 5.9). The monitoring period was 1 month: a total of 444 recordings were conducted, 15 recordings per patient averagely. In total, 82% of the recordings performed did not require any intervention, while 18% led to the production of a report and subsequent intervention by a nurse who verified, together with the specialist, the need to intervene (i.e. the patient accessed the clinic for medical control and/or modification of oxygen therapy). A total of 17 patients compiled a usability questionnaire. The service was perceived as useful and well-structured, although it often required caregiver support.ConclusionsUsing continuous home-monitoring care with an oxygen saturation device seems feasible and useful for patients who could be followed at home avoiding going back to the hospital every time a trend oximetry is needed. Further improvements in connections, data flow processes, and simplifications, based on patients’ feedback, are needed to scale up the service.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T07:00:48Z
DOI: 10.1177/20552076231194547
Issue No: Vol. 9 (2023)
- Use of focused computerized cognitive training (Neuroflex) to improve
symptoms in women with persistent chemotherapy-related cognitive
impairment
Authors: Jennifer N. Vega, Paul A. Newhouse, Alexander C. Conley, Sarah M. Szymkowicz, Xuewen Gong, Sarah Cote, Ingrid Mayer, Warren D. Taylor, Sarah Shizuko Morimoto
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
PurposeChemotherapy-related cognitive impairment (CRCI) is a distressing and increasingly recognized long-term sequela reported by breast cancer patients following cancer treatment. There is an urgent but unmet clinical need for treatments that improve CRCI. In this context, we proposed the use of a novel cognitive enhancement strategy called Neuroflex to target CRCI experienced by breast cancer survivors.MethodsThe primary aim of this pilot study was to evaluate the feasibility and acceptability of Neuroflex, a novel digital cognitive enhancement strategy, in breast and gynecologic cancer survivors with CRCI. Secondary analyses focused on whether improvements in performance on Neuroflex were associated with improvement in subjective cognitive complaints and objective cognitive performance measures.ResultsParticipants (N = 21) completed an average of 7.42 hours of Neuroflex training per week, an average of 44.5 (±1.01) hours total, and had a 100% completion rate. Participants exhibited significant improvement in self-reported cognitive function as well as significant improvement on tasks of verbal learning and memory and auditory working memory. Participants also exhibited improvement in mood, as well as improvement on a disability assessment.ConclusionsResults demonstrate feasibility and that breast cancer survivors are capable of completing a lengthy and challenging cognitive training program. Secondly, Neuroflex may confer specific cognitive benefits to both self-reported and objective performance. Results strongly support further investigation of Neuroflex in a larger controlled trial to establish efficacy for CRCI symptoms. Further studies may also result in optimization of this digital intervention for women with CRCI.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T06:59:50Z
DOI: 10.1177/20552076231192754
Issue No: Vol. 9 (2023)
- Assessing cancer-related cognitive function in the context of everyday
life using ecological mobile cognitive testing: A protocol for a
prospective quantitative study
Authors: Ashley M Henneghan, Kathleen M Van Dyk, Robert A Ackerman, Emily W Paolillo, Raeanne C Moore
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveMillions of cancer survivors are at risk for cancer-related cognitive impairment (CRCI), yet accurate and accessible assessments of cognitive functioning remain limited. Ecological mobile cognitive testing (EMCT) could offer a solution. This paper presents the protocol for a study that aims to (1) establish the reliability and validity of EMCT to assess CRCI in breast cancer survivors, and (2) prospectively evaluate within-person processes (and interactions) among context, mood, and behavior that explain cognitive variability, everyday functioning, and quality of life of cancer survivors.MethodsParticipants will include breast cancer survivors (>21 years old) who are within 5 years of completing chemotherapy treatment. Participants will complete two virtual visits (baseline, follow-up) 2 months apart to assess self-reported cognitive symptoms and cognitive performance, sociodemographic characteristics, clinical history, everyday functioning, and quality of life. Between virtual visits, EMCT will be used to sample cognitive functioning every other day (28 times total). We will use linear mixed-effect regressions and single-level multiple regression models to analyze the data.ResultsWe anticipate a minimum of 124 breast cancer survivors enrolling and completing data collection. Study results will be published in peer-reviewed scientific journals.ConclusionsOur findings will have broad implications for assessing CRCI in an ecologically valid and person-centered way using EMCT. We aim to provide this protocol to aid researchers who would like to apply this approach to their studies.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T05:10:08Z
DOI: 10.1177/20552076231194944
Issue No: Vol. 9 (2023)
- Deep learning-enhanced diabetic retinopathy image classification
Authors: Ghadah Alwakid, Walaa Gouda, Mamoona Humayun, Noor Zaman Jhanjhi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDiabetic retinopathy (DR) can sometimes be treated and prevented from causing irreversible vision loss if caught and treated properly. In this work, a deep learning (DL) model is employed to accurately identify all five stages of DR.MethodsThe suggested methodology presents two examples, one with and one without picture augmentation. A balanced dataset meeting the same criteria in both cases is then generated using augmentative methods. The DenseNet-121-rendered model on the Asia Pacific Tele-Ophthalmology Society (APTOS) and dataset for diabetic retinopathy (DDR) datasets performed exceptionally well when compared to other methods for identifying the five stages of DR.ResultsOur propose model achieved the highest test accuracy of 98.36%, top-2 accuracy of 100%, and top-3 accuracy of 100% for the APTOS dataset, and the highest test accuracy of 79.67%, top-2 accuracy of 92.%76, and top-3 accuracy of 98.94% for the DDR dataset. Additional criteria (precision, recall, and F1-score) for gauging the efficacy of the proposed model were established with the help of APTOS and DDR.ConclusionsIt was discovered that feeding a model with higher-quality photographs increased its efficiency and ability for learning, as opposed to both state-of-the-art technology and the other, non-enhanced model.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T05:09:29Z
DOI: 10.1177/20552076231194942
Issue No: Vol. 9 (2023)
- Computer habits and digital literacy in geriatric patients: A survey
Authors: Bodil B Jørgensen, Merete Gregersen, Søren H Pallesen, Else Marie S Damsgaard
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveAmong hospitalised geriatric patients, only half are computer users. However, many of them refrain from using telehealth solutions. This study aimed to investigate geriatric patients’ computer and Internet habits and digital literacy and their associations with stress levels and frequency of Internet use.MethodsInpatients and outpatients aged 65 years or older, all computer users, were consecutively surveyed. Besides information about computer and Internet habits, computer support, and computer stress, the survey also collected information about digital literacy using the electronic Health Literacy Assessment toolkit.ResultsA total of 124 computer users with a mean age of 80.6 ± 7.4 years participated in the study from 1 October to 1 December 2019. Most patients received computer support from their children and grandchildren, whereas 6% did not seek support. They found themselves ‘most familiar with using a keyboard’ (79%), 59% ‘were unfamiliar with the Copy Paste function’, and only one-third ‘were open to new ways of using computers’. Digital literacy was associated with the frequency of Internet use (P = 0.001), and higher digital literacy was associated with less computer stress (P = 0.01).ConclusionsGeriatric computer users are challenged by their basic computer skills, which may influence their choice of participation in telehealth solutions. If telehealth solutions are to succeed among geriatric patients, individualised computer support based on their basic computer skills and user-friendly computer devices are a prerequisite. For ongoing support, it is also necessary to introduce people close to the patient to telehealth solutions.
Citation: DIGITAL HEALTH
PubDate: 2023-08-14T05:05:30Z
DOI: 10.1177/20552076231191004
Issue No: Vol. 9 (2023)
- Ukraine refugee health screening service in Wales Ukraine/Powys case study
2022 by Powys Teaching Health Board and technology-enabled care Cymru
Authors: Megan Whistance, Bronwen Thomas, Gemma Johns, Alka Ahuja, Mike Ogonovsky, Sara Khalil, Tracey Johns
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The development of the new health screening service for Ukraine Refugees put in place by Powys Teaching Health Board in 2022 has seen extensive use from Ukrainian families in need of extra support from the National Health Service (NHS) and signposting to specific NHS departments. To discuss the experiences of the staff from Powys regarding their role in setting up the screening service and working within it, Research Assistants from Technology Enabled Care, Wales conducted interviews with two staff members. These clinical leads suggested improvements for the screening service, as captured through analysing the data collected via the interviews. This included recognition of benefits, challenges and future recommendations.
Citation: DIGITAL HEALTH
PubDate: 2023-08-11T10:10:28Z
DOI: 10.1177/20552076231191890
Issue No: Vol. 9 (2023)
- Ehealth and lifestyle change: The mediating roles of social support and
patient empowerment
Authors: Piper Liping Liu, Yu Zheng, Xinshu Zhao
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThe purpose of this study was to investigate the impact of eHealth, the use of information and communications technologies to improve or enable health and health care, on lifestyle behaviors through social support and patient empowerment as serial mediators.MethodsWe conducted an anonymous online survey of 29 items in October 2019 to assess Chinese people's eHealth activities (i.e. engaging in online health-related activities), social support (including emotional and instrumental support) and patient empowerment, for a lifestyle change. A total of 681 respondents aged 18 or above (49.9% males) with an average age of 30.8 completed the survey.ResultsSocial support (including emotional and instrumental support) and patient empowerment were found to be salient mediators between eHealth and lifestyle behaviors. Specifically, engaging in eHealth activities can improve both perceived emotional support and instrumental support from care networks, of which both would increase patient empowerment, which subsequently prompted healthy lifestyle behaviors (β = .01, confidence interval (CI): [.003, .013] for emotional support as the first mediator; β
Citation: DIGITAL HEALTH
PubDate: 2023-08-11T10:06:48Z
DOI: 10.1177/20552076231191974
Issue No: Vol. 9 (2023)
- Machine learning-based prognostic modeling of patients with acute heart
failure receiving furosemide in intensive care units
Authors: Tadashi Kamio, Masaru Ikegami, Yoshihito Machida, Tomoko Uemura, Naotaka Chino, Masao Iwagami
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
PurposeThis study developed machine learning models to predict in-hospital mortality, initiation of acute renal replacement therapy, and mechanical ventilation in patients with acute heart failure receiving furosemide in intensive care units.MethodAn extensive database comprising static and dynamic features obtained from a Japanese hospital chain was used to construct and train the machine learning models.ResultsThe results revealed that the proposed machine learning models predict in-hospital mortality, initiation of acute renal replacement therapy, and mechanical ventilation with good accuracy. However, the optimal models vary depending on the predicted outcomes. The linear support vector machine classification models exhibited the highest in-hospital mortality and mechanical ventilation prediction accuracy, with the area under the receiver operating characteristic curve of 0.73 and 0.73, respectively, whereas the multi-layer neural network exhibited the highest accuracy for acute renal replacement therapy initiation prediction with an area under the receiver operating characteristic curve of 0.70.ConclusionsIn conclusion, this study demonstrated that machine learning models could help predict the clinical outcomes of patients with acute heart failure receiving furosemide. However, the optimal models may differ depending on the outcome of interest.
Citation: DIGITAL HEALTH
PubDate: 2023-08-11T07:00:44Z
DOI: 10.1177/20552076231194933
Issue No: Vol. 9 (2023)
- A SuperLearner-enforced approach for the estimation of treatment effect in
pediatric trials
Authors: Danila Azzolina, Rosanna Comoretto, Liviana Da Dalt, Silvia Bressan, Dario Gregori
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundRandomized Clinical Trials (RCT) represent the gold standard among scientific evidence. RCTs are tailored to control selection bias and the confounding effect of baseline characteristics on the effect of treatment. However, trial conduction and enrolment procedures could be challenging, especially for rare diseases and paediatric research. In these research frameworks, the treatment effect estimation could be compromised. A potential countermeasure is to develop predictive models on the probability of the baseline disease based on previously collected observational data. Machine learning (ML) algorithms have recently become attractive in clinical research because of their flexibility and improved performance compared to standard statistical methods in developing predictive models.ObjectiveThis manuscript proposes an ML-enforced treatment effect estimation procedure based on an ensemble SuperLearner (SL) approach, trained on historical observational data, to control the confounding effect.MethodsThe REnal SCarring Urinary infEction trial served as a motivating example. Historical observational study data have been simulated through 10,000 Monte Carlo (MC) runs. Hypothetical RCTs have been also simulated, for each MC run, assuming different treatment effects of antibiotics combined with steroids. For each MC simulation, the SL tool has been applied to the simulated observational data. Furthermore, the average treatment effect (ATE), has been estimated on the trial data and adjusted for the SL predicted probability of renal scar.ResultsThe simulation results revealed an increased power in ATE estimation for the SL-enforced estimation compared to the unadjusted estimates for all the algorithms composing the ensemble SL.
Citation: DIGITAL HEALTH
PubDate: 2023-08-07T08:01:47Z
DOI: 10.1177/20552076231191967
Issue No: Vol. 9 (2023)
- Patient and parent perspectives on the utility of telemedicine for initial
surgical gender care consultations: A cross-sectional survey
Authors: Joseph A Martínez, Baraa Hijaz, Sangeeta Subedi, Elizabeth R Boskey, Oren Ganor
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionThe COVID-19 pandemic has expanded the use of telemedicine to patient populations that were previously constrained to in-person visits. Few studies have investigated the role that telemedicine plays in shaping the care of these patient populations. This project explores the impact of telemedicine for one such population: patients and parents of gender-diverse individuals seeking gender-affirming surgery.MethodsA 10-question survey using previously validated questions was completed by 34 patients and 9 parents of patients (aged 15–31) who received virtual care at the Center for Gender Surgery at Boston Children's Hospital between March 2020 and April 2021. The survey was divided into two parts. The first section collected demographic information. The second assessed participant perspectives on remote surgical gender care through a series of Likert-type and open-ended questions.ResultsA total of 100% of the respondents felt that their telemedicine visit was convenient; 60% (18) of the patients and 87% (7) of the parents stated that they look forward to future use of this modality. Free responses highlighted common perspectives on remote surgical gender care, including the increased accessibility of gender-affirming care through telehealth, the limitations of telehealth for addressing physical and relational aspects of gender care, patients’ desire for autonomy and privacy during telehealth visits, and parents’ desire to be involved throughout their children's gender journey.ConclusionThese results demonstrate the unique ability of telemedicine, if implemented thoughtfully, to enhance outcomes for patients seeking surgical gender affirmation.
Citation: DIGITAL HEALTH
PubDate: 2023-08-07T08:00:43Z
DOI: 10.1177/20552076231191619
Issue No: Vol. 9 (2023)
- Australian women's judgements about using artificial intelligence to read
mammograms in breast cancer screening
Authors: Stacy M Carter, Lucy Carolan, Yves Saint James Aquino, Helen Frazer, Wendy A Rogers, Julie Hall, Chris Degeling, Annette Braunack-Mayer, Nehmat Houssami
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveMammographic screening for breast cancer is an early use case for artificial intelligence (AI) in healthcare. This is an active area of research, mostly focused on the development and evaluation of individual algorithms. A growing normative literature argues that AI systems should reflect human values, but it is unclear what this requires in specific AI implementation scenarios. Our objective was to understand women's values regarding the use of AI to read mammograms in breast cancer screening.MethodsWe ran eight online discussion groups with a total of 50 women, focused on their expectations and normative judgements regarding the use of AI in breast screening.ResultsAlthough women were positive about the potential of breast screening AI, they argued strongly that humans must remain as central actors in breast screening systems and consistently expressed high expectations of the performance of breast screening AI. Women expected clear lines of responsibility for decision-making, to be able to contest decisions, and for AI to perform equally well for all programme participants. Women often imagined both that AI might replace radiographers and that AI implementation might allow more women to be screened: screening programmes will need to communicate carefully about these issues.ConclusionsTo meet women's expectations, screening programmes should delay implementation until there is strong evidence that the use of AI systems improves screening performance, should ensure that human expertise and responsibility remain central in screening programmes, and should avoid using AI in ways that exacerbate inequities.
Citation: DIGITAL HEALTH
PubDate: 2023-08-07T08:00:06Z
DOI: 10.1177/20552076231191057
Issue No: Vol. 9 (2023)
- Medical text classification based on the discriminative pre-training model
and prompt-tuning
Authors: Yu Wang, Yuan Wang, Zhenwan Peng, Feifan Zhang, Luyao Zhou, Fei Yang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Medical text classification, as a fundamental medical natural language processing task, aims to identify the categories to which a short medical text belongs. Current research has focused on performing the medical text classification task using a pre-training language model through fine-tuning. However, this paradigm introduces additional parameters when training extra classifiers. Recent studies have shown that the “prompt-tuning” paradigm induces better performance in many natural language processing tasks because it bridges the gap between pre-training goals and downstream tasks. The main idea of prompt-tuning is to transform binary or multi-classification tasks into mask prediction tasks by fully exploiting the features learned by pre-training language models. This study explores, for the first time, how to classify medical texts using a discriminative pre-training language model called ERNIE-Health through prompt-tuning. Specifically, we attempt to perform prompt-tuning based on the multi-token selection task, which is a pre-training task of ERNIE-Health. The raw text is wrapped into a new sequence with a template in which the category label is replaced by a [UNK] token. The model is then trained to calculate the probability distribution of the candidate categories. Our method is tested on the KUAKE-Question Intention Classification and CHiP-Clinical Trial Criterion datasets and obtains the accuracy values of 0.866 and 0.861. In addition, the loss values of our model decrease faster throughout the training period compared to the fine-tuning. The experimental results provide valuable insights to the community and suggest that prompt-tuning can be a promising approach to improve the performance of pre-training models in domain-specific tasks.
Citation: DIGITAL HEALTH
PubDate: 2023-08-07T06:55:45Z
DOI: 10.1177/20552076231193213
Issue No: Vol. 9 (2023)
- A survey of artificial intelligence in tongue image for disease diagnosis
and syndrome differentiation
Authors: Qi Liu, Yan Li, Peng Yang, Quanquan Liu, Chunbao Wang, Keji Chen, Zhengzhi Wu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The rapid development of artificial intelligence technology has gradually extended from the general field to all walks of life, and intelligent tongue diagnosis is the product of a miraculous connection between this new discipline and traditional disciplines. We reviewed the deep learning methods and machine learning applied in tongue image analysis that have been studied in the last 5 years, focusing on tongue image calibration, detection, segmentation, and classification of diseases, syndromes, and symptoms/signs. Introducing technical evolutions or emerging technologies were applied in tongue image analysis; as we have noticed, attention mechanism, multiscale features, and prior knowledge were successfully applied in it, and we emphasized the value of combining deep learning with traditional methods. We also pointed out two major problems concerned with data set construction and the low reliability of performance evaluation that exist in this field based on the basic essence of tongue diagnosis in traditional Chinese medicine. Finally, a perspective on the future of intelligent tongue diagnosis was presented; we believe that the self-supervised method, multimodal information fusion, and the study of tongue pathology will have great research significance.
Citation: DIGITAL HEALTH
PubDate: 2023-08-07T06:54:19Z
DOI: 10.1177/20552076231191044
Issue No: Vol. 9 (2023)
- Medical journals and advertiser tracking—Consequences for patients,
clinicians, and editors
Authors: Ravi Gupta, Ari B Friedman, Matthew S McCoy
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Medical journal websites frequently contain tracking code that transfers data about journal readers to third parties. These data give drug, device, and other medical product companies a potentially powerful resource for targeting advertisements and other marketing materials to journal readers based on unique attributes and medical interests that can be inferred from the articles they read. Thus, while editors may strictly regulate the content of advertisements that such companies place in their journals’ pages, they simultaneously provide those companies with the means to target readers in other forums, possibly in ways that subvert editorial guidelines. We examine the implications of third-party tracking on medical journal webpages, and recommend actions that publishers, editors, and academic societies can take to curb it.
Citation: DIGITAL HEALTH
PubDate: 2023-08-07T06:52:38Z
DOI: 10.1177/20552076231176654
Issue No: Vol. 9 (2023)
- The behaviour change behind a successful pilot of hypoglycaemia reduction
with HYPO-CHEAT
Authors: Chris Worth, Paul W Nutter, Maria Salomon-Estebanez, Sameera Auckburally, Mark J Dunne, Indraneel Banerjee, Simon Harper
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundChildren with hypoglycaemia disorders, such as congenital hyperinsulinism (CHI), are at constant risk of hypoglycaemia (low blood sugars) with the attendant risk of brain injury. Current approaches to hypoglycaemia detection and prevention vary from fingerprick glucose testing to the provision of continuous glucose monitoring (CGM) to machine learning (ML) driven glucose forecasting. Recent trends for ML have had limited success in preventing free-living hypoglycaemia, due to a focus on increasingly accurate glucose forecasts and a failure to acknowledge the human in the loop and the essential step of changing behaviour. The wealth of evidence from the fields of behaviour change and persuasive technology (PT) allows for the creation of a theory-informed and technologically considered approach.ObjectivesWe aimed to create a PT that would overcome the identified barriers to hypoglycaemia prevention for those with CHI to focus on proactive prevention rather than commonly used reactive approaches.MethodsWe used the behaviour change technique taxonomy and persuasive systems design models to create HYPO-CHEAT (HYpoglycaemia-Prevention-thrOugh-Cgm-HEatmap-Assisted-Technology): a novel approach that presents aggregated CGM data in simple visualisations. The resultant ease of data interpretation is intended to facilitate behaviour change and subsequently reduce hypoglycaemia.ResultsHYPO-CHEAT was piloted in 10 patients with CHI over 12 weeks and successfully identified weekly patterns of hypoglycaemia. These patterns consistently correlated with identifiable behaviours and were translated into both a change in proximal fingerprick behaviour and ultimately, a significant reduction in aggregated hypoglycaemia from 7.1% to 5.4% with four out of five patients showing clinically meaningful reductions in hypoglycaemia.ConclusionsWe have provided pilot data of a new approach to hypoglycaemia prevention that focuses on proactive prevention and behaviour change. This approach is personalised for individual patients with CHI and is a first step in changing our approach to hypoglycaemia prevention in this group.
Citation: DIGITAL HEALTH
PubDate: 2023-08-04T06:36:27Z
DOI: 10.1177/20552076231192011
Issue No: Vol. 9 (2023)
- Cost effectiveness of a telerehabilitation intervention vs home based care
Authors: Aurélie Duruflé, Claire Le Meur, Patrice Piette, Bastien Fraudet, Emilie Leblong, Philippe Gallien
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ContextSeveral options are available for the care of neurological conditions including care delivered in rehabilitation centres, at home or remotely. While economic studies are available comparing centres and homes, very little economic data relates to mobile teams comparing face-to-face and remote care.ObjectiveTo conduct an economic study comparing face-to-face care at home and care delivered remotely (tele-rehabilitation).MethodA randomised clinical study with two groups; a control group receiving home care and an experimental group receiving tele-rehabilitation. The primary outcome measure was the ICER (Incremental Cost Effectiveness Ratio).ParticipantsPatients with severe neurological disabilitiesResults80 patients were enrolled in the study; 77 were analysed to calculate the ICER, which was positive and located in the SW quadrant. A bootstrap with 1000 replications was positioned at 72.8% in the SW quadrant.ConclusionTele-rehabilitation is an acceptable alternative to the management of neurological patients at home. In the mildest cases, remote-rehabilitation may even be dominant. More extensive studies are needed to specify the indications.
Citation: DIGITAL HEALTH
PubDate: 2023-08-04T06:04:08Z
DOI: 10.1177/20552076231191001
Issue No: Vol. 9 (2023)
- Comparison of effectiveness of different training tools on the level of
knowledge about emergency management of avulsed teeth in non-dentists
Authors: Zekiye Şeyma Gümüşboğa, Gülsüm Duruk
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTooth avulsion is a type of trauma requiring an emergency response, and the level of knowledge of non-dentists on the emergency management of avulsed teeth is important for the prognosis of affected teeth. This study aimed to compare the effectiveness of training given using different tools on the level of knowledge about the emergency management of avulsed teeth in non-dentists.MethodsA total of 125 individuals (female, 32.8%; male, 67.2%; mean age, 38.5 ± 7.32 years) participated in the study. The participants were randomly assigned to three groups, and the training was offered to these groups using different training tools (group 1, storybook; group 2, poster; group 3, ToothSOS App). A survey was conducted on all participants to measure their knowledge levels before training (T0), immediately after (T1), and 1 month later (T2). The Mann–Whitney U, Kruskal–Wallis, Wilcoxon, and Friedman tests were used for statistical analysis.ResultsThe participants’ mean correct answer scores on a scale from 0 to 21 were 7.76 ± 4.00, 5.47 ± 4.71, and 7.38 ± 2.96 at T0 in groups 1, 2, and 3, respectively, and their mean scores increased to 14.68 ± 4.10, 13.74 ± 3.28, and 13.86 ± 3.01 at T1 and 13.41 ± 3.34, 12.34 ± 3.77, and 13.66 ± 3.56 at T2. The correct answer scores increased significantly at both T1 and T2 in all groups (p
Citation: DIGITAL HEALTH
PubDate: 2023-08-04T05:45:10Z
DOI: 10.1177/20552076231192148
Issue No: Vol. 9 (2023)
- A predictive decision support system for coronavirus disease 2019 response
management and medical logistic planning
Authors: Sofiane Atek, Filippo Bianchini, Corrado De Vito, Vincenzo Cardinale, Simone Novelli, Cristiano Pesaresi, Marco Eugeni, Massimo Mecella, Antonello Rescio, Luca Petronzio, Aldo Vincenzi, Pasquale Pistillo, Gianfranco Giusto, Giorgio Pasquali, Domenico Alvaro, Paolo Villari, Marco Mancini, Paolo Gaudenzi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveCoronavirus disease 2019 demonstrated the inconsistencies in adequately responding to biological threats on a global scale due to a lack of powerful tools for assessing various factors in the formation of the epidemic situation and its forecasting. Decision support systems have a role in overcoming the challenges in health monitoring systems in light of current or future epidemic outbreaks. This paper focuses on some applied examples of logistic planning, a key service of the Earth Cognitive System for Coronavirus Disease 2019 project, here presented, evidencing the added value of artificial intelligence algorithms towards predictive hypotheses in tackling health emergencies.MethodsEarth Cognitive System for Coronavirus Disease 2019 is a decision support system designed to support healthcare institutions in monitoring, management and forecasting activities through artificial intelligence, social media analytics, geospatial analysis and satellite imaging. The monitoring, management and prediction of medical equipment logistic needs rely on machine learning to predict the regional risk classification colour codes, the emergency rooms attendances, and the forecast of regional medical supplies, synergically enhancing geospatial and temporal dimensions.ResultsThe overall performance of the regional risk colour code classifier yielded a high value of the macro-average F1-score (0.82) and an accuracy of 85%. The prediction of the emergency rooms attendances for the Lazio region yielded a very low root mean square error (
Citation: DIGITAL HEALTH
PubDate: 2023-08-02T06:20:44Z
DOI: 10.1177/20552076231185475
Issue No: Vol. 9 (2023)
- A survey of the knowledge, perceptions of and attitudes to digital health
of healthcare professionals in 14 Bulgarian hospitals: First large-scale
study on digital health in Bulgarian inpatient facilities
Authors: Damyan Petrov, Mila Petrova, Irena Mladenova, Nedko Dimitrov, Galina Mratskova
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo explore the knowledge, perceptions of and attitudes to digital health of Bulgarian hospital professionals in the first study of digital health in this professional group.MethodsA paper-based questionnaire was administered to doctors, trainee doctors, nurses, midwives, and laboratory assistants working in multiprofile or specialized hospitals. Topics included the following: state, objectives, benefits, and future of digital health; data storage, access, security, and sharing; main software used; patient-held Personal Information System (PIS); and telemedicine. A total of 1187 participants from 14 hospitals completed the survey in two phases: September 2013–April 2014 and May 2015–April 2017. Data were analyzed through descriptive statistics and multilevel logistic regression.ResultsThree-quarters of participants evaluated the state of development of digital health in Bulgaria as subpar (36.0% negative; 38.9% passable; 24.5% positive). 27.2% (323) endorsed patients having unconditional access to their data. In contrast, 89.5% (1062) of participants considered it appropriate to have full access to patient data recorded by colleagues. Doctors were more likely to endorse patients having access to their data than healthcare specialists (OR = 1.79 at facility, OR = 1.77 at location). ConclusionThe largely negative or lukewarm attitudes toward the state of development of digital health in Bulgaria are likely to result from the high number of failed projects, unmet expectations, misunderstood benefits, and unforeseen challenges. This study provides a much-needed stimulus and baseline for researching the ways in which the digital health landscape in Bulgaria has matured—or not.
Citation: DIGITAL HEALTH
PubDate: 2023-08-02T06:19:25Z
DOI: 10.1177/20552076231185276
Issue No: Vol. 9 (2023)
- Feasibility of wearable devices and machine learning for sleep
classification in children with Rett syndrome: A pilot study
Authors: Miroslava Migovich, Akshith Ullal, Cary Fu, Sarika U Peters, Nilanjan Sarkar
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Sleep is vital to many processes involved in the well-being and health of children; however, it is estimated that 80% of children with Rett syndrome suffer from sleep disorders. Caregiver reports and questionnaires, which are the current method of studying sleep, are prone to observer bias and missed information. Polysomnography is considered the gold standard for sleep analysis but is labor and cost-intensive and limits the frequency of data collection for sleep disorder studies. Wearable digital health technologies, such as actigraphy devices, have shown potential and feasibility as a method for sleep analysis in Rett syndrome, but have not been validated against polysomnography. Furthermore, the collected accelerometer data has limitations due to the rigidity, periodic limb movement, and involuntary muscle contractions prevalent in Rett syndrome. Heart rate and electrodermal activity, along with other physiological signals, have been linked to sleep stages and can be utilized with machine learning to provide better resistance to noise and false positives than actigraphy. This research aims to address the gap in Rett syndrome sleep analysis by comparing the performance of a machine learning model utilizing both accelerometer data and physiological data features to the gold-standard polysomnography for sleep analysis in Rett syndrome. Our analytical validation pilot study ([math] = 7) found that using physiological and accelerometer features, our machine learning models can differentiate between awake, non-rapid eye movement sleep, and rapid eye movement sleep in Rett syndrome children with an accuracy of 85.1% when using an individual model. Additionally, this work demonstrates that it is feasible to use digital health technologies in Rett syndrome, even at a young age, without data loss or interference from repetitive movements that are characteristic of Rett syndrome.
Citation: DIGITAL HEALTH
PubDate: 2023-08-02T05:23:14Z
DOI: 10.1177/20552076231191622
Issue No: Vol. 9 (2023)
- The challenges of telephone consultation program during severe acute
respiratory syndrome-coronavirus-2 epidemic in Iran: A qualitative study
Authors: Javad Moghri, Fatemeh Kokabisaghi, Seyed Saeid Tabatabaee, Hasan Niroumand Sadabad
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionWith the spread of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) disease and its potential risks for vulnerable groups such as the elderly with chronic diseases, telehealth appointments gained more attention around the world. However, using such a system brought about challenges to patients and service providers that need to be addressed by policymakers for system improvement.PurposeThe present study was conducted with the aim of investigating the challenges of the telephone consultation program, which was run by the Social Security Insurance Organization of Iran during the epidemic of SARS-CoV-2.MethodsThis qualitative study was conducted through semi-structured interviews with physicians who participated in the program, using a purposive sampling approach. The interviews were recorded, transcribed verbatim, and analyzed through conventional content analysis by ATLAS.ti9 software.FindingsBased on the results of the qualitative content analysis, the challenges in three categories, including program development, implementation, and evaluation and monitoring, and with 10 themes (planning challenges, infrastructure provision, education and culture building, legal issues, motivational mechanisms, effective communication, efficiency, and effectiveness of care, organization, monitoring, and evaluation) and 26 sub-themes were extracted.ConclusionTelephone appointments allow medical centers to serve some patients better. However, properly implementing the telephone consultation program requires better planning, training, appropriate infrastructure, and continuous evaluation and improvement of processes.
Citation: DIGITAL HEALTH
PubDate: 2023-08-01T06:23:13Z
DOI: 10.1177/20552076231191041
Issue No: Vol. 9 (2023)
- Improving clinical trial recruitment with warm transfers
Authors: Kyle Peer, Jonathan Cotliar, Andrew Goulian
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
During recruitment for a large, decentralized clinical trial for high-risk individuals with COVID-19, respondents were either transferred in real-time to a clinical research coordinator (i.e. warm transfer), or a callback time was arranged. A retrospective analysis was conducted on 2341 respondents comparing the rate of enrollment among those who were warm-transferred and those for whom a callback was arranged. A respondent who warm-transferred was significantly more likely to enroll in the clinical trial.
Citation: DIGITAL HEALTH
PubDate: 2023-07-31T10:45:35Z
DOI: 10.1177/20552076231191315
Issue No: Vol. 9 (2023)
- The effect of digitalization on service orientation and service perception
among Israeli healthcare professionals: A qualitative study
Authors: Lior Naamati-Schneider
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveHealthcare systems globally are adapting to rapid changes, including digitalization, to thrive. The main objective of this study is to investigate the impact of adapting to rapid changes, including embracing digitalization on the services provided by healthcare organizations, by mapping the healthcare professionals’ perceptions and characterizing their experiences, as well as examining the difficulties and barriers they face in transforming their organization.MethodsThis qualitative study, based on semi-structured in-depth interviews with 38 healthcare professionals, examines the impact of embracing digitalization in service and clinical care and their perception of service. Interviews were analyzed using a categorial deductive and inductive approach across three levels.ResultsEight main themes arose from the analysis: The need for change, The importance of change, Communication, Training, Competitive leverage, Challenges and barriers and Implications for patient–therapist relationship. The themes and subthemes were examined through the three levels of organizational change—the system, the organization, and the personal level. The results of the study indicate limited embrace of change within the systemic and organizational levels and inconsistencies across the three levels. The study also highlights the barriers and difficulties that stand in the way of these processes of change and development.ConclusionsTo ensure successful implementation, these processes require systemic planning, including budgeting for personnel training, organizational adjustments, and technological equipment. Additionally, addressing personal-level considerations such as relevant training and setting boundaries for caregivers is crucial to prevent burnout. Effective planning and management of these changes will facilitate optimal assimilation and enhance system efficiency.
Citation: DIGITAL HEALTH
PubDate: 2023-07-31T03:43:41Z
DOI: 10.1177/20552076231191892
Issue No: Vol. 9 (2023)
- CYBER-AIDD: A novel approach to implementing improved cyber security
resilience for large Australian healthcare providers using a Unified
Modelling Language ontology
Authors: Martin Dart, Mohiuddin Ahmed
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
PurposeThis paper proposes a novel cyber security risk governance framework and ontology for large Australian healthcare providers, using the structure and simplicity of the Unified Modelling Language (UML). This framework is intended to mitigate impacts from the risk areas of: (1) cyber-attacks, (2) incidents, (3) data breaches, and (4) data disclosures.MethodsUsing a mixed-methods approach comprised of empirical evidence discovery and phenomenological review, existing literature is sourced to confirm baseline ontological definitions. These are supplemented with Australian government reports, professional standards publications and legislation covering cyber security, data breach reporting and healthcare governance. Historical examples of healthcare cyber security incidents are reviewed, and a cyber risk governance UML presented to manage the defined problem areas via a single, simplified ontological diagram.ResultsA clear definition of ‘cyber security’ is generated, along with the ‘CYBER-AIDD’ risk model. Specific examples of cyber security incidents impacting Australian healthcare are confirmed as N = 929 over 5 years, with human factors the largest contributor. The CYBER-AIDD UML model presents a workflow across four defined classes, providing a clear approach to implementing the controls required to mitigate risks against verified threats.ConclusionsThe governance of cyber security in healthcare is complex, in part due to a lack of clarity around key terms and risks, and this is contributing to consistently poor operational outcomes. A focus on the most essential avenues of risk, using a simple UML model, is beneficial in describing these risks and designing governance controls around them.
Citation: DIGITAL HEALTH
PubDate: 2023-07-31T03:43:03Z
DOI: 10.1177/20552076231191095
Issue No: Vol. 9 (2023)
- The deep learning algorithm estimates chest radiograph-based sex and age
as independent risk factors for future cardiovascular outcomes
Authors: Hao-Chun Liao, Chin Lin, Chih-Hung Wang, Wen-Hui Fang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesChest X-rays (CXRs) convey much illegible physiological information that deep learning model (DLM) has been reported interpreting successfully. Since the electrocardiogram age established by DLM was revealed as a heart biological marker, we hypothesize that CXR age has similar potential to describe the heart and lung states. Therefore, we developed a DLM to predict sex and age through CXR and analyzed its relation with future cardiovascular diseases (CVD).MethodsA total of 90,396 CXRs aged 20 to 90 were collected and separated into a development set with 53,102 CXRs and demographic information pairs, a tuning set with 7073 pairs, an internal validation set with 17,364 pairs, and an external validation set with 12,857 pairs. The study trained DLM with development set for estimating age and sex and compared them to actual information.ResultsThe mean absolute errors of predicted age were 4.803 and 4.313 years in the internal and external validation sets, respectively. The area under the curve of sex analysis was 0.9993 and 0.9988 in the internal and external validation sets, respectively. Patients whose CXR age was 5 years older than chronologic age lead to higher risk of all-cause mortality (hazard ratio (HR): 2.42, 95% confidence interval (CI): 2.00–2.92), cardiovascular (CV)-cause mortality (HR: 7.57, 95% CI: 4.55–12.60), new-onset heart failure (HR: 2.07, 95% CI: 1.56–2.76), new-onset chronic kidney disease (HR: 1.73, 95% CI: 1.46–2.05), new-onset acute myocardial infarction (HR: 1.80, 95% CI: 1.12–2.92), new-onset stroke (HR: 1.45, 95% CI: 1.10–1.90), new-onset coronary artery disease (HR: 1.26, 95% CI: 1.04–1.52), and new-onset atrial fibrillation (HR: 1.43, 95% CI: 1.01–2.02).ConclusionsUsing DLM to predict CXR age provided additional information for future CVDs. Older CXR age is an accessible risk classification tool for clinician use.
Citation: DIGITAL HEALTH
PubDate: 2023-07-28T07:38:17Z
DOI: 10.1177/20552076231191055
Issue No: Vol. 9 (2023)
- Digital health technologies supporting the application of comprehensive
geriatric assessments in long-term care settings or community care: A
systematic review
Authors: Mauricio Molinari-Ulate, Aysan Mahmoudi, Esther Parra-Vidales, Juan-Luis Muñoz-Sánchez, Manuel A Franco-Martín, Henriëtte G van der Roest
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo provide high-quality elderly care, digital health technologies (DHTs) can potentially assist in reaching the full capacity of comprehensive geriatric assessments (CGAs) to improve communication and data transfer on patients’ medical and treatment plan information and health decision-making. This systematic review aimed to describe the evidence on the feasibility and usability, efficacy and effectiveness, and implementation outcomes of DHTs developed to facilitate the administration of CGAs for long-term care settings or community care and to describe their technical features and components.MethodsA search strategy was conducted in three databases, targeting studies evaluating the DHTs facilitating the administration of CGAs used in long-term care settings or community care. Studies in English and Spanish published up to 5 April 2023 were considered.ResultsFour DHTs supporting the administration of the CGAs were identified. Limited information was found on the technical features and required hardware. Some of the barriers identified regarding usability can be overcome with novel technologies; however, training of health professionals on the assessments and staff knowledge regarding the purpose of the data collected are not technology related and need to be addressed.ConclusionsBarriers regarding usability were related to experienced difficulties navigating the software, unstable network connectivity, and length of the assessment. Feasibility obstacles were associated with the lack of training to use the DHT, availability and accessibility to hardware (e.g. laptops), and lack of insight into the clinical benefits of collected data. Further research must focus on these areas to improve the implementation and usefulness of these DHTs.
Citation: DIGITAL HEALTH
PubDate: 2023-07-28T07:37:33Z
DOI: 10.1177/20552076231191008
Issue No: Vol. 9 (2023)
- Development and validation of automated electronic health record data
reuse for a multidisciplinary quality dashboard
Authors: Tom Ebbers, Robert P Takes, Jimmie Honings, Ludi E Smeele, Rudolf B Kool, Guido B van den Broek
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo describe the development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard.Materials and methodsComparative study analyzing a manually extracted and an automatically extracted dataset with 262 patients treated for HNC cancer in a tertiary oncology center in the Netherlands in 2020. The primary outcome measures were the percentage of agreement on data elements required for calculating quality indicators and the difference between indicators results calculated using manually collected and indicators that used automatically extracted data.ResultsThe results of this study demonstrate high agreement between manual and automatically collected variables, reaching up to 99.0% agreement. However, some variables demonstrate lower levels of agreement, with one variable showing only a 20.0% agreement rate. The indicator results obtained through manual collection and automatic extraction show high agreement in most cases, with discrepancy rates ranging from 0.3% to 3.5%. One indicator is identified as a negative outlier, with a discrepancy rate of nearly 25%.ConclusionsThis study shows that it is possible to use routinely collected structured data to reliably measure the quality of care in real-time, which could render manual data collection for quality measurement obsolete. To achieve reliable data reuse, it is important that relevant data is recorded as structured data during the care process. Furthermore, the results also imply that data validation is conditional to development of a reliable dashboard.
Citation: DIGITAL HEALTH
PubDate: 2023-07-28T07:36:37Z
DOI: 10.1177/20552076231191007
Issue No: Vol. 9 (2023)
- The effects of electronic-based lifestyle interventions on nonalcoholic
fatty liver disease: A systematic review
Authors: Najmeh Seifi, Hossein Bahari, Sanaz Soltani, Mahya Nikoumanesh, Mojtaba Hajipoor, Gordon A. Ferns, Majid Ghayour-Mobarhan
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveLifestyle interventions are increasingly becoming an integrated part of nonalcoholic fatty liver disease (NAFLD) management. Electronic lifestyle interventions may be able to expand the access and utility of this approach. This study aimed to synthesize the evidence for the effects of electronic-based lifestyle interventions on weight, anthropometric, and liver enzyme measurements in patients with NAFLD.MethodsMedline, Scopus, and Web of Science were searched up to February 2023. Clinical trials investigating the effects of electronic lifestyle interventions on weight, body mass index (BMI), waist circumference (WC), and liver enzymes in NAFLD patients were reviewed. After reviewing full-text articles, seven clinical trials were included in the systematic review.ResultsTwo articles included telephone calls, one was based on text messaging, two studies were based on web-based lifestyle modifications, and two used mobile apps. Except for one, all other six studies indicated a significant impact on weight loss. BMI was reported in six of seven studies. Except for one, BMI was significantly reduced in the group receiving e-health. WC was reported in four studies, which indicated a significant reduction in the e-health intervention group. Alanine transaminase (ALT) was reported in all the included studies. Except for two, others demonstrated a significant improvement in ALT in the e-health intervention groups. As reported in four studies, Aspartate transaminase (AST) significantly decreased in the group receiving e-health interventions, except in one study.ConclusionsThe results support applying electronic lifestyle interventions in NAFLD patients to reduce weight, BMI, WC, AST, and ALT.
Citation: DIGITAL HEALTH
PubDate: 2023-07-28T07:35:59Z
DOI: 10.1177/20552076231187597
Issue No: Vol. 9 (2023)
- Testing a modified electronic version of the Edmonton symptom assessment
system-revised for remote online completion with ambulatory cancer
patients in Alberta, Canada
Authors: Linda Watson, Claire Link, Siwei Qi, Andrea DeIure, Lindsi Chmielewski, April Hildebrand, Louise Smith, Lisa Barbera
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe cancer program in Alberta, Canada routinely collects patient-reported outcomes using the Edmonton symptom assessment system-revised (ESAS-r). The program recently launched the province's new clinical information system which has expanded functionality, allowing patients to complete symptom questionnaires remotely online, instead of completing a paper form at the clinic. This study aimed to test a modified electronic version of the ESAS-r [(e)ESAS-r] with patients, to assess the feasibility of completion and questionnaire clarity.MethodsStaff, patients, and other stakeholders worked to create modified definitions for ESAS-r symptoms, to aid in patient understanding. Patient and family advisors were recruited to test the questionnaire. Participants completed an online mock-up of the (e)ESAS-r and answered questions about technical issues. One-to-one cognitive interviews were held to discuss each symptom definition in detail. Modifications were made based on the feedback and a second round of interviews was held to finalize the wording.ResultsIn total, 19 patients and 7 family advisors participated. All but one (96.2%) completed the questionnaire without assistance and had no technical issues. Participants requested certain wording modifications and that definitions be added for all symptoms for consistency. Very few participants reported any confusion with the final definitions.ConclusionsThe (e)ESAS-r was tested for clarity and ease of completion and was determined to be suitable for remote online use with ambulatory cancer patients. The enhanced definitions on the new questionnaire were clear to patients and helped ensure they understood the meaning of each symptom they were asked to rate.
Citation: DIGITAL HEALTH
PubDate: 2023-07-27T07:53:33Z
DOI: 10.1177/20552076231190998
Issue No: Vol. 9 (2023)
- LWSleepNet: A lightweight attention-based deep learning model for sleep
staging with singlechannel EEG
Authors: Chenguang Yang, Baozhu Li, Yamei Li, Yixuan He, Yuan Zhang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionSleep is vital to human health, and sleep staging is an essential process in sleep assessment. However, manual classification is an inefficient task. Along with the increased demand for portable sleep quality detection devices, lightweight automatic sleep staging needs to be developed.MethodsThis study proposes a novel attention-based lightweight deep learning model called LWSleepNet. A depthwise separable multi-resolution convolutional neural network is introduced to analyze the input feature map and captures features at multiple frequencies using two different sized convolutional kernels. The temporal feature extraction module divides the input into patches and feeds them into a multi-head attention block to extract time-dependent information from sleep recordings. The model's convolution operations are replaced with depthwise separable convolutions to minimize its number of parameters and computational cost. The model's performance on two public datasets (Sleep-EDF-20 and Sleep-EDF-78) was evaluated and compared with those of previous studies. Then, an ablation study and sensitivity analysis were performed to evaluate further each module.ResultsLWSleepNet achieves an accuracy of 86.6% and Macro-F1 score of 79.2% for the Sleep-EDF-20 dataset and an accuracy of 81.5% and Macro-F1 score of 74.3% for the Sleep-EDF-78 dataset with only 55.3 million floating-point operations per second and 180 K parameters.ConclusionOn two public datasets, LWSleepNet maintains excellent prediction performance while substantially reducing the number of parameters, demonstrating that our proposed Light multiresolution convolutional neural network and temporal feature extraction modules can provide excellent portability and accuracy and can be easily integrated into portable sleep monitoring devices.
Citation: DIGITAL HEALTH
PubDate: 2023-07-27T07:53:15Z
DOI: 10.1177/20552076231188206
Issue No: Vol. 9 (2023)
- A systematic review of digital health technologies for the care of older
adults during COVID-19 pandemic
Authors: Chenyu Zou, Abbey Harvard, Jingjing Qian, Brent I Fox
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDuring the Coronavirus Disease 2019 (COVID-19) pandemic, digital health technologies (DHTs) became increasingly important, especially for older adults. The objective of this systematic review was to synthesize evidence on the rapid implementation and use of DHTs among older adults during the COVID-19 pandemic.MethodsA structured, electronic search was conducted on 9 November 2021, and updated on 5 January 2023, among five databases to select DHT interventional studies conducted among older adults during the pandemic. The bias of studies was assessed using Version 2 of the Cochrane Risk-of-Bias Tool for randomized trials (RoB 2) and Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I).ResultsAmong 20 articles included in the review, 14 (70%) focused on older adults with chronic diseases or symptoms, such as dementia or cognitive impairment, type 2 diabetes, and obesity. DHTs included traditional telehealth interventions via telephone, video, and social media, as well as emerging technologies such as Humanoid Robot and Laser acupuncture teletherapy. Using RoB 2 and ROBINS-I, four studies (20%) were evaluated as high or serious overall risk of bias. DHTs have shown to be effective, feasible, acceptable, and satisfactory for older adults during the COVID-19 pandemic compared to usual care. In addition, some studies also highlighted challenges with technology, hearing difficulties, and communication barriers within the vulnerable population.ConclusionsDuring the COVID-19 pandemic, DHTs had the potential to improve various health outcomes and showed benefits for older adults’ access to health care services.
Citation: DIGITAL HEALTH
PubDate: 2023-07-27T05:49:55Z
DOI: 10.1177/20552076231191050
Issue No: Vol. 9 (2023)
- Facilitators and barriers to blood pressure telemonitoring: A
mixed-methods study
Authors: Chinwe E Eze, Michael P Dorsch, Antoinette B Coe, Corey A Lester, Lorraine R Buis, Karen B Farris
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundTelemonitoring of blood pressure (BP) may improve BP control. However, many patients are not using BP telemonitoring due to personal, technological, and health system barriers. Individuals are required to have electronic health literacy (e-HL), defined as knowledge and skills to use technology services effectively, such as BP telemonitoring.ObjectiveThe objective was to determine the facilitators and barriers experienced by patients with hypertension in telemonitoring of BP using the e-HL framework (e-HLF).MethodsThis study was a prospective mixed-methods study using a convergent design. We recruited a convenience sample of 21 patients with hypertension. The qualitative section was online or phone individual in-depth interviews based on the e-HLF, which has seven domains. The quantitative section was an online survey consisting of demographics, an e-HL questionnaire, and patient–provider communication preferences. A joint display was used in the mixed-methods analysis.ResultsFive themes including knowledge, motivation, skills, systems, and behaviors along with 28 subthemes comprising facilitators or barriers of BP telemonitoring were identified. The mixed-methods results showed concordance between the participants’ e-HL status and their experiences in the ability to actively engage with BP monitoring and managing digital services (domain 3) of the e-HLF. Other e-HL domains showed discordance.ConclusionPatients may engage with BP telemonitoring when they feel the usefulness of concurrent access to telemonitoring services that suit their needs.
Citation: DIGITAL HEALTH
PubDate: 2023-07-26T06:46:50Z
DOI: 10.1177/20552076231187585
Issue No: Vol. 9 (2023)
- Relationship between citizens’ perspective on digital health and
underlying health risks
Authors: Esben RG Pedersen, Frantisek Sudzina
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDigital health has been gaining widespread attention but has not been fully integrated into the existing healthcare system. However, it remains unclear whether the new digital health solutions align with users’ needs and wants. This study examines how citizens perceive the functionalities of digital health and how different health risks influence their perception.MethodsUsing an online survey, data are collected from over 4000 Danish citizens. The data are analysed using linear regression models.ResultsThe results show how users’ perceptions of digital health differ significantly. Users are highly interested in data sharing across different healthcare stakeholders but less interested in online health communities. The results also show that the support for digital health is correlated with various health risks, including age, smoking and social network. However, health risks do not have uniform relationship with the perceived value of digital health.ConclusionsWhile developing and implementing new digital health solutions, it is important to consider the perceptions of people who are expected to benefit from such solutions. This study contributes to the literature by deepening the knowledge of how citizens with different risk profiles perceive the multitude of digital health tools being introduced in the healthcare sector.
Citation: DIGITAL HEALTH
PubDate: 2023-07-26T05:41:17Z
DOI: 10.1177/20552076231191045
Issue No: Vol. 9 (2023)
- The scope of metaverse in enhancing telepsychiatry training and digital
literacy among psychiatrists
Authors: Faisal A Nawaz, Wajeeha Bilal, Hira Anas Khan, Ruthwik Duvuru, Hanan Derby, Victor Pereira-Sanchez
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Citation: DIGITAL HEALTH
PubDate: 2023-07-26T05:40:18Z
DOI: 10.1177/20552076231191040
Issue No: Vol. 9 (2023)
- Toward a meta-vaccine future: Promoting vaccine confidence in the
metaverse
Authors: Faisal A Nawaz, Yosra Magdi Mekki, Zoaib Habib Tharwani, Hira Anas Khan, Sean Kaisser Shaeen, Thomas Boillat, Nabil Zary, Susu M Zughaier
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The metaverse has a promising role to serve as a global platform and tackle one of the most intractable public health challenges; vaccine hesitancy. Active efforts in this field can enhance vaccine acceptance thus leading to better community health protection. By embracing digital health innovations, the metaverse potentially creates an interactive environment for interdisciplinary collaborations that can foster novel approaches in tackling vaccine hesitancy as well as future pandemics. This paper aims to highlight the unique areas where the metaverse can enhance vaccination confidence, educate about vaccine working principles, and offer collaborative healthcare initiatives in this virtual community.
Citation: DIGITAL HEALTH
PubDate: 2023-07-24T08:39:58Z
DOI: 10.1177/20552076231171477
Issue No: Vol. 9 (2023)
- Development of pediatric acute care education (PACE): An adaptive
electronic learning (e-learning) environment for healthcare providers in
Tanzania
Authors: Peter Andrew Meaney, Adolfine Hokororo, Theopista Masenge, Joseph Mwanga, Florence Salvatory Kalabamu, Marc Berg, Boris Rozenfeld, Zachary Smith, Neema Chami, Namala Mkopi, Castory Mwanga, Ambrose Agweyu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Globally, inadequate healthcare provider (HCP) proficiency with evidence-based guidelines contributes to millions of newborn, infant, and child deaths each year. HCP guideline proficiency would improve patient outcomes. Conventional (in person) HCP in-service education is limited in 4 ways: reach, scalability, adaptability, and the ability to contextualize. Adaptive e-learning environments (AEE), a subdomain of e-learning, incorporate artificial intelligence technology to create a unique cognitive model of each HCP to improve education effectiveness. AEEs that use existing internet access and personal mobile devices may overcome limits of conventional education. This paper provides an overview of the development of our AEE HCP in-service education, Pediatric Acute Care Education (PACE). PACE uses an innovative approach to address HCPs’ proficiency in evidence-based guidelines for care of newborns, infants, and children. PACE is novel in 2 ways: 1) its patient-centric approach using clinical audit data or frontline provider input to determine content and 2) its ability to incorporate refresher learning over time to solidify knowledge gains. We describe PACE's integration into the Pediatric Association of Tanzania's (PAT) Clinical Learning Network (CLN), a multifaceted intervention to improve facility-based care along a single referral chain. Using principles of co-design, stakeholder meetings modified PACE's characteristics and optimized integration with CLN. We plan to use three-phase, mixed-methods, implementation process. Phase I will examine the feasibility of PACE and refine its components and protocol. Lessons gained from this initial phase will guide the design of Phase II proof of concept studies which will generate insights into the appropriate empirical framework for (Phase III) implementation at scale to examine effectiveness.
Citation: DIGITAL HEALTH
PubDate: 2023-07-24T08:38:58Z
DOI: 10.1177/20552076231180471
Issue No: Vol. 9 (2023)
- Complex interactive multimodal intervention to improve personalized stress
management among healthcare workers in China: A knowledge translation
protocol
Authors: Quan Wang, Jean-Paul Collet, Junhua Mei, Guohua Chen, Sufang Huang, Yuan Yang, Wei Wang, Fengfei Ding
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesNumerous stress management interventions have been implemented in the workplace, but few are adapted to the healthcare setting. Due to the nature of their jobs, healthcare workers (HCWs) may find it difficult to adopt recommended stress management strategies. We present the protocol for a 12-week personalized stress management intervention among HCWs to change their behavior as well as improve physiological/psychological outcomes.MethodsIt is a pragmatic quasi-experimental study involving stressed HCWs from two general hospitals in Wuhan, China. The intervention group will receive a complex interactive multimodal intervention, including advanced education via mobile connection, participation in a web-based social network, tailored feedback, and the support of a nurse coach, while the control group will engage in self-guided stress management.ResultsThe primary outcome is centered on behavioral measures, namely improvements in stress management practice frequency after a 12-week intervention. The secondary outcomes are the changes in stress-related physiological indices (i.e. high frequency variability and normalized unit assessed by Holter) and psychological indicators (scores on the Perceived Stress Scale and Depression, Anxiety, Stress Scale) following 12 weeks of treatment.ConclusionThe knowledge translation intervention builds on a body of work defining the role of individualized instruction and feedback intervention, as well as group intervention through WeChat social network and personalized coaching. We believe this novel intervention will help HCWs promote their stress management awareness and skills, and ultimately benefit their long-term health.Trial RegistrationClinicalTrials.gov., NCT05239065. Registered 14 February 2022—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05239065.
Citation: DIGITAL HEALTH
PubDate: 2023-07-24T08:38:40Z
DOI: 10.1177/20552076231184052
Issue No: Vol. 9 (2023)
- Cardiac surgery risk prediction using ensemble machine learning to
incorporate legacy risk scores: A benchmarking study
Authors: Tim Dong, Shubhra Sinha, Ben Zhai, Daniel P Fudulu, Jeremy Chan, Pradeep Narayan, Andy Judge, Massimo Caputo, Arnaldo Dimagli, Umberto Benedetto, Gianni D Angelini
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe introduction of new clinical risk scores (e.g. European System for Cardiac Operative Risk Evaluation (EuroSCORE) II) superseding original scores (e.g. EuroSCORE I) with different variable sets typically result in disparate datasets due to high levels of missingness for new score variables prior to time of adoption. Little is known about the use of ensemble learning to incorporate disparate data from legacy scores. We tested the hypothesised that Homogenenous and Heterogeneous Machine Learning (ML) ensembles will have better performance than ensembles of Dynamic Model Averaging (DMA) for combining knowledge from EuroSCORE I legacy data with EuroSCORE II data to predict cardiac surgery risk.MethodsUsing the National Adult Cardiac Surgery Audit dataset, we trained 12 different base learner models, based on two different variable sets from either EuroSCORE I (LogES) or EuroScore II (ES II), partitioned by the time of score adoption (1996–2016 or 2012–2016) and evaluated on holdout set (2017–2019). These base learner models were ensembled using nine different combinations of six ML algorithms to produce homogeneous or heterogeneous ensembles. Performance was assessed using a consensus metric.ResultsXgboost homogenous ensemble (HE) was the highest performing model (clinical effectiveness metric (CEM) 0.725) with area under the curve (AUC) (0.8327; 95% confidence interval (CI) 0.8323–0.8329) followed by Random Forest HE (CEM 0.723; AUC 0.8325; 95%CI 0.8320–0.8326). Across different heterogenous ensembles, significantly better performance was obtained by combining siloed datasets across time (CEM 0.720) than building ensembles of either 1996–2011 (t-test adjusted, p = 1.67×10−6) or 2012–2019 (t-test adjusted, p = 1.35×10−193) datasets alone.ConclusionsBoth homogenous and heterogenous ML ensembles performed significantly better than DMA ensemble of Bayesian Update models. Time-dependent ensemble combination of variables, having differing qualities according to time of score adoption, enabled previously siloed data to be combined, leading to increased power, clinical interpretability of variables and usage of data.
Citation: DIGITAL HEALTH
PubDate: 2023-07-21T06:11:45Z
DOI: 10.1177/20552076231187605
Issue No: Vol. 9 (2023)
- Application of artificial intelligence in medical technologies: A
systematic review of main trends
Authors: Olga Vl Bitkina, Jaehyun Park, Hyun K. Kim
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveArtificial intelligence (AI) has been increasingly applied in various fields of science and technology. In line with the current research, medicine involves an increasing number of artificial intelligence technologies. The introduction of rapid AI can lead to positive and negative effects. This is a multilateral analytical literature review aimed at identifying the main branches and trends in the use of using artificial intelligence in medical technologies.MethodsThe total number of literature sources reviewed is n = 89, and they are analyzed based on the literature reporting evidence-based guideline PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for a systematic review.ResultsAs a result, from the initially selected 198 references, 155 references were obtained from the databases and the remaining 43 sources were found on open internet as direct links to publications. Finally, 89 literature sources were evaluated after exclusion of unsuitable references based on the duplicated and generalized information without focusing on the users.ConclusionsThis article is identifying the current state of artificial intelligence in medicine and prospects for future use. The findings of this review will be useful for healthcare and AI professionals for improving the circulation and use of medical AI from design to implementation stage.
Citation: DIGITAL HEALTH
PubDate: 2023-07-19T05:53:42Z
DOI: 10.1177/20552076231189331
Issue No: Vol. 9 (2023)
- Generalizing factors of COVID-19 vaccine attitudes in different regions: A
summary generation and topic modeling approach
Authors: Yang Liu, Jiale Shi, Chenxu Zhao, Chengzhi Zhang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe goal of this study is to use summary generation and topic modeling to identify factors contributing to vaccine attitudes for three different vaccine brands, with the aim of generalizing these factors across different regions.MethodsA total of 5562 tweets about three vaccine brands (Sinovac, AstraZeneca, and Pfizer) were collected from 14 December 2020 to 30 December 2021. BERTopic clustering is used to group the tweets into topics, and then contrastive learning (CL) is adopted to generate summaries of each topic. The main content of each topic is generalized into three factors that contribute to vaccine attitudes: vaccine-related factors, health system-related factors, and individual social attributes.ResultsBERTopic clustering outperforms Latent Dirichlet Allocation clustering in our analysis. It can also be found that using CL for summary generation helped to better model the topics, particularly at the center-point of the clustering. Our model identifies three main factors contributing to vaccine attitudes that are consistent across different regions.ConclusionsOur study demonstrates the effectiveness of deep learning methods for identifying factors contributing to vaccine attitudes in different regions. By determining these factors, policymakers and medical institutions can develop more effective strategies for addressing concerns related to the vaccination process.
Citation: DIGITAL HEALTH
PubDate: 2023-07-19T05:52:42Z
DOI: 10.1177/20552076231188852
Issue No: Vol. 9 (2023)
- Assessment of a wearable fall prevention system at a veterans health
administration hospital
Authors: Thomas F Osborne, Zachary P Veigulis, David M Arreola, Ilya Vrublevskiy, Paola Suarez, Catherine Curtin, Evann Schalch, Rachel C Cabot, Angela Gant-Curtis
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveIn-hospital falls are a significant cause of morbidity and mortality. The Veterans Health Administration (VHA) has designated fall prevention as a major focus area. The objective of this report is to assess the performance of a new sensor-enabled wearable system to prevent patient falls.MethodsAn integrated sensor-enabled wearable SmartSock system was utilized to prevent falls at the acute care wards of a large VA hospital. Individual patients were only provided the SmartSocks when they were determined to be at high risk of falling. All fall count rates, with and without using the SmartSock, were evaluated and compared for individual patients. SmartSock sensor and electronic health record data were combined to assess the system's performance from February 10, 2021, through October 31, 2021.ResultsThere were 20.7 falls per 1000 ward days of care (WDOC) for those not using the SmartSocks compared to 9.2 falls per 1000 WDOC for patients using the SmartSocks. This represents a reduction of falls by more than half. These findings are further confirmed with a negative binomial regression model, which showed the use of the SmartSock had a statistically significant effect on the rate of falls (p = 0.03) when length of stay was held constant and demonstrated the odds of fall incident rate of 0.48 (95% CI, 0.24–0.92), that is less than half compared to when patients were not wearing the SmartSock.ConclusionThe use of a sensor-enabled wearable SmartSock fall prevention system resulted in a clinically meaningful and statistically significant decrease in falls in the acute care setting.
Citation: DIGITAL HEALTH
PubDate: 2023-07-19T05:52:04Z
DOI: 10.1177/20552076231187727
Issue No: Vol. 9 (2023)
- Automatically detecting activities of daily living from in-home sensors as
indicators of routine behaviour in an older population
Authors: Claire M Timon, Pamela Hussey, Hyowon Lee, Catriona Murphy, Harsh Vardan Rai, Alan F Smeaton
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe NEX project has developed an integrated Internet of Things (IoT) system coupled with data analytics to offer unobtrusive health and wellness monitoring supporting older adults living independently at home. Monitoring involves visualising a set of automatically detected activities of daily living (ADLs) for each participant. ADL detection allows the incorporation of additional participants whose ADLs are detected without system re-training.MethodsFollowing a user needs and requirements study involving 426 participants, a pilot trial and a friendly trial of the deployment, an action research cycle (ARC) trial was completed. This involved 23 participants over a 10-week period each with [math]20 IoT sensors in their homes. During the ARC trial, participants took part in two data-informed briefings which presented visualisations of their own in-home activities. The briefings also gathered training data on the accuracy of detected activities. Association rule mining was used on the combination of data from sensors and participant feedback to improve the automatic ADL detection.ResultsAssociation rule mining was used to detect a range of ADLs for each participant independently of others and then used to detect ADLs across participants using a single set of rules for each ADL. This allows additional participants to be added without the necessity of them providing training data.ConclusionsAdditional participants can be added to the NEX system without the necessity to re-train the system for automatic detection of their ADLs.
Citation: DIGITAL HEALTH
PubDate: 2023-07-19T01:36:33Z
DOI: 10.1177/20552076231184084
Issue No: Vol. 9 (2023)
- Effectiveness of a personalized digital exercise and nutrition-based rehab
program for patients with gastric cancer after surgery: Study protocol for
a randomized controlled trial
Authors: Inah Kim, Ji Young Lim, Jong Kwang Kim, Jun Ho Lee, Tae Sung Sohn, Sungsoo Park, Seok Ho Kang, Ji Youl Lee, Ji Hye Hwang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundPatients with gastric cancer often encounter impaired quality of life and reduced tolerability to adjuvant treatments after surgery. Weight preservation is crucial for the overall prognosis of these patients, and exercise and supplemental nutrition play the main role. This study is the first randomized clinical trial to apply personalized, treatment stage-adjusted digital intervention with wearable devices in gastric cancer rehabilitation intervention for 12 months, commencing immediately after surgery.MethodsThis is a prospective, multicenter, two-armed, randomized controlled trial and aims to recruit 324 patients from two hospitals. Patients will be randomly allocated to two groups for 1 year of rehabilitation, starting immediately after the operation: a personalized digital therapeutic (intervention) group and a conventional education-based rehabilitation (control) group. The primary objective is to clarify the effect of mobile applications and wearable smart bands in reducing weight loss in patients with gastric cancer. The secondary outcomes are quality of life measured by the EORTC-QLQ-C30 and STO22; nutritional status by mini nutrition assessment; physical fitness level measured by grip strength test, 30-s chair stand test and 2-min walk test; physical activity measured by IPAQ-SF; pain intensity; skeletal muscle mass; and fat mass. These measurements will be performed on enrollment and at 1, 3, 6, and 12 months thereafter.ConclusionsDigital therapeutic programs include exercise and nutritional interventions modified by age, body mass index, surgery type and postoperative days. Thus, expert intervention is pivotal for precise and safe calibration of this program.Trial registrationClinicaltrials.gov identifier: NCT04907591 (registration date: June 11, 2020; https://clinicaltrials.gov/ct2/show/NCT04907591).
Citation: DIGITAL HEALTH
PubDate: 2023-07-17T07:05:24Z
DOI: 10.1177/20552076231187602
Issue No: Vol. 9 (2023)
- Process model of emotion regulation-based digital intervention for
emotional problems
Authors: Diyang Qu, Dongyu Liu, Chengxi Cai, Xuan Zhang, Jiaao Yu, Quan Zhang, Kunxu Liu, Ziqian Wei, Jiajia Tan, Zaixu Cui, Xiaoqian Zhang, Runsen Chen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundTo address the lack of mental health practitioners in developing countries, the current study explored the feasibility of a newly developed self-guided digital intervention program TEA (training for emotional adaptation) in alleviating depressive and anxiety symptoms, as one of a few studies which adapted from theoretical models with effective intervention techniques.MethodsThe first part of this study involved 11 professional mental health practitioners giving feedback on the feasibility of the TEA; while the second part involved a mixed-method single-arm study with 32 participants recruited online, who went through the seven intervention sessions within 14 days. The questionnaires were collected before, after, 14 days after, and 30 days after intervention. Additionally, 10 participants were invited to semi-structured interviews regarding their suggestions.ResultsPractitioners thought that the TEA showed high professionalism (8.91/10) and is suitable for treating emotional symptoms (8.09/10). The generalized estimating equation model showed that the TEA significantly reduced participants' depressive and anxiety symptoms, while the effects of the intervention remained 30 days post intervention (Cohen's d > 1). Thematic analysis revealed three main themes about future improvement, including content improvement, interaction improvement, and bug-fixing.ConclusionsTo address the current needs for digital mental health intervention programs to account for the insufficient availability of mental health services in China, the current study provides preliminary evidence of the effectiveness of TEA, with the potential to address the urgent need for remote mental health services.Trial registrationThe study was registered at the Chinese Clinical Trial Register (ChiCTR), with number [ChiCTR2200065944].
Citation: DIGITAL HEALTH
PubDate: 2023-07-17T05:29:12Z
DOI: 10.1177/20552076231187476
Issue No: Vol. 9 (2023)
- Development and validation of a quality assessment tool to assess online
nutrition information
Authors: Cassandra H Ellis, J Bernadette Moore, Peter Ho, Charlotte EL Evans
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
SettingThe internet is an important source of health information but is unregulated. Little research has focused on the assessment of digital information related to nutrition.AimTo develop and validate a novel online quality assessment tool (OQAT) for quality assessment of online nutrition information.MethodThe OQAT was developed and validated in six distinct stages. After reviewing the literature, a framework and criteria were developed and formalised. Next, the quality assessment criteria were piloted on a subset of data and criteria refined. The established criteria were then validated against a previously validated assessment tool, and reliability was tested. Finally, the validated OQAT was used to assess the quality of articles from a 24-h collection period, 19 April 2021.ResultsThe final OQAT consisted of 10 key questions. Twenty-six news articles were assessed independently by two raters. Comparison of scores found moderate internal consistency (α = 0.382). Cohen's Kappa coefficient demonstrated high interrater agreement (k = 0.653, p
Citation: DIGITAL HEALTH
PubDate: 2023-07-17T05:07:32Z
DOI: 10.1177/20552076231187249
Issue No: Vol. 9 (2023)
- Enhanced electrocardiogram machine learning-based classification with
emphasis on fusion and unknown heartbeat classes
Authors: Amjed Al-mousa, Joud Baniissa, Tala Hashem, Tala Ibraheem
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Building an electrocardiogram (ECG) heartbeat classification model is essential for early arrhythmia detection. This research aims to build a reliable model that can classify heartbeats into five heartbeat types: normal beat (N), supraventricular ectopic beat (SVEB), ventricular ectopic beat (VEB), fusion beat (F), and unknown beat (Q), with a focus on enhancing the predictions of the uncommon Q and F heartbeats. The base dataset used is the MIT-BIH SupraVentricular Database, which was used to train and compare the performance of five machine learning models: logistic regression, Random Forest (RF), K-nearest neighbor, linear support vector machine, and linear discriminant analysis. In addition to using the synthetic minority oversampling technique, data extracted from multiple databases for the F and Q classes were combined with the original base dataset. These methods resulted in significant improvement in the recall for the rare F and Q classes when compared to the literature. The RF algorithm produced the best performance with an accuracy of 97% and recall values equal to 97%, 93%, 95%, 95%, and 30% for N, SVEB, VEB, F, and Q, respectively.
Citation: DIGITAL HEALTH
PubDate: 2023-07-17T03:15:12Z
DOI: 10.1177/20552076231187608
Issue No: Vol. 9 (2023)
- How did Chinese public health authorities promote COVID-19 vaccination on
social media' A content analysis of the vaccination promotion posts
Authors: Chen Luo, Runtao Dai, Yuying Deng, Anfan Chen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDrawing upon the health belief model, this study aims to analyze the message characteristics of coronavirus disease 2019 (COVID-19) vaccination promotion messages posted by influential Chinese public health institutions and how those characteristics affect audiences’ participative engagement on Weibo, which is a popular social media site in China.MethodsTwo Chinese phrases for the COVID-19 vaccine were adopted as search terms to retrieve qualified posts on Weibo from 1 December 2019 to 18 March 2023. A total of 2546 posts by the top nine most impactful public health institutions were retained for quantitative content analysis. Message characteristics derived from the health belief model and participative engagement indicators were coded by the authors.ResultsAmong health belief model constructs, the collective-oriented constructs (i.e., benefits, cues to action, and susceptibility) appeared in almost half of the posts, while the individual-oriented constructs (i.e., barriers, self-efficacy, and severity) were mentioned less. Moreover, negative binomial regression models revealed that collective-oriented constructs and self-efficacy facilitated engagement, while other constructs played impeding roles.ConclusionsAppearances and functions of the health belief model's constructs in the COVID-19 vaccination promotion context are closely associated with China's collectivistic culture. Furthermore, constructs conforming to people's psychological traits are likely to promote public engagement and may facilitate vaccination behavior.
Citation: DIGITAL HEALTH
PubDate: 2023-07-17T03:12:54Z
DOI: 10.1177/20552076231187474
Issue No: Vol. 9 (2023)
- Effectiveness of pedometer- and accelerometer-based interventions in
improving physical activity and health-related outcomes among college
students: A systematic review and meta-analysis
Authors: Sanying Peng, Ahmad Tajuddin Othman, Ahmad Zamri Khairani, Gao zeng, Zhou Xiaogang, Yuan Fang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAlthough the pedometer- and accelerometer-based interventions (PABI) have demonstrated efficacy in improving physical activity (PA) and health-related outcomes, the dearth of empirical evidence in college students warrants further investigation.ObjectiveThis systematic review and meta-analysis aim to examine the effects of PABI on improving PA and health-related outcomes among college students.MethodsPubMed, Web of Science, Embase, Cochrane Library, and PsycINFO were searched for relevant literature from inception to 20 February 2022. Randomized controlled trials (RCTs) conducted among college students with PABI to increase objectively measured PA as the primary outcome were included in this study.ResultsA total of nine RCTs with 527 participants were included in this study. The combined results showed that PABI significantly improved PA (standardized mean difference = 0.41, 95% confidence interval (CI): 0.08, 0.74, P = 0.016) and significantly contributed to weight loss (mean differences (MD) = −1.56 kg, 95% CI: −2.40 kg, −0.73 kg, P
Citation: DIGITAL HEALTH
PubDate: 2023-07-13T06:32:10Z
DOI: 10.1177/20552076231188213
Issue No: Vol. 9 (2023)
- Smartphone use and well-being in Pakistan: Comparing the effect of
self-reported and actual smartphone use
Authors: Waqas Ejaz, Sacha Altay, Ghazala Naeem
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivePast work has shown that smartphone use has negative effects on well-being. Yet, most evidence relies on self-reported measures of smartphone use and comes from Western democracies. We examined the relationship between both self-reported and actual smartphone use and well-being in Pakistan, a country that is under-researched in the Global South. Additionally, we investigated the moderating effect of the fear of missing out (FoMO).MethodsWe conducted an online survey among 427 Pakistani citizens. Participants reported their smartphone use and well-being (i.e., levels of depression, loneliness, and life satisfaction). At the end of the survey, participants were asked to upload screenshots of their respective ‘Screen Time’ (for iOS) or ‘Digital Well-being’ (for Android) apps, which we used to measure their actual smartphone use.ResultsWe found a moderate association between self-reported and actual smartphone use (r = .36); on average, participants underreported their daily smartphone use by 11 min. Actual smartphone use was negatively associated with well-being, while self-reported use showed no statistically significant association. FoMO was positively associated with actual smartphone use but not with self-reported use. Finally, FoMO moderated the relationship between self-reported use and well-being.ConclusionOur findings show that the relationship between smartphone use and well-being depends on how smartphone use is measured and is moderated by FoMO. Moreover, we find that mobile data donation is viable in Pakistan, which should encourage future research to use it as a complement to self-reported media use more often.
Citation: DIGITAL HEALTH
PubDate: 2023-07-13T06:30:21Z
DOI: 10.1177/20552076231186075
Issue No: Vol. 9 (2023)
- Advancing the digital and computational capabilities of healthcare
providers: A qualitative study of a hospital organisation in the NHS
Authors: John Gardner, Daniel Herron, Nick McNally, Bryan Williams
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveHealthcare systems require transformation to meet societal challenges and projected health demands. Digital and computational tools and approaches are fundamental to this transformation, and hospitals have a key role to play in their development and implementation. This paper reports on a study with the objective of exploring the challenges encountered by hospital leaders and innovators as they implement a strategy to become a data-driven hospital organisation. In doing so, this paper provides guidance to future leaders and innovators seeking to build computational and digital capabilities in complex clinical settings.MethodsInterviews were undertaken with 42 participants associated with a large public hospital organisation within England's National Health Service. Using the concept of institutional readiness as an analytical framework, the paper explores participants’ perspectives on the organisation's capacity to support the development of, and benefit from, digital and computational approaches.ResultsParticipants’ accounts reveal a range of specific institutional readiness criteria relating to organisational vision, technical capability, organisational agility, and talent and skills that, when met, enhance the organisations’ capacity to support the development and implementation of digital and computational tools. Participant accounts also reveal challenges relating to these criteria, such as unrealistic expectations and the necessary prioritisation of clinical work in resource-constrained settings.ConclusionsThe paper identifies a general set of institutional readiness criteria that can guide future hospital leaders and innovators aiming to improve their organisation's digital and computational capability. The paper also illustrates the challenges of pursuing digital and computational innovation in resource-constrained hospital environments.
Citation: DIGITAL HEALTH
PubDate: 2023-07-13T05:03:52Z
DOI: 10.1177/20552076231186513
Issue No: Vol. 9 (2023)
- Feasibility and acceptability testing of CommSense: A novel communication
technology to enhance health equity in clinician–patient interactions
Authors: Virginia LeBaron, Tabor Flickinger, David Ling, Hansung Lee, James Edwards, Anant Tewari, Zhiyuan Wang, Laura E Barnes
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundQuality patient–clinician communication is paramount to achieving safe and compassionate healthcare, but evaluating communication performance during real clinical encounters is challenging. Technology offers novel opportunities to provide clinicians with actionable feedback to enhance their communication skills.MethodsThis pilot study evaluated the acceptability and feasibility of CommSense, a novel natural language processing (NLP) application designed to record and extract key metrics of communication performance and provide real-time feedback to clinicians. Metrics of communication performance were established from a review of the literature and technical feasibility verified. CommSense was deployed on a wearable (smartwatch), and participants were recruited from an academic medical center to test the technology. Participants completed a survey about their experience; results were exported to SPSS (v.28.0) for descriptive analysis.ResultsForty (n = 40) healthcare participants (nursing students, medical students, nurses, and physicians) pilot tested CommSense. Over 90% of participants “strongly agreed” or “agreed” that CommSense could improve compassionate communication (n = 38, 95%) and help healthcare organizations deliver high-quality care (n = 39, 97.5%). Most participants (n = 37, 92.5%) “strongly agreed” or “agreed” they would be willing to use CommSense in the future; 100% (n = 40) “strongly agreed” or “agreed” they were interested in seeing information analyzed by CommSense about their communication performance. Metrics of most interest were medical jargon, interruptions, and speech dominance.ConclusionParticipants perceived significant benefits of CommSense to track and improve communication skills. Future work will deploy CommSense in the clinical setting with a more diverse group of participants, validate data fidelity, and explore optimal ways to share data analyzed by CommSense with end-users.
Citation: DIGITAL HEALTH
PubDate: 2023-07-11T07:03:43Z
DOI: 10.1177/20552076231184991
Issue No: Vol. 9 (2023)
- Usability evaluation of mobile phone technologies for capturing cancer
patient-reported outcomes and physical functions
Authors: Ingrid Oakley-Girvan, Reem Yunis, Stephanie J Fonda, Elad Neeman, Raymond Liu, Sara Aghaee, Maya E Ramsey, Ai Kubo, Sharon W Davis
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundBy eliminating the requirement for participants to make frequent visits to research sites, mobile phone applications (“apps”) may help to decentralize clinical trials. Apps may also be an effective mechanism for capturing patient-reported outcomes and other endpoints, helping to optimize patient care during and outside of clinical trials.ObjectivesWe report on the usability of Digital BioMarkers for Clinical Impact (DigiBioMarC™ (DBM)), a novel smartphone-based app used by cancer patients in conjunction with a wearable device (Apple Watch®). DBM is designed to collect patient-reported outcomes and record physical functions.MethodsIn a fully decentralized “bring-your-own-device” smartphone study, we enrolled 54 cancer patient and caregiver dyads from Kaiser Permanente Northern California (KPNC) from October 2020 through March 2021. Patients used the app for at least 28 days, completed weekly questionnaires about their symptoms, physical functions, and mood, and performed timed physical tasks. Usability was determined through a subset of the Mobile App Rating Scale (MARS), the full System Usability Scale (SUS), the Net Promoter Score (NPS), and semi-structured interviews.ResultsWe obtained usability survey data from 50 of 54 patients. Median responses to the selected MARS questions and the mean SUS scores indicated above average usability. The NPS from the semi-structured interviews at the end of the study was 24, indicating a favorable score.ConclusionsCancer patients reported above average usability for the DBM app. Qualitative analyses indicated that the app was easy to use and helpful. Future work will emphasize implementing further patient recommendations and evaluating the app's clinical efficacy in multiple settings.
Citation: DIGITAL HEALTH
PubDate: 2023-07-11T06:15:42Z
DOI: 10.1177/20552076231186515
Issue No: Vol. 9 (2023)
- Improving people's health by burning low-pollution coal to improve air
quality for thermal power generation
Authors: Tin-Chih Toly Chen, Teng Chieh Chang, Yu-Cheng Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Eliminating the NOx emission after coal combustion is a critical task for thermal power plants to reduce threats to the human body, such as respiratory diseases, heart disease, lung disease and even lung cancer. To this end, various treatments have been taken to optimize, monitor and control the combustion process. However, optimizing the coal composition prior to combustion can further reduce possible NOx emissions. This topic was rarely discussed in the past. To fill this gap, this study proposes a fuzzy big data analytics approach. The proposed methodology combines recursive feature elimination, fuzzy c-means, XG Boost, support vector regression, random forests, decision trees and deep neural networks to predict post-combustion NOx emission based on coal composition and specification. Subsequently, additional treatments can be implemented to optimize boiler configuration and combustion conditions with pollution prevention equipment. In other words, the method proposed in this study is a kind of pretreatment. The proposed methodology has been applied to the real case of a thermal power plant in Taiwan. Experimental results showed that the prediction accuracy using the proposed methodology was significantly better than several existing methods. The forecasting error, measured in terms of root mean square error and mean absolute percentage error, was only 14.55 ppm and 8.9%, respectively.
Citation: DIGITAL HEALTH
PubDate: 2023-07-11T06:15:02Z
DOI: 10.1177/20552076231185280
Issue No: Vol. 9 (2023)
- Virtual versus in-person multidisciplinary musculoskeletal tumor
conferences in times of COVID-19
Authors: Vanessa Hirth, Nikolas Schopow, Jan Pfränger, Elisabeth Roschke, Christoph-Eckhard Heyde, Georg Osterhoff
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionMultidisciplinary tumor conferences are a fundamental component in the treatment of oncological patients. The COVID-19 pandemic and its resulting social distancing restrictions offered the opportunity to compare in-person to virtual multidisciplinary tumor conferences.MethodsRetrospective analysis of first-time presentations in tumor conferences at a university musculoskeletal tumor center in the time periods from September 2019 to February 2020 (in-person) and May 2020 to October 2020 (virtual).ResultsA total of 209 patients were first-time discussed in one of 52 analyzed musculoskeletal multidisciplinary tumor conferences (105 patients in 25 in-person, and 104 patients 27 virtual meetings). The total number of participants was slightly lower with virtual meetings (p
Citation: DIGITAL HEALTH
PubDate: 2023-07-11T06:14:04Z
DOI: 10.1177/20552076231179045
Issue No: Vol. 9 (2023)
- Analysis of the opinions of individuals on the COVID-19 vaccination on
social media
Authors: Akshay Kaushal, Anandadeep Mandal, Diksha Khanna, Animesh Acharjee
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The COVID-19 pandemic continues to threaten public health globally. To develop effective interventions and campaigns to raise vaccination rates, policy makers need to understand people's attitudes towards vaccination. We examine the perspectives of people in India, the United States, Canada, and the United Kingdom on the administration of different COVID-19 vaccines. We analyse how public opinion and emotional tendencies regarding the COVID-19 vaccines relate to popular issues on social media. We employ machine learning algorithms to forecast thoughts based on the social media posts. The prevailing emotional tendency indicates that individuals have faith in immunisation. However, there is a likelihood that significant statements or events on a national, international, or political scale influence public perception of vaccinations. We show how public health officials can track public attitudes and opinions towards vaccine-related information in a geo-aware manner, respond to the sceptics, and increase the level of vaccine trust in a particular region or community.
Citation: DIGITAL HEALTH
PubDate: 2023-07-10T08:52:42Z
DOI: 10.1177/20552076231186246
Issue No: Vol. 9 (2023)
- Mortality risk prediction of the electrocardiogram as an informative
indicator of cardiovascular diseases
Authors: Dung-Jang Tsai, Yu-Sheng Lou, Chin-Sheng Lin, Wen-Hui Fang, Chia-Cheng Lee, Ching-Liang Ho, Chih-Hung Wang, Chin Lin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe electrocardiogram (ECG) may be the most popular test in the management of cardiovascular disease (CVD). Although wide applications of artificial intelligence (AI)-enabled ECG have been developed, an integrating indicator for CVD risk stratification was not investigated. Since mortality may be the most important global outcome, this study aimed to develop a survival deep learning model (DLM) to establish a critical ECG value and explore the associations with various CVD events.MethodsWe trained a DLM with 451,950 12-lead resting ECGs obtained from 210,552 patients, for whom 23,592 events occurred. The internal validation set included 27,808 patients with one ECG for each patient. The external validations were performed in a community hospital with 33,047 patients and two transnational data sets with 233,647 and 1631 ECGs. We distinguished the cause of mortality and additionally investigated CVD-related outcomes, including new-onset acute myocardial infarction (AMI), stroke (STK), and heart failure (HF).ResultsThe DLM achieved C-indices of 0.858/0.836 in internal/external validation sets by using ECG over a 10-year period. The high-mortality-risk group identified by the proposed DLM presented a hazard ratio (HR) of 14.16 (95% confidence interval (CI): 11.33–17.70) compared to the low-risk group in the internal validation and presented a higher risk of cardiovascular (CV) mortality (HR: 18.50, 95% CI: 9.82–34.84), non-CV mortality (HR: 13.68, 95% CI: 10.76–17.38), AMI (HR: 4.01, 95% CI: 2.24–7.17), STK (HR: 2.15, 95% CI: 1.70–2.72), and HF (HR: 6.66, 95% CI: 4.54–9.77), which was consistent in an independent community hospital. The transnational validation also revealed HRs of 4.91 (95% CI: 2.63–9.16) and 2.29 (95% CI: 2.15–2.44) for all-cause mortality in the SaMi-Trop and Clinical Outcomes in Digital Electrocardiography 15% (CODE15) cohorts.ConclusionsThe mortality risk by AI-enabled ECG may be applied in passive electronic-health-record-based CVD risk screening, which may identify more asymptomatic and unaware high-risk patients.
Citation: DIGITAL HEALTH
PubDate: 2023-07-10T08:39:23Z
DOI: 10.1177/20552076231187247
Issue No: Vol. 9 (2023)
- Prediction of intrapartum fever using continuously monitored vital signs
and heart rate variability
Authors: Shubham Debnath, Robert Koppel, Nafeesa Saadi, Debra Potak, Barry Weinberger, Theodoros P Zanos
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesNeonatal early onset sepsis (EOS), bacterial infection during the first seven days of life, is difficult to diagnose because presenting signs are non-specific, but early diagnosis before birth can direct life-saving treatment for mother and baby. Specifically, maternal fever during labor from placental infection is the strongest predictor of EOS. Alterations in maternal heart rate variability (HRV) may precede development of intrapartum fever, enabling incipient EOS detection. The objective of this work was to build a predictive model for intrapartum fever.MethodsContinuously measured temperature, heart rate, and beat-to-beat RR intervals were obtained from wireless sensors on women (n = 141) in labor; traditional manual vital signs were taken every 3–6 hours. Validated measures of HRV were calculated in moving 5-minute windows of RR intervals: standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences (RMSSD) between normal heartbeats.ResultsFever (>38.0 °C) was detected by manual or continuous measurements in 48 women. Compared to afebrile mothers, average SDNN and RMSSD in febrile mothers decreased significantly (p
Citation: DIGITAL HEALTH
PubDate: 2023-07-10T06:49:23Z
DOI: 10.1177/20552076231187594
Issue No: Vol. 9 (2023)
- Digital health for all: How digital health could reduce inequality and
increase universal health coverage
Authors: Steven van de Vijver, Paulien Tensen, Gershim Asiki, Ana Requena-Méndez, Michiel Heidenrijk, Karien Stronks, Frank Cobelens, Jettie Bont, Charles Agyemang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Digital transformation in health care has a lot of opportunities to improve access and quality of care. However, in reality not all individuals and communities are benefiting equally from these innovations. People in vulnerable conditions, already in need of more care and support, are often not participating in digital health programs. Fortunately, numerous initiatives worldwide are committed to make digital health accessible to all citizens, stimulating the long-cherished global pursuit of universal health coverage. Unfortunately initiatives are not always familiar with each other and miss connection to jointly make a significant positive impact. To reach universal health coverage via digital health it is necessary to facilitate mutual knowledge exchange, both globally and locally, to link initiatives and apply academic knowledge into practice. This will support policymakers, health care providers and other stakeholders to ensure that digital innovations can increase access to care for everyone, leading towards Digital health for all.
Citation: DIGITAL HEALTH
PubDate: 2023-07-07T11:14:52Z
DOI: 10.1177/20552076231185434
Issue No: Vol. 9 (2023)
- Electronic health literacy and its association with lifestyle behavior
among undergraduate students: A cross-sectional survey
Authors: Tamadur Shudayfat, Salam Bani Hani, Emad Shdaifat, Khalid Al-Mugheed, Samira Ahmed Alsenany, Sally Mohammed Farghaly Abdelaliem
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThis study aims to assess healthy lifestyle behaviors among undergraduate students and determine the association between electronic health literacy with lifestyle behavior among undergraduate Jordanian university students.MethodsA descriptive cross-sectional design was used. The study recruited 404 participants utilizing undergraduate students from public and private universities. The e-Health literacy scale was used to assess the level of health information literacy among university students.ResultsData were collected from 404 participants who reported very good health status, the majority of the participants were female 57.2% with an average age of 19.3 years. The results showed that participants had good health behavior in terms of exercise, taking breakfast, smoking status, and sleeping status. The results have shown an inadequate level of e-Health literacy 16.61 (SD = 4.10) out of 40. The vast majority of students, in terms of their attitudes toward the Internet, thought that Internet health information was very useful/useful (95.8%). Also, they thought that online health information was very important /important (97.3%). The results showed that students who were attending public universities had higher e-Health literacy scores rather than those who were attending private universities, t (402) = 1.81, p = .014. The mean e-Health literacy score for nonmedical students was higher than those for medical students (p = .022).ConclusionThe study's findings provide important insights into the health behaviors and electronic health literacy of undergraduate students in Jordanian universities, and offer valuable guidance for future health education programs and policies aimed at promoting healthy lifestyles in this population.
Citation: DIGITAL HEALTH
PubDate: 2023-07-07T07:42:58Z
DOI: 10.1177/20552076231185429
Issue No: Vol. 9 (2023)
- An exploratory analysis of the effect size of the mobile mental health
Application, mindLAMP
Authors: Sarah Chang, Noy Alon, John Torous
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesDespite the proliferation of mobile mental health apps, evidence of their efficacy around anxiety or depression is inadequate as most studies lack appropriate control groups. Given that apps are designed to be scalable and reusable tools, insights concerning their efficacy can also be assessed uniquely through comparing different implementations of the same app. This exploratory analysis investigates the potential to report a preliminary effect size of an open-source smartphone mental health app, mindLAMP, on the reduction of anxiety and depression symptoms by comparing a control implementation of the app focused on self-assessment to an intervention implementation of the same app focused on CBT skills.MethodsA total of 328 participants were eligible and completed the study under the control implementation and 156 completed the study under the intervention implementation of the mindLAMP app. Both use cases offered access to the same in-app self-assessments and therapeutic interventions. Multiple imputations were utilized to impute the missing Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 survey scores of the control implementation.ResultsPost hoc analysis revealed small effect sizes of Hedge's g = 0.34 for Generalized Anxiety Disorder-7 and Hedge's g = 0.21 for Patient Health Questionnaire-9 between the two groups.ConclusionsmindLAMP shows promising results in improving anxiety and depression outcomes in participants. Though our results mirror the current literature in assessing mental health apps’ efficacy, they remain preliminary and will be used to inform a larger, well-powered study to further elucidate the efficacy of mindLAMP.
Citation: DIGITAL HEALTH
PubDate: 2023-07-07T07:23:08Z
DOI: 10.1177/20552076231187244
Issue No: Vol. 9 (2023)
- Medical artificial intelligence ethics: A systematic review of empirical
studies
Authors: Lu Tang, Jinxu Li, Sophia Fantus
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundArtificial intelligence (AI) technologies are transforming medicine and healthcare. Scholars and practitioners have debated the philosophical, ethical, legal, and regulatory implications of medical AI, and empirical research on stakeholders’ knowledge, attitude, and practices has started to emerge. This study is a systematic review of published empirical studies of medical AI ethics with the goal of mapping the main approaches, findings, and limitations of scholarship to inform future practice considerations.MethodsWe searched seven databases for published peer-reviewed empirical studies on medical AI ethics and evaluated them in terms of types of technologies studied, geographic locations, stakeholders involved, research methods used, ethical principles studied, and major findings.FindingsThirty-six studies were included (published 2013-2022). They typically belonged to one of the three topics: exploratory studies of stakeholder knowledge and attitude toward medical AI, theory-building studies testing hypotheses regarding factors contributing to stakeholders’ acceptance of medical AI, and studies identifying and correcting bias in medical AI.InterpretationThere is a disconnect between high-level ethical principles and guidelines developed by ethicists and empirical research on the topic and a need to embed ethicists in tandem with AI developers, clinicians, patients, and scholars of innovation and technology adoption in studying medical AI ethics.
Citation: DIGITAL HEALTH
PubDate: 2023-07-07T06:08:29Z
DOI: 10.1177/20552076231186064
Issue No: Vol. 9 (2023)
- ‘My words become my hands’: Yoga instructors’ experiences of
adapting teleyoga in the SAGE fall prevention trial—A qualitative
analysis
Authors: Heidi Gilchrist, Abby Haynes, Juliana S Oliveira, Catherine Sherrington, Lana Clementson, Janetta Glenn, June Jones, Romina Sesto, Anne Tiedemann
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis research identifies practical lessons regarding the delivery of teleyoga. Our objectives are to (1) describe challenges and opportunities experienced by yoga instructors when moving the Successful AGEing (SAGE) yoga programme online, and (2) describe how yoga instructors adapted to manage the challenges and leverage opportunities presented by teleyoga.MethodsThis study is a secondary analysis of the data from a previous realist process evaluation of the SAGE yoga trial. The SAGE yoga trial is testing the effect of a yoga-based exercise programme on falls among 700 community-dwelling people aged 60+ years. We draw on focus groups and interviews with four SAGE yoga instructors which we analysed using previously developed programme theories combined with inductive coding and an analytical workshop.ResultsThe concerns of the yoga instructors about teleyoga can be characterised into four broad issues: threats to safety, altered interpersonal dynamics, facilitating mind–body connection and difficulties with technology. The SAGE instructors identified eight modifications they used to manage these challenges: a 1:1 participant interview prior to programme commencement, more descriptive verbal instructions, increased focus on interoception, increased attention and support, slower more structured class flow, simplifying poses, adapting the studio environment and IT support.ConclusionsWe have created a typology of strategies for addressing challenges in the delivery of teleyoga for older people. As well as maximising engagement with teleyoga, these manageable strategies could be applied by other instructors to a wide range of telehealth classes, improving the uptake and adherence of beneficial online programmes and services.
Citation: DIGITAL HEALTH
PubDate: 2023-07-06T07:59:54Z
DOI: 10.1177/20552076231185273
Issue No: Vol. 9 (2023)
- The relationship between media use and sports participation behavior: A
meta-analysis
Authors: Yu Tian, Pengfei Yang, Desheng Zhang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe use of media profoundly affects people's sports participation behavior. Past research has presented mixed results on the relationship between media use and sports participation behaviors. Therefore, the relationship between media use and sports participation behavior should be revisited.MethodsA meta-analysis of 17 independent studies from 12 literature was conducted to determine whether (a) media use positively influences sports participation behaviors, and (b) form of media, media measurement methods, study subjects, and culture moderated these relationships. Pearson's correlation was used to conduct a random-effects meta-analysis and examine the moderating effects.ResultsThe results showed a positive correlation between media use and sports participation behaviors (r = 0.193, 95% CI = [0.047,0.329]). Traditional media showed stronger correlations and moderating effects than new media; however, the time variable (in media measurement methods) and primary and secondary school students (in study subjects) showed negative correlations between media use and sports participation behavior. The positive and moderating effects on this relationship were higher in Eastern cultures than in Western cultures. These results suggest that media use and sports participation behavior were positively correlated, moderated by the form of media, media measurement methods, study subjects, and culture within studies.ConclusionsFrom the effect test results, a significant positive relationship was found between media use and sports participation behavior (both physical participation behavior and consumption behavior). The two were influenced by several moderating variables including the form of media, media measurement methods, study subjects, and culture, and the influence of media measurement methods was the greatest.
Citation: DIGITAL HEALTH
PubDate: 2023-07-06T06:32:30Z
DOI: 10.1177/20552076231185476
Issue No: Vol. 9 (2023)
- Wearable technology in the sports medicine clinic to guide the
return-to-play and performance protocols of athletes following a COVID-19
diagnosis
Authors: Dhruv R Seshadri, Ethan R Harlow, Mitchell L Thom, Michael S Emery, Dermot M Phelan, Jeffrey J Hsu, Peter Düking, Kristof De Mey, Joseph Sheehan, Benjamin Geletka, Robert Flannery, Jacob G Calcei, Michael Karns, Michael J Salata, Tim J Gabbett, James E Voos
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The coronavirus disease 2019 (COVID-19) pandemic has enabled the adoption of digital health platforms for self-monitoring and diagnosis. Notably, the pandemic has had profound effects on athletes and their ability to train and compete. Sporting organizations worldwide have reported a significant increase in injuries manifesting from changes in training regimens and match schedules resulting from extended quarantines. While current literature focuses on the use of wearable technology to monitor athlete workloads to guide training, there is a lack of literature suggesting how such technology can mediate the return to sport processes of athletes infected with COVID-19. This paper bridges this gap by providing recommendations to guide team physicians and athletic trainers on the utility of wearable technology for improving the well-being of athletes who may be asymptomatic, symptomatic, or tested negative but have had to quarantine due to a close exposure. We start by describing the physiologic changes that occur in athletes infected with COVID-19 with extended deconditioning from a musculoskeletal, psychological, cardiopulmonary, and thermoregulatory standpoint and review the evidence on how these athletes may safely return to play. We highlight opportunities for wearable technology to aid in the return-to-play process by offering a list of key parameters pertinent to the athlete affected by COVID-19. This paper provides the athletic community with a greater understanding of how wearable technology can be implemented in the rehabilitation process of these athletes and spurs opportunities for further innovations in wearables, digital health, and sports medicine to reduce injury burden in athletes of all ages.
Citation: DIGITAL HEALTH
PubDate: 2023-07-06T06:31:30Z
DOI: 10.1177/20552076231177498
Issue No: Vol. 9 (2023)
- Hemolytic-Pred: A machine learning-based predictor for hemolytic proteins
using position and composition-based features
Authors: Gulnaz Perveen, Fahad Alturise, Tamim Alkhalifah, Yaser Daanial Khan
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe objective of this study is to propose a novel in-silico method called Hemolytic-Pred for identifying hemolytic proteins based on their sequences, using statistical moment-based features, along with position-relative and frequency-relative information.MethodsPrimary sequences were transformed into feature vectors using statistical and position-relative moment-based features. Varying machine learning algorithms were employed for classification. Computational models were rigorously evaluated using four different validation. The Hemolytic-Pred webserver is available for further analysis at http://ec2-54-160-229-10.compute-1.amazonaws.com/.ResultsXGBoost outperformed the other six classifiers with an accuracy value of 0.99, 0.98, 0.97, and 0.98 for self-consistency test, 10-fold cross-validation, Jackknife test, and independent set test, respectively. The proposed method with the XGBoost classifier is a workable and robust solution for predicting hemolytic proteins efficiently and accurately.ConclusionsThe proposed method of Hemolytic-Pred with XGBoost classifier is a reliable tool for the timely identification of hemolytic cells and diagnosis of various related severe disorders. The application of Hemolytic-Pred can yield profound benefits in the medical field.
Citation: DIGITAL HEALTH
PubDate: 2023-07-05T07:13:27Z
DOI: 10.1177/20552076231180739
Issue No: Vol. 9 (2023)
- Core stability status classification based on mediolateral head motion
during rhythmic movements and functional movement tests
Authors: Siwoo Jeong, Si-Hyun Kim, Kyue-Nam Park
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveCore stability assessment is paramount for the prevention of low back pain, with core stability being considered as the most critical factor in such pain. The objective of this study was to develop a simple model for the automated assessment of core stability status.MethodsTo assess core stability—defined as the ability to control trunk position relative to the pelvic position - we used an inertial measurement unit sensor embedded within a wireless earbud to estimate the mediolateral head angle during rhythmic movements (RMs) such as cycling, walking, and running. The activities of muscles around the trunk were analyzed by an experienced, highly trained individual. Functional movement tests (FMTs) were performed, including single-leg squat, lunge, and side lunge. Data was collected from 77 participants, who were then classified into good and poor core stability groups based on their Sahrmann core stability test scores.ResultsFrom the head angle data, we extrapolated the symmetry index (SI) and amplitude of mediolateral head motion (Amp). Support vector machine and neural network models were trained and validated using these features. In both models, the accuracy was similar across three feature sets for RMs, FMTs, and full, and support vector machine accuracy (∼87%) is greater than neural network (∼75%).ConclusionThe use of this model, trained with head motion-related features obtained during RMs or FMTs, can help to accurately classify core stability status during activities.
Citation: DIGITAL HEALTH
PubDate: 2023-07-05T05:24:14Z
DOI: 10.1177/20552076231186217
Issue No: Vol. 9 (2023)
- Perceptions of a machine learning-based lower-limb exercise training
system among older adults with knee pain
Authors: Tianrong Chen, Calvin Kalun Or
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo facilitate the older adults with knee pain to perform exercises and improve knee health, we proposed the design of a machine learning-based system for lower-limb exercise training that features three main components: video demonstration of exercises, real-time movement feedback, and tracking of exercise progress. At this early stage of design, we aimed to examine the perceptions of a paper-based prototype among older adults with knee pain and investigate the factors that may influence their perceptions of the system.MethodsA cross-sectional survey of the participants’ (N = 94) perceptions of the system was conducted using a questionnaire, which assessed their perceived effects of the system, perceived ease of use of the system, attitude toward the system, and intention to use the system. Ordinal logistic regression was conducted to examine whether the participants’ perceptions of the system were influenced by their demographic and clinical characteristics, physical activity level, and exercise experience.ResultsThe participants’ responses to the perception statements exhibited consensus agreement (≥ 75%). Age, gender, duration of knee pain, knee pain intensity, experience with exercise therapy, and experience with technology-supported exercise programs were significantly associated with the participants’ perceptions of the system.ConclusionsOur results demonstrate that the system appears promising for use by older adults to manage their knee pain. Therefore, it is needed to develop a computer-based system and further investigate its usability, acceptance, and clinical effectiveness.
Citation: DIGITAL HEALTH
PubDate: 2023-07-04T07:11:19Z
DOI: 10.1177/20552076231186069
Issue No: Vol. 9 (2023)
- How general practitioners and patients discuss type 2 diabetes mellitus
and cardiovascular diseases concerns during consultations: Implications
for digital health
Authors: Urvashi Rohilla, Jayashanthi P Ramarao, Jared Lane, Neha N Khatri, James Smith, Kathleen Yin, Annie YS Lau
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo analyse general practitioner–patient consultations about type 2 diabetes mellitus or cardiovascular diseases and describe (i) the nature of self-management discussions; (ii) actions required from patients during and after consultation regarding self-management; and (iii) implications for digital health to support patients during (and after) consultation.MethodThis study screened 281 general practitioner consultations conducted in 2017 within the UK general practice setting from an existing dataset containing videos and transcripts of consultations between GPs and patients. Secondary analysis was conducted using a multi-method approach, including descriptive, content, and visualisation analysis, to inform the nature of self-management discussions, what actions are required from patients, and whether digital technology was mentioned during the consultation to support self-management.ResultsAnalysis of eligible 19 consultations revealed a discord between what self-management actions are required of patients during and after consultations. Lifestyle discussions are often discussed in depth, but these discussions rely heavily on subjective inquiry and recall. Some patients in these cohorts are overwhelmed by self-management, to the detriment of their personal health. Digital support for self-management was not a major topic of discussion, however, we identified a number of emergent gaps where digital technology can support self-management concerns.ConclusionThere is potential for digital technology to reconcile what actions are required of patients during and after consultations. Furthermore, a number of emergent themes around self-management have implications for digitalisation.
Citation: DIGITAL HEALTH
PubDate: 2023-07-04T07:10:30Z
DOI: 10.1177/20552076231176162
Issue No: Vol. 9 (2023)
- Text classification technique for discovering country-based publications
from international COVID-19 publications
Authors: Farshid Danesh, Meisam Dastani
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe significant increase in the number of COVID-19 publications, on the one hand, and the strategic importance of this subject area for research and treatment systems in the health field, on the other hand, reveals the need for text-mining research more than ever. The main objective of the present paper is to discover country-based publications from international COVID-19 publications with text classification techniques.MethodsThe present paper is applied research that has been performed using text-mining techniques such as clustering and text classification. The statistical population is all COVID-19 publications from PubMed Central® (PMC), extracted from November 2019 to June 2021. Latent Dirichlet allocation (LDA) was used for clustering, and support vector machine (SVM), scikit-learn library, and Python programming language were used for text classification. Text classification was applied to discover the consistency of Iranian and international topics.ResultsThe findings showed that seven topics were extracted using the LDA algorithm for international and Iranian publications on COVID-19. Moreover, the COVID-19 publications show the largest share in the subject area of “Social and Technology in COVID-19” at the international (April 2021) and national (February 2021) levels with 50.61% and 39.44%, respectively. The highest rate of publications at international and national levels was in April 2021 and February 2021, respectively.ConclusionOne of the most important results of this study was discovering a common trend and consistency of Iranian and international publications on COVID-19. Accordingly, in the topic category “Covid-19 Proteins: Vaccine and Antibody Response,” Iranian publications have a common publishing and research trend with international ones.
Citation: DIGITAL HEALTH
PubDate: 2023-07-04T05:57:00Z
DOI: 10.1177/20552076231185674
Issue No: Vol. 9 (2023)
- A pilot project investigating the use of ONCOpatient®—An electronic
patient-reported outcomes app for oncology patients
Authors: Bojan Macanovic, David O’Reilly, Harry Harvey, Danial Hadi, Maeve Cloherty, Pauline O’Dea, Derek G. Power, Dearbhaile C. Collins, Roisin M. Connolly, Richard M. Bambury, Seamus O’Reilly
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
PurposeTo investigate the feasibility of implementing a remote patient monitoring system using an electronic patient-reported outcomes (ePROs) platform in a tertiary cancer center in the Republic of Ireland.MethodsPatients receiving oral chemotherapy and oncology clinicians were invited to participate in the study. Patients were asked to submit weekly symptom questionnaires through an ePRO mobile phone application (app)—ONCOpatient®. Clinical staff were invited to use the ONCOpatient® clinician interface. After 8 weeks all participants submitted evaluation questionnaires.ResultsThirteen patients and five staff were enrolled in the study. The majority of patients were female (85%) with a median age of 48 years (range 22–73). Most (92%) were enrolled over telephone requiring on average 16 minutes. Compliance with the weekly assessments was 91%. Alerts were triggered by 40% of patients who then required phone calls to aid with symptom management. At the end of study, 87% of patients reported they would use the app frequently, 75% reported that the platform met their expectations, and 25% that it exceeded their expectations. Similarly, 100% of staff reported they would use the app frequently, 60% reported that it met their expectations, and 40% that it exceeded their expectations.ConclusionsOur pilot study showed that it is feasible to implement ePRO platforms in the Irish clinical setting. Small sample bias was recognized as a limitation, and we plan to confirm our findings on a larger cohort of patients. In the next phase we will integrate wearables including remote blood pressure monitoring.
Citation: DIGITAL HEALTH
PubDate: 2023-07-03T05:36:29Z
DOI: 10.1177/20552076231185428
Issue No: Vol. 9 (2023)
- Using a complexity science approach to evaluate the effectiveness of
just-in-time adaptive interventions: A meta-analysis
Authors: Zhan Xu, Eline Smit
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveJust-in-time adaptive interventions (JITAIs), which allow individuals to receive the right amount of tailored support at the right time and place, hold enormous potential for promoting behavior change. However, research on JITAIs’ implementation and evaluation is still in its early stages, and more empirical evidence is needed. This meta-analysis took a complexity science approach to evaluate the effectiveness of JITAIs that promote healthy behaviors and assess whether key design principles can increase JITAIs’ impacts.MethodsWe searched five databases for English-language papers. Study eligibility required that interventions objectively measured health outcomes, had a control condition or pre-post-test design, and were conducted in the real-world setting. We included randomized and non-randomized trials. Data extraction encompassed interventions’ features, methodologies, theoretical foundations, and delivery modes. RoB 2 and ROBINS-I were used to assess risk of bias.ResultsThe final analysis included 21 effect sizes with 592 participants. All included studies used pre- and post-test design. A three-level random meta-analytic model revealed a medium effect of JITAIs on objective behavior change (g = 0.77 (95% confidence interval (CI); 0.32 to 1.22), p
Citation: DIGITAL HEALTH
PubDate: 2023-07-03T05:35:19Z
DOI: 10.1177/20552076231183543
Issue No: Vol. 9 (2023)
- Wearable devices in palliative care for people 65 years and older: A
scoping review
Authors: Rada Sandic Spaho, Lisbeth Uhrenfeldt, Theofanis Fotis, Ingjerd Gåre Kymre
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe objective of this scoping review is to map existing evidence on the use of wearable devices in palliative care for older people.MethodsThe databases searched included MEDLINE (via Ovid), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Google Scholar, which was included to capture grey literature. Databases were searched in the English language, without date restrictions. Reviewed results included studies and reviews involving patients aged 65 years or older who were active users of non-invasive wearable devices in the context of palliative care, with no limitations on gender or medical condition. The review followed the Joanna Briggs Institute's comprehensive and systematic guidelines for conducting scoping reviews.ResultsOf the 1,520 reports identified through searching the databases, reference lists, and citations, six reports met our inclusion criteria. The types of wearable devices discussed in these reports were accelerometers and actigraph units. Wearable devices were found to be useful in various health conditions, as the patient monitoring data enabled treatment adjustments. The results are mapped in tables as well as a Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) chart.ConclusionsThe findings indicate limited and sparse evidence for the population group of patients aged 65 years and older in the palliative context. Hence, more research on this particular age group is needed. The available evidence shows the benefits of wearable device use in enabling patient-centred palliative care, treatment adjustments and symptom management, and reducing the need for patients to travel to clinics while maintaining communication with healthcare professionals.
Citation: DIGITAL HEALTH
PubDate: 2023-07-03T05:34:10Z
DOI: 10.1177/20552076231181212
Issue No: Vol. 9 (2023)
- Towards multimodal boosting of motivation for fall-preventive physical
activity in seniors: An iterative development evaluation study
Authors: Å. Revenäs, L. Ström, A. Cicchetti, M. Ehn
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundMany seniors need to increase their physical activity (PA) and participation in fall prevention exercise. Therefore, digital systems have been developed to support fall-preventive PA. Most of them lack video coaching and PA monitoring, two functionalities that may be relevant for increasing PA.ObjectiveTo develop a prototype of a system to support seniors’ fall-preventive PA, which includes also video coaching and PA monitoring, and to evaluate its feasibility and user experience.MethodsA system prototype was conceived by integrating applications for step-monitoring, behavioural change support, personal calendar, video-coaching and a cloud service for data management and co-ordination. Its feasibility and user experience were evaluated in three consecutive test periods combined with technical development. In total, 11 seniors tested the system at home for four weeks with video coaching from health care professionals.ResultsInitially, the system's feasibility was non-satisfactory due to insufficient stability and usability. However, most problems could be addressed and amended. In the third (last) test period, both seniors and coaches experienced the system prototype to be fun, flexible and awareness-raising. Interestingly, the video coaching which made the system unique compared to similar systems was highly appreciated. Nonetheless, even the users in the last test period highlighted issues due to insufficient usability, stability and flexibility. Further improvements in these areas are needed.ConclusionsVideo coaching in fall-preventive PA can be valuable for both seniors and health care professionals. High reliability, usability and flexibility of systems supporting seniors are essential.
Citation: DIGITAL HEALTH
PubDate: 2023-07-03T05:32:44Z
DOI: 10.1177/20552076231180973
Issue No: Vol. 9 (2023)
- Artificial intelligence in healthcare: Complementing, not replacing,
doctors and healthcare providers
Authors: Emre Sezgin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The utilization of artificial intelligence (AI) in clinical practice has increased and is evidently contributing to improved diagnostic accuracy, optimized treatment planning, and improved patient outcomes. The rapid evolution of AI, especially generative AI and large language models (LLMs), have reignited the discussions about their potential impact on the healthcare industry, particularly regarding the role of healthcare providers. Concerning questions, “can AI replace doctors'” and “will doctors who are using AI replace those who are not using it'” have been echoed. To shed light on this debate, this article focuses on emphasizing the augmentative role of AI in healthcare, underlining that AI is aimed to complement, rather than replace, doctors and healthcare providers. The fundamental solution emerges with the human–AI collaboration, which combines the cognitive strengths of healthcare providers with the analytical capabilities of AI. A human-in-the-loop (HITL) approach ensures that the AI systems are guided, communicated, and supervised by human expertise, thereby maintaining safety and quality in healthcare services. Finally, the adoption can be forged further by the organizational process informed by the HITL approach to improve multidisciplinary teams in the loop. AI can create a paradigm shift in healthcare by complementing and enhancing the skills of healthcare providers, ultimately leading to improved service quality, patient outcomes, and a more efficient healthcare system.
Citation: DIGITAL HEALTH
PubDate: 2023-07-03T04:29:31Z
DOI: 10.1177/20552076231186520
Issue No: Vol. 9 (2023)
- Analysis of the effect of glutamyltransferase on hyperlipidemia based on
decision tree
Authors: Tingting Zhang, Dantong Ouyang, Chenglin Sun, Yaru Bi, Lili He, Hongtao Bai
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThis study is designed to analyze the potential influencing factors of hyperlipidemia, and to explore the relationship between liver function indicators such as gamma-glutamyltransferase (GGT) and hyperlipidemia.MethodsData were derived from 7599 outpatients who visited the Department of Endocrinology of the First Hospital of Jilin University (2017–2019). A multinomial regression model is used to identify related factors of hyperlipidemia and the decision tree method is used to explore the general rules in hyperlipidemia patients and non-hyperlipidemia patients on these factors.ResultsThe average of age, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure, aspartate aminotransferase, alanine aminotransferase (ALT), GGT and glycosylated hemoglobin (HbA1c) in the hyperlipidemia group are higher than those in the non-hyperlipidemia group. In multiple regression analysis, SBP, BMI, fasting plasma glucose, 2-h postprandial blood glucose, HbA1c, ALT, GGT are associated with triglyceride. For people with HbA1c less than 6.0%, controlling GGT within 30 IU/L reduces the prevalence of hypertriglyceridemia by 4%, and for people with metabolic syndrome with impaired glucose tolerance controlling GGT within 20 IU/L reduces the prevalence of hypertriglyceridemia by 11%.ConclusionsEven when GGT is in the normal range, the prevalence of hypertriglyceridemia increases with its gradual increase. Controlling GGT in people with normoglycemia and impaired glucose tolerance can reduce the risk of hyperlipidemia.
Citation: DIGITAL HEALTH
PubDate: 2023-07-03T04:29:03Z
DOI: 10.1177/20552076231185441
Issue No: Vol. 9 (2023)
- Exploring the use of digital technology to deliver healthcare services
with explicit consideration of health inequalities in UK settings: A
scoping review
Authors: Albert Farre, Mei Fang, Beth Hannah, Meiko Makita, Alison McFadden, Deborah Menezes, Andrea Rodriguez, Judith Sixsmith, Nicola M Gray
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo map and explore existing evidence on the use of digital technology to deliver healthcare services with explicit consideration of health inequalities in UK settings.MethodsWe searched six bibliographic databases, and the National Health Service (NHS) websites of each UK nation (England, Scotland, Wales, Northern Ireland). Restrictions were applied on publication date (2013–2021) and publication language (English). Records were independently screened against eligibility criteria by pairs of reviewers from the team. Articles reporting relevant qualitative and/or quantitative research were included. Data were synthesised narratively.ResultsEleven articles, reporting data from nine interventions, were included. Articles reported findings from quantitative (n = 5), qualitative (n = 5), and mixed-methods (n = 1) studies. Study settings were mainly community based, with only one hospital based. Two interventions targeted service users, and seven interventions targeted healthcare providers. Two studies were explicitly and directly aimed at (and designed for) addressing health inequalities, with the remaining studies addressing them indirectly (e.g. study population can be classed as disadvantaged). Seven articles reported data on implementation outcomes (acceptability, appropriateness, and feasibility) and four articles reported data on effectiveness outcomes, with only one intervention demonstrating cost-effectiveness.ConclusionsIt is not yet clear if digital health interventions/services in the UK work for those most at risk of health inequalities. The current evidence base is significantly underdeveloped, and research/intervention efforts have been largely driven by healthcare provider/system needs, rather than those of service users. Digital health interventions can help address health inequalities, but a range of barriers persist, alongside a potential for exacerbation of health inequalities.
Citation: DIGITAL HEALTH
PubDate: 2023-06-30T05:49:53Z
DOI: 10.1177/20552076231185442
Issue No: Vol. 9 (2023)
- Improving accessibility of scientific research by artificial
intelligence—An example for lay abstract generation
Authors: Boris Schmitz
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The role of scientific research in modern society is essential for driving innovation, informing policy decisions, and shaping public opinion. However, communicating scientific findings to the general public can be challenging due to the technical and complex nature of scientific research. Lay abstracts are written summaries of scientific research that are designed to be easily understandable and provide a concise and clear overview of key findings and implications. Artificial intelligence language models have the potential to generate lay abstracts that are consistent and accurate while reducing the potential for misinterpretation or bias. This study presents examples of artificial intelligence-generated lay abstracts of recently published articles, which were produced using different currently available artificial intelligence tools. The generated abstracts were of high linguistic quality and accurately represented the findings of the original articles. Adopting lay summaries can increase the visibility, impact, and transparency of scientific research, and enhance scientists’ reputation among peers, while currently, available artificial intelligence models offer solutions to produce lay abstracts. However, the coherence and accuracy of artificial intelligence language models must be validated before they can be used for this purpose without restrictions.
Citation: DIGITAL HEALTH
PubDate: 2023-06-30T05:21:42Z
DOI: 10.1177/20552076231186245
Issue No: Vol. 9 (2023)
- Multilayer perceptron-based self-care early prediction of children with
disabilities
Authors: Rahman Ali, Jamil Hussain, Seung Won Lee
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Early identification of children with self-care impairments is one of the key challenges professional therapists face due to the complex and time-consuming detection process using relevant self-care activities. Due to the complex nature of the problem, machine-learning methods have been widely applied in this area. In this study, a feed-forward artificial neural network (ANN)-based self-care prediction methodology, called multilayer perceptron (MLP)-progressive, has been proposed. The proposed methodology integrates unsupervised instance-based resampling and randomizing preprocessing techniques to MLP for improved early detection of self-care disabilities in children. Preprocessing of the dataset affects the MLP performance; hence, randomization and resampling of the dataset improves the performance of the MLP model. To confirm the usefulness of MLP-progressive, three experiments were conducted, including validating MLP-progressive methodology over multi-class and binary-class datasets, impact analysis of the proposed preprocessing filters on the model performance, and comparing the MLP-progressive results with state-of-the-art studies. The evaluation metrics accuracy, precision, recall, F-measure, TP rate, FP rate, and ROC were used to measure performance of the proposed disability detection model. The proposed MLP-progressive model outperforms existing methods and attains a classification accuracy of 97.14% and 98.57% on multi-class and binary-class datasets, respectively. Additionally, when evaluated on the multi-class dataset, significant improvements in accuracies ranging from 90.00% to 97.14% were observed when compared to state-of-the-art methods.
Citation: DIGITAL HEALTH
PubDate: 2023-06-30T05:21:07Z
DOI: 10.1177/20552076231184054
Issue No: Vol. 9 (2023)
- Usability evaluation of a self-management mobile application for
individuals with a mild traumatic brain injury
Authors: Marquise M. Bonn, Laura J Graham, Stephanie Marrocco, Samantha Jeske, Becky Moran, Dalton L. Wolfe
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveMild traumatic brain injuries (mTBIs) are common and may result in persisting symptoms. Mobile health (mHealth) applications enhance treatment access and rehabilitation. However, there is limited evidence to support mHealth applications for individuals with an mTBI. The primary purpose of this study was to evaluate user experiences and perceptions of the Parkwood Pacing and Planning™ application, an mHealth application developed to help individuals manage their symptoms following an mTBI. The secondary purpose of this study was to identify strategies to improve the application. This study was conducted as part of the development process for this application.MethodsA mixed methods co-design encompassing an interactive focus group and a follow-up survey was conducted with patient and clinician-participants (n = 8, four per group). Each group participated in a focus group consisting of an interactive scenario-based review of the application. Additionally, participants completed the Internet Evaluation and Utility Questionnaire (UQ). Qualitative analysis on the interactive focus group recordings and notes was performed using phenomenological reflection through thematic analyses. Quantitative analysis included descriptive statistics of demographic information and UQ responses.ResultsOn average, clinician and patient-participants positively rated the application on the UQ (4.0 ± .3, 3.8 ± .2, respectively). User experiences and recommendations for improving the application were categorized into four themes: simplicity, adaptability, conciseness, and familiarity.ConclusionPreliminary analyses indicates patients and clinicians have a positive experience when using the Parkwood Pacing and Planning™ application. However, modifications that improve simplicity, adaptability, conciseness, and familiarity may further improve the user's experience.
Citation: DIGITAL HEALTH
PubDate: 2023-06-30T05:19:42Z
DOI: 10.1177/20552076231183555
Issue No: Vol. 9 (2023)
- Need assessment for history-taking instruction program using chatbot for
nursing students: A qualitative study using focus group interviews
Authors: Yanya Chen, Qingran Lin, Xiaohan Chen, Taoran Liu, Qiqi Ke, Qiaohong Yang, Bingsheng Guan, Wai-kit Ming
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
PurposeA comprehensive health history contributes to identifying the most appropriate interventions and care priorities. However, history-taking is challenging to learn and develop for most nursing students. Chatbot was suggested by students to be used in history-taking training. Still, there is a lack of clarity regarding the needs of nursing students in these programs. This study aimed to explore nursing students’ needs and essential components of chatbot-based history-taking instruction program.MethodsThis was a qualitative study. Four focus groups, with a total of 22 nursing students, were recruited. Colaizzi's phenomenological methodology was used to analyze the qualitative data generated from the focus group discussions.ResultsThree main themes and 12 subthemes emerged. The main themes included limitations of clinical practice for history-taking, perceptions of chatbot used in history-taking instruction programs, and the need for history-taking instruction programs using chatbot. Students had limitations in clinical practice for history-taking. When developing chatbot-based history-taking instruction programs, the development should reflect students’ needs, including feedback from the chatbot system, diverse clinical situations, chances to practice nontechnical skills, a form of chatbot (i.e., humanoid robots or cyborgs), the role of teachers (i.e., sharing experience and providing advice) and training before the clinical practice.ConclusionNursing students had limitations in clinical practice for history-taking and high expectations for chatbot-based history-taking instruction programs.
Citation: DIGITAL HEALTH
PubDate: 2023-06-30T02:22:27Z
DOI: 10.1177/20552076231185435
Issue No: Vol. 9 (2023)
- Adherence to unsupervised exercise in sedentary individuals: A randomised
feasibility trial of two mobile health interventions
Authors: Daniel J Bannell, Madeleine France-Ratcliffe, Benjamin James Roy Buckley, Anthony Crozier, Andrew P Davies, Katie L. Hesketh, Helen Jones, Matthew Cocks, Victoria S Sprung
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionAdherence to unsupervised exercise is poor, yet unsupervised exercise interventions are utilised in most healthcare settings. Thus, investigating novel ways to enhance adherence to unsupervised exercise is essential. This study aimed to examine the feasibility of two mobile health (mHealth) technology–supported exercise and physical activity (PA) interventions to increase adherence to unsupervised exercise.MethodsEighty-six participants were randomised to online resources (n = 44, females n = 29) or MOTIVATE (n = 42, females n = 28). The online resources group had access to booklets and videos to assist in performing a progressive exercise programme. MOTIVATE participants received exercise counselling sessions supported via mHealth biometrics which allowed instant participant feedback on exercise intensity, and communication with an exercise specialist. Heart rate (HR) monitoring, survey-reported exercise behaviour and accelerometer-derived PA were used to quantify adherence. Remote measurement techniques were used to assess anthropometrics, blood pressure, HbA1c and lipid profiles.ResultsHR–derived adherence rates were 22 ± 34% and 113 ± 68% in the online resources and MOTIVATE groups, respectively. Self-reported exercise behaviour demonstrated moderate (Cohen's d = 0.63, CI = 0.27 to 0.99) and large effects (Cohen's d = 0.88, CI = 0.49 to 1.26) in favour of online resources and MOTIVATE groups, respectively. When dropouts were included, 84% of remotely gathered data were available, with dropouts removed data availability was 94%.ConclusionData suggest both interventions have a positive impact on adherence to unsupervised exercise but MOTIVATE enables participants to meet recommended exercise guidelines. Nevertheless, to maximise adherence to unsupervised exercise, future appropriately powered trials should explore the effectiveness of the MOTIVATE intervention.
Citation: DIGITAL HEALTH
PubDate: 2023-06-28T07:25:35Z
DOI: 10.1177/20552076231183552
Issue No: Vol. 9 (2023)
- ChatGPT's potential role in non-English-speaking outpatient clinic
settings
Authors: Zhoule Zhu, Yuqi Ying, Junming Zhu, Hemmings Wu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Researchers recently utilized ChatGPT as a tool for composing clinic letters, highlighting its ability to generate accurate and empathetic communications. Here we demonstrated the potential application of ChatGPT as a medical assistant in Mandarin Chinese-speaking outpatient clinics, aiming to improve patient satisfaction in high-patient volume settings. ChatGPT achieved an average score of 72.4% in the Chinese Medical Licensing Examination's Clinical Knowledge section, ranking within the top 20th percentile. It also demonstrated its potential for clinical communication in non-English speaking environments. Our study suggests that ChatGPT could serve as an interface between physicians and patients in Chinese-speaking outpatient settings, possibly extending to other languages. However, further optimization is required, including training on medical-specific datasets, rigorous testing, privacy compliance, integration with existing systems, user-friendly interfaces, and the development of guidelines for medical professionals. Controlled clinical trials and regulatory approval are necessary before widespread implementation. As chatbots’ integration into medical practice becomes more feasible, rigorous early investigations and pilot studies can help mitigate potential risks.
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T08:14:02Z
DOI: 10.1177/20552076231184091
Issue No: Vol. 9 (2023)
- Using the TIDieR checklist to describe development and integration of a
web-based intervention promoting healthy eating and regular exercise among
older cancer survivors
Authors: Laura Q. Rogers, Dori Pekmezi, Yu-Mei Schoenberger-Godwin, Kevin R. Fontaine, Nataliya V. Ivankova, Amber W. Kinsey, Teri Hoenemeyer, Michelle Y. Martin, Maria Pisu, David Farrell, Jonathan Wall, Kaitlyn Waugaman, Robert A. Oster, Kelly Kenzik, Kerri Winters-Stone, Wendy Demark-Wahnefried
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo facilitate replication and future intervention design of web-based multibehavior lifestyle interventions, we describe the rationale, development, and content of the AiM, Plan, and act on LIFestYles (AMPLIFY) Survivor Health intervention which provides healthy eating and exercise behavior change support for older cancer survivors. The intervention promotes weight loss, improvements in diet quality, and meeting exercise recommendations.MethodsThe Template for Intervention Description and Replication (TIDieR) checklist was used to provide a comprehensive description of the AMPLIFY intervention, consistent with CONSORT recommendations.ResultsA social cognitive theory web-based intervention founded on the core components of efficacious print and in-person interventions was conceptualized and developed through an iterative collaboration involving cancer survivors, web design experts, and a multidisciplinary investigative team. The intervention includes the AMPLIFY website, text and/or email messaging, and a private Facebook group. The website consists of: (1) Sessions (weekly interactive e-learning tutorials); (2) My Progress (logging current behavior, receiving feedback, setting goals); (3) Tools (additional information and resources); (4) Support (social support resources, frequently asked questions); and (5) Home page. Algorithms were used to generate fresh content daily and weekly, tailor information, and personalize goal recommendations. An a priori rubric was used to facilitate intervention delivery as healthy eating only (24 weeks), exercise only (24 weeks), or both behaviors concurrently over 48 weeks.ConclusionsOur TIDieR-guided AMPLIFY description provides pragmatic information helpful for researchers designing multibehavior web-based interventions and enhances potential opportunities to improve such interventions.
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T08:13:33Z
DOI: 10.1177/20552076231182805
Issue No: Vol. 9 (2023)
- Israel's first national remote cardiac rehabilitation program: A
retrospective analysis
Authors: Irene Nabutovsky, Daniel Breitner, Alexis Heller, Merav Moreno, Yoav Levine, Yarin Klempfner, Mickey Scheinowitz, Robert Klempfner
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
AimsCardiac rehabilitation is an essential component of secondary prevention consistently unexploited by most eligible patients. Accordingly, the remote cardiac rehabilitation program (RCRP) was developed to create optimal conditions for remote instruction and supervision for patients to enable successful completion of the program.MethodsThis study comprised 306 patients with established coronary heart disease who underwent a 6-month RCRP. RCRP involves regular exercise, monitored by a smartwatch that relays data to the operations center and a mobile application on the patient's smartphone. A stress test was performed immediately before the RCRP and repeated after 3 months. The aims were to determine the effectiveness of the RCRP in improving aerobic capacity, and correlating the program goals and first-month activity, with attaining program goals during the last month.ResultsParticipants were mostly male (81.5%), aged 58 ± 11, enrolled in the main after a myocardial infarction or coronary interventions. Patients exercised aerobically for 183 min each week, 101 min (55% of total exercise) at the target heart rate. There was a significant improvement in exercise capacity, assessed by stress tests, metabolic equivalents which increased from 9.5 ± 3 to 11.4 ± 7(p
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T08:12:24Z
DOI: 10.1177/20552076231180762
Issue No: Vol. 9 (2023)
- Effects of electronic personal health information technology on American
women's cancer screening behaviors mediated through cancer worry:
Differences and similarities between 2017 and 2020
Authors: Piper Liping Liu, Jizhou Francis Ye, Harris Song Ao, Shuxin Sun, Yu Zheng, Qingrui Li, Guangchao Charles Feng, Haiyan Wang, Xinshu Zhao
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundsThanks to their accessibility and low cost, electronic personal health information (ePHI) technologies have been widely used to facilitate patient–physician communication and promote health prevention behaviors (e.g. cancer screening). Despite that empirical evidence has supported the association between ePHI technology use and cancer screening behaviors, the underlying mechanism through which ePHI technology use influences cancer screening behaviors remains a topic of discussion.ObjectiveThis study investigates the relationship between ePHI technology uses and cancer screening behaviors of American women and examines the mediating role of cancer worry.MethodsData for this study were from the Health Information National Trends Survey (HINTS) collected in 2017 (HINTS 5 Cycle 1) and 2020 (HINTS 5 Cycle 4). The final sample included 1914 female respondents in HINTS 5 Cycle 1 and 2204 in HINTS 5 Cycle 4. Mann–Whitney U test, two-sample t-test, and mediation analysis were performed. We also referred to the regression coefficients generated by min–max normalization as percentage coefficients (bp) for the comparison.ResultsThis study reports increased usage of ePHI technologies (from 1.41 in 2017 to 2.19 to 2020), increased cancer worry (from 2.60 in 2017 to 2.84 in 2020), and a stable level of cancer screening behaviors (from 1.44 in 2017 to 1.34 in 2020) among American women. Cancer worry was found to mediate the ePHI effect on cancer screening behaviors (bp = 0.005, 95% confidence interval [0.001, 0.010]) in a positive complementary mediation in 2020.ConclusionsThe research findings support a positive association between ePHI technology use and cancer screening behaviors, and cancer worry has been identified as a salient mediator. An understanding of the mechanism that prompts US women's cancer screening practices provides practical implications for health campaign practitioners.
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T07:03:12Z
DOI: 10.1177/20552076231185271
Issue No: Vol. 9 (2023)
- Bibliometric analysis of medical and health research collaboration between
China and ASEAN countries
Authors: Xia Liang, Ruhao Zhang, Shuyun Wang, Ranfeng Hang, Siyuan Wang, Yajie Zhao, Yutong Sun, Zhaoquan Huang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo reveal the characteristics, development trend and potential opportunities of China–ASEAN collaboration in the medical and health field based on bibliometrics.MethodsScopus and International Center for the Study of Research Lab (ICSR Lab) was used to analyze the scale, collaboration network and distribution, impact of cooperative papers, collaboration dominance and evolution of the literature on China–ASEAN medical and health collaboration in the Scopus database from 1992 to 2022.ResultsFrom 1992 to 2022, 19,764 articles on medical and health collaboration between China and ASEAN were filtered for analysis. The number of China–ASEAN collaborations has shown a clear upward trend over the years, indicating a gradually closer and improved collaboration relationship overall. The institutional collaboration network between China and ASEAN countries was obviously clustered, and the network connectivity was limited. The substantial differences between the median and mean values of citation impact of China–ASEAN medical and health research collaboration reflected that the collaboration was ‘less’ but ‘better’. The dominance share of collaboration between China and the main ASEAN countries was fluctuating upward and has become more and more stable after 2004. Most of the China–ASEAN collaboration focused on their own characteristic research topics. In recent years, collaboration in infectious diseases and public health had expanded significantly, while other research topics had maintained in a complementary development trend.ConclusionCollaboration between China and ASEAN in the medical and health field has exhibited a progressively closer relationship, and the trend of complementary research has remained stable. However, there are still areas of concern, including the limited scale of collaboration, narrow scope of participation and weak dominance.
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T07:02:32Z
DOI: 10.1177/20552076231184993
Issue No: Vol. 9 (2023)
- Research on a real-time dynamic monitoring method for silent aspiration
after stroke based on semisupervised deep learning: A protocol study
Authors: Jia Qiao, Yuan-tong Jiang, Yong Dai, Yan-bin Gong, Meng Dai, Yan-xia Liu, Zu-lin Dou
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study aims to establish a real-time dynamic monitoring system for silent aspiration (SA) to provide evidence for the early diagnosis of and precise intervention for SA after stroke.MethodsMultisource signals, including sound, nasal airflow, electromyographic, pressure and acceleration signals, will be obtained by multisource sensors during swallowing events. The extracted signals will be labeled according to videofluoroscopic swallowing studies (VFSSs) and input into a special dataset. Then, a real-time dynamic monitoring model for SA will be built and trained based on semisupervised deep learning. Model optimization will be performed based on the mapping relationship between multisource signals and insula-centered cerebral cortex–brainstem functional connectivity through resting-state functional magnetic resonance imaging. Finally, a real-time dynamic monitoring system for SA will be established, of which the sensitivity and specificity will be improved by clinical application.ResultsMultisource signals will be stably extracted by multisource sensors. Data from a total of 3200 swallows will be obtained from patients with SA, including 1200 labeled swallows from the nonaspiration category from VFSSs and 2000 unlabeled swallows. A significant difference in the multisource signals is expected to be found between the SA and nonaspiration groups. The features of labeled and pseudolabeled multisource signals will be extracted through semisupervised deep learning to establish a dynamic monitoring model for SA. Moreover, strong correlations are expected to be found between the Granger causality analysis (GCA) value (from the left middle frontal gyrus to the right anterior insula) and the laryngeal rise time (LRT). Finally, a dynamic monitoring system will be established based on the former model, by which SA can be identified precisely.ConclusionThe study will establish a real-time dynamic monitoring system for SA with high sensitivity, specificity, accuracy and F1 score.
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T07:01:32Z
DOI: 10.1177/20552076231183548
Issue No: Vol. 9 (2023)
- Feasibility, performance and acceptability of an innovative vital signs
monitor for sick newborns in Western Kenya: A mixed-methods study
Authors: Assumpta Nantume, Bertha Akinyi Oketch, Dickson Otiangala, Sona Shah, Teresa Cauvel, Boniface Nyumbile, Bernard Olayo
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionLow- and middle-income countries (LMICs) account for 99% of the global neonatal mortality. Limited access to advanced technology, such as bedside patient monitors contributes to disproportionately poor outcomes for critically ill newborns in LMICs. We designed a study to assess the feasibility, performance, and acceptability of a low-cost wireless wearable technology for continuous monitoring of sick newborns in resource-limited settings.MethodsThis was a mixed-methods implementation study conducted between March and April 2021 at two health facilities in Western Kenya. Inclusion criteria for newborns monitored included: age 0 to 28 days, birthweight ≥2.0 kg, low-to-moderate severity of illness at admission and the guardian's willingness to provide informed consent. Medical staff who participated in monitoring the newborns were surveyed about their experience with the technology. We used descriptive statistics to summarize our quantitative findings and qualitative data was coded and analyzed as an iterative process to summarize quotes on user acceptability.ResultsThe results of the study demonstrated that adoption of neoGuard was feasible and acceptable in this setting. Medical staff described the technology as safe, user-friendly and efficient, after successfully monitoring 134 newborns. Despite the positive user experience, we did observe some notable technology performance issues such as a high percentage of missing vital signs data.ConclusionThe results of this study were critical in informing the iterative process of refining and validating an innovative vital signs monitor for patients in resource-limited settings. Further research and development are underway to optimize neoGuard's performance and to examine its clinical impact and cost effectiveness.
Citation: DIGITAL HEALTH
PubDate: 2023-06-26T07:00:25Z
DOI: 10.1177/20552076231182799
Issue No: Vol. 9 (2023)
- Cocreation of a conversational agent to help patients adhere to their
varenicline treatment: A study protocol
Authors: Nadia Minian, Kamna Mehra, Jonathan Rose, Scott Veldhuizen, Laurie Zawertailo, Matt Ratto, Julia Lecce, Peter Selby
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveVarenicline is the most efficacious approved smoking cessation medication, making it one of the most cost-effective clinical interventions for reducing tobacco-related morbidity and mortality. Adhering to varenicline is strongly associated with smoking cessation. Healthbots have the potential to help people adhere to their medications by scaling up evidence-based behavioral interventions. In this protocol, we outline how we will follow the UK's Medical Research Council's guidance to codesign a theory-informed, evidence-based, and patient-centered healthbot to help people adhere to varenicline.MethodsThe study will utilize the Discover, Design and Build, and Test framework and will include three phases: (a) a rapid review and interviews with 20 patients and 20 healthcare providers to understand barriers and facilitators to varenicline adherence (Discover phase); (b) Wizard of Oz test to design the healthbot and get a sense of the questions that chatbot has to be able to answer (Design phase); and (c) building, training, and beta-testing the healthbot (Building and Testing phases) where the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability framework will be used to develop the healthbot using the simplest sensible solution, and 20 participants will beta test the healthbot. We will use the Capability, Opportunity, Motivation-Behavior (COM-B) model of behavior change and its associated framework, the Theoretical Domains Framework, to organize the findings.ConclusionsThe present approach will enable us to systematically identify the most appropriate features for the healthbot based on a well-established behavioral theory, the latest scientific evidence, and end users’ and healthcare providers’ knowledge.
Citation: DIGITAL HEALTH
PubDate: 2023-06-23T07:02:52Z
DOI: 10.1177/20552076231182807
Issue No: Vol. 9 (2023)
- The place of digital triage in a complex healthcare system: An interview
study with key stakeholders in Australia's national provider
Authors: Kate Churruca, Louise A Ellis, Catherine Pope, Jennifer MacLellan, Yvonne Zurynski, Jeffrey Braithwaite
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundDigital triage tools such as telephone advice and online symptom checkers are now commonplace in health systems internationally. Research has focused on consumers’ adherence to advice, health outcomes, satisfaction, and the degree to which these services manage demand for general practice or emergency departments. Such studies have had mixed findings, leaving equivocal the role of these services in healthcare.ObjectiveWe examined stakeholders’ perspectives on Healthdirect, Australia's national digital triage provider, focusing on its role in the health system, and barriers to operation, in the context of the COVID-19 pandemic.MethodsKey stakeholders took part in semi-structured interviews conducted online in the third quarter of 2021. Transcripts were coded and thematically analysed.ResultsParticipants (n = 41) were Healthdirect staff (n = 13), employees of Primary Health Networks (PHNs; n = 12), clinicians (n = 9), shareholder representatives (n = 4), consumer representatives (n = 2) and other policymakers (n = 1). Eight themes emerged from the analysis: (1) information and guidance in navigating the system, (2) efficiency through appropriate care, (3) value for consumers' (4) the difficulties in triage at a distance, (5) competition and the unfulfilled promise of integration, (6) challenges in promoting Healthdirect, (7) monitoring and evaluating digital triage services and (8) rapid change, challenge and opportunity from COVID-19.ConclusionStakeholders varied in their views of the purpose of Healthdirect's digital triage services. They identified challenges in lack of integration, competition, and the limited public profile of the services, issues largely reflective of the complexity of the policy and health system landscape. There was acknowledgement of the value of the services during the COVID-19 pandemic, and an expectation of them realising greater potential in the wake of the rapid uptake of telehealth.
Citation: DIGITAL HEALTH
PubDate: 2023-06-23T07:02:12Z
DOI: 10.1177/20552076231181201
Issue No: Vol. 9 (2023)
- Embedding digital sleep health into primary care practice: A triangulation
of perspectives from general practitioners, nurses, and pharmacists
Authors: Janet MY Cheung, Zoe Menczel Schrire, Melissa Aji, Matthew Rahimi, Helena Salomon, Iliana Doggett, Nicholas Glozier, Delwyn J. Bartlett, Keith Wong, Ronald R. Grunstein, Christopher J. Gordon
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionWhile digital health interventions (DHIs) can potentially address the unmet needs for sleep health services, little is known about their implementation in practice. The current study aimed to explore primary care health providers’ attitudes and beliefs towards DHIs for sleep and implementation into practice.MethodsA cross-sectional online survey was administered to Australian primary care health professionals: general practitioners (GPs), community nurses, and community pharmacists. Semi-structured interviews were conducted within a sub-sample of participants exploring their experiences with DHIs and perceived barriers/facilitators for embedding DHIs into primary care. Semi-structured interviews were thematically analysed using the framework approach to contextualise survey findings.ResultsNinety-six surveys were returned (GPs = 36, nurses = 30, and pharmacists = 30) and 45 interviews conducted (GPs = 17, nurses = 14, and pharmacists = 14). From the survey, GPs were more likely to endorse familiarity (p = 0.009) and use (p
Citation: DIGITAL HEALTH
PubDate: 2023-06-23T07:01:33Z
DOI: 10.1177/20552076231180970
Issue No: Vol. 9 (2023)
- To chat or bot to chat: Ethical issues with using chatbots in mental
health
Authors: Simon Coghlan, Kobi Leins, Susie Sheldrick, Marc Cheong, Piers Gooding, Simon D'Alfonso
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
This paper presents a critical review of key ethical issues raised by the emergence of mental health chatbots. Chatbots use varying degrees of artificial intelligence and are increasingly deployed in many different domains including mental health. The technology may sometimes be beneficial, such as when it promotes access to mental health information and services. Yet, chatbots raise a variety of ethical concerns that are often magnified in people experiencing mental ill-health. These ethical challenges need to be appreciated and addressed throughout the technology pipeline. After identifying and examining four important ethical issues by means of a recognised ethical framework comprised of five key principles, the paper offers recommendations to guide chatbot designers, purveyers, researchers and mental health practitioners in the ethical creation and deployment of chatbots for mental health.
Citation: DIGITAL HEALTH
PubDate: 2023-06-23T05:58:52Z
DOI: 10.1177/20552076231183542
Issue No: Vol. 9 (2023)
- Identification and description of telerehabilitation assessments for
individuals with neurological conditions: A scoping review
Authors: Jennifer O’Neil, Keely Barnes, Erin Morgan Donnelly, Lisa Sheehy, Heidi Sveistrup
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe clinical adoption of telerehabilitation accelerated rapidly over the last few years, creating opportunities for clinicians and researchers to explore the use of digital technologies and telerehabilitation in the assessment of deficits related to neurological conditions. The objectives of this scoping review were to identify outcome measures used to remotely assess the motor function and participation in people with neurological conditions and report, when available, the psychometric data of these remote outcome measures.MethodsMEDLINE (Ovid), CINAHL, PubMed, PsychINFO, EMBASE, and Cochrane databases were searched between December 13, 2020, and January 4, 2021, for studies investigating the use of remote assessments to evaluate motor function and participation in people with neurological conditions. An updated search was completed on May 9, 2022, using the same databases and search terms. Two reviewers independently screened each title and abstract, followed by full-text screening. Data extraction was completed using a pre-piloted data extraction sheet where outcome measures were reported as per the International Classification of Functioning, Disability and Health.ResultsFifty studies were included in this review. Eighteen studies targeted outcomes related to body structures and 32 targeted those related to activity limitation and participation restriction. Seventeen studies reported psychometric data; of these, most included reliability and validity data.ConclusionClinical assessments of motor function of people living with neurological conditions can be completed in a telerehabilitation or remote context using validated and reliable remote assessment measures.
Citation: DIGITAL HEALTH
PubDate: 2023-06-23T05:58:12Z
DOI: 10.1177/20552076231183233
Issue No: Vol. 9 (2023)
- Online public information about advance care planning: An evaluation of UK
and international websites
Authors: Anne Canny, Bruce Mason, Clare Atkins, Rebecca Patterson, Lorna Moussa, Kirsty Boyd
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionHealthcare information is increasingly internet-based. Standards require websites to be ‘perceivable, operable, understandable and robust’ with relevant content for citizens in appropriate language. This study examined UK and international websites offering public healthcare information on advance care planning (ACP) using current recommendations for website accessibility and content and informed by a public engagement exercise.MethodsGoogle searches identified websites in English from health service providers, governmental or third sector organisations based in the UK and internationally. Target keywords that would be used by a member of the public informed the search terms. Data extraction used criterion-based assessment and web content analysis of the first two pages of each search result. Public patient representatives as key members of the multidisciplinary research team guided the development of the evaluation criteria.ResultsA total of 1158 online searches identified 89 websites, reduced to 29 by inclusion/exclusion criteria. Most sites met international recommendations for knowledge/understanding about ACP. Differences in terminology, lack of information about ACP limitations and non-adherence to recommended reading levels, accessibility standards and translation options were apparent. Sites targeting members of the public used more positive, non-technical language than those for both professional and lay users.ConclusionsSome websites met accepted standards required to facilitate understanding and public engagement in ACP. Others could be improved significantly. Website providers have important roles and responsibilities in increasing people's understanding of their health conditions, future care options and ability to take an active role in planning for their health and care.
Citation: DIGITAL HEALTH
PubDate: 2023-06-22T07:23:42Z
DOI: 10.1177/20552076231180438
Issue No: Vol. 9 (2023)
- mHealth in sub-Saharan Africa and Europe: A systematic review comparing
the use and availability of mHealth approaches in sub-Saharan Africa and
Europe
Authors: Genet Tadese Aboye, Martijn Vande Walle, Gizeaddis Lamesgin Simegn, Jean-Marie Aerts
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundmHealth can help with healthcare service delivery for various health issues, but there's a significant gap in the availability and use of mHealth systems between sub-Saharan Africa and Europe, despite the ongoing digitalization of the global healthcare system.ObjectiveThis work aims to compare and investigate the use and availability of mHealth systems in sub-Saharan Africa and Europe, and identify gaps in current mHealth development and implementation in both regions.MethodsThe study adhered to the PRISMA 2020 guidelines for article search and selection to ensure an unbiased comparison between sub-Saharan Africa and Europe. Four databases (Scopus, Web of Science, IEEE Xplore, and PubMed) were used, and articles were evaluated based on predetermined criteria. Details on the mHealth system type, goal, patient type, health concern, and development stage were collected and recorded in a Microsoft Excel worksheet.ResultsThe search query produced 1020 articles for sub-Saharan Africa and 2477 articles for Europe. After screening for eligibility, 86 articles for sub-Saharan Africa and 297 articles for Europe were included. To minimize bias, two reviewers conducted the article screening and data retrieval. Sub-Saharan Africa used SMS and call-based mHealth methods for consultation and diagnosis, mainly for young patients such as children and mothers, and for issues such as HIV, pregnancy, childbirth, and child care. Europe relied more on apps, sensors, and wearables for monitoring, with the elderly as the most common patient group, and the most common health issues being cardiovascular disease and heart failure.ConclusionWearable technology and external sensors are heavily used in Europe, whereas they are seldom used in sub-Saharan Africa. More efforts should be made to use the mHealth system to improve health outcomes in both regions, incorporating more cutting-edge technologies like wearables internal and external sensors. Undertaking context-based studies, identifying determinants of mHealth systems use, and considering these determinants during mHealth system design could enhance mHealth availability and utilization.
Citation: DIGITAL HEALTH
PubDate: 2023-06-22T06:50:05Z
DOI: 10.1177/20552076231180972
Issue No: Vol. 9 (2023)
- Patients, carers and healthcare providers’ perspectives on a
patient-owned surveillance system for diabetic foot ulcer care: A
qualitative study
Authors: Zhiwen Joseph Lo, Bryan Chong, Elaine Tan, Desmond Ooi, Huiling Liew, Wai Han Hoi, Yuan Teng Cho, Kyle Wu, Naren Kumar Surendra, Maleyka Mammadova, Audrey Nah, Victor Goh, Josip Car
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDigital health has recently gained a foothold in monitoring and improving diabetes care. We aim to explore the views of patients, carers and healthcare providers (HCPs) regarding the use of a novel patient-owned wound surveillance application as part of outpatient management of patients with diabetic foot ulcers (DFUs).MethodsSemi-structured online interviews were conducted with patients, carers and HCPs in wound care for DFUs. The participants were recruited from a primary care polyclinic network and two tertiary hospitals in Singapore, within the same healthcare cluster. Purposive maximum variation sampling was used to select participants with differing attributes to ensure heterogeneity. Common themes relating to the wound imaging app were captured.ResultsA total of 20 patients, 5 carers and 20 HCPs participated in the qualitative study. None of the participants have used a wound imaging app before. Regarding a patient-owned wound surveillance app, all were open and receptive to the system and workflow for use in DFU care. Four major themes emerged from patients and carers: (1) technology, (2) application features and usability, (3) feasibility of using the wound imaging application and (4) logistics of care. Four major themes were identified from HCPs: (1) attitudes towards wound imaging app, (2) preferences regarding functionality, (3) perceived challenges for patients/carers and (4) perceived barriers for HCPs.ConclusionOur study highlighted several barriers and facilitators from patients, carers and HCPs regarding the use of a patient-owned wound surveillance app. These findings demonstrate the potential of digital health and areas to improve and tailor a DFU wound app suitable for implementation in the local population.
Citation: DIGITAL HEALTH
PubDate: 2023-06-22T06:05:16Z
DOI: 10.1177/20552076231183544
Issue No: Vol. 9 (2023)
- Global research landscape on artificial intelligence in arthroplasty: A
bibliometric analysis
Authors: Zhuo Li, Zulipikaer Maimaiti, Jun Fu, Ji-Ying Chen, Chi Xu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundArtificial intelligence (AI) has promising applications in arthroplasty. In response to the knowledge explosion resulting from the rapid growth of publications, we applied bibliometric analysis to explore the research profile and topical trends in this field.MethodsThe articles and reviews related to AI in arthroplasty were retrieved from 2000 to 2021. The Java-based Citespace, VOSviewer, R software-based Bibiometrix, and an online platform systematically evaluated publications by countries, institutions, authors, journals, references, and keywords.ResultsA total of 867 publications were included. Over the past 22 years, the number of AI-related publications in the field of arthroplasty has grown exponentially. The United States was the most productive and academically influential country. The Cleveland Clinic was the most prolific institution. Most publications were published in high academic impact journals. However, collaborative networks revealed a lack and imbalance of inter-regional, inter-institutional, and inter-author cooperation. Two emerging research areas represented the development trends: major AI subfields such as machine learning and deep learning, and the other is research related to clinical outcomes.ConclusionAI in arthroplasty is evolving rapidly. Collaboration between different regions and institutions should be strengthened to deepen our understanding further and exert critical implications for decision-making. Predicting clinical outcomes of arthroplasty using novel AI strategies may be a promising application in this field.
Citation: DIGITAL HEALTH
PubDate: 2023-06-21T07:04:05Z
DOI: 10.1177/20552076231184048
Issue No: Vol. 9 (2023)
- Emotional activation in video conferences equals that in in person
meetings
Authors: Michelle Jerkku, Jonas Nordin, Niclas Kaiser
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe purpose of this study was to increase our understanding of VCPs’ impact on the therapeutic factor emotion processing by investigating possible differences in emotional activation during autobiographical recall in VCPs and in person.MethodsWe recruited 30 adult participants aged 21–53 (M = 26.50, SD = 6.68) with no current psychiatric diagnoses to join a controlled experiment. All participants completed two relaxation sessions and two autobiographical recall sessions. Each type of session was delivered once over a VCP and once in person. Emotional activation was measured by heart rate, skin conductance and self-assessment of affects during each session.ResultsNo significant differences in activation during autobiographical recall between VCP and in person.ConclusionsThis result may indicate the viability of VCPs for work with emotion processing. We discuss the results in light of clients’ and therapists’ concerns about using VCPs in emotional work, with the caution that further practical implications should be considered.
Citation: DIGITAL HEALTH
PubDate: 2023-06-21T05:55:24Z
DOI: 10.1177/20552076231183551
Issue No: Vol. 9 (2023)
- Mapping the youth soccer: A bibliometrix analysis using R-tool
Authors: Bo Liu, Chang-jing Zhou, Hao-wei Ma, Bo Gong
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
In recent years, there has been an increase in the scientific production of youth soccer. However, a panoramic map of research on this subject does not exist. The aim of this study was to identify global research trends in youth soccer over time, among the main levels of analysis: sources, authors, documents, and keywords. The bibliometric software Biblioshiny was used to analyze 2606 articles in Web of Science (WoS) published between 2012 and 2021. The main conclusion is that US and UK scholars dominate the research; the topics of research are changing with the real needs, and research on the topic of performance has been of interest to scholars; talent identification and development, performance, injury prevention, and concussion are the studies of interest to scholars in this area. This finding, which offers a global picture of youth soccer research over time, can help future research in this or similar domains.
Citation: DIGITAL HEALTH
PubDate: 2023-06-21T05:54:15Z
DOI: 10.1177/20552076231183550
Issue No: Vol. 9 (2023)
- Developing an eMental health monitoring module for older mourners using
fuzzy cognitive maps
Authors: Lena Brandl, Lex van Velsen, Jeannette Brodbeck, Sofia Jacinto, Dennis Hofs, Dirk Heylen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveEffective internet interventions often combine online self-help with regular professional guidance. In the absence of regularly scheduled contact with a professional, the internet intervention should refer users to professional human care if their condition deteriorates. The current article presents a monitoring module to recommend proactively seeking offline support in an eMental health service to aid older mourners.MethodThe module consists of two components: a user profile that collects relevant information about the user from the application, enabling the second component, a fuzzy cognitive map (FCM) decision-making algorithm that detects risk situations and to recommend the user to seek offline support, whenever advisable. In this article, we show how we configured the FCM with the help of eight clinical psychologists and we investigate the utility of the resulting decision tool using four fictitious scenarios.ResultsThe current FCM algorithm succeeds in detecting unambiguous risk situations, as well as unambiguously safe situations, but it has more difficulty classifying borderline cases correctly. Based on recommendations from the participants and an analysis of the algorithm's erroneous classifications, we propose how the current FCM algorithm can be further improved.ConclusionThe configuration of FCMs does not necessarily demand large amounts of privacy-sensitive data and their decisions are scrutable. Thus, they hold great potential for automatic decision-making algorithms in mental eHealth. Nevertheless, we conclude that there is a need for clear guidelines and best practices for developing FCMs, specifically for eMental health.
Citation: DIGITAL HEALTH
PubDate: 2023-06-20T06:44:50Z
DOI: 10.1177/20552076231183549
Issue No: Vol. 9 (2023)
- The processes of engagement in information-seeking behavior for
individuals with diabetes who developed diabetic foot ulcer: A
constructivist grounded theory study
Authors: Idevania G Costa, Pilar Camargo-Plazas
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
To describe the process of engagement in information seeking behavior for individuals with type 1 and type 2 diabetes.MethodologyConstructivist grounded theory. The data was gathered through thirty semi-structured interviews of participants attending a wound care clinic in Southeast, Ontario, Canada. The waiting period taken to seek appropriate help varied from weeks to months.Results“The processes of engagement in information-seeking behavior about diabetes” are organized as follows: 1) discovering diabetes, 2) reactions to the diagnosis, and 3) engaging in self-directed learning. For most participants, the diagnosis of diabetes was unexpected and usually confirmed after a long period of experiencing a diversity of symptoms. The terms used mostly by participants were “I started to wonder” and “Something was wrong with me.” After being diagnosed with diabetes, participants sought information to learn about it. Most of them engaged in self-directed learning to acquire knowledge about their illness.ConclusionAlthough the Internet is often used to seek information, healthcare providers and support network also played an important role in supporting participants information-seeking behavior learn about diabetes. The unique needs of people with diabetes must be taken into consideration during their diabetes care journey. These findings call for the need to provide education about diabetes from the time they are diagnosed and direct them to reliable resources of information.
Citation: DIGITAL HEALTH
PubDate: 2023-06-20T06:43:53Z
DOI: 10.1177/20552076231177155
Issue No: Vol. 9 (2023)
- Telemonitoring as a Telehealth strategy to contain the COVID-19 pandemic
in a Brazilian capital
Authors: Valter Luiz Moreira de Rezende, Edna Regina Silva Pereira, Barbara Souza Rocha, Marta Maria Alves da Silva, Alexandre Chater Taleb
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study aimed to describe and analyze the process of creating and implementing telemonitoring services for COVID-19 cases, focusing on strengths and weaknesses.MethodsA single case study incorporating qualitative and quantitative data using descriptive and exploratory approach was performed from 24 March 2020 to 24 March 2021 in a Brazilian capital city. Data collection took place through interviews, document analysis, and direct observation. Thematic content analysis was performed, and the results were presented in categories.ResultsThe project included 512 health professionals, and 102,000 patients were monitored. The service was designed to break the chain of transmission, reinforce biosecurity measures, and provide comprehensive care to patients. Initially, two levels of monitoring were created. The first was a multidisciplinary health team that made calls to patients in the database. If the patients showed warning signs or aggravation, they were referred to the physician's monitoring referral service. Subsequently, a third level was created and staffed by psychologists. The main challenges were the number of patients notified, needing to update the contact forms as COVID-19 knowledge increased, and inconsistent telephone numbers recorded in the notifications.ConclusionsTelemonitoring allowed signs of worsening COVID-19 to be identified, monitored thousands of people, and stopped infected patients from circulating. Adapting the existing telehealth structure was a viable, agile, and powerful strategy to reach a large number of people.
Citation: DIGITAL HEALTH
PubDate: 2023-06-20T02:16:35Z
DOI: 10.1177/20552076231182786
Issue No: Vol. 9 (2023)
- Integrated health system to assess and manage frailty in community
dwelling: Co-design and usability evaluation
Authors: Cristian Moral, Rodrigo Pérez-Rodríguez, Elena Villalba-Mora, Jaime Barrio-Cortes, Xavier Ferre, Leocadio Rodríguez-Mañas
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveWe aimed to co-create and evaluate an integrated system to follow-up frailty in a community dwelling environment and provide a multi-modal tailored intervention. Frailty and dependency among the older population are a major challenge to the sustainability of healthcare systems. Special attention must be paid to the needs and particularities of frail older persons as a vulnerable group.MethodsTo ensure the solution fits all the stakeholders’ needs, we performed several participatory design activities with them, such as pluralistic usability walkthroughs, design workshops, usability tests and a pre-pilot. The participants in the activities were older people; their informal carers; and specialized and community care professionals. In total, 48 stakeholders participated.ResultsWe created and evaluated an integrated system consisting of four mobile applications and a cloud server, which has been evaluated through a 6-months clinical trial, where secondary endpoints were both usability and user experience evaluation. In total, 10 older adults and 12 healthcare professionals participated in the intervention group using the technological system. Both patients and professionals have positively evaluated their applications.ConclusionBoth older adults and healthcare professionals have considered the resulted system easy to use and learn, consistent and secure. In general terms, they also would like to keep using it in the future.
Citation: DIGITAL HEALTH
PubDate: 2023-06-20T02:15:57Z
DOI: 10.1177/20552076231181229
Issue No: Vol. 9 (2023)
- Use of mobile applications and health technologies among dementia
caregivers with chronic conditions: A cross-sectional study
Authors: Kyra Jennifer Waligora Mendez, Alain Bernard Labrique, Chakra Budhathoki, Tatiana Sadak, Elizabeth K. Tanner, Valerie T. Cotter, Hae-Ra Han
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveAlmost 80% of people, who are caring for someone with dementia, have one or more chronic conditions and require self-management support. New technologies offer promising solutions; however, little is known about what technologies caregivers use for their health or in general. This study aimed to describe the prevalence of mobile application (app) and health-related technology use among caregivers who have chronic conditions and care for someone with dementia.MethodsA cross-sectional study was conducted with 122 caregivers recruited online and from communities in the Baltimore-metropolitan area. Data were collected with online surveys and computer-assisted telephone interviews. Descriptive and inferential statistics were used to analyze survey data.ResultsStudy participants were primarily female (95 of 122, 77.9%), middle-aged (average 53 years, standard deviation (SD) 17), well educated (average 16 years, SD 3.3), an adult child of the person with dementia (53 of 122, 43.4%), and had 4 chronic conditions on average (SD 2.6). Over 90% of caregivers used mobile apps (116 of 122), spending a range of 9 to 82 min on each app. Most caregivers reported using social media apps (96 of 116, 82.8%), weather apps (96 of 116, 82.8%), and/or music or entertainment apps (89 of 116, 76.7%). Among caregivers using each app type, more than half of caregivers used social media (66 of 96, 69%), games (49 of 74, 66%), weather (62 of 96, 65%), and/or music or entertainment apps (51 of 89, 57%) daily. Caregivers also used several technologies to support their own health—the most common being websites, mobile devices, and health-related mobile apps.ConclusionThis study supports the feasibility of using technologies to promote health behavior change and support self-management among caregivers.
Citation: DIGITAL HEALTH
PubDate: 2023-06-16T12:29:34Z
DOI: 10.1177/20552076231181213
Issue No: Vol. 9 (2023)
- Money can’t buy happiness: A randomized controlled trial of a digital
mental health app with versus without financial incentives
Authors: Cheryl Chang, Emma Palermo, Sky Deswert, Alyssa Brown, Heather J Nuske
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Mental health disorders are prevalent among college students and increasing in frequency and severity. However, there is a significant gap between those who need treatment and those who engage in treatment. Given the documented efficacy of financial incentives for promoting health behavior change and engagement in treatment, financial incentives may help, along with nonfinancial behavioral incentives such as motivational messaging, gamification, and loss aversion techniques. We compared brief (28-day) use of two versions of a behavioral economics-inspired digital mental health app, NeuroFlow: (1) the full app including financial incentives and nonfinancial behavioral incentives (treatment group) and (2) a version of the app with nonfinancial behavioral incentives only (control group). In our intent-to-treat analyses, in order to examine the primary outcome of app engagement, a one-way analysis of variance (ANOVA) (treatment vs. control) was conducted, and to examine the secondary outcomes (depression, anxiety, emotion dysregulation, and wellbeing), a two-way repeated measures ANOVAs (treatment vs. control × baseline vs. post-trial) were conducted. We found that there were no differences between treatment groups on app engagement or the change in the mental health/wellness outcome measures. There was a main effect of timepoint on symptoms of anxiety and emotion dysregulation, such that there were significantly lower self-reported symptoms at post-trial relative to baseline. Our results suggest that financial incentives in digital mental health apps over and above nonfinancial behavioral incentives do not have an impact on app engagement or mental health/wellness outcomes.
Citation: DIGITAL HEALTH
PubDate: 2023-06-16T12:29:17Z
DOI: 10.1177/20552076231170693
Issue No: Vol. 9 (2023)
- Description of apps targeting stroke patients: A review of apps store
Authors: Wenjing Cao, Azidah Abdul Kadir, Yuhui Wang, Juan Wang, Bolin Dai, Yilin Zheng, Pengjuan Mu, Chencheng Hu, Jianlu Chen, Luo Na, Intan Idiana Hassan
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAs a principal cause of mortality and disability worldwide, stroke imposes considerable burdens on society and effects on the lives of patients, families, and communities. Owing to their growing global popularity, health-related applications (apps) offer a promising approach to stroke management but show a knowledge gap regarding mobile apps for stroke survivors.MethodsThis review was conducted across the Android and iOS app stores in September–December 2022 to identify and describe all apps targeting stroke survivors. Apps were included if they were designed for stroke management and contained at least one of the following components: medication taking, risk management, blood pressure management, and stroke rehabilitation. Apps were excluded if they were unrelated to health, not in Chinese or English, or the targeted users were healthcare professionals. The included apps were downloaded, and their functionalities were investigated.ResultsThe initial search yielded 402 apps, with 115 eligible after title and description screening. Some apps were later excluded due to duplicates, registration problems, or installation failures. In total, 83 apps were included for full review and evaluated by three independent reviewers. Educational information was the most common function (36.1%), followed by rehabilitation guidance (34.9%), communication with healthcare providers (HCPs), and others (28.9%). The majority of these apps (50.6%) had only one functionality. A minority had contributions from an HCP or patients.ConclusionWith the widespread accessibility and availability of smartphone apps across the mHealth landscape, an increasing number of apps targeting stroke survivors are being released. One of the most important findings is that the majority of the apps were not specifically geared toward older adults. Many of the currently available apps lack healthcare professionals’ and patients’ involvement in their development, and most offer limited functionality, thus requiring further attention to the development of customized apps.
Citation: DIGITAL HEALTH
PubDate: 2023-06-16T07:11:24Z
DOI: 10.1177/20552076231181473
Issue No: Vol. 9 (2023)
- Online medical consultation in China: Evidence from obesity doctors
Authors: Donglei Yu, Yaolin Hu, Jian Wang, Stephen Nicholas, Elizabeth Maitland
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveOnline medical consultation (OMC) is increasingly used in China, but there have been few in-depth studies of consultation arrangements and fee structures of online doctors in China. This research assessed the consultation arrangements and fee structure of OMC in China by undertaking a case study of obesity doctors from four representative OMC platforms.MethodsDetailed information, including fees, waiting time and doctor information, was collected from four obesity OMC platforms and analyzed using descriptive statistical analysis.ResultsThe obesity OMC platforms in China shared similarities in the use of big data and artificial intelligence (AI) but differed across service access, specific consultation arrangements and fees. Big data search and AI response technologies were used by most platforms to match users with doctors and reduce doctors’ pressure. The descriptive statistical analysis showed that the higher the rank of the online doctor, the higher the online fee and the longer the wait time. Through a comparison with offline hospitals, we found online doctors’ fees exceeded offline hospital doctors’ fees by up to 90%.ConclusionsOMC platforms can gain competitive advantages over offline medical institutions through the following measures: make fuller use of big data and AI technologies to provide users with longer duration, lower cost and more efficient consultation services; provide better user experience than offline medical institutions; use big data and fee advantages to screen doctors to match users’ consultation needs instead of screening by the rank of doctors only; and cooperate with commercial insurance providers to provide innovative health care packages.
Citation: DIGITAL HEALTH
PubDate: 2023-06-16T06:09:13Z
DOI: 10.1177/20552076231182789
Issue No: Vol. 9 (2023)
- The importance of trusting conditions for organizations’ readiness to
implement mHealth to support healthy lifestyle behaviors: An interview
study within Swedish child and school healthcare
Authors: Maria Fagerström, Marie Löf, Ulrika Müssener, Kristin Thomas
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo explore perceptions among nurses, managers, and policymakers regarding organizational readiness to implement mHealth for the promotion of healthy lifestyle behaviors in child and school healthcare.MethodsIndividual semi-structured interviews with nurses (n = 10), managers (n = 10), and policymakers (n = 8) within child and school healthcare in Sweden. Inductive content analysis was used for data analysis.ResultsData showed that various trust-building aspects in health care organizations may contribute to readiness to implement mHealth. Several aspects were perceived to contribute trusting conditions: (a) how health-related data could be stored and managed; (b) how mHealth aligned with current organizational ways of working; (c) how implementation of mHealth was governed; and (d) camaraderie within a healthcare team to facilitate use of mHealth in practice. Poor capability to manage health-related data, as well as lack of governance of mHealth implementation were described as dealbreakers for readiness to implement mHealth in healthcare organizations.ConclusionsHealthcare professionals and policymakers perceived that trusting conditions for mHealth implementation within organizations were central for readiness. Specifically, governance of mHealth implementation and the ability to manage health-data produced by mHealth were perceived critical for readiness.
Citation: DIGITAL HEALTH
PubDate: 2023-06-14T06:59:14Z
DOI: 10.1177/20552076231181476
Issue No: Vol. 9 (2023)
- Technology acceptance of digital devices for home use: Qualitative results
of a mixed methods study
Authors: Johanna Graeber, Elke Warmerdam, Svenja Aufenberg, Christopher Bull, Kristen Davies, Jan Dixon, Kirsten Emmert, Claire Judd, Corina Maetzler, Ralf Reilmann, Wan-Fai Ng, Victoria Macrae, Walter Maetzler, Hanna Kaduszkiewicz
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDigital devices have demonstrated benefits to patients with chronic and neurodegenerative diseases. But when patients use medical devices in their homes, the technologies have to fit into their lives. We investigated the technology acceptance of seven digital devices for home use.MethodsWe conducted 60 semi-structured interviews with participants of a larger device study on their views on the acceptability of seven devices. Transcriptions were analysed using qualitative content analysis.ResultsBased on the unified theory of acceptance and use of technology, we evaluated effort, facilitating conditions, performance expectancy and social influence of each device.In the effort category, five themes emerged: (a) the hassle to use the device; (b) its usability; (c) comfort; (d) disturbance to daily life; and (e) problems during usage. Facilitating conditions consisted of five themes: (a) expectations regarding a device; (b) quality of the instructions; (c) insecurities with usage; (d) possibilities of optimization; and (e) possibilities to use the device longer. Regarding performance expectancy, we identified three themes: (a) insecurities with the performance of a device; (b) feedback; and (c) motivation for using a device. In the social influence category, three themes emerged: (a) reactions of peers; (b) concerns with the visibility of a device; and (c) concerns regarding data privacy.ConclusionsWe identify key factors that determine the acceptability of medical devices for home use from the participants’ perspective. These include low effort of use, minor disruptions to their daily lives and good support from the study team.
Citation: DIGITAL HEALTH
PubDate: 2023-06-14T06:58:29Z
DOI: 10.1177/20552076231181239
Issue No: Vol. 9 (2023)
- The lived experience of people with disabilities during the COVID-19
pandemic on Twitter: Content analysis
Authors: Marlon I. Diaz, Richard J. Medford, Christoph U. Lehmann, Carolyn Petersen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivePeople with disabilities (PWDs) are at greater risk of COVID-19 infection, complications, and death, and experience more difficulty accessing care. We analyzed Twitter tweets to identify important topics and investigate health policies’ effects on PWDs.MethodsTwitter's application programming interface was used to access its public COVID-19 stream. English-language tweets from January 2020 to January 2022 containing a combination of keywords related to COVID-19, disability, discrimination, and inequity were collected and refined to exclude duplicates, replies, and retweets. The remaining tweets were analyzed for user demographics, content, and long-term availability.ResultsThe collection yielded 94,814 tweets from 43,296 accounts. During the observation period, 1068 (2.5%) accounts were suspended and 1088 (2.5%) accounts were deleted. Account suspension and deletion among verified users tweeting about COVID-19 and disability were 0.13% and 0.3%, respectively. Emotions were similar among active, suspended, and deleted users, with general negative and positive emotions most common followed by sadness, trust, anticipation, and anger. The overall average sentiment for the tweets was negative. Ten of the 12 topics identified (96.8%) related to pandemic effects on PWDs; “politics that rejects and leaves the disabled, elderly, and children behind” (48.3%) and “efforts to support PWDs in the COVID crisis” (31.8%) were most common. The sample of tweets by organizations (43.9%) was higher for this topic than for other COVID-19-related topics the authors have investigated.ConclusionsThe primary discussion addressed how pandemic politics and policies disadvantage PWDs, older adults, and children, and secondarily expressed support for these populations. The increased level of Twitter use by organizations suggests a higher level of organization and advocacy within the disability community than in other groups. Twitter may facilitate recognition of increased harm to or discrimination against specific populations such as people living with disability during national health events.
Citation: DIGITAL HEALTH
PubDate: 2023-06-14T06:20:16Z
DOI: 10.1177/20552076231182794
Issue No: Vol. 9 (2023)
- Knowledge and perception of primary care healthcare professionals on the
use of artificial intelligence as a healthcare tool
Authors: Queralt Miró Catalina, Aïna Fuster-Casanovas, Josep Vidal-Alaball, Anna Escalé-Besa, Francesc X Marin-Gomez, Joaquim Femenia, Jordi Solé-Casals
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe rapid digitisation of healthcare data and the sheer volume being generated means that artificial intelligence (AI) is becoming a new reality in the practice of medicine. For this reason, describing the perception of primary care (PC) healthcare professionals on the use of AI as a healthcare tool and its impact in radiology is crucial to ensure its successful implementation.MethodsObservational cross-sectional study, using the validated Shinners Artificial Intelligence Perception survey, aimed at all PC medical and nursing professionals in the health region of Central Catalonia.ResultsThe survey was sent to 1068 health professionals, of whom 301 responded. And 85.7% indicated that they understood the concept of AI but there were discrepancies in the use of this tool; 65.8% indicated that they had not received any AI training and 91.4% that they would like to receive training. The mean score for the professional impact of AI was 3.62 points out of 5 (standard deviation (SD) = 0.72), with a higher score among practitioners who had some prior knowledge of and interest in AI. The mean score for preparedness for AI was 2.76 points out of 5 (SD = 0.70), with higher scores for nursing and those who use or do not know if they use AI.ConclusionsThe results of this study show that the majority of professionals understood the concept of AI, perceived its impact positively, and felt prepared for its implementation. In addition, despite being limited to a diagnostic aid, the implementation of AI in radiology was a high priority for these professionals.
Citation: DIGITAL HEALTH
PubDate: 2023-06-14T01:13:47Z
DOI: 10.1177/20552076231180511
Issue No: Vol. 9 (2023)
- Predicting hospitalization from real-world measures in patients with
chronic kidney disease: A proof-of-principle study
Authors: Kate Lyden, Nikita Abraham, Robert Boucher, Guo Wei, Victoria Gonce, Judy Carle, Sydney E. Hartsell, Jesse Christensen, Srinivasan Beddhu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo investigate if in-clinic measures of physical function and real-world measures of physical behavior and mobility effort are associated with one another and to determine if they predict future hospitalization in participants with chronic kidney disease (CKD).MethodsIn this secondary analysis, novel real-world measures of physical behavior and mobility effort, including the best 6-minute step count (B6SC), were derived from passively collected data from a thigh worn actigraphy sensor and compared to traditional in-clinic measures of physical function (e.g. 6-minute walk test (6MWT). Hospitalization status during 2 years of follow-up was determined from electronic health records. Correlation analyses were used to compare measures and Cox Regression analysis was used to compare measures with hospitalization.ResultsOne hundred and six participants were studied (69 ± 13 years, 43% women). Mean ± SD baseline measures for 6MWT was 386 ± 66 m and B6SC was 524 ± 125 steps. Forty-four hospitalization events over 224 years of total follow-up occurred. Good separation was achieved for tertiles of 6MWT, B6SC and steps/day for hospitalization events. This pattern persisted in models adjusted for demographics (6MWT: HR = 0.63 95% CI 0.43–0.93, B6SC: HR = 0.75, 95% CI 0.56–1.02 and steps/day: HR = 0.75, 95% CI 0.50–1.13) and further adjusted for morbidities (6MWT: HR = 0.54, 95% CI 0.35–0.84, B6SC: HR = 0.70, 95% CI 0.49–1.00 and steps/day: HR = 0.69, 95% CI 0.43–1.09).ConclusionDigital health technologies can be deployed remotely, passively, and continuously to collect real-world measures of physical behavior and mobility effort that differentiate risk of hospitalization in patients with CKD.
Citation: DIGITAL HEALTH
PubDate: 2023-06-13T06:08:29Z
DOI: 10.1177/20552076231181234
Issue No: Vol. 9 (2023)
- Social media use, uncertainty, and negative affect in times of pandemic
crisis
Authors: Yun Wu, Zihao An, Yi Lin, Jingyue Zhang, Bo Jing, Kaiping Peng
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveA common assertion in the social media literature is that passive media use undermines affective wellbeing, and active media use enhances it. The present study investigated the effects of social media use on negative affective wellbeing during pandemic crises and examined the mechanism underlying these effects through perceived uncertainty.MethodsThree studies were conducted during the Delta variant phase in the post-peak period of the COVID-19 pandemic in China. Participants were recruited from the medium-high-risk infection areas in late August 2022. Study 1 used a cross-sectional survey to explore the relationships between social media use, uncertainty, and negative affect during the pandemic crisis. Study 2 employed a repeated-measures experiment to demonstrate how social media use and (un)certainty impact negative affect. Study 3 utilized a one-week experience sampling design to examine the role of uncertainty in the relationship between social media use and negative affect in real life.ResultsDespite some inconsistencies regarding social media use's direct effect on negative affect, across the three studies, perceived uncertainty was critical in linking pandemic-related social media use to individuals’ negative affect, particularly for passive use.ConclusionsThe relationships between social media use and affective wellbeing are complex and dynamic. While the perception of uncertainty provided an underlying mechanism that links social media use to individuals’ affective wellbeing, this mechanism may be further moderated by individual-level factors. More research is needed as we seek to understand how social media use impacts affective wellbeing in uncertain contexts.
Citation: DIGITAL HEALTH
PubDate: 2023-06-12T11:01:37Z
DOI: 10.1177/20552076231181227
Issue No: Vol. 9 (2023)
- The feasibility and effectiveness of telecare consultations in nurse-led
post-acute stroke clinics: A study protocol
Authors: Arkers Kwan Ching Wong, Jonathan Bayuo, Frances Kam Yuet Wong, Vivian Wai Yan Kwok, Bernard Man Kam Yuen, Ching Sing Fong, Shun Tim Chan, Hoi Lam Pung, Oi Lam Kwek
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundGlobally, nurse-led post-acute stroke clinics have been developed to provide secondary care services to stroke survivors. Although synthesized evidence supports the idea that the secondary prevention services delivered by nurses in these clinics can improve the functional ability of stroke survivors and reduce their readmission rates, long travel and waiting times, high costs, and the pandemic have limited the utilization of such clinics. Telecare consultations are a new modality for expanding public access to healthcare services, although how it can be applied in nurse-led clinics has not been reported.ObjectiveThe aim of this study is to determine the feasibility and effects of telecare consultations in nurse-led post-acute stroke clinics.MethodsThe study adopts a quasi-experimental design. The participants will receive three secondary stroke care consultations in 3 months provided via telecare by experienced advanced practice nurses. The outcome measures include feasibility (reasons for refusing to participate and for dropping-out, the attitudes and satisfaction of both the advanced practice nurses and their patients towards the programme), and preliminary effectiveness (degree of disability after stroke, activities of daily living, instrumental activities of daily living, health-related quality of life, depression) outcomes. Data will be collected at pre-(T1) and post-(T2) intervention.ConclusionsThe findings of this study may help facilitate the implementation of telecare consultations in a nurse-led post-acute stroke clinic, which may benefit the stroke survivors who are having mobility restrictions from accessing customary healthcare services and may protect them from being exposed to the infectious risk.
Citation: DIGITAL HEALTH
PubDate: 2023-06-12T11:00:28Z
DOI: 10.1177/20552076231180759
Issue No: Vol. 9 (2023)
- Evaluating the utility of daily speech assessments for monitoring
depression symptoms
Authors: Melisa Gumus, Danielle D DeSouza, Mengdan Xu, Celia Fidalgo, William Simpson, Jessica Robin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDepression is a common mental health disorder and a major public health concern, significantly interfering with the lives of those affected. The complex clinical presentation of depression complicates symptom assessments. Day-to-day fluctuations of depression symptoms within an individual bring an additional barrier, since infrequent testing may not reveal symptom fluctuation. Digital measures such as speech can facilitate daily objective symptom evaluation. Here, we evaluated the effectiveness of daily speech assessment in characterizing speech fluctuations in the context of depression symptoms, which can be completed remotely, at a low cost and with relatively low administrative resources.MethodsCommunity volunteers (N = 16) completed a daily speech assessment, using the Winterlight Speech App, and Patient Health Questionnaire-9 (PHQ-9) for 30 consecutive business days. We calculated 230 acoustic and 290 linguistic features from individual's speech and investigated their relationship to depression symptoms at the intra-individual level through repeated measures analyses.ResultsWe observed that depression symptoms were linked to linguistic features, such as less frequent use of dominant and positive words. Greater depression symptomatology was also significantly correlated with acoustic features: reduced variability in speech intensity and increased jitter.ConclusionsOur findings support the feasibility of using acoustic and linguistic features as a measure of depression symptoms and propose daily speech assessment as a tool for better characterization of symptom fluctuations.
Citation: DIGITAL HEALTH
PubDate: 2023-06-12T10:59:59Z
DOI: 10.1177/20552076231180523
Issue No: Vol. 9 (2023)
- Assessment of eHealth literacy to reduce financial toxicity and improve
shared decision-making in cancer patients: A cross-sectional study
Authors: Richard Huan Xu, Ling-ling Wang, Ling-ming Zhou, Eliza Lai-yi Wong, Dong Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThis study aimed to investigate the associations between eHealth literacy, preferences for financial decision-making, and financial toxicity (FT) in a sample of Chinese cancer patients.MethodsEligible cancer patients were invited to participate in a cross-sectional survey from January to April 2021. Three measures (eHealth literacy scale, control preference scale, and COST) were used to analyze patients’ eHealth literacy, decisional preferences, and FT, respectively. Wilcoxon signed-rank test and Kruskal–Wallis H test assessed the differences between population subgroups. Binary logistic and multivariate linear regression models were used to assess the relationships between eHealth literacy, decisional preferences, and FT.ResultsA total of 590 cancer patients completed the questionnaire. We found that high FT was associated with poor ECOG performance, severe cancer stage, and longer cancer duration. Patients who preferred to adopt collaborative attitude toward decision-making showed a significantly higher eHealth literacy. However, there was an inverse relationship between eHealth literacy and a patient-driven attitude toward decision-making in female cancer patients. Regression analysis indicated that patients who were highly educated and actively employed might report a higher eHealth literacy. A significant relationship was found between high eHealth literacy and low FT. However, this relationship became insignificant when the background characteristics of cancer patients were taken into account.ConclusionsA relationship between enhanced eHealth literacy, preference for collaborative decision-making, and low risk of FT is identified.Practical implicationInterventions to improve patients’ ability to use quality and reliable web-based information on cancer care should be encouraged.
Citation: DIGITAL HEALTH
PubDate: 2023-06-12T09:35:55Z
DOI: 10.1177/20552076231181475
Issue No: Vol. 9 (2023)
- Electronic consultation accessibility influence on patient assessments: A
case–control study with user-generated tags of physician expertise
Authors: Haiyan Yu, Ya-Ling Chiu, Jying-Nan Wang, Jiang Yu, Yuan-Teng Hsu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveIn online health communities (OHCs), patients often list their physicians’ expertise by user-generated tags based on their consulted diseases. These expertise tags play an essential role in recommending the match of physicians to future patients. However, few studies have examined the impact of the accessibility of e-consults on patient assessments using marking of the physicians’ expertise in OHCs. This study aims to investigate what are the patient assessments of the physicians’ expertise if they have e-consult accessibility.MethodsThrough a case–control study, this article examined the effect of e-consult accessibility on patient-generated tags of physician expertise in OHCs. With data collected from the Good Doctor website, the samples consisted of 9841 physicians from 1255 different hospitals widely distributed in China. The breadth of voted expertise (BE) is measured by the number of consulted disease-related labels marked by a physician's served patients (SP). The volume of votes (VV) is measured by the number of a physician's votes given by the SP. The degree of voted diversity (DD) is measured by the information entropy of each physician's service expertise (labeled and voted by patients). The data analysis of e-consult accessibility is conducted by estimating the average treatment effect on the DD of physicians’ expertise.ResultsFor the BE, its mean was 7.305 for the case group of physicians with e-consults accessible (photo and text queries), while the mean was 9.465 for the control for physicians without e-consults. For the VV, its mean was 39.720 for the case group, while the mean was 84.565 for the control. For the DD, its mean on patient-generated tags was 2.103 for the case group, which is 0.413 lower than the control group.ConclusionThe availability of e-consults increases the concentration on physician expertise in the patient-generated tags. e-Consults reinforce the increment of the already-received physician expertise (reflected in tags), reducing the tag information diversity.
Citation: DIGITAL HEALTH
PubDate: 2023-06-12T09:35:16Z
DOI: 10.1177/20552076231180693
Issue No: Vol. 9 (2023)
- Effectiveness of biofeedback-assisted asynchronous telerehabilitation in
musculoskeletal care: A systematic review
Authors: Dora Janela, Fabíola Costa, Brandon Weiss, Anabela C. Areias, Maria Molinos, Justin K. Scheer, Jorge Lains, Virgílio Bento, Steven P. Cohen, Fernando Dias Correia, Vijay Yanamadala
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundMusculoskeletal conditions are the leading cause of disability worldwide. Telerehabilitation may be a viable option in the management of these conditions, facilitating access and patient adherence. Nevertheless, the impact of biofeedback-assisted asynchronous telerehabilitation remains unknown.ObjectiveTo systematically review and assess the effectiveness of exercise-based asynchronous biofeedback-assisted telerehabilitation on pain and function in individuals with musculoskeletal conditions.MethodsThis systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The search was conducted using three databases: PubMed, Scopus, and PEDro. Study criteria included articles written in English and published from January 2017 to August 2022, reporting interventional trials evaluating exercise-based asynchronous telerehabilitation using biofeedback in adults with musculoskeletal disorders. The risks of bias and certainty of evidence were appraised using the Cochrane tool and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE), respectively. The results are narratively summarized, and the effect sizes of the main outcomes were calculated.ResultsFourteen trials were included: 10 using motion tracker technology (N = 1284) and four with camera-based biofeedback (N = 467). Telerehabilitation with motion trackers yields at least similar improvements in pain and function in people with musculoskeletal conditions (effect sizes: 0.19–1.45; low certainty of evidence). Uncertain evidence exists for the effectiveness of camera-based telerehabilitation (effect sizes: 0.11–0.13; very low evidence). No study found superior results in a control group.ConclusionsAsynchronous telerehabilitation may be an option in the management of musculoskeletal conditions. Considering its potential for scalability and access democratization, additional high-quality research is needed to address long-term outcomes, comparativeness, and cost-effectiveness and identify treatment responders.
Citation: DIGITAL HEALTH
PubDate: 2023-06-10T04:29:49Z
DOI: 10.1177/20552076231176696
Issue No: Vol. 9 (2023)
- Which are the vital factors of mobile personal health records applications
that promote continued usage' A perspective on technology fit and social
capital
Authors: Yao-Yuan Liu, Hsi-Peng Lu, Chiao-Shan Chen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionWith the widespread use of mobile devices and the rapid development of mobile networks, connecting mobile personal health record (mPHR) apps to wearable devices to collect personal health data for analysis and community activities has become a trend for health promotion. Therefore, the present study aims to explore the vital factors that impact the sustained usage of mPHR apps.ObjectiveIn this study, we identified social lock-in as a major research gap in the current era of social media and the Internet. Therefore, to explore the effects of mPHR apps on continued app usage intention, we combined technology fit (individual-technology, synchronicity-technology, and task-technology fit) and social capital (structural, relational, and cognitive capital) to develop a novel study model.MethodsThe purpose of this research is to investigate the willingness to participate in the mPHR apps. It collected 565 valid users’ responses through the online questionnaire with a structural equation modeling approach.ResultsThat technology and social lock-in significantly affected the willingness of users to continue using mPHR apps (β = 0.38, P
Citation: DIGITAL HEALTH
PubDate: 2023-06-09T06:18:34Z
DOI: 10.1177/20552076231181216
Issue No: Vol. 9 (2023)
- Needs of patients with multi-morbidity and heart failure for the
development of a mHealth to improve their self-management: A qualitative
analysis
Authors: Pilar Bas-Sarmiento, Martina Fernández-Gutiérrez, Miriam Poza-Méndez, Mª Ángeles Carrasco-Bernal, Magdalena Cuenca-García, Mercedes Díaz-Rodríguez, Mª Paz Gómez-Jiménez, Olga Paloma-Castro, Alezandra Torres-Castaño, Antonio-Jesús Marín-Paz
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo provide practical information regarding needs, preferences of content and format of an app to assist the self-management in patients with multi-morbidity and heart failure (HF).MethodsThe three-phase study was conducted in Spain. Six integrative reviews, a qualitative methodology based on Van Manen's hermeneutic phenomenology through semi-structured interviews and user stories were used. Data collection continued until data saturation was reached. All data were transcribed verbatim and analysed using a framework approach. Thematic analysis technique following the methods of Braun and Clarke was used for emerging themes.ResultsIntegrative reviews conducted included practical recommendations to include in the content and format of the App and helped create the interview guide. Interviews revealed 15 subthemes that captured the meaning of narratives offering contextual insights into the development of the App. The main effective mechanisms of multicomponent interventions for patients with HF must contain (a) components that increase the patient's understanding of HF, (b) self-care, (c) self-efficacy and participation of the family/informal caregiver, (4) psychosocial well-being and (5) professional support and use of technology. User stories revealed that patients prioritized improvements in direct contact with health services in case of emergency (90%), nutritional information (70%), type of exercises in order to improve their physical condition (75%) and information about food and drug interaction (60%). The importance of motivation messages (60%) was highlighted by transversal way.ConclusionsThe three-phase process integrating theoretical basis, evidence from integrative reviews and research findings from target users has been considered a guide for future app development.
Citation: DIGITAL HEALTH
PubDate: 2023-06-09T05:28:11Z
DOI: 10.1177/20552076231180466
Issue No: Vol. 9 (2023)
- Benzodiazepine-related dementia risks and protopathic biases revealed by
multiple-kernel learning with electronic medical records
Authors: Takashi Hayakawa, Takuya Nagashima, Hayato Akimoto, Kimino Minagawa, Yasuo Takahashi, Satoshi Asai
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesTo simultaneously estimate how the risk of incident dementia nonlinearly varies with the administration period and cumulative dose of benzodiazepines, the duration of disorders with an indication for benzodiazepines, and other potential confounders, with the goal of settling the controversy over the role of benzodiazepines in the development of dementia.MethodsThe classical hazard model was extended using the techniques of multiple-kernel learning. Regularised maximum-likelihood estimation, including determination of hyperparameter values with 10-fold cross-validation, bootstrap goodness-of-fit test, and bootstrap estimation of confidence intervals, was applied to cohorts retrospectively extracted from electronic medical records of our university hospitals between 1 November 2004 and 31 July 2020. The analysis was mainly focused on 8160 patients aged 40 or older with new onset of insomnia, affective disorders, or anxiety disorders, who were followed up for [math] years.ResultsBesides previously reported risk associations, we detected significant nonlinear risk variations over 2–4 years attributable to the duration of insomnia and anxiety disorders, and to the administration period of short-acting benzodiazepines. After nonlinear adjustment for potential confounders, we observed no significant risk associations with long-term use of benzodiazepines.ConclusionsThe pattern of the detected nonlinear risk variations suggested reverse causation and confounding. Their putative bias effects over 2–4 years suggested similar biases in previously reported results. These results, together with the lack of significant risk associations with long-term use of benzodiazepines, suggested the need to reconsider previous results and methods for future analysis.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T07:27:59Z
DOI: 10.1177/20552076231178577
Issue No: Vol. 9 (2023)
- Use of Bluetooth contact tracing technology to model COVID-19 quarantine
policies in high-risk closed populations
Authors: Yinxiaohe Sun, Joel Ruihan Koo, Minah Park, Huso Yi, Borame L Dickens, Alex R Cook
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T07:26:30Z
DOI: 10.1177/20552076231178418
Issue No: Vol. 9 (2023)
- Virtual fall program assessment for frail Canadian community-dwelling
older adults: Examining equitable accessibility
Authors: Sophie M. Weiss, Matthew Castelo, Barbara Liu, Mireille Norris
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveIn response to COVID-19, the fall prevention program (FPP) at Sunnybrook Health Sciences Centre was modified to be delivered virtually. We compared patient populations assessed for the FPP virtually versus in-person to explore equitable accessibility.MethodsA retrospective chart review was performed. All patients assessed virtually from the beginning of the COVID-19 pandemic until the end of abstraction (April 25, 2022) were compared to a historic sample of patients assessed in-person beginning in January 2019. Demographics, measures of frailty, co-morbidity, and cognition were abstracted. Wilcoxon Rank Sum tests and Fisher's Exact tests were used for continuous and categorical variables, respectively.ResultsThirty patients were assessed virtually and compared to 30 in-person historic controls. Median age was 80 years (interquartile range 75–85), 82% were female, 70% were university educated, the median Clinical Frailty Score was 5 out of 9, and 87% used>5 medications. Once normalized, frailty scores showed no difference (p = 0.446). The virtual cohort showed significantly higher outdoor walking aid use (p = 0.015), reduced accuracy with clock drawing (p = 0.020), and nonsignificant trends toward using>10 medications, requiring assistance with>3 instrumental activities of daily living (IADLs), and higher treatment attendance. No significant differences were seen for time-to-treat (p = 0.423).ConclusionPatients assessed virtually were similarly frail as the in-person controls but had increased use of walking aids, medications, IADL assistance, and cognitive impairment. In a Canadian context, frail and high socioeconomic status older adults continued to access treatment through virtual FPP assessments during the COVID-19 pandemic highlighting both the benefits of virtual care and potential inequity.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T06:55:00Z
DOI: 10.1177/20552076231178410
Issue No: Vol. 9 (2023)
- Social media use and COVID-19 vaccine status among a nationally
representative population sample in Uganda
Authors: Abigail R Greenleaf, Ashley Croker-Benn, Dorothy Aibo, Sam Biraro, Veronica Mugisha, Muhire H Kwizera, Richard Kabanda, Jessica Justman, Wafaa M El-Sadr
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThe effect of social media on COVID-19 vaccination behavior is sub-Saharan Africa is unclear. We conducted a study to determine social media use among a random nationally representative sample of adults in Uganda and assessed the association between recent social media use and COVID-19 vaccination uptake.MethodsWe used data from the 2020 general population survey in Uganda, the Population-based HIV Impact Assessment Survey, to identify a probability sample for a mobile phone survey and included nonphone owners in the phone survey by asking phone owners to pass the phone.ResultsIn March 2022, of the 1022 survey participants, 213 (20%) did not own a mobile phone, 842 (80%) owned a mobile phone, of whom 199 (24%) indicated social media use, and 643 (76%) of whom did not use social media. Among all participants, the most frequent source of COVID-19 vaccine information was radio. Overall, 62% reported receiving the COVID-19 vaccination. The multivariable logistic regression model found that social media use was not associated with vaccination status.ConclusionSocial media users in this population sample from Uganda—who were mainly young, urban residents with higher educational attainment—continue to utilize TV, radio and health care workers for public health messages, thus the Government of Uganda should continue to conduct public health communication through these mediums.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T06:05:21Z
DOI: 10.1177/20552076231180733
Issue No: Vol. 9 (2023)
- Design propositions for nudging in healthcare: Adoption of national
electronic health record systems
Authors: Stefanie Steinhauser, Georgios Raptis
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesElectronic health records (EHRs) are considered important for improving efficiency and reducing costs of a healthcare system. However, the adoption of EHR systems differs among countries and so does the way the decision to participate in EHRs is presented. Nudging is a concept that deals with influencing human behaviour within the research stream of behavioural economics. In this paper, we focus on the effects of the choice architecture on the decision for the adoption of national EHRs. Our study aims to link influences on human behaviour through nudging with the adoption of EHRs to investigate how choice architects can facilitate the adoption of national information systems.MethodsWe employ a qualitative explorative research design, namely the case study method. Using theoretical sampling, we selected four cases (i.e., countries) for our study: Estonia, Austria, the Netherlands, and Germany. We collected and analyzed data from various primary and secondary sources: ethnographic observation, interviews, scientific papers, homepages, press releases, newspaper articles, technical specifications, publications from governmental bodies, and formal studies.ResultsThe findings from our European case studies show that designing for EHR adoption should encompass choice architecture elements (i.e., defaults), technical elements (i.e., choice granularity and access transparency), and institutional elements (i.e., regulations for data protection, information campaigns, and financial incentives) in combination.ConclusionsOur findings provide insights on the design of the adoption environments of large-scale, national EHR systems. Future research could estimate the magnitude of effects of the determinants.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T05:40:08Z
DOI: 10.1177/20552076231181208
Issue No: Vol. 9 (2023)
- Factors associated with fall risk of community-dwelling older people: A
decision tree analysis
Authors: Kenneth N K Fong, Raymond C K Chung, Patrick P C Sze, Carmen K M NG
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo examine the predictive attributes for accidental falls in community-dwelling older people in Hong Kong using decision tree analysis.MethodsWe recruited 1151 participants with an average age of 74.8 years by convenience sampling from a primary healthcare setting to carry out the cross-sectional study over 6 months. The whole dataset was divided into two sets, namely training set and test set, which respectively occupied 70% and 30% of the whole dataset. The training dataset was used first; decision tree analysis was used to identify possible stratifying variables that could help to generate separate decision models.ResultsThe number of fallers was 230 with 20% 1-year prevalence. There were significant differences in gender, use of walking aids, presence of chronic diseases, and co-morbidities including osteoporosis, depression, and previous upper limb fractures, and performance in the Timed Up and Go test and the Functional Reach test among the baselines between the faller and non-faller groups. Three decision tree models for the dependent dichotomous variables (fallers, indoor fallers, and outdoor fallers) were generated, with overall accuracy rates of the models of 77.40%, 89.44% and 85.76%, respectively. Timed Up and Go, Functional Reach, body mass index, high blood pressure, osteoporosis, and number of drugs taken were identified as stratifying variables in the decision tree models for fall screening.ConclusionThe use of decision tree analysis for clinical algorithms for accidental falls in community-dwelling older people creates patterns for decision-making in fall screening, which also paves the way for utility-based decision-making using supervised machine learning in fall risk detection.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T05:39:50Z
DOI: 10.1177/20552076231181202
Issue No: Vol. 9 (2023)
- The social grounds of self-tracking in insurance: A mixed-method approach
to adoption and use
Authors: Bastien Presset, Fabien Ohl
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Scholars have explored the role of self-tracking in mediating people's values, perceptions, and practices. But little is known about its institutionalised forms, although it is becoming a routine component of health policies and insurance programs. Furthermore, the role of structural elements such as sociodemographic variables, socialisations, and trajectories has been neglected. Using both quantitative (n = 818) and qualitative (n = 44) data gathered from users and non-users of an insurance program's self-tracking intervention, and drawing from Bourdieu's theoretical framework, we highlight the impact of users’ social background on the adoption and use of the technology. We show that older, poorer, and less educated individual are less likely to adopt the technology, and describe four prototypical categories of users, the meritocrats, the litigants, the scrutinisers and the good-intentioned. Each category displays different reasons and ways to use the technology that are grounded in users’ socialisations and life trajectories. Results suggest that too much emphasis may have been put on self-tracking's transformative powers and not enough on its reproductive inertia, with important consequences for both scholars, designers, and public health stakeholders.
Citation: DIGITAL HEALTH
PubDate: 2023-06-08T05:38:30Z
DOI: 10.1177/20552076231180731
Issue No: Vol. 9 (2023)
- Prospective mixed-methods study evaluating the potential of a voicebot
(CovBot) to relieve German health authorities during the COVID-19
infodemic
Authors: Vanessa Voelskow, Claudia Meßner, Tobias Kurth, Amelie Busam, Toivo Glatz, Natalie Ebert
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundDuring the COVID-19 pandemic, telephone hotlines of local health authorities in Germany were overloaded due to information requests by the public.ObjectiveEvaluating the use of a COVID-19-specific voicebot (CovBot) in local health authorities in Germany during the COVID-19 pandemic. This study investigates the performance of the CovBot by assessing a perceptible relief of staff in the hotline service.MethodsThis prospective mixed-methods study enrolled local health authorities in Germany from 01 February 2021 to 11 February 2022 to deploy the CovBot, which was mainly designed to answer frequently asked questions. To capture the user perspective and acceptance, we performed semistructured interviews and online surveys with their staff, conducted an online survey among callers, and analyzed the performance metrics of the CovBot.ResultsThe CovBot was implemented in 20 local health authorities serving 6.1 million German citizens and processed almost 1.2 million calls during the study period. The overall assessment was that the CovBot contributed to a perceived relief of the hotline service. In a survey among callers, 79% indicated that a voicebot could not replace a human. The analyzed anonymous metadata revealed that 15% of calls hung up immediately, 32% after hearing an FAQ answer, and 51% of calls were forwarded to the local health authority offices.ConclusionsA voicebot primarily answering FAQs can provide additional support to relieve the hotline service of local health authorities in Germany during the COVID-19 pandemic. For complex concerns, a forwarding option to a human proved to be an essential functionality.
Citation: DIGITAL HEALTH
PubDate: 2023-06-07T07:33:18Z
DOI: 10.1177/20552076231180677
Issue No: Vol. 9 (2023)
- Role of Internet of things in diabetes healthcare: Network infrastructure,
taxonomy, challenges, and security model
Authors: Muhammad Shoaib Farooq, Shamyla Riaz, Rabia Tehseen, Uzma Farooq, Khalid Saleem
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The Internet of things (IoT) is an emerging technology that enables ubiquitous devices to connect with the Internet. IoT technology has revolutionized the medical and healthcare industry by interconnecting smart devices and sensors. IoT-based devices and biosensors are ideal to detect diabetes disease by collecting the accurate value of glucose continuously. Diabetes is one of the well-known and major chronic diseases that has a worldwide social impact on community life. Blood glucose monitoring is a challenging task, and there is a need to propose a proper architecture of the noninvasive glucose sensing and monitoring mechanism, which could make diabetic people aware of self-management techniques. This survey presents a rigorous discussion of diabetes types and presents detection techniques based on IoT technology. In this research, an IoT-based healthcare network infrastructure has been proposed for monitoring diabetes disease based on big data analytics, cloud computing, and machine learning. The proposed infrastructure could handle the symptoms of diabetes, collect data, analyze it, and then transmit the results to the server for the next action. Besides, presented an inclusive survey on IoT-based diabetes monitoring applications, services, and proposed solutions. Furthermore, based on IoT technology the diabetes disease management taxonomy has also been presented. Finally, presented the attacks taxonomy as well as discussed challenges, and proposed a lightweight security model in order to secure the patient's health data.
Citation: DIGITAL HEALTH
PubDate: 2023-06-07T05:37:05Z
DOI: 10.1177/20552076231179056
Issue No: Vol. 9 (2023)
- Fragmented care trajectories in municipal healthcare: Local sensemaking of
digital documentation
Authors: Julie Duval Jensen, Loni Ledderer, Raymond Kolbæk, Kirsten Beedholm
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveSince the 1990s, almost all healthcare organisations have had electronic health records (EHR) to organise and manage treatment, care and work routines. This article aims to understand how healthcare professionals (HCPs) make sense of digital documentation practice.MethodsBased on a case study design, field observations and semi-structured interviews were conducted in a Danish municipality. A systematic analysis based on Karl Weick's sensemaking theory was applied to investigate what cues HCPs extract from timetables in the EHR and how institutional logics frame the enactment of documentation practice.ResultsThe analysis uncovered three themes: making sense of planning, making sense of tasks and making sense of documentation. The themes illustrate that HCPs make sense of the digital documentation practice as a dominant managerial tool designed to control resources and work routines. This sensemaking leads to a task-oriented practice which centres on delivering fragmented tasks according to a timetable.ConclusionHCPs mitigate fragmentation by responding to a care professional logic, where they document to share information and carry out invisible work outside of timetables and scheduled tasks. However, HCPs are focused on solving specific tasks by the minute with the possible consequence that continuity and their overview of the service user's care and treatment disappear. In conclusion, the EHR system eliminates a holistic view of care trajectories, leaving it up to HCPs to collaborate in an effort to obtain continuity for the service user.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T07:06:01Z
DOI: 10.1177/20552076231180521
Issue No: Vol. 9 (2023)
- Prediction of mortality risk and duration of hospitalization of COVID-19
patients with chronic comorbidities based on machine learning algorithms
Authors: Parastoo Amiri, Mahdieh Montazeri, Fahimeh Ghasemian, Fatemeh Asadi, Saeed Niksaz, Farhad Sarafzadeh, Reza Khajouei
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe severity of coronavirus (COVID-19) in patients with chronic comorbidities is much higher than in other patients, which can lead to their death. Machine learning (ML) algorithms as a potential solution for rapid and early clinical evaluation of the severity of the disease can help in allocating and prioritizing resources to reduce mortality.ObjectiveThe objective of this study was to predict the mortality risk and length of stay (LoS) of patients with COVID-19 and history of chronic comorbidities using ML algorithms.MethodsThis retrospective study was conducted by reviewing the medical records of COVID-19 patients with a history of chronic comorbidities from March 2020 to January 2021 in Afzalipour Hospital in Kerman, Iran. The outcome of patients, hospitalization was recorded as discharge or death. The filtering technique used to score the features and well-known ML algorithms were applied to predict the risk of mortality and LoS of patients. Ensemble Learning methods is also used. To evaluate the performance of the models, different measures including F1, precision, recall, and accuracy were calculated. The TRIPOD guideline assessed transparent reporting.ResultsThis study was performed on 1291 patients, including 900 alive and 391 dead patients. Shortness of breath (53.6%), fever (30.1%), and cough (25.3%) were the three most common symptoms in patients. Diabetes mellitus(DM) (31.3%), hypertension (HTN) (27.3%), and ischemic heart disease (IHD) (14.2%) were the three most common chronic comorbidities of patients. Twenty-six important factors were extracted from each patient's record. Gradient boosting model with 84.15% accuracy was the best model for predicting mortality risk and multilayer perceptron (MLP) with rectified linear unit function (MSE = 38.96) was the best model for predicting the LoS. The most common chronic comorbidities among these patients were DM (31.3%), HTN (27.3%), and IHD (14.2%). The most important factors in predicting the risk of mortality were hyperlipidemia, diabetes, asthma, and cancer, and in predicting LoS was shortness of breath.ConclusionThe results of this study showed that the use of ML algorithms can be a good tool to predict the risk of mortality and LoS of patients with COVID-19 and chronic comorbidities based on physiological conditions, symptoms, and demographic information of patients. The Gradient boosting and MLP algorithms can quickly identify patients at risk of death or long-term hospitalization and notify physicians to do appropriate interventions.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T07:04:58Z
DOI: 10.1177/20552076231170493
Issue No: Vol. 9 (2023)
- Design and assessment of amblyopia, strabismus, and myopia treatment and
vision training using virtual reality
Authors: Hoi Sze Chan, Yuk Ming Tang, Chi Wai Do, Horace Ho Yin Wong, Lily YL Chan, Suet To
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundVirtual reality is a relatively new intervention that has the potential to be used in the treatment of eye and vision problems. This article reviews the use of virtual reality-related interventions in amblyopia, strabismus, and myopia research.MethodsSources covered in the review included 48 peer-reviewed research published between January 2000 and January 2023 from five electronic databases (ACM Digital Library, IEEE Xplore, PubMed, ScienceDirect and Web of Science). To prevent any missing relevant articles, the keywords, and terms used in the search included “VR”, “virtual reality”, “amblyopia”, “strabismus,” and “myopia”. Quality assessment and data extraction were performed independently by two authors to form a narrative synthesis to summarize findings from the included research.ResultsTotal number of 48 references were reviewed. There were 31 studies published on amblyopia, 18 on strabismus, and 6 on myopia, with 7 studies overlapping amblyopia and strabismus. In terms of technology, smartphone-based virtual reality headset viewers were utilized more often in amblyopia research, but commercial standalone virtual reality headsets were used more frequently in myopia and strabismus-related research. The software and virtual environment were mostly developed based on vision therapy and dichoptic training paradigms.ConclusionIt has been suggested that virtual reality technology offers a potentially effective tool for amblyopia, strabismus, and myopia studies. Nonetheless, a variety of factors, especially the virtual environment and systems employed in the data presented, must be explored before determining whether virtual reality can be effectively applied in clinical settings. This review is significant as the technology in virtual reality software and application design features have been investigated and considered for future reference.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T07:02:42Z
DOI: 10.1177/20552076231176638
Issue No: Vol. 9 (2023)
- Exploring patient participation during video consultations: A qualitative
study
Authors: Martin Vinther Bavngaard, Elle Christine Lüchau, Elisabeth Assing Hvidt, Anette Grønning
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveVideo consultations enable a digital point of contact between the general practitioner and patient. With their medium-specific characteristics, video consultations may create novel conditions for the enactment of patient participation during consultations. Although numerous studies have explored patients’ experiences of video consultations, research explicitly investigating patient participation within this new consultation setting remains sparse. This qualitative study explores how patients participate during interactions with their general practitioner by drawing on the affordances of video consultations.MethodsThe data corpus comprises eight recorded video consultations (59 minutes and 19 seconds in total) between patients and their general practitioner, all subjected to reflexive thematic analysis yielding three themes illustrating concrete participatory use cases.ResultsWe find that video consultations provide an accessible format for patients otherwise unable to attend a physical consultation due to physical and mental barriers. Moreover, patients participate by drawing on resources situated in their spatial setting to settle health-related questions of doubt arising during the consultation. Lastly, we posit that patients enact participation by visually communicating their impromptu engagement in decision-making and reporting to their general practitioner by making use of the qualities of their smartphone during their consultation.ConclusionsOur findings illustrate how video consultations provide a communicative context in which patients may enact distinct forms of participation by drawing on its technologically contingent affordances during interactions with their general practitioner. More research is needed to explore the participatory opportunities of video consultations in telemedical healthcare services for different patient groups.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T06:38:41Z
DOI: 10.1177/20552076231180682
Issue No: Vol. 9 (2023)
- Predictors of sustained use of mobile health applications: Content
analysis of user perspectives from a fever management app
Authors: Sara Hamideh Kerdar, Moritz Gwiasda, Bettina Berger, Larisa Rathjens, Silke Schwarz, Ekkehart Jenetzky, David D Martin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesMobile health applications could be means of educating and changing behaviours of their users. Their features and qualities determine the sustainability of use. The FeverApp with two main features of information and documentation is a research-based app. In this observational cohort study, to evaluate the influential predictors of use, users’ feedback on the FeverApp, were analyzed.MethodsFeedback is given using a structured questionnaire, four Likert items and two open questions regarding positive and negative impressions, available via app menu. Conventional content analysis (inductive approach) on the two open questions was performed. Comments were grouped into 12 codes. These codes were grouped hierarchically in an iterative process into nine subcategories and lastly into two main categories ‘format’ and ‘content’. Descriptive and quantitative analysis were performed.ResultsOut of 8243 users, 1804 of them answered the feedback questionnaire. The features of the app (N = 344), followed by the information aspect (N = 330) were most frequently mentioned. Documentation process (N = 226), request for new features or improvement of the current ones (N = 193), and functioning (N = 132) were also highlighted in users’ feedback. App's ease of use, design and being informative were important for the users. The first impression of the app seems important as the majority of feedback were given during the first month of using the app.ConclusionIn-app feedback function could highlight shortcomings and strengths of mobile health apps. Taking users’ feedback into consideration could increase the chance of sustained use. Besides ease of use and clear, likeable designs, users want apps that serve their needs while saving time.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T06:38:01Z
DOI: 10.1177/20552076231180418
Issue No: Vol. 9 (2023)
- Assessing the use of a noninvasive monitoring system providing multiple
Authors: Itzhak Sharabi, Roei Merin, Yuri Gluzman, Rozi Grinshpan, Angelika Shtivelman, Arik Eisenkraft, Ronen Rubinshtein
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundContinuous monitoring of ECG, respiratory rate, systolic and diastolic blood pressure, pulse rate, cardiac output, and cardiac index is important in patients with ST-elevation myocardial infarction (STEMI) admitted to the intensive cardiac care unit (ICCU). However, monitoring these parameters in this setting and in these patients using noninvasive, wireless devices has not been conducted so far. We aimed to assess the use of a novel noninvasive continuous monitoring device in STEMI patients admitted to the ICCU.MethodsParticipants included STEMI patients that were admitted to the ICCU after primary percutaneous coronary intervention (PPCI). Patients were continuously monitored using a novel wearable chest patch monitor.ResultsFifteen patients with STEMI who underwent PPCI were included in this study. The median age was 52.8 years, the majority were males, and the median body mass index (BMI) was 25.7. Monitoring lasted for 66 ± 16 hours, and included the automatic collection and recording of all vitals, freeing the nursing staff to focus on other tasks. The user experience of nurses as reflected in filled questionnaires showed high satisfaction rates in all aspects.ConclusionA novel noninvasive, wireless device showed high feasibility in continuously monitoring multiple crucial parameters in STEMI patients admitted to the ICCU after PPCI.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T06:37:03Z
DOI: 10.1177/20552076231179014
Issue No: Vol. 9 (2023)
- Screening for degenerative cervical myelopathy with the 10-second
grip-and-release test using a smartphone and machine learning: A pilot
study
Authors: Takuya Ibara, Ryota Matsui, Takafumi Koyama, Eriku Yamada, Akiko Yamamoto, Kazuya Tsukamoto, Hidetoshi Kaburagi, Akimoto Nimura, Toshitaka Yoshii, Atsushi Okawa, Hideo Saito, Yuta Sugiura, Koji Fujita
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveEarly detection and intervention are essential for the mitigation of degenerative cervical myelopathy (DCM). However, although several screening methods exist, they are difficult to understand for community-dwelling people, and the equipment required to set up the test environment is expensive. This study investigated the viability of a DCM-screening method based on the 10-second grip-and-release test using a machine learning algorithm and a smartphone equipped with a camera to facilitate a simple screening system.MethodsTwenty-two participants comprising a group of DCM patients and 17 comprising a control group participated in this study. A spine surgeon diagnosed the presence of DCM. Patients performing the 10-second grip-and-release test were filmed, and the videos were analyzed. The probability of the presence of DCM was estimated using a support vector machine algorithm, and sensitivity, specificity, and area under the curve (AUC) were calculated. Two assessments of the correlation between estimated scores were conducted. The first used a random forest regression model and the Japanese Orthopaedic Association scores for cervical myelopathy (C-JOA). The second assessment used a different model, random forest regression, and the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire.ResultsThe final classification model had a sensitivity of 90.9%, specificity of 88.2%, and AUC of 0.93. The correlations between each estimated score and the C-JOA and DASH scores were 0.79 and 0.67, respectively.ConclusionsThe proposed model could be a helpful screening tool for DCM as it showed excellent performance and high usability for community-dwelling people and non-spine surgeons.
Citation: DIGITAL HEALTH
PubDate: 2023-06-06T02:32:17Z
DOI: 10.1177/20552076231179030
Issue No: Vol. 9 (2023)
- Association of digital health literacy and information-seeking behaviors
among physicians during COVID-19 in Ethiopia: A cross-sectional study
Authors: Bayou Tilahun Assaye, Mitiku Kassa, Muluken Belachew, Sefefe Birhanu, Aynadis Worku
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundUniversal access to health information is a requirement for all global health strategies in the era of pandemics. Getting health information from the internet is a great concern for the quality of patient healthcare. This study aimed to determine the association between digital health literacy and information-seeking behavior among physicians during COVID-19.MethodsAn institutional-based cross-sectional study was conducted from December to February 2021 with a total sample size of 423. A pretest was performed among physicians before the actual data collection. After the data collection, the data were checked, cleaned, and exported into STATA v. 14. Descriptive statistics, binary logistic regression, and multivariable logistic regression analysis were applied. Then a 95% CI and a p-value of less than 0.05 were used to declare statistical significance.ResultsThe study revealed that 53.81% of physicians had high digital health literacy and 52.46% had high information-seeking behaviors. Health information-seeking behaviors were determined by digital health literacy, which was 2.25 times more likely than those who had low digital health literacy (AOR = 2.25, 95% CI: [1.11–4.57]). Health-related websites (67.5%) were the most common sources of health information, and 63.30% of physicians find digital health literacy easy or very easy to learn. However, 206 (50.92%) find it difficult or very difficult to decide if the information is reliable, verified, and up-to-date. Internet access (AOR = 1.90, 95% CI: [1.16–3.12]), frequency of searching for information (AOR = 5.35, 95% CI: [2.01–14.29]). All were discovered to be significantly associated with physicians’ health information-seeking behaviors.ConclusionsDigital health literacy is a key to seeking health information online for appropriate decision-making. Increasing internet access, and providing ICT training, and integrate it into the health information revolution agendas, helping to disseminate health information and provide timely, reliable, and relevant news and genuine information needed for their work.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T06:54:33Z
DOI: 10.1177/20552076231180436
Issue No: Vol. 9 (2023)
- Exploring the mass adoption potential of wearable fitness devices in
Malaysia
Authors: Naeem Hayat, Anas A Salameh, Abdullah Al Mamun, Syed Shah Alam, Noor Raihani Zainol
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe current study explores the formation of an intention to use wearable fitness devices (WFDs) with wearable fitness attributes and health consciousness (HCS). Moreover, the research examines the use of WFDs with the health motivation (HMT) and intention to use WFDs. The study also exposes the moderating effect of HMT between the intention to use WFDs and the use of WFDs.MethodsFive hundred and twenty-five adults participated in the current study, and data were collected from January 2021 to March 2021 through the online survey of Malaysian respondents. The cross-sectional data was analyzed using the second-generation statistical method of partial least square structural equation modeling.ResultsHCS is insignificantly associated with the intention to use WFDs. Perceived compatibility, perceived product value, perceived usefulness, and perceived technology accuracy significantly influence the intention to use WFDs. HMT significantly impacts the adoption of WFDs; however, the intention to use WFDs negatively but significantly influences the use of WFDs. Lastly, the association between the intention to use WFDs and the adoption of WFDs is significantly moderated by HMT.ConclusionsOur study findings illuminate the significant impact of technology-level attributes of WFDs on the intention to use WFDs. However, an insignificant impact of HCS on the intention to use WFDs was reported. Our result confirms that HMT plays a significant role in the use of WFDs. Such as the moderating role of HMT is vital to transform the intention to use WFDs into the adoption of WFDs.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T06:29:32Z
DOI: 10.1177/20552076231180728
Issue No: Vol. 9 (2023)
- MonDiaL-CAD: Monkeypox diagnosis via selected hybrid CNNs unified with
feature selection and ensemble learning
Authors: Omneya Attallah
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveRecently, monkeypox virus is slowly evolving and there are fears it will spread as COVID-19. Computer-aided diagnosis (CAD) based on deep learning approaches especially convolutional neural network (CNN) can assist in the rapid determination of reported incidents. The current CADs were mostly based on an individual CNN. Few CADs employed multiple CNNs but did not investigate which combination of CNNs has a greater impact on the performance. Furthermore, they relied on only spatial information of deep features to train their models. This study aims to construct a CAD tool named “Monkey-CAD” that can address the previous limitations and automatically diagnose monkeypox rapidly and accurately.MethodsMonkey-CAD extracts features from eight CNNs and then examines the best possible combination of deep features that influence classification. It employs discrete wavelet transform (DWT) to merge features which diminishes fused features' size and provides a time-frequency demonstration. These deep features’ sizes are then further reduced via an entropy-based feature selection approach. These reduced fused features are finally used to deliver a better representation of the input features and feed three ensemble classifiers.ResultsTwo freely accessible datasets called Monkeypox skin image (MSID) and Monkeypox skin lesion (MSLD) are employed in this study. Monkey-CAD could discriminate among cases with and without Monkeypox achieving an accuracy of 97.1% for MSID and 98.7% for MSLD datasets respectively.ConclusionsSuch promising results demonstrate that the Monkey-CAD can be employed to assist health practitioners. They also verify that fusing deep features from selected CNNs can boost performance.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T06:28:32Z
DOI: 10.1177/20552076231180054
Issue No: Vol. 9 (2023)
- Development and initial application of a harmonised multi-jurisdiction
work injury compensation database
Authors: Michael Di Donato, Luke R. Sheehan, Shannon Gray, Ross Iles, Caryn van Vreden, Alex Collie
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesWorkers’ compensation schemes provide funding for wage replacement and healthcare for injured and ill workers. In Australia, workers’ compensation schemes operate independently in different jurisdictions, making comparisons of health service use challenging. We sought to develop and deploy a new database of health service and income support data, harmonising data from multiple Australian workers’ compensation jurisdictions.MethodsWe worked with workers’ compensation authorities from six Australian jurisdictions to combine claims, healthcare, medicines and wage replacement data for a sample of compensated workers with claims for musculoskeletal conditions. We designed a structured relational database and developed a bespoke health services coding scheme to harmonise data across jurisdictions.ResultsThe Multi-Jurisdiction Workers’ Compensation Database contains four data sets: claims, services, medicines and wage replacement. The claims data set contains 158,946 claims for low back pain (49.6%), limb fracture (23.8%) and non-specific limb conditions (26.7%). The services data set contains a total of 4.2 million cleaned and harmonised services including doctors (29.9%), physical therapists (56.3%), psychological therapists (2.8%), diagnostic procedures (5.5%) and examinations and assessments (5.6%). The medicines data set contains 524,380 medicine dispenses, with 208,504 (39.8%) dispenses for opioid analgesics.ConclusionsThe development of this database presents potential opportunities to gain a greater understanding of health service use in the Australian workers’ compensation sector, to measure the impact of policy change on health services and to provide a method for further data harmonisation. Future efforts could seek to conduct linkage with other data sources.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T06:27:13Z
DOI: 10.1177/20552076231176695
Issue No: Vol. 9 (2023)
- Perceived benefits of digital health and social services among older
adults: A population-based cross-sectional survey
Authors: Emma Kainiemi, Petra Saukkonen, Lotta Virtanen, Tuulikki Vehko, Maiju Kyytsönen, Mari Aaltonen, Tarja Heponiemi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe aim of this study was to describe the benefits of digital health and social services perceived by older adults and to examine factors associated with perceiving these benefits. Several factors related to (a) sociodemographic characteristics, (b) area of residence, (c) physical, cognitive, psychological, and social functioning, and (d) Internet use, were examined.MethodsThe present sample included 8019 respondents aged between 75 and 99 years. The inverse probability weighting method was used to correct for bias. Linear regression analyses were used to examine the associations.ResultsThe ease of use of the services regardless of the time and location was perceived as the most beneficial. Convenient distance to local health or social services (parameter estimate = 0.15 [0.08–0.23]), good functional ability (PE = 0.08 [0.01–0.14]), good vision (PE = 0.15 [0.04–0.25]), ability to learn (PE = 0.05 [0.01–0.10]) and living with someone (PE = 0.08 [95% CI 0.04–0.13]) were associated with perceiving more benefits. In addition, access to the Internet (PE = 0.12 [0.06–0.19]) and independent use of the Internet (PE = 0.23 [0.17–0.29]) were associated with perceiving more benefits.ConclusionsOlder adults who are healthier, have a social relationship in their everyday life or have easier access to traditional services seem to perceive more benefits from digital health and social services. Digital services should be developed to correspond with special needs caused by disadvantages in health and the social environment. To facilitate the use of digital health and social services, more efforts should be made to enhance older adults’ perceptions of their benefits.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T06:26:13Z
DOI: 10.1177/20552076231173559
Issue No: Vol. 9 (2023)
- Remote vision testing of central retinal acuity and comparison with
clinic-based Snellen acuity testing in patients followed for retinal
conditions
Authors: Earnest P Chen, Michael Mills, Tara Gallagher, Andrew Polis, Sophie Blasberg, Peter Pham, Ronald C Gentile, Tsontcho Ianchulev
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionThe unmet need for remote monitoring of visual function with home-based, patient-centric technologies became increasingly palpable during the COVID-19 pandemic. Many patients with chronic eye conditions lack access to office-based examinations. Here, we evaluate the efficacy of the Accustat® test, a virtual application for measuring near visual acuity on any portable electronic device via telehealth.Materials and methodsThirty-three adult subjects from the telehealth remote monitoring service of a retina practice performed the Accustat® acuity testing at home. All patients underwent in-office general eye examination with additional fundoscopic examination and optical coherence tomography retina imaging. Best corrected visual acuity assessment using a Snellen chart was compared with remote visual acuity assessment with the Accustat® test. Visual acuity was analyzed and compared between the best-corrected near visual acuity potential achieved on the Accustat® and in-office distance best-corrected Snellen visual acuity.ResultsThe mean logarithm of the minimum angle of resolution (logMAR) visual acuities of all eyes tested using the Accustat test was 0.19 ± 024 and for the office Snellen test 0.21 ± 0.21. A linear regression model with 95% confidence intervals reveals that there is a strong linear relationship between Accustat logMAR and office Snellen logMAR. Bland–Altman analysis demonstrated 95.2% significant agreement between Accustat and Office Snellen’s best corrected visual acuity. Intraclass correlation coefficient (ICC = 0.94) demonstrated a strong positive correlation between at home versus office visual acuity.ConclusionThere was a high correlation between the visual acuity measured with the Accustat near vision digital self-test and the office Snellen acuity test, suggesting the potential utility of scalable remote monitoring of central retinal function via telehealth.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T05:25:24Z
DOI: 10.1177/20552076231180727
Issue No: Vol. 9 (2023)
- A machine learning approach on chest X-rays for pediatric pneumonia
detection
Authors: Natali Barakat, Mahmoud Awad, Bassam A Abu-Nabah
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAccording to the World Health Organization (WHO), pneumonia is the leading infectious cause of death in children below 5 years old. Hence, the early detection of pediatric pneumonia is crucial to reduce its morbidity and mortality rates. Even though chest radiography is the most commonly employed modality for pneumonia detection, recent studies highlight the existence of poor interobserver agreement in the chest X-ray interpretation of healthcare practitioners when it comes to diagnosing pediatric pneumonia. Thus, there is a significant need for automating the detection process to minimize the potential human error. Since Artificial Intelligence tools such as Deep Learning (DL) and Machine Learning (ML) have the potential to automate disease detection, many researchers explored how such tools can be implemented to detect pneumonia in chest X-rays. Notably, the majority of efforts tackled this problem from a DL point of view. However, ML has shown a higher potential for medical interpretability while being less computationally demanding than DL.ObjectiveThe aim of this paper is to automate the early detection process of pediatric pneumonia using ML as it is less computationally demanding than DL.MethodsThe proposed approach entails performing data augmentation to balance the classes of the utilized dataset, optimizing the feature extraction scheme, and evaluating the performance of several ML models. Moreover, the performance of this approach is compared to a TL benchmark to evaluate its candidacy.ResultsUsing the proposed approach, the Quadratic SVM model yielded an accuracy of 97.58%, surpassing the accuracies reported in the current ML literature. In addition, this model classification time was significantly smaller than that of the TL benchmark.ConclusionThe results strongly support the candidacy of the proposed approach in reliably detecting pediatric pneumonia.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T05:21:12Z
DOI: 10.1177/20552076231180008
Issue No: Vol. 9 (2023)
- Virtual reality for healthcare: A scoping review of commercially available
applications for head-mounted displays
Authors: Samar Helou, Nour Khalil, Melissa Daou, Elie El Helou
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis scoping review aimed to describe the scope of commercially available virtual reality (VR) healthcare applications for mainstream head-mounted displays (HMD)s.MethodsA search was conducted during late April and early May 2022 over five major VR app stores using “health,” “healthcare,” “medicine,” and “medical” as keywords. Apps were screened based on their title and description sections. Metadata collected included: title, description, release date, price (free or paid), multilingual support, VR app store availability, and HMD support.ResultsThe search yielded 1995 apps, out of which 60 met the inclusion criteria. The analysis showed that the number of healthcare VR apps has been steadily increasing since 2016, but no developer has released more than two apps so far. Most of the reviewed apps can run on HTC Vive, Oculus Quest, and Valve Index. Thirty-four (56.7%) apps had a free version, and 12 (20%) apps were multilingual, i.e., supported languages other than English. The reviewed apps fell into eight major themes: life science education (3D anatomy, physiology and pathology, biochemistry, and genetics); rehabilitation (physical, mental, and phobia therapy); public health training (safety, life-saving skills, and management); medical training (surgical and patient simulators); role-playing as a patient; 3D medical imagery viewing; children's health; and online health communities.ConclusionsAlthough commercial healthcare VR is still in its early phases, end-users can already access a broad range of healthcare VR apps on mainstream HMDs. Further research is needed to assess the usefulness and usability of existing apps.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T05:19:52Z
DOI: 10.1177/20552076231178619
Issue No: Vol. 9 (2023)
- Evaluation of response to incentive recruitment strategies in a social
media-based survey
Authors: Megumi Ichimiya, Hope Muller-Tabanera, Jennifer Cantrell, Jeffrey B Bingenheimer, Raquel Gerard, Elizabeth C Hair, Dante Donati, Nandan Rao, W Douglas Evans
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study aimed to examine varying incentives on acceptance to participate in an online survey on social media and to identify related demographic factors.MethodsThe study used Facebook and targeted its users aged 18 to 24 years in the United States. During recruitment, participants were randomized to one of the three types of incentives for survey completion, (1) a $5 gift card, (2) a lottery for a $200 gift card, and (3) a $5 gift card plus a lottery for a $200 gift card. Acceptance rates for survey participation were compared across three incentives using percentages, 95% logit-transformed confidence intervals, and Pearson’s chi-squared tests. The survey asked about cognition and behaviors around smoking and vaping.ResultsThe ads had 1,782,931 impressions, 1,104,139 reaches, and 11,878 clicks. The average ad frequency was 1.615, and the click-through rate was 0.67%. Males clicked less than females when seeing the ads. The acceptance rates for the three incentives were 63.7%, 37.2%, and 64.6%, respectively. A Chi-square test confirmed that the lottery-only group had a lower acceptance rate compared to those guaranteed an incentive, including the gift card group and the gift card and lottery group. Further analyses indicated that males did not opt into the survey as often as females when given the lottery-only incentive option, and those who did not meet their financial expenses opted into the survey more often than those who had more money than their expenses when given the lottery-only incentive option.ConclusionsThis study suggests that incentives guaranteed to all participants, even if the incentive's value is small, may lead to higher acceptance rates compared to a lottery for a greater incentive in social media-based surveys.
Citation: DIGITAL HEALTH
PubDate: 2023-06-05T05:19:13Z
DOI: 10.1177/20552076231178430
Issue No: Vol. 9 (2023)
- User-centered design of feedback regarding health-related behaviors
derived from wearables: An approach targeting older adults and persons
living with neurodegenerative disease
Authors: Karen Van Ooteghem, F Elizabeth Godkin, Vanessa Thai, Kit B Beyer, Benjamin F Cornish, Kyle S Weber, Hannah Bernstein, Soha O Kheiri, Richard H Swartz, Brian Tan, William E McIlroy, Angela C Roberts
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThere has been tremendous growth in wearable technologies for health monitoring but limited efforts to optimize methods for sharing wearables-derived information with older adults and clinical cohorts. This study aimed to co-develop, design and evaluate a personalized approach for information-sharing regarding daily health-related behaviors captured with wearables.MethodsA participatory research approach was adopted with: (a) iterative stakeholder, and evidence-led development of feedback reporting; and (b) evaluation in a sample of older adults (n = 15) and persons living with neurodegenerative disease (NDD) (n = 25). Stakeholders included persons with lived experience, healthcare providers, health charity representatives and individuals involved in aging/NDD research. Feedback report information was custom-derived from two limb-mounted inertial measurement units and a mobile electrocardiography device worn by participants for 7–10 days. Mixed methods were used to evaluate reporting 2 weeks following delivery. Data were summarized using descriptive statistics for the group and stratified by cohort and cognitive status.ResultsParticipants (n = 40) were 60% female (median 72 (60–87) years). A total of 82.5% found the report easy to read or understand, 80% reported the right amount of information was shared, 90% found the information helpful, 92% shared the information with a family member or friend and 57.5% made a behavior change. Differences emerged in sub-group comparisons. A range of participant profiles existed in terms of interest, uptake and utility.ConclusionsThe reporting approach was generally well-received with perceived value that translated into enhanced self-awareness and self-management of daily health-related behaviors. Future work should examine potential for scale, and the capacity for wearables-derived feedback to influence longer-term behavior change.
Citation: DIGITAL HEALTH
PubDate: 2023-06-02T07:22:44Z
DOI: 10.1177/20552076231179031
Issue No: Vol. 9 (2023)
- Attitudes of psychiatrists toward telepsychiatry: A policy Delphi study
Authors: Maya Negev, Tamir Magal, Hanoch Kaphzan
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesTo delineate areas of consensus and disagreements among practicing psychiatrists from various levels of clinical experience, hierarchy and organizations, and to test their ability to converge toward agreement, which will enable better integration of telepsychiatry into mental health services.MethodsTo study attitudes of Israeli public health psychiatrists, we utilized a policy Delphi method, during the early stages of the COVID pandemic. In-depth interviews were conducted and analyzed, and a questionnaire was generated. The questionnaire was disseminated amongst 49 psychiatrists, in two succeeding rounds, and areas of consensus and controversies were identified.ResultsPsychiatrists showed an overall consensus regarding issues of economic and temporal advantages of telepsychiatry. However, the quality of diagnosis and treatment and the prospect of expanding the usage of telepsychiatry to normal circumstances—beyond situations of pandemic or emergency were disputed. Nonetheless, efficiency and willingness scales slightly improved during the 2nd round of the Delphi process. Prior experience with telepsychiatry had a strong impact on the attitude of psychiatrists, and those who were familiar with this practice were more favorable toward its usage in their clinic.ConclusionsWe have delineated experience as a major impact on the attitudes toward telepsychiatry and the willingness for its assimilation in clinical practice as a legitimate and trustworthy method. We have also observed that the organizational affiliation significantly affected psychiatrists’ attitude, when those working at local clinics were more positive toward telepsychiatry compared with employees of governmental institutions. This might be related to experience and differences in organizational environment. Taken together, we recommend to include hands-on training of telepsychiatry in medical education curriculum during residency, as well as refresher exercises for attending practitioners.
Citation: DIGITAL HEALTH
PubDate: 2023-06-02T06:38:29Z
DOI: 10.1177/20552076231177132
Issue No: Vol. 9 (2023)
- An interpretable artificial neural network model for predicting hypoxemia
via an online tool in adult (18–64) patients during
esophagogastroduodenoscopy
Authors: Weigen Xiong, Daizun Zou, Zhaojing Fang, Xiuxiu Zhao, Chen Chen, Jianjun Zou, Yanna Si
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundThe hypoxemia risk in adult (18–64) patients treated with esophagogastroduodenoscopy (EGD) under sedation often poses a dilemma for anesthesiologists. We aimed to establish an artificial neural network (ANN) model to solve this problem, and introduce the Shapley additive explanations (SHAP) algorithm to further improve the interpretability.MethodsThe relevant data of patients underwent routine anesthesia-assisted EGD were collected. Elastic network was used to filter the optimal features. Airway-ANN and Basic-ANN models were established based on all collected indicators and remaining variables excluding airway assessment indicators, respectively. The performance of Basic-ANN, Airway-ANN and STOP-BANG was evaluated by the area under the precision-recall curve (AUPRC) on temporal validation set. The SHAP was used for revealing the predictive behavior of our best model.Results999 patients were eventually included. The AUPRC value of Airway-ANN model was significantly higher than Basic-ANN model in the temporal validation set (0.532 vs 0.429, P
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T06:32:27Z
DOI: 10.1177/20552076231180522
Issue No: Vol. 9 (2023)
- Untargeted metabolomics characterization of the resectable pancreatic
ductal adenocarcinoma
Authors: Ying-Ying Cao, Kai Guo, Rui Zhao, Yuan Li, Xiao-Jing Lv, Zi-Peng Lu, Lei Tian, Shuai Ren, Zhong-Qiu Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundDiagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to the lack of specific symptoms and screening methods. Only less than 10% of PDAC patients are candidates for surgery at the time of diagnosis. Thus, there is a great global unmet need for valuable biomarkers that could improve the opportunity to detect PDAC at the resectable stage. This study aimed to develop a potential biomarker model for the detection of resectable PDAC by tissue and serum metabolomics.MethodsUltra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS) was performed for metabolome quantification in 98 serum samples (49 PDAC patients and 49 healthy controls (HCs)) and 20 pairs of matched pancreatic cancer tissues (PCTs) and adjacent noncancerous tissues (ANTs) from PDAC patients. Univariate and multivariate analyses were used to profile the differential metabolites between PDAC and HC.ResultsA total of 12 differential metabolites were present in both serum and tissue samples of PDAC. Among them, a total of eight differential metabolites showed the same expressional levels, including four upregulated and four downregulated metabolites. Finally, a panel of three metabolites including 16-hydroxypalmitic acid, phenylalanine, and norleucine was constructed by logistic regression analysis. Notably, the panel was capable of distinguishing resectable PDAC from HC with an AUC value of 0.942. Additionally, a multimarker model based on the 3-metabolites-based panel and CA19-9 showed a better performance than the metabolites panel or CA19-9 alone (AUC: 0.968 vs. 0.942, 0.850).ConclusionsTaken together, the resectable early-stage PDAC has unique metabolic features in serum and tissue samples. The defined panel of three metabolites has the potential value for early screening of PDAC at the resectable stage.
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T06:31:07Z
DOI: 10.1177/20552076231179007
Issue No: Vol. 9 (2023)
- Design, development, utility and usability testing of the EMPOWER-SUSTAIN
Self-Management Mobile App© among primary care physicians and patients
with metabolic syndrome
Authors: Maryam Hannah Daud, Fakhrul Hazman Yusoff, Suraya Abdul-Razak, Noorhida Baharudin, Mohamed-Syarif Mohamed-Yassin, Siti Fatimah Badlishah-Sham, Azlina Wati Nikmat, Mohamad Rodi Isa, Nursuriati Jamil, Hapizah Nawawi, Anis Safura Ramli
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study aimed to design, develop, assess and refine the EMPOWER-SUSTAIN Self-Management Mobile App© among primary care physicians (PCP) and patients with metabolic syndrome (MetS) in primary care.MethodologyUsing the software-development-life-cycle (SDLC) iterative model, storyboard and wireframe were drafted; and a mock prototype was designed to illustrate the content and function graphically. Subsequently, a working prototype was developed. Qualitative studies using the ‘think-aloud’ and cognitive-task-analysis methods were conducted for the utility and usability testing. Topic guide was based on the 10-Nielsen's-Heuristic-Principles. Utility testing was conducted among PCP in which they ‘thought-aloud’ while performing tasks using the mobile app. Usability testing was conducted among MetS patients after they were given the app for 3 weeks. They ‘thought-aloud’ while performing tasks using the app. Interviews were audio- and video-recorded, and transcribed verbatim. Thematic content analysis was performed.ResultSeven PCP and nine patients participated in the utility and usability testing, respectively. Six themes (efficiency of use, user control and freedom, appearance and aesthetic features, clinical content, error prevention, and help and documentation) emerged. PCP found the mobile app attractive and relevant sections were easy to find. They suggested adding ‘zoom/swipe’ functions and some parts needed bigger fonts. Patients commented that the app was user-friendly, has nice interface, and straightforward language. It helped them understand their health better. Based on these findings, the mobile app was refined.ConclusionThis app was produced using a robust SDLC method to increase users’ satisfaction and sustainability of its use. It could potentially improve self-management behaviour among MetS patients in primary care.
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T06:30:07Z
DOI: 10.1177/20552076231176645
Issue No: Vol. 9 (2023)
- Student perspectives on the integration of artificial intelligence into
healthcare services
Authors: Muna N Ahmad, Saja A Abdallah, Saddam A Abbasi, Atiyeh M Abdallah
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundHealthcare workers are often overworked, underfunded, and face many challenges. Integration of artificial intelligence into healthcare service provision can tackle these challenges by relieving burdens on healthcare workers. Since healthcare students are our future healthcare workers, we assessed the knowledge, attitudes, and perspectives of current healthcare students at Qatar University on the implementation of artificial intelligence into healthcare services.MethodsThis was a cross-sectional study of QU-Health Cluster students via an online survey over a three-week period in November 2021. Chi-squared tests and gamma coefficients were used to compare differences between categorical variables.ResultsOne hundred and ninety-three QU-Health students responded. Most participants had a positive attitude towards artificial intelligence, finding it useful and reliable. The most popular perceived advantage of artificial intelligence was its ability to speed up work processes. Around 40% expressed concern about a threat to job security from artificial intelligence, and a majority believed that artificial intelligence cannot provide sympathetic care (57.9%). Participants who felt that artificial intelligence can better make diagnoses than humans also agreed that artificial intelligence could replace their job (p = 0.005). Male students had more knowledge (p = 0.005) and received more training (p = 0.005) about healthcare artificial intelligence. Participants cited a lack of expert mentorship as a barrier to obtaining knowledge about artificial intelligence, followed by lack of dedicated courses and funding.ConclusionsMore resources are required for students to develop a good understanding about artificial intelligence. Education needs to be supported by expert mentorship. Further work is needed on how best to integrate artificial intelligence teaching into university curricula.
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T06:28:06Z
DOI: 10.1177/20552076231174095
Issue No: Vol. 9 (2023)
- WeChat-based mobile health management for short-stature children with
long-term growth hormone therapy: A nonexperimental study
Authors: Qingling Zhu, Ying Li, Yajun Su, Liuhong Huang, Jiajia Liu, Weihua Lin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo evaluate the role of a WeChat-based mobile platform in growth hormone therapy.MethodGrowth hormone therapy and health education information for height growth were embedded in a WeChat-based mobile platform, and the platform was evaluated through medical staff assessments, patient volunteer assessments and quantitative scoring criteria.ResultsIn the medical staff evaluation, both clinicians and nurses had a positive attitude towards the mobile platform, believing that the design of the mobile platform was clearly visualized and easy to operate. In family volunteers’ evaluations, the summary of β-testing results showed that 90–100% of parents had a positive attitude towards the WeChat-based mobile platform. Parents of the patients and doctors and nurses assessed the mobile platform by reviewing quantitative scoring standards developed by professional researchers. All scores were>16 (the average score was 18–19.3). Children treated with growth hormone therapy were included for compliance tracking for one year, and patient adherence was described in this study.ConclusionThe interaction based on the WeChat platform and the health education of the public have greatly increased the interaction between doctors and patients, and improved patient satisfaction and compliance.
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T05:36:55Z
DOI: 10.1177/20552076231179849
Issue No: Vol. 9 (2023)
- Are dental x-rays safe' Content analysis of English and Chinese
YouTube videos
Authors: Andy Wai Kan Yeung, Emil D Parvanov, Jarosław Olav Horbańczuk, Maria Kletecka-Pulker, Oliver Kimberger, Harald Willschke, Atanas G Atanasov
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study provided a content analysis of English and Chinese YouTube videos related to dental radiation safety.MethodThe search string, entered in English and Chinese respectively, was: (dental x-ray safe). The searches were performed and exported with Apify YouTube scraper. By screening the resultant videos and their related videos (as recommended by YouTube), a total of 89 videos were screened. Finally, 45 videos (36 English and nine Chinese) were included and analyzed. The specific information regarding dental radiation was evaluated. The Patient Education Material Assessment Tool for Audiovisual Materials was used to assess understandability and actionability.ResultsThere was no significant difference between the English and Chinese videos in terms of view count, like count, comment count, and video duration. Half of the videos explicitly reassured the audience that dental x-rays are safe. Two of the English videos specifically stated that dental x-rays do not cause cancers. Numerous analogies were made in regard to radiation dose, such as equivalence to taking a flight or eating some bananas. About 41.7% of the English videos and 33.3% of the Chinese videos mentioned that patients could be further protected from scatter radiation by wearing a lead apron and thyroid collar. Videos had a good understandability score (91.3) but a poor actionability score (0).ConclusionsSome of the analogies and the claimed radiation dose were questionable. One Chinese video even wrongly stated that dental x-rays are nonionizing radiation. The videos generally did not mention their information sources or the underlying radiation protection principles.
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T05:35:56Z
DOI: 10.1177/20552076231179053
Issue No: Vol. 9 (2023)
- Developing and pre-testing a digital decision-tree smartphone application
for smoking prevention and cessation among HIV care providers
Authors: Irene Tamí-Maury, Samuel Tundealao, Jenna Guzman, Valeri Noé-Díaz, Christine Markham, Karen Vigil
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThe diagnosis and continuous care of chronic conditions such as HIV infection present potential teachable moments for delivering smoking prevention and cessation interventions for patients. We designed and pre-tested a prototype of a smartphone application(app), Decision-T, specifically designed to assist healthcare providers when providing personalized smoking prevention and cessation services to their patients.MethodsWe developed the Decision-T app based on transtheoretical algorithm for smoking prevention and cessation following the 5-A's model. We employed a mixed-methods approach among 18 HIV-care providers recruited from Houston Metropolitan Area for pre-testing the app. Each provider participated in three mock sessions, and the average time spent at each session was measured. We measured accuracy by comparing the smoking prevention and cessation treatment offered by the HIV-care provider using the app to that chosen by the tobacco specialist who designed the case. The system usability scale (SUS) was used to assess usability quantitatively , while individual interview transcripts were analyzed to determine usability qualitatively. STATA-17/SE and Nvivo-V12 were used for quantitative and qualitative analysis, respectively.ResultsThe average time for completing each mock session was 5 min 17 s. The participants achieved an overall average accuracy of 89.9%. The average SUS score achieved was 87.5(±10.26). After analyzing the transcripts, five themes (app's contents are beneficial and straightforward, design is easy to understand, user's experience is uncomplicated, tech is intuitive, and app needs improvements) emerged.ConclusionsThe decision-T app can potentially increase HIV-care providers’ engagement in offering smoking prevention and cessation behavioral and pharmacotherapy recommendations to their patients briefly and accurately.
Citation: DIGITAL HEALTH
PubDate: 2023-06-01T05:34:28Z
DOI: 10.1177/20552076231179029
Issue No: Vol. 9 (2023)
- The landscape of biomedical research progress, challenges and prospects in
Saudi Arabia-A systematic review
Authors: Mohy Uddin, Naif Khalaf Alharbi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionThe main objective of this review was to synthesize the progress, challenges and prospects of biomedical research in Saudi Arabia in order to provide a holistic view to all stakeholders, such as policy makers, decision makers, and local researchers along with external collaborators interested in the field of biomedical research in this region.MethodsA systematic review was conducted using the scientific literature for bibliometric studies in the field of biomedical research in Saudi Arabia that comprehensively covered past few decades using PubMed. The search was performed by combining verified Medical Subject Heading (MeSH) terms: “biomedical research”, “bibliometrics”, “Saudi Arabia” using boolean operator “AND”. The data collection was done from January to June 2022 by both authors.ResultsOut of 202 articles yielded from initial search, 13 articles met all of the inclusion criteria and were examined in details. The outcome of analysis showed that with the augmentation of Research and Development (R&D) globalization in Saudi Arabia, researchers are publishing internationally and collaborating globally, academic and research centers are enriching research environment and policies, and government is taking many initiatives to bolster biomedical research; but still more improvements needs to be achieved by Saudi Arabia to be in the list of strong competitive leading nations in the global biomedical research field.ConclusionsThere were various key challenges related to biomedical publications and bibliometric aspects for Saudi Arabia that included: publishing preferences, quality of publications, indexing services, international scientific community, and importantly barriers related to planning, funding, training, resources and support at institutional and national levels. This review provided some insights and recommendations to enhance biomedical research in Saudi Arabia that included: effective policies, health priorities, building infrastructures, greater investments, high incentives, skilled recruitment, competitive training and engagement of community that can play a vital role in this context.
Citation: DIGITAL HEALTH
PubDate: 2023-05-31T05:11:43Z
DOI: 10.1177/20552076231178621
Issue No: Vol. 9 (2023)
- Baseline evaluation of nursing students’ informatics competency for
digital health practice: A descriptive exploratory study
Authors: Kalpana Raghunathan, Lisa McKenna, Monica Peddle
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionThe healthcare system is increasingly technology-dependent and proficiency in informatics skills is essential for health professionals to efficiently operate in the contemporary clinical environment. Nurses are major users of digital health technologies and graduates need to be well-prepared and confident to use the different available clinical systems competently as they transition from education to practice.AimTo explore undergraduate nursing students’ self-perceptions of informatics competence, set within a larger research project.MethodDescriptive, exploratory cross-sectional research design, with online self-assessment survey of undergraduate nursing students (n = 142). Data were analysed with descriptive, correlation and comparative statistics.ResultsParticipants’ perceived overall mean informatics competency was at the level of somewhat competent, with only 40.84% (n = 58) at the level of competent. The highest mean value was in foundational information and communication skills and the lowest in information and knowledge management. Formal informatics education within curriculum was limited and lacked uniformity, as was prior exposure to important simulated informatics tools in preparation for practice. Factors including academic year level, computer experience and previous experience using clinical systems had a significant impact on participants’ perceived informatics competency.ConclusionEven though informatics competence is vital for clinical practice, with technology becoming pervasive within healthcare, nursing students’ preparedness for digital health was sub-optimal. There were gaps in students’ critical informatics practice knowledge with implications for work readiness of future graduates and nurse education practice.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T11:53:16Z
DOI: 10.1177/20552076231179051
Issue No: Vol. 9 (2023)
- Preliminary effectiveness of an evidence-based mobile application to
promote resilience among working adults in Singapore and Hong Kong:
Intensive longitudinal study
Authors: Sean Han Yang Toh, Sze Chi Lee, Feodora Roxanne Kosasih, Jia W. Lim, Oliver Sündermann
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Evidence-based mobile health (mHealth) applications on smartphones are a cost-effective way for employees to take proactive steps to improve well-being and performance. However, little is known about what sustains engagement on these applications and whether they could dynamically improve occupational outcomes such as resilience and mood. Using real-world data, this intensive longitudinal study examines (a) which employees would continually engage with a cognitive behavioural therapy-informed mHealth application (‘Intellect’); and (b) if daily engagement of ‘Intellect’ would relate to better occupational outcomes on the following day. A total of 515 working adults in Singapore and Hong Kong (Mage = 32.4, SDage = 8.17) completed daily in-app items on mood and resilience components (i.e. sleep hours, sleep quality, physical activity, and stress levels). Our results revealed that employees with lower baseline resilience (β = −0.048, odds ratio (OR) = 0.953, p
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T11:52:49Z
DOI: 10.1177/20552076231178616
Issue No: Vol. 9 (2023)
- Training for virtual care: What do the experts think'
Authors: Vernon Curran, Ann Hollett, Emily Peddle
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionVirtual care has expanded during COVID-19 and enabled continued access to healthcare services. As with the introduction of any new technology in healthcare delivery, the preparation of healthcare providers for adopting and using such systems is imperative. The purpose of this qualitative study was to explore experts’ ascribed opinions on healthcare providers’ continuing professional development (CPD) needs in virtual care.MethodsSemistructured interviews were conducted with a purposive sample of key informants representing Canadian provincial and national organizations with expertise in virtual care delivery.ResultsThree main areas of knowledge, skills, and abilities that would be most helpful for healthcare providers in preparing to adopt and use virtual care were identified. The use of technology necessitates knowledge of how to integrate technology and virtual care in the practice workflow. This includes knowing how to use the technology and the privacy and security of the technology. Providers need to be able to adapt their clinical skills to virtual care and build rapport through good communication with patients. Virtual care is not appropriate for all visits, therefore providers need to understand when an in-person visit is necessary with respect to the nature of the appointment, as well as contextual factors for individual patients. Finally, providers need to adapt their examination skills to virtual care.DiscussionBeyond the COVID-19 pandemic, virtual care will have a continuing role in enhancing continuity of care through access that is more convenient. Key informants identified barriers and challenges in adopting and using virtual care effectively, fundamental knowledge, skills and/or abilities required, and important topics and/or educational experiences to guide CPD program development on virtual care for healthcare providers.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T08:13:40Z
DOI: 10.1177/20552076231179028
Issue No: Vol. 9 (2023)
- Subjective well-being, happiness, and environmental health factors related
to women planning a pregnancy or pregnant, using mobile health
intervention
Authors: Juan Antonio Ortega-García, Miguel Felipe Sánchez-Sauco, José Alberto Zafra-Rodríguez, Laura Teresa Cabrera-Rivera, Francisco Díaz-Martínez, Eduardo Manuel Llegus-Santiago, Juan Luis Delgado-Marín, Esteban Orenes-Piñero, Nicole Kloosterman, Albert Bach, Carlos Ojeda-Sánchez, Rebecca Ramis
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesTo compare the environmental health results in women trying to get pregnant or pregnant using a mobile health application (Green Page) through healthcare professionals or self-completed by women, and to explore the relationship between the subjective well-being of these women with their lifestyles and environmental factors.MethodsA descriptive study with mixed methods was conducted in 2018. A mobile health survey was used in two phases. Phase 1 was a cross-sectional study through professionals (n = 1100) followed by phase 2, a convenience sampling through women's self-reporting (n = 3425). A personalized report was downloadable with health recommendations for the well-being of the mother and child.ResultsOf the 3205 participants (mean age = 33 years, SD = 0.2 years), 1840 were planning a pregnancy and 1365 were pregnant. One in five pregnant women had a low level of happiness. Globally, subjective well-being and happiness were found to be negatively associated with lack of contact with nature, sedentary lifestyle, excess weight, environmental exposure, and older age in pregnancy. Precisely 45%, 60%, and 14% of women were exposed to tobacco, alcohol, and illegal drugs, respectively. The women self-reported levels of risk factors higher than when the tool was used by or through professionals.ConclusionsThe use of mobile health interventions focused on environmental health during planning or pregnancy periods could help improve the quality of healthcare and foster greater involvement of women in their self-care process, thus promoting empowerment, healthier environments, and lifestyles. Ensuring equity of access and data protection are global challenges to be addressed.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T08:09:51Z
DOI: 10.1177/20552076231177146
Issue No: Vol. 9 (2023)
- Design suggestions for a persuasive e-coaching application: A study on
informal caregivers’ needs
Authors: Shweta Premanandan, Awais Ahmad, Åsa Cajander, Pär Ågerfalk, Lisette van Gemert-Pijnen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveInformal caregivers such as relatives or close friends of patients are essential for caregiving at home. However, caregiving is a complex experience that may affect the caregivers’ well-being. Therefore, there is a need to provide support for caregivers, which we address in this article by proposing design suggestions for an e-coaching application. This study identifies the unmet needs of caregivers in Sweden and provides design suggestions for an e-coaching application using the persuasive system design (PSD) model. The PSD model offers a systematic approach to designing IT interventions.MethodsA qualitative research design was used, and semi-structured interviews were conducted with 13 informal caregivers from different municipalities in Sweden. A thematic analysis was performed to analyze the data. The PSD model was used to map the needs emerging from this analysis to propose design suggestions for an e-coaching application for caregivers.ResultsSix needs were identified, and based on them, we proposed design suggestions for an e-coaching application using the PSD model. These unmet needs are monitoring and guidance, assistance to avail formal care services, access to practical information without being overwhelmed, feeling of community, access to informal support, and grief acceptance. The last two needs could not be mapped using the existing PSD model, resulting in an extended PSD model.ConclusionThis study revealed the important needs of informal caregivers based on which design suggestions for an e-coaching application were presented. We also proposed an adapted PSD model. This adapted PSD model can be further used for designing digital interventions in caregiving.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T08:08:20Z
DOI: 10.1177/20552076231177129
Issue No: Vol. 9 (2023)
- Determinants of the implementation of artificial intelligence-based
screening for diabetic retinopathy—a cross-sectional study with general
practitioners in Germany
Authors: Larisa Wewetzer, Linda A. Held, Katja Goetz, Jost Steinhäuser
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDiabetic retinopathy (DR) may lead to irreversible damage to the eye and cause blindness if diagnosed in its advanced stages. Artificial intelligence (AI) may support screening and contribute to a timely diagnosis. The aim of this study was to evaluate factors that might influence the success of implementing AI-supported devices for DR screenings in general practice.MethodsA questionnaire with modules on attitudes toward digital solutions, technical factors, perceived patient perspectives, and sociodemographic data was constructed and 2100 general practitioners (GPs) in Germany were invited to participate via a personal letter.ResultsTwo hundred nine physicians participated in the survey (10% response rate, mean age = 54 years, 46% women). Acquisition costs (mean = 1.37), remuneration (mean = 1.46), and running costs (mean = 1.40) were considered particularly relevant in the context of AI-based screening tools. GPs indicated that a mean of €27.00 (SD = 19) was considered to be an appropriate reimbursement for an AI-based screening for DR in their practice. Less relevant factors were availability of a smartphone used in the practice (mean = 2.53) and time until the examination result was available (mean = 2.29). Important technical factors were practicability of the device (mean = 1.27), unproblematic installation of any necessary software (mean = 1.34), and the integrability into the practice information system (mean = 1.44). Considering the patient welfare, physicians rated the accuracy of the examination, omission of pupil dilation, and the duration of the examination as the most important factors. Participants ranked the factors broadening the scope of care, strengthening the primary care (PC) range, and signs of modern medical practice as the most important factors for making an AI-based screening tool attractive for their practice.ConclusionsThese findings serve as a basis for a successful implementation of AI-assisted screening devices in PC and might facilitate early screenings for ophthalmological diseases in general practice. The most relevant barriers that need to be overcome for a successful implementation of such tools include clarification of the costs and reimbursement policies.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T08:07:42Z
DOI: 10.1177/20552076231176644
Issue No: Vol. 9 (2023)
- Developing a prediction model for successful aging among the elderly using
machine learning algorithms
Authors: Maryam Ahmadi, Raoof Nopour, Somayeh Nasiri
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe aging phenomenon has an increasing trend worldwide which caused the emergence of the successful aging (SA)1 concept. It is believed that the SA prediction model can increase the quality of life (QoL)2 in the elderly by decreasing physical and mental problems and enhancing their social participation. Most previous studies noted that physical and mental disorders affected the QoL in the elderly but didn't pay much attention to the social factors in this respect. Our study aimed to build a prediction model for SA based on the physical, mental, and specially more social factors affecting SA.MethodsThe 975 cases related to SA and non-SA of the elderly were investigated in this study. We used the univariate analysis to determine the best factors affecting the SA. AB3, XG-Boost J-48, RF4, artificial neural network5, support vector machine6, and NB7 algorithms were used for building the prediction models. To get the best model predicting the SA, we compared them using positive predictive value (PPV)8, negative predictive value (NPV)9, sensitivity, specificity, accuracy, F-measure, and area under the receiver operator characteristics curve (AUC).ResultsComparing the machine learning10 model's performance showed that the random forest (RF) model with PPV = 90.96%, NPV = 99.21%, sensitivity = 97.48%, specificity = 97.14%, accuracy = 97.05%, F-score = 97.31%, AUC = 0.975 is the best model for predicting the SA.ConclusionsUsing prediction models can increase the QoL in the elderly and consequently reduce the economic cost for people and societies. The RF can be considered an optimal model for predicting SA in the elderly.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T05:10:11Z
DOI: 10.1177/20552076231178425
Issue No: Vol. 9 (2023)
- Hospital length of stay prediction for general surgery and total knee
arthroplasty admissions: Systematic review and meta-analysis of published
prediction models
Authors: Swapna Gokhale, David Taylor, Jaskirath Gill, Yanan Hu, Nikolajs Zeps, Vincent Lequertier, Helena Teede, Joanne Enticott
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveSystematic review of length of stay (LOS) prediction models to assess the study methods (including prediction variables), study quality, and performance of predictive models (using area under receiver operating curve (AUROC)) for general surgery populations and total knee arthroplasty (TKA).MethodLOS prediction models published since 2010 were identified in five major research databases. The main outcomes were model performance metrics including AUROC, prediction variables, and level of validation. Risk of bias was assessed using the PROBAST checklist.ResultsFive general surgery studies (15 models) and 10 TKA studies (24 models) were identified. All general surgery and 20 TKA models used statistical approaches; 4 TKA models used machine learning approaches. Risk scores, diagnosis, and procedure types were predominant predictors used. Risk of bias was ranked as moderate in 3/15 and high in 12/15 studies. Discrimination measures were reported in 14/15 and calibration measures in 3/15 studies, with only 4/39 externally validated models (3 general surgery and 1 TKA). Meta-analysis of externally validated models (3 general surgery) suggested the AUROC 95% prediction interval is excellent and ranges between 0.803 and 0.970.ConclusionThis is the first systematic review assessing quality of risk prediction models for prolonged LOS in general surgery and TKA groups. We showed that these risk prediction models were infrequently externally validated with poor study quality, typically related to poor reporting. Both machine learning and statistical modelling methods, plus the meta-analysis, showed acceptable to good predictive performance, which are encouraging. Moving forward, a focus on quality methods and external validation is needed before clinical application.
Citation: DIGITAL HEALTH
PubDate: 2023-05-30T03:58:19Z
DOI: 10.1177/20552076231177497
Issue No: Vol. 9 (2023)
- mHealth in Sub-Saharan Africa and Europe: Context of current health,
healthcare status, and demographic structure
Authors: Genet Tadese Aboye, Martijn Vande Walle, Gizeaddis Lamesgin Simegn, Jean-Marie Aerts
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionThe advent of digital systems and global mobile phone availability presents an opportunity for better healthcare access and equity. However, the disparity in the usage and availability of mHealth systems between Europe and Sub-Saharan Africa (SSA) has not been explored in relation to current health, healthcare status, and demographics.ObjectiveThis study aimed to compare mHealth system availability and use in SSA and Europe in the above-mentioned context.MethodsThe study analyzed health, healthcare status, and demographics in both regions. It assessed mortality, disease burden, and universal health coverage. A systematic narrative review was conducted to thoroughly assess available data on mHealth availability and use, guiding future research in the field.ResultsSSA is on the verge of stages 2 and 3 in the demographic transition with a youthful population and high birth rate. Communicable, maternal, neonatal, and nutritional diseases contribute to high mortality and disease burden, including child mortality. Europe is on the verge of stages 4 and 5 in the demographic transition with low birth and death rates. Europe's population is old, and non-communicable diseases (NCDs) pose major health challenges. The mHealth literature adequately covers cardiovascular disease/heart failure, and cancer. However, it lacks approaches for respiratory/enteric infections, malaria, and NCDs.ConclusionsmHealth systems in SSA are underutilized than in Europe, despite alignment with the region's demographics and major health issues. Most initiatives in SSA lack implementation depth, with only pilot tests or small-scale implementations. Europe's reported cases highlight actual implementation and acceptability, indicating a strong implementation depth of mHealth systems.
Citation: DIGITAL HEALTH
PubDate: 2023-05-29T07:14:06Z
DOI: 10.1177/20552076231178420
Issue No: Vol. 9 (2023)
- Associations between health literacy, digital skill, and eHealth literacy
among older Chinese adults: A cross-sectional study
Authors: Shaojie Li, Guanghui Cui, Yongtian Yin, Huilan Xu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDigital divide in health-related technology use is a prominent issue for older adults. Improving eHealth literacy may be an important solution to this problem. This study aimed to explore the associations between health literacy, digital skills, and eHealth literacy among older Chinese adults.MethodsA total of 2,144 older adults (mean age, 72.01 ± 6.96 years) from Jinan City, China participated in this study. The eHealth Literacy Scale was used to measure eHealth literacy in older adults. A linear regression model was used to analyze the associations among health literacy, digital skills, and eHealth literacy in older Chinese adults.ResultsThe mean eHealth literacy score of the older adults was 17.56 ± 9.61. After adjusting for sociodemographic characteristics and experience of Internet usage, the results of the linear regression showed that health literacy (B = 0.258, 95% confidence interval (CI) = 0.215–0.302, P
Citation: DIGITAL HEALTH
PubDate: 2023-05-26T06:05:09Z
DOI: 10.1177/20552076231178431
Issue No: Vol. 9 (2023)
- Patterns of acceptance and use of digital health services among the
persistent frequent attenders of outpatient care: A qualitatively driven
multimethod analysis
Authors: Lotta Virtanen, Anu-Marja Kaihlanen, Emma Kainiemi, Petra Saukkonen, Tarja Heponiemi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveUtilising digital health services in the treatment of patients who frequently attend outpatient care could be beneficial for patients’ health and the sustainability of health systems but carries the risk of digital exclusion. This study aimed to explore the patterns of acceptance and use of digital health services among frequent attenders (FAs), which may help in the assessment of patients’ digital suitability.MethodsPersistent FAs (N = 30) were recruited by random sampling from one Finnish municipality. The semistructured interviews were conducted in February–May 2021. We analysed the data with qualitative content analysis using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Additionally, we quantified the data for two-step cluster analyses to create separate cluster models that grouped FAs based on acceptance and use of (a) digital services for self-management of health and (b) telemedicine services.ResultsBased on digital self-management, FAs were defined as Self-Managers, Supported Self-Managers, and Non-Self-Managers. Based on telemedicine use, they were grouped into Telemedicine Users, Doubtful Telemedicine Users, and Telemedicine Refusers. The clusters described different opportunities, awareness, and interest in using digital health services. Referral from professionals seemed to promote digital service use. For some, digital services were not accessible.ConclusionsOur findings emphasise the importance of assessing the suitability of FAs to digital health services, as their readiness to use may vary. Professionals should recommend digital services that support individual health to suitable patients. More accessible digital services could promote digital suitability despite functional limitations.
Citation: DIGITAL HEALTH
PubDate: 2023-05-26T06:04:09Z
DOI: 10.1177/20552076231178422
Issue No: Vol. 9 (2023)
- The BEM Program: An innovative online parenting program for
socioeconomically disadvantaged caregiver–child dyads in Brazil
Authors: Katherine Solís-Cordero, Patricia Marinho, Patricia Camargo, Silvia Takey, Rogério Lerner, Elizabeth Fujimori
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo describe the BEM Program, an innovative online parenting program for socioeconomically disadvantaged caregiver–child dyads in Brazil.MethodsThe Template for Intervention Description and Replication checklist was used to describe the BEM Program in detail.ResultsThe BEM Program (an acronym for Brincar Ensina Mudar in Portuguese, “Play Teaches Change” in English) refers to the change in adult, child, and dyad outcomes that can be observed through incorporating playful interactions between the caregiver and their child into their daily household chores. Content consisting of 8 videos and 40 text and audio messages was sent entirely online through WhatsApp®. Thus, the Program could be accessed wherever caregivers wanted, if they had their smartphone and Internet access.ConclusionsThe detailed description of an innovative online parenting program focused on caregiver–child interaction and child development contributes to the scarce evidence on this type of programs. Adherence to the program continues to represent one of the main challenges to overcome.
Citation: DIGITAL HEALTH
PubDate: 2023-05-26T06:03:29Z
DOI: 10.1177/20552076231178415
Issue No: Vol. 9 (2023)
- Using less keystrokes to achieve high top-1 accuracy in Chinese clinical
text entry
Authors: Tao Li, Lei Yu, Liang Zhou, Panzhang Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAs a routine task, physicians spend substantial time and keystrokes on text entry. Documentation burden is increasingly associated with physician burnout. Predicting at top-1 with less keystrokes (TLKs) is a hot topic for smart text entry. In Western countries, contextual autocomplete is deployed to alleviate the burden. Chinese text entry is intercepted by input method engines (IMEs), which cut off suggestions from electronic health records (EHRs).ObjectiveTo explore a user-friendly approach to make text entry easier and faster for Chinese physicians.MethodsPhysicians were shadowed to uncover the real-word input behaviors. System logs were collected for behavior validation and then used for context-based learning. An in-line web-based popup layer was proposed to hold the best suggestion from EHRs. Keystrokes per character and TLK rate were evaluated quantitatively. Questionnaires were used for qualitative assessment. Nine hundred fifty-two physicians were enrolled in a field testing.Results14 facilitators and 17 barriers related to IMEs were identified after shadowing. With system logs, physicians tended to split long words into short units, which were 1–4 in length. 81.7% of these units were disyllables. Compared to the control group, the intervention group improved TLK rate by 40.3% (p
Citation: DIGITAL HEALTH
PubDate: 2023-05-26T05:05:29Z
DOI: 10.1177/20552076231179027
Issue No: Vol. 9 (2023)
- Doctoral: A smartphone-based decision support tool for the early detection
of oral potentially malignant disorders
Authors: Olga Di Fede, Vera Panzarella, Fortunato Buttacavoli, Gaetano La Mantia, Giuseppina Campisi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Oral potentially malignant disorders can be defined as mucosal lesions and conditions with an increased risk of malignant transformation. Oral potentially malignant disorders are a significant health burden, and they are often diagnosed late due to scant attention to routine dental practice and the low number of specialized oral medicine centres. This report summarizes the DoctOral experience, a research initiative, providing a free smartphone-based decision support tool for the general medical/dental practitioner; the tool is based on the clinical appearance of oral lesions. Captured, oral pictures can be immediately examined via interactive decision trees and constructed on the smartphone. Such decision trees are expressed in standard formats, and they are readily accessible for facilitating the completion of a hypothetical diagnostic path. Since October 2017 the DoctOral mobile app has been downloaded by 10K + users, achieving a score of 4.8 out of 5. DoctOral also supports an unfolding joint initiative, called DoctOralAI: this involves selecting reference images, with which to create an open-source model, and perform a Case-Based Reasoning method, both of which are combined with machine learning. The DoctOral mobile app has revolutionized oral pathology by providing dental students and professionals with an interactive platform for recognizing and diagnosing oral lesions.
Citation: DIGITAL HEALTH
PubDate: 2023-05-26T05:03:09Z
DOI: 10.1177/20552076231177141
Issue No: Vol. 9 (2023)
- Intelligent lung cancer MRI prediction analysis based on cluster
prominence and posterior probabilities utilizing intelligent Bayesian
methods on extracted gray-level co-occurrence (GLCM) features
Authors: Jing Yang, Por Lip Yee, Abdullah Ayub Khan, Hanen Karamti, Elsayed Tag Eldin, Amjad Aldweesh, Atef El Jery, Lal Hussain, Abdulfattah Omar
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Lung cancer is the second foremost cause of cancer due to which millions of deaths occur worldwide. Developing automated tools is still a challenging task to improve the prediction. This study is specifically conducted for detailed posterior probabilities analysis to unfold the network associations among the gray-level co-occurrence matrix (GLCM) features. We then ranked the features based on t-test. The Cluster Prominence is selected as target node. The association and arc analysis were determined based on mutual information. The occurrence and reliability of selected cluster states were computed. The Cluster Prominence at state ≤330.85 yielded ROC index of 100%, relative Gini index of 99.98%, and relative Gini index of 100%. The proposed method further unfolds the dynamics and to detailed analysis of computed features based on GLCM features for better understanding of the hidden dynamics for proper diagnosis and prognosis of lung cancer.
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T11:21:42Z
DOI: 10.1177/20552076231172632
Issue No: Vol. 9 (2023)
- A study to explore the usefulness of a mobile health application to
support people with mild cognitive and/or communication impairment due to
dementia and their carers
Authors: Sudeh Cheraghi-Sohi, Karen Davies, Lorenzo Gordon, Huw Jones, Caroline Sanders, Bie Nio Ong
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundMobile apps for health (mHealth) have the potential to support people living with dementia. However, dementia is a complex and progressive condition that imposes specific constraints on the introduction/use of mhealth. Few studies have explored mHealth adoption and use within the complexity of everyday domestic settings. This study used an existing App co-designed with people living with mild cognitive and communication impairment (PWMCCI) due to learning disabilities and examined the usefulness for PWMICCI due to dementia and their carers.MethodsA qualitative study of people with dementia and their carers. Data were collected in a phased approach to identify the potential need for, as well as the usability and utility of the app. Analysis employed the Domestication of Technology Model (DTM) to explore, in a novel way mHealth, in this user group(s).ResultsMost participants did not adopt the mHealth during the study period but some (n = 2) did routinely as it fulfilled a unique, unmet need. The use of DTM highlighted the complexities of dementia, pressure on carers and duplication of effort created barriers to app adoption and use in the long term.ConclusionsThe ability of mHealth to support PWMCCI due to dementia and/or their carers may have potential. Users were motivated to try the technology but for any potential to be fully realised, the interplay between complexity of the condition including its progressive nature, demand on carers and nature of the technology needs to be more fully understood. Such issues place unique constraints around the size and window of opportunities for mHealth in this user group.
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T08:23:53Z
DOI: 10.1177/20552076231173560
Issue No: Vol. 9 (2023)
- COVID-19 misinformation on YouTube: An analysis of its impact and
subsequent online information searches for verification
Authors: Sabrina Heike Kessler, Edda Humprecht
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesCOVID-19 vaccination misinformation on YouTube can have negative effects on users. Some, after being exposed to such misinformation, may search online for information that either debunks or confirms it. This study's objective is to examine the impact of YouTube videos spreading misinformation about COVID-19 vaccination and the influencing variables, as well as subsequent information seeking and its effect on attitudes toward vaccination.MethodsIn this observational and survey study, we used a three-group pre-test and post-tests design (N = 106 participants). We examined the effects of YouTube videos containing misinformation about COVID-19 vaccination on attitudes toward vaccination via surveys, employed screen recordings with integrated eye tracks to examine subsequent online information searches, and again surveyed participants to examine the effects of the individual searches on their attitudes.ResultsReceiving misinformation via video tended to have negative effects, mostly on unvaccinated participants. After watching the video, they believed and trusted less in the effectiveness of the vaccines. Internet searches led to more positive attitudes toward vaccination, regardless of vaccination status or prior beliefs. The valences of search words entered and search duration were independent of the participants’ prior attitudes. Misinforming content was rarely selected and perceived (read). In general, participants were more likely to perceive supportive and mostly neutral information about vaccination.ConclusionMisinformation about COVID-19 vaccination on YouTube can have a negative impact on recipients. Unvaccinated citizens in particular are a vulnerable group to online misinformation; therefore, it is important to take action against misinformation on YouTube. One approach could be to motivate users to verify online content by doing their own information search on the internet, which led to positive results in the study.
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T08:21:23Z
DOI: 10.1177/20552076231177131
Issue No: Vol. 9 (2023)
- Investigating information needs and preferences regarding digital mental
health services among medical and psychology students in Germany: A
qualitative study
Authors: Pia Braun, Ann-Kathrin Schwientek, Peter Angerer, Lisa Guthardt, Andrea Icks, Adrian Loerbroks, Jennifer Apolinário-Hagen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundSince 2020, physicians and psychotherapists in Germany can prescribe digital mental health services (dMHSs). However, even future healthcare professionals (HCPs), such as medical and psychology students, remain reluctant to use dMHSs, although they are a risk group for mental health issues themselves. Reasons include scepticism and lacking awareness of dMHSs, which can be addressed by acceptance-facilitating interventions (AFIs) such as information strategies. To date, though, little is known about their information needs.MethodsSemi-structured interviews with n = 21 students were conducted between August and September 2021. Students of legal age studying psychology or medicine at a German university could participate. Interview recordings were transcribed verbatim and content-analyzed according to Mayring, using deductive and inductive coding.ResultsMost students reported having little experience with dMHSs. Digital health has barely been raised in their study, even though it was perceived as crucial for personal needs as well as in preparation for their work as HCPs. Students favoured receiving information on and recommendations for dMHSs from their university via, e.g. social media or seminars. Among others, information about data safety, scientific evidence base and application scope were preferred. Additionally, information on costs as well as user reviews seemed to be essential components of information strategies because students were concerned that high costs or low usability would hinder uptake.ConclusionsThe results give first insights on how future HCPs would like to be informed on dMHSs. Future research should focus on systematic variations of AFIs' components mimicking real-world decision scenarios to increase the adoption of dMHSs.
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T08:20:04Z
DOI: 10.1177/20552076231173568
Issue No: Vol. 9 (2023)
- The “Lazio ADVICE” telemedicine platform: First results of general
practitioners’ usage, facilitators and barriers in the Local Health
Authority Roma 1
Authors: Andrea Barbara, Leonardo Villani, Paolo Lombardo, Paolo Parente, Antonella Gemma, Debora Angeletti, Tiziana Chiriaco, Antonio Mastromattei, Svetlana Akselrod, Mauro Goletti, Enrico Di Rosa, Corrado De Vito
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundTelemedical approaches represent a valuable tool for the management of coronavirus disease 2019 patients, allowing daily clinical assessment, monitoring of vital parameters, remote visits, and prescription of treatment or hospitalization in case of clinical worsening. This cross-sectional study aims to evaluate the use, barriers and facilitators of the “Lazio ADVICE” telemedical platform, a regional system for remote assistance for coronavirus disease 2019 patients at home, according to General Practitioners and Family Pediatricians of the Local Health Authority Roma 1, during the coronavirus disease 2019 pandemic.MethodsAn interview-based survey was performed between December 2020 and January 2021. The survey investigated the demographic information of General Practitioner and Family Pediatricians, the knowledge of the platform, frequency of utilization, usefulness, strengths and weaknesses, and hypothesis of future implementation proposed.ResultsWe interviewed 214 physicians and 89 (41.6%) were classified as users and 125 (58.4%) as non-users. Older age and working in District 1, 14 and 15 (vs. District 13) significantly reduced the probability of using the platform physician. Among the 89 users, 19 (21.3%) used the platform every day or even several times a day, 40 (44.9%) several times a week but less than one access per day, 30 (33.7%) used the platform several times a month up to one entry per week. Most of them (92.3%) consider the platform useful. Barriers were poor integration with software and work routine (76.4%), and usability issues (53.9%). Among the 125 non-users, 14 (11.2%) didn’t know the existence of the platform, 60 (48.0%) never tried it and 51 (40.8%) tried to use it. Reported reasons for the interruption of use were not very user-friendly (45.1%), perceived useless (37.3%), non-optimal functioning (23.5%), and lack of time (19.6%).ConclusionThe pandemic accelerated the implementation of telemedicine services around Lazio Region, starting a positive and continuous exchange of experiences, activities and best practices among physicians.
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T06:21:40Z
DOI: 10.1177/20552076231174099
Issue No: Vol. 9 (2023)
- The role of accelerator programmes in supporting the adoption of digital
health technologies: A qualitative study of the perspectives of small- and
medium-sized enterprises
Authors: Chidi Njoku, Stuart Green Hofer, Ganesh Sathyamoorthy, Neelam Patel, Henry WW Potts
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveEvidence-based digital health technologies are increasingly important in delivering care to an ageing population with constrained resources. In the United Kingdom, accelerator programmes (APs) have been developed to support the adoption of digital health technologies within the National Health Service. This study aims to explore the perspectives of stakeholders using APs.MethodsStakeholders representing nine small -and medium-sized enterprises (SMEs) that were engaged with three different APs (n = 9). Semi-structured interviews were conducted with key informants between April and September 2018. Framework analysis of the data was performed to explore their perspectives on APs.ResultsFour key themes were generated. Informants reported the need to generate evidence before and during the programme, appreciating different types of evidence and their importance. Informants identified several key factors that were a catalyst for success, including involvement in the programme and access to individuals and organisations that were crucial for support. However, several barriers were identified at the programme and system levels. Finally, informants identified key supporting processes that enhanced the adoption of their innovations.ConclusionSMEs that develop digital health technologies report that, while APs are useful in supporting the adoption of these technologies, some issues remain. These relate to the emphasis on traditional research evidence that remains a challenge for SMEs to generate. Also, several system-level barriers to innovation in healthcare persist. As APs and SMEs continue to create an entrepreneurial ecosystem, there is increased potential for the development of supporting processes and infrastructure to accelerate the efficient and timely adoption of new digital health technologies.
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T06:20:40Z
DOI: 10.1177/20552076231173303
Issue No: Vol. 9 (2023)
- Smartphone addiction, gender and interpersonal attachment: A
cross-sectional analytical survey in Taiwan
Authors: Yi-Ying Wu, Wen-Huei Chou
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
OverviewSmartphone use has dramatically increased worldwide, contributing to a profound change in interpersonal interactions. They have become the primary medium of human interaction, and smartphone addiction, consequently, has become a modern-day reality. Recent research on smartphone addiction has provided diverse explanations regarding the correlation between gender and addiction. Therefore, this study aims to analyse the correlation and variance among smartphone addiction, gender and interpersonal attachment.MethodsThe participants included Taiwanese citizens and the questionnaires were randomly distributed; 1190 valid questionnaires (534 males, 656 females) were collected. Descriptive statistics were computed to observe the average value and standard deviation between interpersonal attachment and gender. Next, Spearman's ρ was conducted to interpret the correlation among smartphone addiction, gender and interpersonal attachment. Finally, the participants were divided into three groups based on their pre-determined level of smartphone addiction: high, moderate and low addictions. The Analysis of variance (ANOVA) was performed based on interpersonal attachment as the independent variable to determine any statistically significant difference among the three levels.ResultsThere are four patterns of interpersonal attachment: secure, avoidant, dismissing and anxious attachments. The correlation analysis revealed a significant positive correlation between interpersonal attachment and smartphone addiction (p > 0.000), while revealing no relationship between gender and smartphone addiction or gender and interpersonal attachment. Additionally, the ANOVA indicated the difference was statistically significant in the groups of high and moderate addictions; no statistical significance was identified in the group of low addiction (p
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T06:02:22Z
DOI: 10.1177/20552076231177134
Issue No: Vol. 9 (2023)
- Effect of interactive multitouch game-based cognitive intervention on
cognitive function in older adults: A randomized controlled trial
Authors: Daeun Ro, Jungsoo Lee, Gihyoun Lee, Seyoung Shin, Yun-Hee Kim
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
PurposeThis study investigated the effects of an interactive multitouch game-based cognitive intervention (ICI) on cognitive function in community-dwelling older adults.MethodsThirty-two older adults (19 women) between 65 and 84 years of age (mean age, 74.47 ± 4.30 years) without a history of neurological disease participated. They were randomized into two groups: intervention and control. The intervention group took part in ICI sessions using HAPPYTABLE® (Spring Soft Co. Ltd, Seoul, Korea) (ICI group), and the control group underwent a traditional paper-and-pencil-based cognitive intervention (TCI group). Both groups completed 10 intervention sessions over four consecutive weeks. Cognitive function was assessed before (pre-intervention) and after (post-intervention) intervention. Executive function was evaluated through the Color-Word Stroop Test (CWST) and Controlled Oral Word Association Test (COWAT). Memory was assessed through the Verbal Learning Test (VLT) and Rey Complex Figure Test (RCFT).ResultsThe ICI and TCI groups showed significant improvements in some cognitive functions after the intervention. Both groups showed substantial improvements in VLT and RCFT (P
Citation: DIGITAL HEALTH
PubDate: 2023-05-25T06:01:30Z
DOI: 10.1177/20552076231176648
Issue No: Vol. 9 (2023)
- Motivations and perceived harms and benefits of online communication about
self-harm: An interview study with young people
Authors: Pinar Thorn, Louise La Sala, Sarah Hetrick, Simon Rice, Michelle Lamblin, Jo Robinson
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundSelf-harm behaviour is prevalent among young people and online communication about self-harm is frequent. These online communications are associated with potential harms and potential benefits. To date, few studies have explored the motivations and mechanisms involved in youth online communication about self-harm.ObjectiveThis study aimed to explore why young people communicate online about self-harm and the perceived benefits and harms of these communications.MethodsTwenty young people aged between 18 and 25 years completed an online interview. Interviews were audio recorded and transcribed verbatim. Thematic analysis was used to identify themes.ResultsFour main themes are reported: (1) crossing from offline to online—the double-edged affordances of social media: young people engaged in online communication about self-harm because they were unable or unwilling to speak about their experiences in offline contexts. Online spaces afforded anonymity and peer support, which were associated with benefits and harms; (2) user-generated is not quite the same as user-resonated: perceptions were influenced by whether the young person created or viewed or responded to the content. Written and visual content had pros and cons; (3) it's not just you, it's mostly me—individual characteristics influence perceptions: age and mental state influenced perceptions and behavior; and (4) beyond individuals—parameters are protective: leadership and platform policies and procedures aided safety.ConclusionsOnline communication about self-harm is neither entirely helpful nor harmful. Perceptions are influenced by individual, social, and systematic factors. Evidence-based guidelines are needed to increase young people's online self-harm literacy and help them build effective communication skills to buffer psychological and potentially physical harm.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T11:04:55Z
DOI: 10.1177/20552076231176689
Issue No: Vol. 9 (2023)
- Strangers helping strangers in a strange land: Vietnamese immigrant
(expectant) mothers in the US use social media to navigate health issues
in acculturation
Authors: Nhung Nguyen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesTrying to adapt to a new culture, Vietnamese (expectant) mothers in the USA gathered in few Facebook groups with thousands of members discussing pregnancy, health, and child caring issues. However, there is little research exploring how social support was given/taken among these (expectant) mothers. This empirical research aims at shedding light on how such mothers use social media groups for social support seeking/providing regarding health utilization during their acculturation process.MethodsDrawing from Andersen's Behavioral Model of Health Utilization, acculturation, and online social support conceptual frameworks, this study analyzes 18 in-depth interviews with immigrant Vietnamese (expectant) mothers in the United States on the use of social media in navigating health acculturation during their pregnancy and motherhood.ResultsResults show that these mothers give and take all forms of social support including informational, emotional, relational, and instrumental ones. Facebook groups do not provide the best environment for improving “bonding” social capital for its members. However, these groups provide a platform where “strangers help strangers” overcome various barriers to sufficiently understand and independently access and use the official healthcare system. The groups, hence, aid these women's pregnancy and their child(ren)'s health. The informational and emotional support provided by Facebook groups among (soon-to-be) mothers helped them tremendously in overcoming acculturative stress. Moreover, with better language skills, knowledge, and experience in using health and social security systems, help-seekers tend to be transformed into help providers to deliver support for those “newcomers.”ConclusionsThis research provides insights into personal experience on the uses of social media in navigating health behavior in the process of acculturation among Vietnamese immigrant (expectant) mothers in the United States. The research seeks to contribute to the conceptual frameworks and practical experience of behavioral model of health utitlization among immigrant Vietnamese ethnic immigrant pregnant women and mothers of babies and toddlers in navigating health during acculturation process in the United States. The limitations and future research suggestions are also discussed.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T06:50:58Z
DOI: 10.1177/20552076231171507
Issue No: Vol. 9 (2023)
- The effectiveness of wearable activity trackers for increasing physical
activity and reducing sedentary time in older adults: A systematic review
and meta-analysis
Authors: Shuang Wu, Guangkai Li, Litao Du, Si Chen, Xianliang Zhang, Qiang He
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundTraditional interventions such as education and counseling are successful in increasing physical activity (PA) participation, but are usually labor and resource intensive. Wearable activity trackers can objectively record PA and provide feedback to help users to achieve activity goals and are an increasingly popular tool among adults used to facilitate self-monitoring of PA. However, no reviews systematically explored the roles of wearable activity trackers in older populations.MethodsWe searched PubMed, Web of Science, Google Scholar, Embase, Cochrane Library, and Scopus from inception to September 10, 2022. Randomized controlled trials were included. Two reviewers independently conducted study selection, data extraction, risk of bias, and certainty of evidence assessment. A random-effects model was used to evaluate the effect size.ResultsA total of 45 studies with 7144 participants were included. A wearable activity tracker was effective in increasing daily steps (standard mean differences (SMD) = 0.59, 95% confidence interval (CI) (0.44, 0.75)), weekly moderate-to-vigorous PA (MVPA) (SMD = 0.54, 95% CI (0.36, 0.72)), and total daily PA (SMD = 0.21, 95% CI (0.01, 0.40)) and reducing sedentary time (SMD = −0.10, 95% CI (−0.19, −0.01)). Subgroup analysis showed that the effectiveness of wearable activity trackers for daily steps was not influenced by participants and intervention features. However, wearable activity trackers seemed more effective in promoting MVPA of participant's age
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T06:28:03Z
DOI: 10.1177/20552076231176705
Issue No: Vol. 9 (2023)
- User experiences of an American-adapted moderated online social media
platform for first-episode psychosis: Qualitative analysis
Authors: Elena L Pokowitz, Bryan J Stiles, Riya Thomas, Katherine Bullard, Kelsey A Ludwig, John F Gleeson, Mario Alvarez-Jimenez, Diana O Perkins, David L Penn
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesThe current study sought to qualitatively characterize the experiences of American users in a recent open trial of the Horyzons digital platform.MethodsIn total, 20 users on Horyzons USA completed semistructured interviews 12 weeks after their orientation to the platform and addressed questions related to (1) the platform, (2) their online therapist, and (3) the peer workers and community space. A hybrid inductive-deductive coding strategy was used to conduct a thematic analysis of the data (NCT04673851).ResultsThe authors identified seven prominent themes that mapped onto the three components of self-determination theory. Features of the platform itself as well as inter- and intra-personal factors supported the autonomous use of Horyzons. Users also reflected that their perceived competence in social settings and in managing mental health was increased by the familiarity, privacy, and perceived safety of the platform and an emphasis on personalized therapeutic content. The behaviors or traits of online therapists as perceived by users and regular contact with peers and peer support specialists satisfied users’ need for relatedness and promoted confidence in social settings. Users also described aspects of Horyzons USA that challenged their satisfaction of autonomy, competence, and relatedness, highlighting potential areas for future iterations of the platform's content and interface.ConclusionsHoryzons USA is a promising digital tool that provides young adults with psychosis with the means to access tailored therapy material on demand and a supportive digital community to aid in the recovery process.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T06:26:58Z
DOI: 10.1177/20552076231176700
Issue No: Vol. 9 (2023)
- Real-world integration of the protocol for responding to and assessing
patients’ assets, risks, and experiences tool to assess social
determinants of health in the electronic medical record at an academic
medical center
Authors: Carrie R Howell, Heather Bradley, Li Zhang, John D Cleveland, Dustin Long, Trudi Horton, Olivia Krantz, Michael J Mugavero, Winter L Williams, Alesha Amerson, Andrea L Cherrington
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR).MethodsWe employed the collection of the PRAPARE tool in the EMR of a large academic health system in the ambulatory clinic and emergency department setting. After integration, we evaluated SDoH prevalence, levels of missingness, and data anomalies to inform ongoing collection. We summarized responses using descriptive statistics and hand-reviewed data text fields and patterns in the data. Data on patients who were administered with the PRAPARE from February to December 2020 were extracted from the EMR. Patients missing ≥ 12 PRAPARE questions were excluded. Social risks were screened using the PRAPARE. Information on demographics, admittance status, and health coverage were extracted from the EMR.ResultsAssessments with N = 6531 were completed (mean age 54 years, female (58.6%), 43.8% Black). Missingness ranged from 0.4% (race) to 20.8% (income). Approximately 6% of patients were homeless; 8% reported housing insecurity; 1.4% reported food needs; 14.6% had healthcare needs; 8.4% needed utility assistance; and 5% lacked transportation related to medical care. Emergency department patients reported significantly higher proportions of suboptimal SDoH.ConclusionsIntegrating the PRAPARE assessment in the EMR provides valuable information on SDoH amenable to intervention, and strategies are needed to increase accurate data collection and to improve the use of data in the clinical encounter.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T06:25:58Z
DOI: 10.1177/20552076231176652
Issue No: Vol. 9 (2023)
- Dynamics of emotion trends in Canadian Twitter users during COVID-19
confinement in relation to caseloads: Artificial intelligence-based
emotion detection approach
Authors: Swarna Weerasinghe, Oladapo Oyebode, Rita Orji, Stan Matwin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Multiple waves of COVID-19 have significantly impacted the emotional well-being of all, but many were subject to additional risks associated with forced regulations. The objective of this research was to assess the immediate emotional impact, expressed by Canadian Twitter users, and to estimate the linear relationship, with the vicissitudes of COVID caseloads, using ARIMA time-series regression. We developed two Artificial Intelligence-based algorithms to extract tweets using 18 semantic terms related to social confinement and locked down and then geocoded them to tag Canadian provinces. Tweets (n = 64,732) were classified as positive, negative, and neutral sentiments using a word-based Emotion Lexicon. Our results indicated: that Tweeters were expressing a higher daily percentage of negative sentiments representing, negative anticipation (30.1%), fear (28.1%), and anger (25.3%), than positive sentiments comprising positive anticipation (43.7%), trust (41.4%), and joy (14.9%), and neutral sentiments with mostly no emotions, when hash-tagged social confinement and locked down. In most provinces, negative sentiments took on average two to three days after caseloads increase to emerge, whereas positive sentiments took a slightly longer period of six to seven days to submerge. As daily caseloads increase, negative sentiment percentage increases in Manitoba (by 68% for 100 caseloads increase) and Atlantic Canada (by 89% with 100 caseloads increase) in wave 1(with 30% variations explained), while other provinces showed resilience. The opposite was noted in the positive sentiments. The daily percentage of emotional expression variations explained by daily caseloads in wave one were 30% for negative, 42% for neutral, and 2.1% for positive indicating that the emotional impact is multifactorial. These provincial-level impact differences with varying latency periods should be considered when planning geographically targeted, time-sensitive, confinement-related psychological health promotion efforts. Artificial Intelligence-based Geo-coded sentiment analysis of Twitter data opens possibilities for targeted rapid emotion sentiment detection opportunities.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T06:24:59Z
DOI: 10.1177/20552076231171496
Issue No: Vol. 9 (2023)
- A review of multi-factor authentication in the Internet of Healthcare
Things
Authors: Tance Suleski, Mohiuddin Ahmed, Wencheng Yang, Eugene Wang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis review paper aims to evaluate existing solutions in healthcare authentication and provides an insight into the technologies incorporated in Internet of Healthcare Things (IoHT) and multi-factor authentication (MFA) applications for next-generation authentication practices. Our review has two objectives: (a) Review MFA based on the challenges, impact and solutions discussed in the literature; and (b) define the security requirements of the IoHT as an approach to adapting MFA solutions in a healthcare context.MethodsTo review the existing literature, we indexed articles from the IEEE Xplore, ACM Digital Library, ScienceDirect, and SpringerLink databases. The search was refined to combinations of ‘authentication’, ‘multi-factor authentication’, ‘Internet of Things authentication’, and ‘medical authentication’ to ensure that the retrieved journal articles and conference papers were relevant to healthcare and Internet of Things-oriented authentication research.ResultsThe concepts of MFA can be applied to healthcare where security can often be overlooked. The security requirements identified result in stronger methodologies of authentication such as hardware solutions in combination with biometric data to enhance MFA approaches. We identify the key vulnerabilities of weaker approaches to security such as password use against various cyber threats. Cyber threats and MFA solutions are categorised in this paper to facilitate readers’ understanding of them in healthcare domains.ConclusionsWe contribute to an understanding of up-to-date MFA approaches and how they can be improved for use in the IoHT. This is achieved by discussing the challenges, benefits, and limitations of current methodologies and recommendations to improve access to eHealth resources through additional layers of security.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T05:29:38Z
DOI: 10.1177/20552076231177144
Issue No: Vol. 9 (2023)
- Monitoring physical impact and recovery of pancreatic cancer treatment
using consumer wearable health data: A case report
Authors: Cees P van der Schans, Simon van der Schans, Jurjen van der Schans, Caspar Mylius, Joost Klaase
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Consumer wearables health data may reflect the impact of pancreatic cancer and its treatment on cardiorespiratory fitness and the subsequent recovery after treatment. The patient is a 65-year-old male treated for borderline resectable pancreatic cancer. Treatment consisted of four courses of FOLFIRINOX neoadjuvant chemotherapy, a Whipple procedure with a right hemicolectomy and venous segment resection, and eight courses of adjuvant FOLFIRINOX chemotherapy. Physical activity and moderate to vigorous physical activity declined after the onset of symptoms, increased in the weeks before surgery, declined after surgery and then gradually recovered during and after adjuvant chemotherapy. Estimated VO2max remained stable during neoadjuvant chemotherapy, sharply decreased after surgery and then gradually recovered. Heart rate at rest increased and heart rate variability decreased after the onset of symptoms reaching their highest and lowest values after surgery. Both gradually returned to baseline seven months after the last course of chemotherapy. The physical impact of pancreatic cancer and its treatment and recovery was in this case reflected on consumer wearable health data. Seven months after the last chemotherapy recovery was close to baseline values.
Citation: DIGITAL HEALTH
PubDate: 2023-05-23T05:28:40Z
DOI: 10.1177/20552076231177127
Issue No: Vol. 9 (2023)
- Identification of early symptoms of endometriosis through the analysis of
online social networks: A social media study
Authors: Mathilde Fruchart, Fatima El Idrissi, Antoine Lamer, Karim Belarbi, Mohamed Lemdani, Djamel Zitouni, Benjamin C Guinhouya
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveEndometriosis is a complex full-body inflammation disease with an average time to diagnosis of 7–10 years. Social networks give opportunity to patient to openly discuss about their condition, share experiences, and seek advice. Thus, data from social media may provide insightful data about patient's experience. This study aimed at applying a text-mining approach to online social networks in order to identify early signs associated with endometriosis.MethodsAn automated exploration technique of online forums was performed to extract posts. After a cleaning step of the built corpus, we retrieved all symptoms evoked by women, and connected them to the MedDRA dictionary. Then, temporal markers allowed targeting only the earliest symptoms. The latter were those evoked near a marker of precocity. A co-occurrence approach was further applied to better account for the context of evocations.ResultsResults were visualised using the graph-oriented database Neo4j. We collected 7148 discussions threads and 78,905 posts from 10 French forums. We extracted 41 groups of contextualised symptoms, including 20 groups of early symptoms associated with endometriosis. Among these groups of early symptoms, 13 were found to portray already known signs of endometriosis. The remaining 7 clusters of early symptoms were limb oedema, muscle pain, neuralgia, haematuria, vaginal itching, altered general condition (i.e. dizziness, fatigue, nausea) and hot flush.ConclusionWe pointed out some additional symptoms of endometriosis qualified as early symptoms, which can serve as a screening tool for prevention and/or treatment purpose. The present findings offer an opportunity for further exploration of early biological processes triggering this disease.
Citation: DIGITAL HEALTH
PubDate: 2023-05-22T05:10:30Z
DOI: 10.1177/20552076231176114
Issue No: Vol. 9 (2023)
- Assessment of functionalities and attitude toward telemedicine for
patients with cardiovascular disease
Authors: Lieselotte Knaepen, Maarten Falter, Martijn Scherrenberg, Paul Dendale, Lien Desteghe, Hein Heidbuchel
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionMany patients with cardiovascular diseases are only seen by a physician once or twice a year unless urgent symptoms. Recent years have shown an increase in digital technologies to follow patients remotely, that is, telemedicine. Telemedicine can be supportive for follow-up of patients at continuous risk. This study investigated patients’ attitude toward telemedicine, the defined features they consider important and future willingness to pay.MethodsCardiology patients with various types of prior telemedicine follow-up or who never had a telemonitoring follow-up were included. A new self-developed survey was implemented electronically and took 5–10 min to complete.ResultsIn total, 231 patients (191 telemedicine [T] and 40 controls [C]), were included. Most participants owned a smartphone (84.8%) and only 2.2% of the total participants did not own any digital device. The most important feature of telemedicine cited in both groups was personalization (i.e., personalized health tips based on medical history, 89.6%; personalized feedback on entered health parameters 86.1%). The most important motivating factor for the use of telemedicine is recommendation by a physician (84.8%), while the reduction of in-person visits is a minor reason (24.7%). Only half of the participants (67.1%) would be willing to pay for telemedicine tools in the future.ConclusionPatients with cardiovascular disease have a positive attitude to telemedicine, especially when it allows for more personalized care, and when it is advocated by the physician. Participants expect that telemedicine becomes part of reimbursed care. This calls for interactive tools with proven efficacy and safety, while guarding unequal access to care.
Citation: DIGITAL HEALTH
PubDate: 2023-05-19T07:14:21Z
DOI: 10.1177/20552076231176941
Issue No: Vol. 9 (2023)
- Kinect-based objective evaluation of bradykinesia in patients with
Parkinson's disease
Authors: Zhuang Wu, Hongkai Gu, Ronghua Hong, Ziwen Xing, Zhuoyu Zhang, Kangwen Peng, Yijing He, Ludi Xie, Jingxing Zhang, Yichen Gao, Yue Jin, Xiaoyun Su, Hongping Zhi, Qiang Guan, Lizhen Pan, Lingjing Jin
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo quantify bradykinesia in Parkinson's disease (PD) with a Kinect depth camera-based motion analysis system and to compare PD and healthy control (HC) subjects.MethodsFifty PD patients and twenty-five HCs were recruited. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was used to evaluate the motor symptoms of PD. Kinematic features of five bradykinesia-related motor tasks were collected using Kinect depth camera. Then, kinematic features were correlated with the clinical scales and compared between groups.ResultsSignificant correlations were found between kinematic features and clinical scales (P
Citation: DIGITAL HEALTH
PubDate: 2023-05-19T07:13:21Z
DOI: 10.1177/20552076231176653
Issue No: Vol. 9 (2023)
- Digital health interventions to support family caregivers: An updated
systematic review
Authors: Shumenghui Zhai, Frances Chu, Minghui Tan, Nai-Ching Chi, Teresa Ward, Weichao Yuwen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveChronic diseases are the leading causes of death and disability in the U.S., and disease management largely falls onto patients’ family caregivers. The long-term burden and stress of caregiving negatively impact caregivers’ well-being and ability to provide care. Digital health interventions have the potential to support caregivers. This article aims to provide an updated review of interventions using digital health tools to support family caregivers and the scope of the Human-Centered Design (HCD) approaches.MethodsWe conducted a systematic search on July 2019 and January 2021 in PubMed, CINAHL, Embase, Cochrane Library, PsycINFO, ERIC, and ACM Digital Library, limiting to 2014–2021 to identify family caregiver interventions assisted by modern technologies. The Mixed Methods Appraisal Tool and the Grading of Recommendations Assessment, Development and Evaluation were used to evaluate the articles. Data were abstracted and evaluated using Rayyan and Research Electronic Data Capture.ResultsWe identified and reviewed 40 studies from 34 journals, 10 fields, and 19 countries. Findings included patients’ conditions and relationships with family caregivers, how the technology is used to deliver the intervention, HCD methods, theoretical frameworks, components of the interventions, and family caregiver health outcomes.ConclusionThis updated and expanded review revealed that digitally enhanced health interventions were robust at providing high-quality assistance and support to caregivers by improving caregiver psychological health, self-efficacy, caregiving skills, quality of life, social support, and problem-coping abilities. Health professionals need to include informal caregivers as an essential component when providing care to patients. Future research should include more marginalized caregivers from diverse backgrounds, improve the accessibility and usability of the technology tools, and tailor the intervention to be more culturally and linguistically sensitive.
Citation: DIGITAL HEALTH
PubDate: 2023-05-19T07:12:12Z
DOI: 10.1177/20552076231171967
Issue No: Vol. 9 (2023)
- Evaluating digital competencies for allied health professionals in the
United Kingdom
Authors: Geraldine Lee, Emma Caton, Annemarie Knight
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The Covid-19 pandemic accelerated the move to virtual and remote consultations in clinical practice with digital technologies widely implemented. eHealth interventions and use of applications in a variety of conditions means that patients and their families, as well as healthcare professionals, can access and interpret data in real-time, as well as providing trends in various clinical parameters including blood pressure for instance. Despite the aim of digital transformation in the National Health Service in the United Kingdom, this has not been fully realised and there is no consensus on the skills and competencies required for allied health professionals (AHPs). This qualitative study undertook two focus groups with twelve AHPs to evaluate the AHP Digital Competency Framework in the UK. The participants recognised the importance of a digital technology in their clinical practice and perceived digital literacy as essential for AHPs. In relation to the AHP framework, participants agreed that competencies in digital technology were clinically relevant, and assessment of these competencies should be performed regularly in practice. However, the majority were unaware of the AHP digital competency framework and suggested improvements to optimise its use in practice and identified areas for improvement. Overall, the AHP Digital Competency Framework has the potential, with better dissemination and further refinement of the wording, to become a useful tool to support the enhancement of digital competency in AHPs and improve the delivery of patient care.
Citation: DIGITAL HEALTH
PubDate: 2023-05-18T06:53:23Z
DOI: 10.1177/20552076231176658
Issue No: Vol. 9 (2023)
- Correlation and differences of patient-reported outcomes vs. Likert-Rating
of MS symptoms in a real-world cohort using a digital patient app
Authors: Steffeni Mountford, Maria Kahn, Preetha Balakrishnan, Elizabeth Jacyshyn-Owen, Markus Eberl, Benjamin Friedrich, Natalie Joschko, Tjalf Ziemssen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundMultiple Sclerosis (MS) is a chronic and progressive neurological autoimmune disease currently affecting 250,000 individuals in Germany. Patients suffering from the disease can be severely impaired in their day-to-day activities. BRISA is a digital app specifically designed to help MS patients monitor their disease by regularly tracking symptoms. Lengthy and time-consuming questionnaires for patient-reported outcomes (PRO) are the standard method to assess the patients’ current condition. Here, we examine whether simplified versions of these questionnaires can provide comparable information regarding individual symptom presentations in BRISA users.Methods828 users were included in the analysis. Patients who provided onboarding information and answered at least one questionnaire and the corresponding simplified smiley symptoms assessment were included. Correlation of questionnaire and symptom scores was calculated using Pearson's correlation.ResultsOur analysis cohort predominantly consisted of female, 26–55-year-olds. Relapsing-remitting MS (RRMS) was the most common MS type recorded. Most patients were diagnosed 2–5 years ago. Questionnaires regarding fatigue and vision impairment were among the most answered, those regarding bowel movement and sexual satisfaction received fewest responses. Overall, the scores from questionnaires and symptoms correlated positively. Scoring correlation could also be shown across the subgroups divided by gender, age groups, type of MS, and time since diagnosis of the disease.ConclusionScores recorded from traditional PRO questionnaires can be reflected more easily as a trend in a simplified scale using smileys. Nevertheless, traditional questionnaires are needed to also maintain a more objective assessment. In conclusion, the patient will benefit most from an adaptive combination of regular traditional PRO questionnaire assessments and simplified symptom recording.
Citation: DIGITAL HEALTH
PubDate: 2023-05-18T06:08:43Z
DOI: 10.1177/20552076231173520
Issue No: Vol. 9 (2023)
- Use of digital technologies for public health surveillance during the
COVID-19 pandemic: A scoping review
Authors: Lorie Donelle, Leigha Comer, Brad Hiebert, Jodi Hall, Jacob J. Shelley, Maxwell J. Smith, Anita Kothari, Jacquelyn Burkell, Saverio Stranges, Tommy Cooke, James M. Shelley, Jason Gilliland, Marionette Ngole, Danica Facca
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Throughout the COVID-19 pandemic, a variety of digital technologies have been leveraged for public health surveillance worldwide. However, concerns remain around the rapid development and deployment of digital technologies, how these technologies have been used, and their efficacy in supporting public health goals. Following the five-stage scoping review framework, we conducted a scoping review of the peer-reviewed and grey literature to identify the types and nature of digital technologies used for surveillance during the COVID-19 pandemic and the success of these measures. We conducted a search of the peer-reviewed and grey literature published between 1 December 2019 and 31 December 2020 to provide a snapshot of questions, concerns, discussions, and findings emerging at this pivotal time. A total of 147 peer-reviewed and 79 grey literature publications reporting on digital technology use for surveillance across 90 countries and regions were retained for analysis. The most frequently used technologies included mobile phone devices and applications, location tracking technologies, drones, temperature scanning technologies, and wearable devices. The utility of digital technologies for public health surveillance was impacted by factors including uptake of digital technologies across targeted populations, technological capacity and errors, scope, validity and accuracy of data, guiding legal frameworks, and infrastructure to support technology use. Our findings raise important questions around the value of digital surveillance for public health and how to ensure successful use of technologies while mitigating potential harms not only in the context of the COVID-19 pandemic, but also during other infectious disease outbreaks, epidemics, and pandemics.
Citation: DIGITAL HEALTH
PubDate: 2023-05-18T05:33:43Z
DOI: 10.1177/20552076231173220
Issue No: Vol. 9 (2023)
- Sustaining telecare consultations in nurse-led clinics: Perceptions of
stroke patients and advanced practice nurses: A qualitative study
Authors: Arkers Kwan Ching Wong, Jonathan Bayuo, Frances Kam Yuet Wong, Vivian Wai Yan Kwok, Danny Wah Kun Tong, Man King Kwong, Bernard Man Kam Yuen, Ching Sing Fong, Shun Tim Chan, Rinis Sin Yi Chan, Wah Chun Li
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe ongoing pandemic has accentuated the use of telecare services; however, only limited progress has been made in understanding the barriers and facilitators to using these services. In order to move towards sustaining such essential services, the present study aimed to ascertain the experiences of stroke survivors and healthcare providers regarding the utilization of a post-stroke telecare service in Hong Kong.MethodsInterpretive description was employed for this study. Semi-structured discussions and interviews were undertaken with nine stroke survivors and four stroke nurses who delivered the telecare services. The principles of thematic analysis were inductively followed to analyse the data. The Standards for Reporting Qualitative Research checklist was used to guide the reporting of the data.ResultsThree themes emerged: (a) pre-existing post-discharge service pathways; (b) push factors/facilitators for telecare usage; and (c) barriers to telecare usage. Overall, the telecare service was considered a significant alternative and one that complements conventional face-to-face follow-ups. Stroke survivors were motivated to use the service because it was convenient and flexible. However, significant barriers exist, including technical issues and a lack of guidelines and training opportunities for healthcare providers.ConclusionsAlthough telecare is still evolving, several factors drive stroke survivors to use the service. Attention needs to be paid to the emerging barriers to improve long-term usage of the service. Clear guidelines are needed to underpin the development and implementation of telecare services.
Citation: DIGITAL HEALTH
PubDate: 2023-05-16T11:04:45Z
DOI: 10.1177/20552076231176163
Issue No: Vol. 9 (2023)
- The feasibility of remotely monitoring physical, cognitive, and
psychosocial function in individuals with stroke or chronic obstructive
pulmonary disease
Authors: Margaret A French, Eva Keatley, Junyao Li, Aparna Balasubramanian, Nadia N Hansel, Robert Wise, Peter Searson, Anil Singh, Preeti Raghavan, Stephen Wegener, Ryan T Roemmich, Pablo Celnik
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveClinical implementation of remote monitoring of human function requires an understanding of its feasibility. We evaluated adherence and the resources required to monitor physical, cognitive, and psychosocial function in individuals with either chronic obstructive pulmonary disease or stroke during a three-month period.MethodsSeventy-three individuals agreed to wear a Fitbit to monitor physical function and to complete monthly online assessments of cognitive and psychosocial function. During a three-month period, we measured adherence to monitoring (1) physical function using average daily wear time, and (2) cognition and psychosocial function using the percentage of assessments completed. We measured the resources needed to promote adherence as (1) the number of participants requiring at least one reminder to synchronize their Fitbit, and (2) the number of reminders needed for each completed cognitive and psychosocial assessment.ResultsAfter accounting for withdrawals, the average daily wear time was 77.5 ± 19.9% of the day and did not differ significantly between months 1, 2, and 3 (p = 0.30). To achieve this level of adherence, 64.9% of participants required at least one reminder to synchronize their device. Participants completed 61.0% of the cognitive and psychosocial assessments; the portion of assessments completed each month didnot significantly differ (p = 0.44). Participants required 1.13 ± 0.57 reminders for each completed assessment. Results did not differ by disease diagnosis.ConclusionsRemote monitoring of human function in individuals with either chronic obstructive pulmonary disease or stroke is feasible as demonstrated by high adherence. However, the number of reminders required indicates that careful consideration must be given to the resources available to obtain high adherence.
Citation: DIGITAL HEALTH
PubDate: 2023-05-16T11:03:44Z
DOI: 10.1177/20552076231176160
Issue No: Vol. 9 (2023)
- Wearable sensors and features for diagnosis of neurodegenerative diseases:
A systematic review
Authors: Huan Zhao, Junyi Cao, Junxiao Xie, Wei-Hsin Liao, Yaguo Lei, Hongmei Cao, Qiumin Qu, Chris Bowen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveNeurodegenerative diseases affect millions of families around the world, while various wearable sensors and corresponding data analysis can be of great support for clinical diagnosis and health assessment. This systematic review aims to provide a comprehensive overview of the existing research that uses wearable sensors and features for the diagnosis of neurodegenerative diseases.MethodsA systematic review was conducted of studies published between 2015 and 2022 in major scientific databases such as Web of Science, Google Scholar, PubMed, and Scopes. The obtained studies were analyzed and organized into the process of diagnosis: wearable sensors, feature extraction, and feature selection.ResultsThe search led to 171 eligible studies included in this overview. Wearable sensors such as force sensors, inertial sensors, electromyography, electroencephalography, acoustic sensors, optical fiber sensors, and global positioning systems were employed to monitor and diagnose neurodegenerative diseases. Various features including physical features, statistical features, nonlinear features, and features from the network can be extracted from these wearable sensors, and the alteration of features toward neurodegenerative diseases was illustrated. Moreover, different kinds of feature selection methods such as filter, wrapper, and embedded methods help to find the distinctive indicator of the diseases and benefit to a better diagnosis performance.ConclusionsThis systematic review enables a comprehensive understanding of wearable sensors and features for the diagnosis of neurodegenerative diseases.
Citation: DIGITAL HEALTH
PubDate: 2023-05-16T11:02:26Z
DOI: 10.1177/20552076231173569
Issue No: Vol. 9 (2023)
- Acceptability of an existing online sexually transmitted and blood-borne
infection testing model among gay, bisexual and other men who have sex
with men in Ontario, Canada
Authors: Joshun JS Dulai, Mark Gilbert, Nathan J Lachowsky, Kiffer G Card, Ben Klassen, Jessy Dame, Ann N Burchell, Catherine Worthington, Aidan Ablona, Praney Anand, Ezra Blaque, Heeho Ryu, MacKenzie Stewart, David J Brennan, Daniel Grace
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesGay, bisexual and other men who have sex with men (GBM) are disproportionately affected by sexually transmitted and blood-borne infections (STBBI) due to stigma and other factors such as structural barriers, which delay STBBI testing in this population. Understanding acceptability of online testing is useful in expanding access in this population, thus we examined barriers to clinic-based testing, acceptability of a potential online testing model, and factors associated with acceptability among GBM living in Ontario.MethodsSex Now 2019 was a community-based, online, bilingual survey of GBM aged ≥15. Prevalence ratios (PR) and 95% confidence intervals (95%CI) were calculated using modified Poisson regression with robust variances. Multivariable modelling was conducted using the Hosmer-Lemeshow-Sturdivant approach.ResultsAmong 1369 participants, many delayed STBBI testing due to being too busy (31%) or inconvenient clinic hours (29%). Acceptability for online testing was high (80%), with saving time (67%) as the most common benefit, and privacy concerns the most common drawback (38%). Statistically significant predictors of acceptability for online testing were younger age (PR = 0.993; 95%CI: 0.991–0.996); a greater number of different sexual behaviours associated with STBBI transmission (PR = 1.031; 95%CI: 1.018–1.044); identifying as an Indigenous immigrant (PR = 1.427; 95%CI: 1.276–1.596) or immigrant of colour (PR = 1.158; 95%CI: 1.086–1.235) compared with white non-immigrants; and currently using HIV pre-exposure prophylaxis (PrEP) compared to not currently using PrEP (PR = 0.894; 95%CI: 0.828–0.965).ConclusionsAcceptability of online testing was high among GBM in Ontario. Implementing online STBBI testing may expand access for certain subpopulations of GBM facing barriers to current in-person testing.
Citation: DIGITAL HEALTH
PubDate: 2023-05-15T06:32:13Z
DOI: 10.1177/20552076231173557
Issue No: Vol. 9 (2023)
- Neurodata Tracker: Software for computational assessment of hand motor
skills based on optical motion capture in a virtual environment
Authors: David López, Laura Casado-Fernández, Fernando Fernández, Blanca Fuentes, Blanca Larraga-García, Jorge Rodríguez-Pardo, David Hernández, Elisa Alonso, Exuperio Díez-Tejedor, Álvaro Gutiérrez, María Alonso de Leciñana
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesDeficits affecting hand motor skills negatively impact the quality of life of patients. The NeuroData Tracker platform has been developed for the objective and precise evaluation of hand motor deficits. We describe the design and development of the platform and analyse the technological feasibility and usability in a relevant clinical setting.MethodsA software application was developed in Unity (C#) to obtain kinematic data from hand movement tracking by a portable device with two cameras and three infrared sensors (leap motion®). Four exercises were implemented: (a) wrist flexion-extension (b) finger-grip opening-closing (c) finger spread (d) fist opening-closing. The most representative kinematic parameters were selected for each exercise. A script in Python was integrated in the platform to transform real-time kinematic data into relevant information for the clinician. The application was tested in a pilot study comparing the data provided by the tool from ten healthy subjects without any motor impairment and ten patients diagnosed with a stroke with mild to moderate hand motor deficit.ResultsThe NeuroData Tracker allowed the parameterization of kinematics of hand movement and the issuance of a report with the results. The comparison of the data obtained suggests the feasibility of the tool for detecting differences between patients and healthy subjects.ConclusionsThis new platform based on optical motion capturing provides objective measurement of hand movement allowing quantification of motor deficits. These findings require further validation of the tool in larger trials to verify its usefulness in the clinical setting.
Citation: DIGITAL HEALTH
PubDate: 2023-05-11T06:20:59Z
DOI: 10.1177/20552076231174786
Issue No: Vol. 9 (2023)
- Assessment of content, behavior change techniques, and quality of
unintended pregnancy apps in Spain: Systematic search on app stores
Authors: Rubén Martín-Payo, Xana Gonzalez-Mendez, Sergio Carrasco-Santos, Aranzazu Muñoz-Mancisidor, Cristina Papin-Cano, María del Mar Fernandez-Alvarez
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveUnintended pregnancies are a public health problem that represents 48% of global pregnancies. Despite the proliferation of smartphones there is limited data on the app's features on unintended pregnancy. The purpose of this research was to identify free apps available in Spanish, in the iOS Store and Google Play, which can be recommended to prevent unintended pregnancies in adolescents.MethodsA systematic search to identify apps was performed in the iOS App Store and in Google Play aiming to replicate the way a patient might access an “unintended pregnancy prevention” app. Additionally, the quality, using the Mobile Application Rating Scale, and content were assessed.ResultsA total of 4614 apps were identified, of which 8 were retrieved for assessment (0.17%). The mean for objective and subject quality was 3.39 (standard deviation (SD) = 0.694) and 1.84 (SD = 0.626), respectively. A total of 16 thematic categories were identified. The mean of topics covered in the apps was 5.38 (SD = 2.925) being those related to contraception the more frequent.ConclusionThe results of the present study suggest that only a small percentage of free pregnancy prevention apps in Spanish should be recommended. The contents of the apps retrieved meet the potential necessities of adolescents.
Citation: DIGITAL HEALTH
PubDate: 2023-05-11T06:20:29Z
DOI: 10.1177/20552076231173563
Issue No: Vol. 9 (2023)
- Attitudes and associated factors of patients’ adoption of patient
accessible electronic health records in China — A mixed methods study
Authors: Jing Liu, Xiaoqian Gong, Mark Weal, Wei Dai, Shengchao Hou, Jingdong Ma
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAlthough patient accessible electronic health records (PAEHRs) offer great potential in enhancing the provision of patient-centered care and improving satisfaction, the adoption rate is still low. Currently, few studies are there for researchers and health organization leaders to understand patients’ thoughts and related factors of PAEHRs adoption in developing countries. China adopted more limited practices of PAEHRs, among which we selected Yuebei People's Hospital as an example.ObjectiveThe study aimed to research patient attitudes toward PAEHRs use and the associated factors of patients’ adoption of PAEHRs in China, which is achieved by both qualitative and quantitative studies.MethodsThis study employed sequential mixed-methods. The DeLone & McLean information systems (D&M IS) success model, Unified Theory of Acceptance and Use of Technology (UTAUT) and task-technology fit (TTF) model were used to guide the research. Finally, we collected 28 valid in-depth interview responses, 51 valid semi-structured interview responses and 235 valid questionnaire responses. The research model was tested and validated using data collected.ResultsThe findings of the qualitative study reveal that patients’ rate perceived task productivity and customer satisfaction as benefits, and poor-quality information as flaws. Results of the quantitative study show that the drivers of behavioral intention are performance expectance, effort expectancy and social influence; the predictors of use behavior are TTF and behavioral intention.ConclusionIt is necessary to consider PAEHRs’ task-tool role in patients’ adoption behavior. Hospitalized patients value PAEHRs’ practical attributes and attach much importance to the information content and application design.
Citation: DIGITAL HEALTH
PubDate: 2023-05-10T04:55:53Z
DOI: 10.1177/20552076231174101
Issue No: Vol. 9 (2023)
- Ensemble machine learning methods in screening electronic health records:
A scoping review
Authors: Christophe AT Stevens, Alexander RM Lyons, Kanika I Dharmayat, Alireza Mahani, Kausik K Ray, Antonio J Vallejo-Vaz, Mansour TA Sharabiani
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundElectronic health records provide the opportunity to identify undiagnosed individuals likely to have a given disease using machine learning techniques, and who could then benefit from more medical screening and case finding, reducing the number needed to screen with convenience and healthcare cost savings. Ensemble machine learning models combining multiple prediction estimates into one are often said to provide better predictive performances than non-ensemble models. Yet, to our knowledge, no literature review summarises the use and performances of different types of ensemble machine learning models in the context of medical pre-screening.MethodWe aimed to conduct a scoping review of the literature reporting the derivation of ensemble machine learning models for screening of electronic health records. We searched EMBASE and MEDLINE databases across all years applying a formal search strategy using terms related to medical screening, electronic health records and machine learning. Data were collected, analysed, and reported in accordance with the PRISMA scoping review guideline.ResultsA total of 3355 articles were retrieved, of which 145 articles met our inclusion criteria and were included in this study. Ensemble machine learning models were increasingly employed across several medical specialties and often outperformed non-ensemble approaches. Ensemble machine learning models with complex combination strategies and heterogeneous classifiers often outperformed other types of ensemble machine learning models but were also less used. Ensemble machine learning models methodologies, processing steps and data sources were often not clearly described.ConclusionsOur work highlights the importance of deriving and comparing the performances of different types of ensemble machine learning models when screening electronic health records and underscores the need for more comprehensive reporting of machine learning methodologies employed in clinical research.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T09:07:33Z
DOI: 10.1177/20552076231173225
Issue No: Vol. 9 (2023)
- Development and usability testing of your MS questionnaire: A
patient-based digital tool to monitor symptoms of multiple sclerosis
Authors: Gavin Giovannoni, Enrique Alvarez, Ellen Tutton, Olaf Hoffmann, Yan Xu, Patrick Vermersch, Celia Oreja-Guevara, Maria Trojano, Ralf Gold, René Robles-Cedeño, Mudeer Khwaja, Bianca Stadler, Jo Vandercappellen, Tjalf Ziemssen
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesWe describe the development of Your Multiple Sclerosis Questionnaire and present the real-world usability testing results of Your Multiple Sclerosis Questionnaire.MethodsThe Your Multiple Sclerosis Questionnaire tool was developed in four stages to collect feedback from people living with MS (plwMS), patient organizations, and clinicians on content, format, and applicability. To assess its usability, 13 clinicians across 7 countries completed an online survey after using the tool with plwMS in a total of 261 consultations from September, 2020 to July, 2021.ResultsThe initial Your Multiple Sclerosis Questionnaire version was based on findings from previous research developing MSProDiscuss™, a clinician-completed tool. Subsequently, insights from plwMS obtained during cognitive debriefing, patient councils and advisory boards led to changes including the addition of mood and sexual problems and the definition of relapse. All 13 clinicians completed the individual survey, whereas 10 clinicians completed the final survey. Clinicians “strongly agreed” or “agreed” that Your Multiple Sclerosis Questionnaire was easy to use and understand (98.5%; 257/261 patient consultations). The clinicians were willing to use the tool again with the same patient (98.1%; 256/261 patient consultations). All clinicians who completed the final survey (100%; 10/10) reported the tool to have a positive influence on their clinical practice, helped patients engage with their MS, facilitated discussion with patients, and complemented neurological assessment.ConclusionYour Multiple Sclerosis Questionnaire benefits both plwMS and clinicians by facilitating a structured discussion and engaging the plwMS to self-monitor and self-manage. Your Multiple Sclerosis Questionnaire is compatible with telemedicine practice and integration of the tool into electronic health records would enable tracking of the disease evolution and individual monitoring of MS symptoms over time.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T07:08:45Z
DOI: 10.1177/20552076231173531
Issue No: Vol. 9 (2023)
- Anonymization of whole slide images in histopathology for research and
education
Authors: Tom Bisson, Michael Franz, Isil Dogan O, Daniel Romberg, Christoph Jansen, Peter Hufnagl, Norman Zerbe
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThe exchange of health-related data is subject to regional laws and regulations, such as the General Data Protection Regulation (GDPR) in the EU or the Health Insurance Portability and Accountability Act (HIPAA) in the United States, resulting in non-trivial challenges for researchers and educators when working with these data. In pathology, the digitization of diagnostic tissue samples inevitably generates identifying data that can consist of sensitive but also acquisition-related information stored in vendor-specific file formats. Distribution and off-clinical use of these Whole Slide Images (WSIs) are usually done in these formats, as an industry-wide standardization such as DICOM is yet only tentatively adopted and slide scanner vendors currently do not provide anonymization functionality.MethodsWe developed a guideline for the proper handling of histopathological image data particularly for research and education with regard to the GDPR. In this context, we evaluated existing anonymization methods and examined proprietary format specifications to identify all sensitive information for the most common WSI formats. This work results in a software library that enables GDPR-compliant anonymization of WSIs while preserving the native formats.ResultsBased on the analysis of proprietary formats, all occurrences of sensitive information were identified for file formats frequently used in clinical routine, and finally, an open-source programming library with an executable CLI tool and wrappers for different programming languages was developed.ConclusionsOur analysis showed that there is no straightforward software solution to anonymize WSIs in a GDPR-compliant way while maintaining the data format. We closed this gap with our extensible open-source library that works instantaneously and offline.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T07:08:27Z
DOI: 10.1177/20552076231171475
Issue No: Vol. 9 (2023)
- Benefits and challenges of tele-dance movement psychotherapy with children
with autism and their parents
Authors: Janet TN Moo, Rainbow TH Ho
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Dance movement psychotherapy can be physically and psychologically beneficial for children with autism spectrum disorder. The coronavirus disease 2019 pandemic required therapy to take place online. However, tele-dance movement psychotherapy with children with autism spectrum disorder has yet to be studied. This mixed methods study involving qualitative research and movement analyses entailed providing tele-dance movement psychotherapy to children with autism spectrum disorder and their parents, during the coronavirus disease 2019 pandemic, and exploring its potential benefits and challenges. The parents who completed the programme reported positive outcomes including the child's social development, enjoyment, improved understanding of their child, insight and ideas, as well as relationship-building. Movement analyses using the Parent Child Movement Scale (PCMS) lent greater insight into these developments. All of the parents reported challenges in participating in tele-dance movement psychotherapy. These were related to screen-to-screen interactions, home, and physical distance. There was a relatively high attrition rate. These findings highlight the challenges of tele-dance movement psychotherapy with children with autism spectrum disorder and the unique benefits of meeting in person whilst the positive outcomes may indicate that tele-dance movement psychotherapy can be beneficial, perhaps particularly as an interim or adjunct form of therapy. Specific measures can be taken to enhance engagement.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T07:03:35Z
DOI: 10.1177/20552076231171233
Issue No: Vol. 9 (2023)
- Assessing the physiological effect of non-driving-related task performance
in conditionally automated driving systems: A systematic review and
meta-analysis protocol
Authors: Rory Coyne, Leona Ryan, Mohamed Moustafa, Alan F Smeaton, Peter Corcoran, Jane C Walsh
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundLevel 3 automated driving systems involve the continuous performance of the driving task by artificial intelligence within set environmental conditions, such as a straight highway. The driver's role in Level 3 is to resume responsibility of the driving task in response to any departure from these conditions. As automation increases, a driver's attention may divert towards non-driving-related tasks (NDRTs), making transitions of control between the system and user more challenging. Safety features such as physiological monitoring thus become important with increasing vehicle automation. However, to date there has been no attempt to synthesise the evidence for the effect of NDRT engagement on drivers’ physiological responses in Level 3 automation.MethodsA comprehensive search of the electronic databases MEDLINE, EMBASE, Web of Science, PsycINFO, and IEEE Explore will be conducted. Empirical studies assessing the effect of NDRT engagement on at least one physiological parameter during Level 3 automation, in comparison with a control group or baseline condition will be included. Screening will take place in two stages, and the process will be outlined within a PRISMA flow diagram. Relevant physiological data will be extracted from studies and analysed using a series of meta-analyses by outcome. A risk of bias assessment will also be completed on the sample.ConclusionThis review will be the first to appraise the evidence for the physiological effect of NDRT engagement during Level 3 automation, and will have implications for future empirical research and the development of driver state monitoring systems.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T06:34:57Z
DOI: 10.1177/20552076231174782
Issue No: Vol. 9 (2023)
- Feasibility, acceptance and factors related to the implementation of
telemedicine in rural areas: A scoping review protocol
Authors: Badra Al Aufa, Ari Nurfikri, Wiwiet Mardiati, Sancoko Sancoko, Heri Yuliyanto, Mochamad Iqbal Nurmansyah, Imas Arumsari, Ibrahim Isa Koire
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundTelemedicine is a quickly developing service that offers more people the access to effective and high-quality healthcare. Societies residing in rural places tend to travel long distances to receive health care, usually have limited access to health care and/or postpone getting health care until a health emergency occurs. However, for telemedicine services to be accessible, a number of prerequisites including the availability of cutting-edge technology and equipment in rural areas must be present.ObjectiveThis scoping review aims to collect all available data on the viability, acceptability, challenges and facilitators of telemedicine in rural areas.MethodsPubMed, Scopus and Medical collection of ProQuest are the databases chosen for an electronic search of the literature. Identification of the title and abstract will be followed by an evaluation of the paper's accuracy and eligibility in a two-fold mode; whereas the identification of papers will be openly and completely described using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flowchart.ConclusionThis scoping review would be among the first to offer a thorough evaluation of issues related to the viability, acceptance and implementation of telemedicine in rural areas. In order to improve the conditions of supply, demand and other circumstances relevant to the implementation of telemedicine, the results would be helpful in providing direction and recommendations for future developments in the usage of telemedicine, particularly in rural areas.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T06:30:38Z
DOI: 10.1177/20552076231171236
Issue No: Vol. 9 (2023)
- Assessing the healthcare quality issues for digital incident reporting in
Sweden: Incident reports analysis
Authors: Md Shafiqur Rahman Jabin, Mary Steen, Dianne Wepa, Patrick Bergman
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis study explored healthcare quality issues affecting the reporting and investigation levels of digital incident reporting systems.MethodsA total of 38 health information technology-related incident reports (free-text narratives) were collected from one of Sweden's national incident reporting repositories. The incidents were analysed using an existing framework, i.e., the Health Information Technology Classification System, to identify the types of issues and consequences. The framework was applied in two fields, ‘event description’ by the reporters and ‘manufacturer's measures’, to assess the quality of reporting incidents by the reporters. Additionally, the contributing factors, i.e., either human or technical factors for both fields, were identified to evaluate the quality of the reported incidents.ResultsFive types of issues were identified and changes made between before-and-after investigations: Machine to software-related issues (n = 8), machine to use-related issues (n = 5), software to software-related issues (n = 5), use to software-related issues (n = 4) and use to use-related issues (n = 1). Over two-thirds (n = 15) of the incidents demonstrated a change in the contributing factors after the investigation. Only four incidents were identified as altering the consequences after the investigation.ConclusionThis study shed some light on the issues of incident reporting and the gap between the reporting and investigation levels. Facilitating sufficient staff training sessions, agreeing on common terms for health information technology systems, refining the existing classifications systems, enforcing mini-root cause analysis, and ensuring unit-based local reporting and standard national reporting may help bridge the gap between reporting and investigation levels in digital incident reporting.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T05:27:00Z
DOI: 10.1177/20552076231174307
Issue No: Vol. 9 (2023)
- Diabetes prevention program outcomes by in-person versus distance delivery
mode among ethnically diverse, primarily lower-income adults
Authors: Kate F Welshons, Nikki A Johnson, Abby L Gold, Marla Reicks
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivePhysical activity and weight loss outcomes of a diabetes prevention program were compared for ethnically diverse adults, with the majority participating in public assistance programs. Outcomes were compared for those who completed the program in person versus by distance delivery.MethodsA two-group, pre–post study design compared National Diabetes Prevention Program outcomes based on in-person delivery (2018–2020 pre-COVID-19 pandemic, n = 47) and distance delivery (after March 2020, n = 31). Outcomes were measured or self-reported depending on the delivery method. Linear mixed models with a random intercept for coach and covariates were used to assess delivery mode group differences in percent weight loss and weekly physical activity minutes.ResultsCompletion rates were similar by in-person versus distance delivery mode (57% vs. 65%). Among those who completed the program, the mean age was 58 years, the mean baseline body mass index was 33, and 39% were Hispanic. The majority were female (87%), participating in a public assistance program (63%), and living in a micropolitan area (61%). Percent weight loss was greater in the distance delivery group (7.7%) compared to the in-person group (4.7%) in the unadjusted analysis (p = 0.009) but not when adjusted for covariates. No differences were observed in adjusted weekly physical activity minutes between the in-person (219 min) versus the distance group (148 min).ConclusionsNo differences were observed by delivery mode in percent weight loss or weekly physical activity minutes, indicating that distance delivery does not compromise program effectiveness.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T05:26:20Z
DOI: 10.1177/20552076231173524
Issue No: Vol. 9 (2023)
- Swapping data: A pragmatic approach for enabling academic-industrial
partnerships
Authors: Julia Kasprzak, Simon Frey, Hermann Oetlinger, C. Benedikt Westphalen, Nicole Erickson, Volker Heinemann, Daniel Nasseh
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesAcademic institutions have access to comprehensive sets of real-world data. However, their potential for secondary use—for example, in medical outcomes research or health care quality management—is often limited due to data privacy concerns. External partners could help achieve this potential, yet documented frameworks for such cooperation are lacking. Therefore, this work presents a pragmatic approach for enabling academic-industrial data partnerships in a health care environment.MethodsWe employ a value-swapping strategy to facilitate data sharing. Using tumor documentation and molecular pathology data, we define a data-altering process as well as rules for an organizational pipeline that includes the technical anonymization process.ResultsThe resulting dataset was fully anonymized while still retaining the critical properties of the original data to allow for external development and the training of analytical algorithms.ConclusionValue swapping is a pragmatic, yet powerful method to balance data privacy and requirements for algorithm development; therefore, it is well suited to enable academic-industrial data partnerships.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T05:25:19Z
DOI: 10.1177/20552076231172120
Issue No: Vol. 9 (2023)
- Healthcare professionals’ perceptions of a web-based application for
using the new National Medication List in Sweden
Authors: Frida Bergman, Tora Hammar
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveDuring the first stage of implementing the National Medication List in Sweden, a web-based application called Förskrivningskollen (FK) was launched. FK includes information about a patient's prescribed and dispensed medications, and it works as a backup system until the healthcare electronic health record (EHR) systems are fully integrated. The aim of this study was to examine the healthcare professionals’ experiences and perceptions of FK.MethodsThe study applied a mixed methods approach, with statistics about the use of FK and a survey with open and closed questions. The respondents (n = 288) were healthcare professionals who were users or potential users of FK.ResultsOverall there was little knowledge about FK and uncertainty regarding working routines and the regulations connected to the application. Lack of interoperability with the EHRs made FK time-consuming to use. Respondents said that the information in FK was not updated, and they were concerned that using FK could lead to a false sense of security about the accuracy of the list. Most clinical pharmacists thought FK added benefit to their clinical work, while as a group, physicians were more ambivalent about FK's benefit.ConclusionsThe concerns of healthcare professionals give important insights for future implementation of shared medication lists. Working routines and regulations linked to FK need to be clarified. In Sweden, the potential value of a national shared medication list will probably not be realized until it is fully integrated into the EHR in a way that supports healthcare professionals’ desired ways of working.
Citation: DIGITAL HEALTH
PubDate: 2023-05-09T05:24:38Z
DOI: 10.1177/20552076231171966
Issue No: Vol. 9 (2023)
- Neural networks based on attention architecture are robust to data
missingness for early predicting hospital mortality in intensive care unit
patients
Authors: Zhixuan Zeng, Yang Liu, Shuo Yao, Jiqiang Liu, Bing Xiao, Chenxue Liu, Xun Gong
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundAlthough the machine learning model developed on electronic health records has become a promising method for early predicting hospital mortality, few studies focus on the approaches for handling missing data in electronic health records and evaluate model robustness to data missingness. This study proposes an attention architecture that shows excellent predictive performance and is robust to data missingness.MethodsTwo public intensive care unit databases were used for model training and external validation, respectively. Three neural networks (masked attention model, attention model with imputation, attention model with missing indicator) based on the attention architecture were developed, using masked attention mechanism, multiple imputation, and missing indicator to handle missing data, respectively. Model interpretability was analyzed by attention allocations. Extreme gradient boosting, logistic regression with multiple imputation and missing indicator (logistic regression with imputation, logistic regression with missing indicator) were used as baseline models. Model discrimination and calibration were evaluated by area under the receiver operating characteristic curve, area under precision-recall curve, and calibration curve. In addition, model robustness to data missingness in both model training and validation was evaluated by three analyses.ResultsIn total, 65,623 and 150,753 intensive care unit stays were respectively included in the training set and the test set, with mortality of 10.1% and 8.5%, and overall missing rate of 10.3% and 19.7%. attention model with missing indicator had the highest area under the receiver operating characteristic curve (0.869; 95% CI: 0.865 to 0.873) in external validation; attention model with imputation had the highest area under precision-recall curve (0.497; 95% CI: 0.480–0.513). Masked attention model and attention model with imputation showed better calibration than other models. The three neural networks showed different patterns of attention allocation. In terms of robustness to data missingness, masked attention model and attention model with missing indicator are more robust to missing data in model training; while attention model with imputation is more robust to missing data in model validation.ConclusionsThe attention architecture has the potential to become an excellent model architecture for clinical prediction task with data missingness.
Citation: DIGITAL HEALTH
PubDate: 2023-05-08T06:33:10Z
DOI: 10.1177/20552076231171482
Issue No: Vol. 9 (2023)
- Workflow assessment of an augmented reality application for planning of
Authors: Matthias Fabian Berger, Raimund Winter, Alexandru-Cristian Tuca, Birgit Michelitsch, Bernhard Schenkenfelder, Robert Hartmann, Michael Giretzlehner, Gernot Reishofer, Lars-Peter Kamolz, David Benjamin Lumenta
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveIn contrast to the rising amount of financial investments for research and development in medical technology worldwide is the lack of usability and clinical readiness of the produced systems. We evaluated an augmented reality (AR) setup under development for preoperative perforator vessel mapping for elective autologous breast reconstruction.MethodsIn this grant-supported research pilot, we used magnetic resonance angiography data (MR-A) of the trunk to superimpose the scans on the corresponding patients with hands-free AR goggles to identify regions-of-interest for surgical planning. Perforator location was assessed using MR-A imaging (MR-A projection) and Doppler ultrasound data (3D distance) and confirmed intraoperatively in all cases. We evaluated usability (System Usability Scale, SUS), data transfer load and documented personnel hours for software development, correlation of image data, as well as processing duration to clinical readiness (time from MR-A to AR projections per scan).ResultsAll perforator locations were confirmed intraoperatively, and we found a strong correlation between MR-A projection and 3D distance measurements (Spearman r = 0.894). The overall usability (SUS) was 67 ± 10 (=moderate to good). The presented setup for AR projections took 173 min to clinical readiness (=availability on AR device per patient).ConclusionIn this pilot, we calculated development investments based on project-approved grant-funded personnel hours with a moderate to good usability outcome resulting from some limitations: assessment was based on one-time testing with no previous training, a time lag of AR visualizations on the body and difficulties in spatial AR orientation. The use of AR systems can provide new opportunities for future surgical planning, but has more potential for educational (e.g., patient information) or training purposes of medical under- and postgraduates (spatial recognition of imaging data associated with anatomical structures and operative planning). We expect future usability improvements with refined user interfaces, faster AR hardware and artificial intelligence-enhanced visualization techniques.
Citation: DIGITAL HEALTH
PubDate: 2023-05-08T04:13:10Z
DOI: 10.1177/20552076231173554
Issue No: Vol. 9 (2023)
- Mental health support for and telehealth use by Australians living with
borderline personality disorder during the onset of the COVID-19 pandemic:
A national study
Authors: Parvaneh Heidari, Jillian H Broadbear, Rita Brown, Nitin P Dharwadkar, Sathya Rao
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo investigate mental health service use and telehealth experience of people living with BPD in Australia during the first year of the COVID-19 pandemic.MethodsAn online survey was used to collect data from people who self-identified with a diagnosis of BPD.ResultsOne hundred and sixty-nine survey responses were included in the analysis. More than half of participants acknowledged receiving information from their health service about resources that they could use if they become distressed. More than 70% of participants used telehealth for receiving mental health services; the majority used telehealth to consult a psychologist or to obtain prescriptions. Telehealth sessions were conducted over the phone, via videoconferencing, or using a mix of the two. While using telehealth, some participants found it more difficult to control their impulses to self-harm, to express thoughts about self-harm and suicide, to control feelings of anger, and to establish and maintain agreed treatment boundaries. Thematic analysis of participants’ experiences of telehealth identified five main themes: Communication challenges, Technology challenges, Privacy concerns, Benefits of telehealth, and Personal preferences.ConclusionThe study findings revealed a variety of positive and negative consumer experiences. While the majority of participants found telehealth somewhat benefitted their mental health, challenges were also reported which raise concerns about the broader utility and effectiveness of telehealth.
Citation: DIGITAL HEALTH
PubDate: 2023-05-05T05:36:56Z
DOI: 10.1177/20552076231169824
Issue No: Vol. 9 (2023)
- Bibliometric and visualized analysis of research relating to minimally
invasive spine surgery reported over the period 2000–2022
Authors: Rui Weng, Dong-Xin Lin, Yu-Ke Song, Hai-Wei Guo, Wen-Sheng Zhang, Xiao-Ming He, Wen-Chao Li, Hong-Heng Lin, Min-Cong He, Qiu-Shi Wei
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundSince entering the 21st century, there has been an increasing interest in minimally invasive surgery for spinal diseases, which has led to the continued development of minimally invasive spine surgery (MISS), with major breakthroughs in technology and technical skills. However, in recent years, there is little relevant research using bibliometrics to analyze the field of MISS research. The purpose of this study is to sort out the publication situation and topic trends of articles in the field of MISS research from the perspective of bibliometrics.MethodsThe articles and reviews related to MISS from 2000 to 2022 were retrieved and downloaded from the Web of Science Core Collection (WOSCC). Visualization and knowledge mapping were performed using three bibliometric tools, including online bibliometric platform, CiteSpace and VOSviewer software. Curve fitting and correlation analysis were performed using Microsoft Excel software. The global research publication output, contributions of countries, institutions, authors, and journals, average citations per item (ACI), Hirsch index (H-index), research hot keywords, etc., in this field were analyzed.ResultsA total of 2384 papers were retrieved, including 2135 original papers and 249 review papers. In the past 22 years, the number of annual publications of MISS research has shown a steady growth trend. China contributed the most papers, and the United States ranked second, but the United States had the highest total citations, and H-index value. The most prolific institutions were Soochow University, Capital Medical University and Wooridul Spine Hospital. In this field, Professors Lee SH, Ahn Y and Yang HL have made significant achievements. However, there is relatively little international collaboration between institutions or researchers. World Neurosurgery is the most published journal on MISS research. According to the keyword co-occurrence analysis, recent keywords mainly focus on researches on minimally invasive modalities, techniques and prognosis, while on the keyword analysis of the ongoing bursts, percutaneous transforaminal endoscopic discectomy, lumbar diskectomy, spinal stenosis, recompression, diskectomy, endoscopic spine surgery, laminectomy, transforaminal lumbar interbody fusion, etc., will likely continue to be a research hotspot in the near future.ConclusionLooking at the temporal trend in the number of publications per year, the number of publications for the MISS study will increase in the near future. China has the highest number of publications, but the US has the highest quality publications. International cooperation needs to be further strengthened. Our findings can provide useful information for the academic community and identify possible research fronts and hotspots in the coming years.
Citation: DIGITAL HEALTH
PubDate: 2023-05-05T05:03:13Z
DOI: 10.1177/20552076231173562
Issue No: Vol. 9 (2023)
- Mental distress and virtual mental health resource use amid the COVID-19
pandemic: Findings from a cross-sectional study in Canada
Authors: Trevor Goodyear, Chris Richardson, Bilal Aziz, Allie Slemon, Anne Gadermann, Zachary Daly, Corey McAuliffe, Javiera Pumarino, Kimberly C Thomson, Emily K Jenkins
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveThis paper characterizes levels of mental distress among adults living in Canada amid the COVID-19 pandemic and examines the extent of virtual mental health resource use, including reasons for non-use, among adults with moderate to severe distress.MethodsData are drawn from a cross-sectional monitoring survey (29 November to 7 December 2021) on the mental health of adults (N = 3030) in Canada during the pandemic. Levels of mental distress were assessed using the Kessler Psychological Distress Scale. Descriptive statistics were used to examine virtual mental health resource use among participants with moderate to severe distress, including self-reported reasons for non-use.ResultsLevels of mental distress were classified as none to low (48.8% of participants), moderate (36.6%), and severe (14.6%). Virtual mental health resource use was endorsed by 14.2% of participants with moderate distress and 32% of those with severe distress. Participants with moderate to severe distress reported a range of reasons for not using virtual mental health resources, including not feeling as though they needed help (37.4%), not thinking the supports would be helpful (26.2%), and preferring in-person supports (23.4%), among other reasons.ConclusionsThis study identified a high burden of mental distress among adults in Canada during the COVID-19 pandemic alongside an apparent mismatch between actual and perceived need for support, including through virtual mental health resources. Findings on virtual mental health resource use, and reasons for non-use, offer directions for mental health promotion and health communication related to mental health literacy and the awareness and appropriateness of virtual mental health resources.
Citation: DIGITAL HEALTH
PubDate: 2023-05-05T05:01:53Z
DOI: 10.1177/20552076231173528
Issue No: Vol. 9 (2023)
- Multilevel modeling of unintended current pregnancy: In the case of
Ethiopian Demographic and Health Survey, 2016
Authors: Belete A Wobse, Tezera A Gashaw
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundUnintended pregnancy has been a major public health and reproductive health issue imposing a great adverse consequence on the mother and child. However, estimates of unintended pregnancy through the appropriate model are lacking. This study is aimed at modeling and assessing the extent of variation and factors associated with unintended pregnancy among women in Ethiopia.MethodsA cross-sectional study was conducted based on 2016 Ethiopian Demographic and Health Survey data related to the reproductive health of 1122 currently pregnant women and a multilevel modeling approach was used.ResultsThe proportion of unintended current pregnancies was 20.1%. According to random intercept with a fixed slope model, women who had 1 to 3 living children and those who had 4 and above were more likely to be unintended (OR = 3.54, 95% CI: 1.985–6.332) and (OR = 5.47, 95% CI: 2.67–11.227), respectively, compared to women with no living children. Also, married women were less likely to be unintended (OR = 0.14, 95% CI: 0.065–0.304) compared to unmarried women. In addition, women having work were more likely to be unintended (OR = 1.56, 95% CI: 1.079–2.255). Furthermore, women who intend to use contraceptive methods were less likely to be unintended (OR = 0.54, 95% CI: 0.362–0.796) compared to women who do not intend.ConclusionThe number of living children, current marital status, the intention of contraceptive use, and respondents’ working status were found to have a significant effect. Giving attention to regional variations and intention of contraceptive use is important to reduce unintended current pregnancies in Ethiopia.
Citation: DIGITAL HEALTH
PubDate: 2023-05-05T05:00:54Z
DOI: 10.1177/20552076231173306
Issue No: Vol. 9 (2023)
- The usability testing of the integrated electronic healthcare services for
diabetes mellitus patients during the pandemic in Indonesia
Authors: Najmiatul Fitria, Lusiana Idrus, Ayuthya Rizky Putri, Yelly Oktavia Sari
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionDiabetes mellitus is a degenerative disease that obliges patients to take continuous healthcare services. During a pandemic situation, all access to healthcare facilities becomes limited. A web-based integrated electronic-healthcare system (IeHS) study was used to overcome this problem. This study aimed to describe patients’ ability to access and understand this web-based application.MethodAn observational study using a web-based IeHS took place in Muara Tebo, Indonesia, in 2021. A total of 82 outpatients with diabetes mellitus participated in this study. These patients belonged to local community-based diabetes mellitus. Only adult patients accustomed to using smartphones were invited to participate in this study. All participants were taught to access the web-based application through video recordings. They were asked to fill out the form regarding their understanding of the web-based integrated e-healthcare application. This form was sent online.ResultsFrom the calculation of the usability scale, the results show that patients have not been able to take advantage of this application in life (the system usability scale (SUS) score 63.38). There is no significant difference between patients’ characteristics and the SUS score.ConclusionParticipants’ condition in this study reflects the general state of outpatients. The ability of these participants to access an internet-based application was related to their education level. This condition becomes a challenge for policymakers to improve local human resources to increase their health literacy.
Citation: DIGITAL HEALTH
PubDate: 2023-05-04T05:31:31Z
DOI: 10.1177/20552076231173227
Issue No: Vol. 9 (2023)
- A comprehensive systematic review and content analysis of active video
game intervention research
Authors: Arlen C Moller, Caio V Sousa, Kelly J Lee, Dar Alon, Amy S Lu
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveIntervention research using digital games to promote physical activity has proliferated. Yet few studies have attempted to systematically catalog features that characterize this research. To address this gap, we undertook a systematic review and content analysis of active video game interventions, examining only published longitudinal interventions that prominently featured active video game technology (≥50% of the intervention).MethodsOur protocol was registered in the International Prospective Register of Systematic Reviews (CRD42020204191). For inclusion, an active video game intervention had to require gross movement beyond finger movement, and target improvement, maintenance, or recovery of health. The intervention design had to include at least two conditions, within- or between-subjects, with ≥10 participants per condition to examine the chronic effects of active video game exposure.ResultsThe search resulted in 232 studies published in English between 1996 and 2020. The majority of active video game interventions (69.8%) targeted physical fitness (physiological functioning as a consequence of physical activity), followed by cognitive performance (11.3%), physical activity (5.5%), or a mixture of those outcomes (13.4%). Total enrollment across all studies was 14,849 participants (MParticipants = 62, SD = 106; MAge = 50.2, SD = 25.2 years; 47.3% men). A strong majority of the samples (69.8%) were recruited from medical subpopulations, and only 30.2% were recruited from the general (healthy) population. A strong majority of active video games (72.0%) were developed by industry for the commercial market, and only 13.3% were funded by government or foundation grants.ConclusionsSuggested directions for improving future active video game development and intervention research include greater consideration of promising features (social connectedness, novelty, narrative, rhythmic movement to music) and new models for productive collaboration between industry and academia.
Citation: DIGITAL HEALTH
PubDate: 2023-05-04T05:31:02Z
DOI: 10.1177/20552076231171232
Issue No: Vol. 9 (2023)
- Digital technology use, technological self-efficacy, and subjective
well-being among North Korean migrants during the COVID-19 pandemic:
Moderated moderation
Authors: Nari Yoo, Sou Hyun Jang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Using digital technology to adapt to their host country is an integral part of social inclusion for migrant and refugee populations. However, researchers have not empirically examined how digital technology use may affect subjective well-being among migrant populations. This study aimed to examine the association between increased digital technology use, technological self-efficacy, and subjective well-being. Using the 2020 Digital Divide Survey in Korea, our sample consists of 6520 native South Koreans and 699 North Korean migrants aged 18 years and older. We examined the three-way interaction of technological self-efficacy and being North Korean migrants in the relationship between the increase in the use of five types of digital technology, technological self-efficacy, and subjective well-being, using hierarchical linear regressions. North Korean migrants were statistically lower than South Korean natives in all types of increased digital technology use. Moderation analysis showed that technological self-efficacy positively moderated the relationship between increased digital technology use and subjective well-being. A three-way interaction showed that this relationship was stronger in North Korean migrants for three types of utilization, networking, information sharing, and life services. Considering the potential benefits of technological self-efficacy for North Korean migrants and what psychosocial digital technology education would be considered.
Citation: DIGITAL HEALTH
PubDate: 2023-05-04T05:13:02Z
DOI: 10.1177/20552076231171503
Issue No: Vol. 9 (2023)
- The role of mobile health in prevention, diagnosis, treatment and
self-care of COVID-19 from the healthcare professionals’ perspectives
Authors: Mahdieh Montazeri, Zahra Galavi, Leila Ahmadian
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
BackgroundTo facilitate disease management, understanding the attitude of healthcare professionals regarding the use of this tool can help mobile health (mHealth) program developers develop appropriate interventions.AimsTo assess the perspective of healthcare professionals regarding the contribution of mobile-based interventions in the prevention, diagnosis, self-care, and treatment (PDST) of COVID-19.MethodsThis is a survey study conducted in 2020 in Iran with 81 questions. In this study mHealth functionalities were categorized into four dimensions including innovative, monitoring and screening, remote services, and education and decision-making. The data were analyzed using descriptive statistics, ANOVA, and the Kruskal–Wallis test to compare the attitudes of the different job groups.ResultsIn total, 123 providers participated, and 87.4% of them reported that mHealth technology is moderate to most helpful for the management of COVID-19. Healthcare professionals believed that mHealth technology could be most helpful in self-care and least helpful in the diagnosis of COVID-19. Regarding the functionalities of the mobile application, the results showed that the use of patient decision aids can be most helpful in self-care and the use of computer games can be least helpful in treatment. The participants believed that mHealth is more effective in monitoring and screening dimensions and less effective in providing remote services.ConclusionsThis study showed that healthcare professionals believed that mHealth technology could have a better contribution to self-care for patients with COVID-19. Therefore, it is better to plan and invest more in the field of self-care to help patients to combat COVID-19. The results of this study revealed which mhealth functionalities work better in four domains of prevention, treatment, self-care, and diagnosis of COVID-19. This can help healthcare authorities to implement appropriate IT-based interventions to combat COVID-19.
Citation: DIGITAL HEALTH
PubDate: 2023-05-02T07:35:54Z
DOI: 10.1177/20552076231171969
Issue No: Vol. 9 (2023)
- An artificial intelligence-based chatbot for prostate cancer education:
Design and patient evaluation study
Authors: Magdalena Görtz, Kilian Baumgärtner, Tamara Schmid, Marc Muschko, Philipp Woessner, Axel Gerlach, Michael Byczkowski, Holger Sültmann, Stefan Duensing, Markus Hohenfellner
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
IntroductionArtificial intelligence (AI) is increasingly used in healthcare. AI-based chatbots can act as automated conversational agents, capable of promoting health and providing education at any time. The objective of this study was to develop and evaluate a user-friendly medical chatbot (prostate cancer communication assistant (PROSCA)) for provisioning patient information about early detection of prostate cancer (PC).MethodsThe chatbot was developed to provide information on prostate diseases, diagnostic tests for PC detection, stages, and treatment options. Ten men aged 49 to 81 years with suspicion of PC were enrolled in this study. Nine of ten patients used the chatbot during the evaluation period and filled out the questionnaires on usage and usability, perceived benefits, and potential for improvement.ResultsThe chatbot was straightforward to use, with 78% of users not needing any assistance during usage. In total, 89% of the chatbot users in the study experienced a clear to moderate increase in knowledge about PC through the chatbot. All study participants who tested the chatbot would like to re-use a medical chatbot in the future and support the use of chatbots in the clinical routine.ConclusionsThrough the introduction of the chatbot PROSCA, we created and evaluated an innovative evidence-based health information tool in the field of PC, allowing targeted support for doctor–patient communication and offering great potential in raising awareness, patient education, and support. Our study revealed that a medical chatbot in the field of early PC detection is readily accepted and benefits patients as an additional informative tool.
Citation: DIGITAL HEALTH
PubDate: 2023-05-02T07:05:34Z
DOI: 10.1177/20552076231173304
Issue No: Vol. 9 (2023)
- User experience evaluation of a 3D virtual reality educational program for
illegal drug use prevention among high school students: Applying the
decomposed theory of planned behavior
Authors: Jong-Long Guo, Ying-Chieh Chang, Fen-He Lin, Ching-Chih Fan, Tzu-Ming Lai, Chiu-Mieh Huang
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo evaluate user acceptability of an immersive three-dimensional virtual reality program for preventing illegal drug use and identify factors associated with continuous usage intention of three-dimensional virtual reality learning among high school students based on the decomposed theory of planned behavior.MethodsIn this cross-sectional observational study, we developed five educational modules and serious games based on three-dimensional virtual reality technology. Ninety student-participants’ experiences were assessed by a structured questionnaire based on the decomposed theory of planned behavior variables. We applied partial least squares structural equation modeling to examine the correlates of continuous usage intention.ResultsThe proposed model demonstrated an acceptable fit to the observed data. Eight of the 11 hypotheses based on the decomposed theory of planned behavior were supported. Continuous usage intention was significantly associated with attitudes, subjective norms, and perceived behavioral control; these variables explained 55.4% of the variance in continuous usage intention. Perceived usefulness and compatibility were significant antecedents of attitude. The significant antecedent of subjective norms was support from school staff. Self-efficacy and resource-facilitating conditions were significant antecedents of perceived behavioral control.ConclusionsOur findings support the applicability of the decomposed theory of planned behavior as a framework for evaluating a three-dimensional virtual reality program for illegal drug use. We recommend that the program be included as teaching material for illegal drug prevention education in senior high schools.
Citation: DIGITAL HEALTH
PubDate: 2023-05-02T07:04:35Z
DOI: 10.1177/20552076231171237
Issue No: Vol. 9 (2023)
- Development of a video-based evidence synthesis knowledge translation
resource: Drawing on a user-centred design approach
Authors: Cristian Deliv, Declan Devane, El Putnam, Patricia Healy, Amanda Hall, Sarah Rosenbaum, Elaine Toomey
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesWe aimed to develop a video animation knowledge translation (KT) resource to explain the purpose, use and importance of evidence synthesis to the public regarding healthcare decision-making.MethodsWe drew on a user-centred design approach to develop a spoken animated video (SAV) by conducting two cycles of idea generation, prototyping, user testing, analysis, and refinement. Six researchers identified the initial key messages of the SAV and informed the first draft of the storyboard and script. Seven members of the public provided input on this draft and the key messages through think-aloud interviews, which we used to develop an SAV prototype. Seven additional members of the public participated in think-aloud interviews while watching the video prototype. All members of the public also completed a questionnaire on perceived usefulness, desirability, clarity and credibility. We subsequently synthesised all data to develop the final SAV.ResultsResearchers identified the initial key messages as 1) the importance of evidence synthesis, 2) what an evidence synthesis is and 3) how evidence synthesis can impact healthcare decision-making. Members of the public rated the initial video prototype as 9/10 for usefulness, 8/10 for desirability, 8/10 for clarity and 9/10 for credibility. Using their guidance and feedback, we produced a three-and-a-half-minute video animation. The video was uploaded on YouTube, has since been translated into two languages, and viewed over 12,000 times to date.ConclusionsDrawing on user-centred design methods provided a structured and transparent approach to the development of our SAV. Involving members of the public enhanced the credibility and usefulness of the resource. Future work could explore involving the public from the outset to identify key messages in developing KT resources explaining methodological topics. This study describes the systematic development of a KT resource with limited resources and provides transferrable learnings for others wishing to do similar.
Citation: DIGITAL HEALTH
PubDate: 2023-05-02T05:18:50Z
DOI: 10.1177/20552076231170696
Issue No: Vol. 9 (2023)
- Rationale and design of the SenseWhy project: A passive sensing and
ecological momentary assessment study on characteristics of overeating
episodes
Authors: Nabil I. Alshurafa, Tammy K. Stump, Christopher S. Romano, Angela F. Pfammatter, Annie W. Lin, Josiah Hester, Donald Hedeker, Evan Forman, Bonnie Spring
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectivesOvereating interventions and research often focus on single determinants and use subjective or nonpersonalized measures. We aim to (1) identify automatically detectable features that predict overeating and (2) build clusters of eating episodes that identify theoretically meaningful and clinically known problematic overeating behaviors (e.g., stress eating), as well as new phenotypes based on social and psychological features.MethodUp to 60 adults with obesity in the Chicagoland area will be recruited for a 14-day free-living observational study. Participants will complete ecological momentary assessments and wear 3 sensors designed to capture features of overeating episodes (e.g., chews) that can be visually confirmed. Participants will also complete daily dietitian-administered 24-hour recalls of all food and beverages consumed.AnalysisOvereating is defined as caloric consumption exceeding 1 standard deviation of an individual's mean consumption per eating episode. To identify features that predict overeating, we will apply 2 complementary machine learning methods: correlation-based feature selection and wrapper-based feature selection. We will then generate clusters of overeating types and assess how they align with clinically meaningful overeating phenotypes.ConclusionsThis study will be the first to assess characteristics of eating episodes in situ over a multiweek period with visual confirmation of eating behaviors. An additional strength of this study is the assessment of predictors of problematic eating during periods when individuals are not on a structured diet and/or engaged in a weight loss intervention. Our assessment of overeating episodes in real-world settings is likely to yield new insights regarding determinants of overeating that may translate into novel interventions.
Citation: DIGITAL HEALTH
PubDate: 2023-04-28T05:10:42Z
DOI: 10.1177/20552076231158314
Issue No: Vol. 9 (2023)
- Screen time, phone usage, and social media usage: Before and during the
COVID-19 pandemic
Authors: Claire Voss, Phoebe Shorter, Jessica Mueller-Coyne, Katherine Turner
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTechnology use has increased in the past several years, especially among younger generations. The COVID-19 pandemic drastically changed how people work, learn, and interact, with many utilizing technology for daily tasks and socializing.MethodsThe current study investigated a sample of college students using a cross-sectional design to determine whether there was a change in how much time students spent on screens, phones, and social media.ResultsFindings indicated that time on screens and phones was significantly higher during the pandemic; however, time spent on social media did not differ significantly.ConclusionThese findings suggest that students are spending more time working and socializing on their screens and phones, yet social media may not be the platform in which students are doing this. Future studies should further explore technology usage and whether these trends during the COVID-19 pandemic will be lasting.
Citation: DIGITAL HEALTH
PubDate: 2023-04-27T05:35:07Z
DOI: 10.1177/20552076231171510
Issue No: Vol. 9 (2023)
- Association of multimorbidity with the use of health information
technology
Authors: Sydney E Manning, Hao Wang, Nilanjana Dwibedi, Chan Shen, R Constance Wiener, Patricia A Findley, Sophie Mitra, Usha Sambamoorthi
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveTo examine the association of multimorbidity with health information technology use among adults in the USA.MethodsWe used cross-sectional study design and data from the Health Information National Trends Survey 5 Cycle 4. Health information technology use was measured with ten variables comprising access, recent use, and healthcare management. Unadjusted and adjusted logistic and multinomial logistic regressions were used to model the associations of multimorbidity with health information technology use.ResultsAmong adults with multimorbidity, health information technology use for specific purposes ranged from 37.8% for helping make medical decisions to 51.7% for communicating with healthcare providers. In multivariable regressions, individuals with multimorbidity were more likely to report general use of health information technology (adjusted odds ratios = 1.48, 95% confidence intervals = 1.01–2.15) and more likely to use health information technology to check test results (adjusted odds ratios = 1.85, 95% confidence intervals = 1.33–2.58) compared to adults with only one chronic condition, however, there were no significant differences in other forms of health information technology use. We also observed interactive associations of multimorbidity and age on various components of health information technology use. Compared to younger adults with multimorbidity, older adults (≥ 65 years of age) with multimorbidity were less likely to use almost all aspects of health information technology.ConclusionHealth information technology use disparities by age and multimorbidity were observed. Education and interventions are needed to promote health information technology use among older adults in general and specifically among older adults with multimorbidity.
Citation: DIGITAL HEALTH
PubDate: 2023-04-26T05:57:39Z
DOI: 10.1177/20552076231163797
Issue No: Vol. 9 (2023)
- Governing through big data: An ethnographic exploration of invisible lives
in China's digital surveillance of the coronavirus disease 2019 pandemic
Authors: Liyuan Zhang, Mohamed Y Rafiq
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
Introduction/BackgroundSince 2020, China has implemented unprecedented digital health surveillance over citizens and residents in response to the coronavirus disease 2019 pandemic. We explore the implementation of Health Code (jiankang ma), a contract-tracing and risk assessment app for coronavirus disease 2019, in China. By engaging with the concept of ‘ocular ethics’, we ask why and how some populations become invisible in China's Health Code surveillance system.MethodsThis study used an ethnographic approach to critically examine the role of digital technology in the coronavirus disease 2019 pandemic governance. Three months of participant observation and 20 interviews were conducted to understand the design of Health Code and the situation of homeless population.ResultsWe find that China's digital health surveillance during the coronavirus disease 2019 pandemic has failed to cover the homeless population, who either fail to access Health Code or find ways to avoid its mandatory health surveillance. We further summarize four problems resulting in their exclusion, including the loss of ID cards, access to smartphones and phone numbers, problematic design and elastic surveillance, and the neglect of homeless community's precarious living situation.ConclusionSituating our work in the literature on theories of surveillance and anthropology of pandemics, we argue that without recognizing the structural problems embedded in homelessness, a large number of poor and homeless migrants are rendered invisible in this data-driven health surveillance, which further pushes them into social exclusion.
Citation: DIGITAL HEALTH
PubDate: 2023-04-25T04:46:30Z
DOI: 10.1177/20552076231170689
Issue No: Vol. 9 (2023)
- The effect of the Ebe Evimde application on the self-efficacy and anxiety
levels of mothers: Randomized controlled trial
Authors: Merve Ayşe Bozkurt, Büşra Cesur
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
ObjectiveFamily health can be improved by making home visits with mobile applications. This study was carried out to evaluate the effect of a mobile application and web-based software called Ebe Evimde (My Home Midwife), which was designed by the researchers for use in the postpartum period, on mothers’ self-efficacy and anxiety levels.MethodsHome visits to 60 mothers in the intervention group, who are over 18 years of age, who have given birth at term, who have no complications in mother and baby, and who are in the second to fifth postpartum days, were made with the online home visits mobile support application Midwifery Home software and their self-efficacy and anxiety levels were evaluated. Mothers were divided into two groups as intervention (60) and control group (60) using a random number table.ResultsWhile there was a significant difference between the pretest and posttest self-efficacy levels of the intervention group, there was no difference between the pretest and posttest self-efficacy levels of the control group. When the groups obtained from the Postpartum Specific Anxiety Scale were examined, it was seen that there was a negative and very strong significant relationship between the pretest and posttest scores of the mothers in the intervention group, while when the relationship between the pretest and posttest scores of the mothers in the control group was examined; no significant relationship was observed.ConclusionThe practice of Ebe Evimde (My Home Midwife) had a positive effect on mothers’ self-efficacy and postpartum anxiety levels.
Citation: DIGITAL HEALTH
PubDate: 2023-04-25T04:46:10Z
DOI: 10.1177/20552076231169840
Issue No: Vol. 9 (2023)
- Using machine learning to modify and enhance the daily living
questionnaire
Authors: Peleg Panovka, Yaron Salman, Hagit Hel-Or, Sara Rosenblum, Joan Toglia, Naomi Josman, Tal Adamit
Abstract: DIGITAL HEALTH, Volume 9, Issue , January-December 2023.
The Daily Living Questionnaire (DLQ) constitutes one of a number of functional cognitive measures, commonly employed in a range of medical and rehabilitation settings. One of the drawbacks of the DLQ is its length which poses an obstacle to conducting efficient and widespread screening of the public and which incurs inaccuracies due to the length and fatigue of the subjects.ObjectiveThis study aims to use Machine Learning (ML) to modify and abridge the DLQ without compromising its fidelity and accuracy.MethodParticipants were interviewed in two separate research studies conducted in the United States of America and Israel, and one unified file was created for ML analysis. An ML-based Computerized Adaptive Testing (ML-CAT) algorithm was applied to the DLQ database to create an adaptive testing instrument—with a shortened test form adapted to individual test scores.ResultsThe ML-CAT approach was shown to reduce the number of tests required on average by 25% per individual when predicting each of the seven DLQ output scores independently and reduce by over 50% when predicting all seven scores concurrently using a single model. These results maintained an accuracy of 95% (5% error) across subject scores. The study pinpoints which DLQ items are more informative in predicting DLQ scores.ConclusionsApplying the ML-CAT model can thus serve to modify, refine and even abridge the current DLQ, thereby enabling wider community screening while also enhancing clinical and research utility.
Citation: DIGITAL HEALTH
PubDate: 2023-04-25T04:44:11Z
DOI: 10.1177/20552076231169818
Issue No: Vol. 9 (2023)
- Temporal processing deficit in children and adolescents wit