Subjects -> HEALTH AND SAFETY (Total: 1464 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (87 journals)
    - HEALTH AND SAFETY (686 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (358 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (112 journals)
    - PHYSICAL FITNESS AND HYGIENE (117 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH AND SAFETY (686 journals)                  1 2 3 4 | Last

Showing 1 - 200 of 203 Journals sorted alphabetically
16 de Abril     Open Access   (Followers: 1)
ACM Transactions on Computing for Healthcare     Hybrid Journal  
Acta Scientiarum. Health Sciences     Open Access   (Followers: 2)
Adultspan Journal     Hybrid Journal   (Followers: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 11)
Advances in Public Health     Open Access   (Followers: 33)
Adversity and Resilience Science : Journal of Research and Practice     Hybrid Journal   (Followers: 3)
African Health Sciences     Open Access   (Followers: 7)
African Journal of Health Professions Education     Open Access   (Followers: 7)
Afrimedic Journal     Open Access   (Followers: 3)
Ageing & Society     Hybrid Journal   (Followers: 40)
Aging and Health Research     Open Access   (Followers: 5)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 9)
AJOB Empirical Bioethics     Hybrid Journal   (Followers: 3)
Akademika     Open Access  
American Journal of Family Therapy     Hybrid Journal   (Followers: 8)
American Journal of Health Economics     Full-text available via subscription   (Followers: 26)
American Journal of Health Education     Hybrid Journal   (Followers: 36)
American Journal of Health Promotion     Hybrid Journal   (Followers: 23)
American Journal of Health Sciences     Open Access   (Followers: 11)
American Journal of Health Studies     Full-text available via subscription   (Followers: 16)
American Journal of Preventive Medicine     Hybrid Journal   (Followers: 33)
American Journal of Public Health     Full-text available via subscription   (Followers: 225)
American Journal of Public Health Research     Open Access   (Followers: 33)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 9)
Annali dell'Istituto Superiore di Sanità     Open Access  
Annals of Global Health     Open Access   (Followers: 10)
Annals of Health Law     Open Access   (Followers: 7)
Applied Biosafety     Hybrid Journal   (Followers: 2)
Applied Ergonomics     Hybrid Journal   (Followers: 18)
Apuntes Universitarios     Open Access   (Followers: 2)
Archives of Community Medicine and Public Health     Open Access   (Followers: 2)
Archives of Medicine and Health Sciences     Open Access   (Followers: 7)
Archives of Suicide Research     Hybrid Journal   (Followers: 13)
Archivos de Prevención de Riesgos Laborales     Open Access  
ASA Monitor     Full-text available via subscription   (Followers: 17)
Asia Pacific Journal of Counselling and Psychotherapy     Hybrid Journal   (Followers: 7)
Asia Pacific Journal of Health Management     Full-text available via subscription   (Followers: 4)
Asia-Pacific Journal of Public Health     Hybrid Journal   (Followers: 12)
Asian Journal of Gambling Issues and Public Health     Open Access   (Followers: 5)
Asian Journal of Medicine and Health     Open Access   (Followers: 1)
Asian Journal of Population Sciences     Open Access   (Followers: 8)
Asian Journal of Social Health and Behavior     Open Access   (Followers: 2)
Atención Primaria     Open Access   (Followers: 2)
Atención Primaria Práctica     Open Access   (Followers: 1)
Australasian Journal of Paramedicine     Open Access   (Followers: 9)
Australian Advanced Aesthetics     Full-text available via subscription   (Followers: 5)
Australian Family Physician     Full-text available via subscription   (Followers: 2)
Australian Indigenous HealthBulletin     Free   (Followers: 5)
Autism & Developmental Language Impairments     Open Access   (Followers: 18)
Bijzijn XL     Hybrid Journal  
Biograph-I : Journal of Biostatistics and Demographic Dynamic     Open Access   (Followers: 4)
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 7)
Biosafety and Health     Open Access  
Biosalud     Open Access  
Birat Journal of Health Sciences     Open Access  
BLDE University Journal of Health Sciences     Open Access   (Followers: 1)
BMC Oral Health     Open Access   (Followers: 5)
BMC Pregnancy and Childbirth     Open Access   (Followers: 20)
Brazilian Journal of Medicine and Human Health     Open Access  
British Journal of Health Psychology     Hybrid Journal   (Followers: 56)
Buletin Penelitian Kesehatan     Open Access  
Buletin Penelitian Sistem Kesehatan     Open Access  
Cadernos de Educação, Saúde e Fisioterapia     Open Access  
Cadernos de Saúde     Open Access  
Cambridge Quarterly of Healthcare Ethics     Hybrid Journal   (Followers: 13)
Canadian Family Physician     Partially Free   (Followers: 14)
Canadian Journal of Community Mental Health     Full-text available via subscription   (Followers: 16)
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 1)
Canadian Journal of Public Health     Hybrid Journal   (Followers: 30)
Cannabis and Cannabinoid Research     Hybrid Journal   (Followers: 2)
Carta Comunitaria     Open Access  
Case Reports in Women's Health     Open Access   (Followers: 4)
CASUS : Revista de Investigación y Casos en Salud     Open Access  
Central Asian Journal of Global Health     Open Access   (Followers: 2)
CES Medicina     Open Access  
CES Salud Pública     Open Access  
Child and Adolescent Obesity     Open Access   (Followers: 8)
Child's Nervous System     Hybrid Journal  
Childhood Obesity and Nutrition     Open Access   (Followers: 12)
Children     Open Access  
Chinese Journal of Physiology     Open Access   (Followers: 1)
CHRISMED Journal of Health and Research     Open Access   (Followers: 1)
Christian Journal for Global Health     Open Access   (Followers: 1)
Ciencia & Salud     Open Access  
Ciencia & Trabajo     Open Access  
Ciencia e Innovación en Salud     Open Access  
Ciencia y Cuidado     Open Access   (Followers: 1)
Ciencia y Salud     Open Access   (Followers: 1)
Ciencia, Tecnología y Salud     Open Access  
Cities & Health     Hybrid Journal   (Followers: 5)
Cleaner and Responsible Consumption     Open Access  
Clinical and Experimental Health Sciences     Open Access   (Followers: 1)
ClinicoEconomics and Outcomes Research     Open Access   (Followers: 1)
Clocks & Sleep     Open Access   (Followers: 2)
CME     Hybrid Journal   (Followers: 1)
Community Health     Open Access   (Followers: 6)
Conflict and Health     Open Access   (Followers: 8)
Contact (CTC)     Open Access   (Followers: 1)
Contraception and Reproductive Medicine     Open Access   (Followers: 2)
Cuaderno de investigaciones: semilleros andina     Open Access  
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 11)
Current Opinion in Environmental Science & Health     Hybrid Journal  
D Y Patil Journal of Health Sciences     Open Access   (Followers: 3)
Das österreichische Gesundheitswesen ÖKZ     Hybrid Journal   (Followers: 2)
Day Surgery Australia     Full-text available via subscription   (Followers: 2)
Design for Health     Hybrid Journal   (Followers: 1)
Digital Health     Open Access   (Followers: 10)
Disaster Medicine and Public Health Preparedness     Hybrid Journal   (Followers: 12)
Discover Social Science and Health     Open Access   (Followers: 17)
Diversity and Equality in Health and Care     Open Access   (Followers: 10)
Diversity of Research in Health Journal     Open Access   (Followers: 1)
Dramatherapy     Hybrid Journal   (Followers: 2)
Drogues, santé et société     Open Access   (Followers: 2)
Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi / Journal of Duzce University Health Sciences Institute     Open Access  
Early Childhood Research Quarterly     Hybrid Journal   (Followers: 26)
East African Journal of Public Health     Full-text available via subscription   (Followers: 3)
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity     Hybrid Journal   (Followers: 23)
EcoHealth     Hybrid Journal   (Followers: 6)
Education for Health     Open Access   (Followers: 9)
Egyptian Journal of Nutrition and Health     Open Access   (Followers: 8)
Egyptian Journal of Occupational Medicine     Open Access   (Followers: 6)
electronic Journal of Health Informatics     Open Access   (Followers: 7)
ElectronicHealthcare     Full-text available via subscription   (Followers: 2)
Emerging Trends in Drugs, Addictions, and Health     Open Access   (Followers: 2)
Ensaios e Ciência : Ciências Biológicas, Agrárias e da Saúde     Open Access  
Environmental Disease     Open Access   (Followers: 3)
Environmental Sciences Europe     Open Access   (Followers: 2)
Epidemics     Open Access   (Followers: 7)
EsSEX : Revista Científica     Open Access  
Estudios sociales : Revista de alimentación contemporánea y desarrollo regional     Open Access  
Ethics & Human Research     Hybrid Journal   (Followers: 4)
Ethics, Medicine and Public Health     Full-text available via subscription   (Followers: 8)
Ethiopian Journal of Health Development     Open Access   (Followers: 7)
Ethiopian Journal of Health Sciences     Open Access   (Followers: 6)
Ethnicity & Health     Hybrid Journal   (Followers: 17)
Eurasian Journal of Health Technology Assessment     Open Access   (Followers: 1)
EUREKA : Health Sciences     Open Access  
European Journal of Health Communication     Open Access  
European Journal of Investigation in Health, Psychology and Education     Open Access   (Followers: 5)
European Medical, Health and Pharmaceutical Journal     Open Access   (Followers: 2)
Evaluation & the Health Professions     Hybrid Journal   (Followers: 11)
Evidência - Ciência e Biotecnologia - Interdisciplinar     Open Access  
Exploratory Research in Clinical and Social Pharmacy     Open Access   (Followers: 4)
Expressa Extensão     Open Access  
F&S Reports     Open Access   (Followers: 2)
Face à face     Open Access  
Families, Systems, & Health     Full-text available via subscription   (Followers: 9)
Family & Community Health     Hybrid Journal   (Followers: 12)
Family Medicine and Community Health     Open Access   (Followers: 8)
Family Relations     Partially Free   (Followers: 12)
FASEB BioAdvances     Open Access   (Followers: 2)
Fatigue : Biomedicine, Health & Behavior     Hybrid Journal   (Followers: 3)
Finnish Journal of eHealth and eWelfare : Finjehew     Open Access  
Food and Public Health     Open Access   (Followers: 11)
Food Hydrocolloids for Health     Open Access  
Food Quality and Safety     Open Access   (Followers: 2)
Frontiers in Digital Health     Open Access   (Followers: 4)
Frontiers in Neuroergonomics     Open Access  
Frontiers in Public Health     Open Access   (Followers: 8)
Frontiers of Health Services Management     Partially Free   (Followers: 7)
Gaceta Sanitaria     Open Access   (Followers: 2)
Galen Medical Journal     Open Access  
Ganesha Journal     Open Access  
Gazi Sağlık Bilimleri Dergisi     Open Access  
Geospatial Health     Open Access   (Followers: 1)
Gestão e Desenvolvimento     Open Access  
Gesundheitsökonomie & Qualitätsmanagement     Hybrid Journal   (Followers: 7)
Giornale Italiano di Health Technology Assessment     Full-text available via subscription  
Global Advances in Health and Medicine     Open Access  
Global Challenges     Open Access   (Followers: 2)
Global Health : Science and Practice     Open Access   (Followers: 7)
Global Health Annual Review     Open Access   (Followers: 2)
Global Health Innovation     Open Access   (Followers: 4)
Global Health Journal     Open Access   (Followers: 2)
Global Health Promotion     Hybrid Journal   (Followers: 16)
Global Journal of Health Science     Open Access   (Followers: 6)
Global Journal of Public Health     Open Access   (Followers: 16)
Global Medical & Health Communication     Open Access   (Followers: 1)
Global Mental Health     Open Access   (Followers: 13)
Global Reproductive Health     Open Access   (Followers: 1)
Global Security : Health, Science and Policy     Open Access   (Followers: 1)
Global Transitions     Open Access   (Followers: 1)
Global Transitions Proceedings     Open Access   (Followers: 3)
Globalization and Health     Open Access   (Followers: 7)
Hacia la Promoción de la Salud     Open Access  
Hastane Öncesi Dergisi     Open Access  
Hastings Center Report     Hybrid Journal   (Followers: 7)
HCU Journal     Open Access  
HEADline     Hybrid Journal  
Health & Place     Hybrid Journal   (Followers: 23)
Health & Justice     Open Access   (Followers: 5)
Health : An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine     Hybrid Journal   (Followers: 21)
Health and Human Rights     Open Access   (Followers: 10)
Health and Social Care Chaplaincy     Hybrid Journal   (Followers: 10)
Health and Social Work     Hybrid Journal   (Followers: 64)
Health Behavior and Policy Review     Full-text available via subscription   (Followers: 5)
Health Behavior Research     Open Access   (Followers: 2)
Health Care Analysis     Hybrid Journal   (Followers: 13)
Health Equity     Open Access   (Followers: 4)

        1 2 3 4 | Last

Similar Journals
Journal Cover
Digital Health
Number of Followers: 10  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2055-2076 - ISSN (Online) 2055-2076
Published by Sage Publications Homepage  [1176 journals]
  • Identifying metabolic dysfunction-associated steatotic liver disease in
           patients with hypertension and pre-hypertension: An interpretable machine
           learning approach

    • Authors: Chen Chen, Wenkang Zhang, Gaoliang Yan, Chengchun Tang
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveMetabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent liver diseases and is associated with pre-hypertension and hypertension. Our research aims to develop interpretable machine learning (ML) models to accurately identify MASLD in hypertensive and pre-hypertensive populations.MethodsThe dataset for 4722 hypertensive and pre-hypertensive patients is from subjects in the NAGALA study. Six ML models, including the decision tree, K-nearest neighbor, gradient boosting, naive Bayes, support vector machine, and random forest (RF) models, were used in this study. The optimal model was constructed according to the performances of models evaluated by K-fold cross-validation (k = 5), the area under the receiver operating characteristic curve (AUC), average precision (AP), accuracy, sensitivity, specificity, and F1. Shapley additive explanation (SHAP) values were employed for both global and local interpretation of the model results.ResultsThe prevalence of MASLD in hypertensive and pre-hypertensive patients was 44.3% (362 cases) and 28.3% (1107 cases), respectively. The RF model outperformed the other five models with an AUC of 0.889, AP of 0.800, accuracy of 0.819, sensitivity of 0.816, specificity of 0.821, and F1 of 0.729. According to the SHAP analysis, the top five important features were alanine aminotransferase, body mass index, waist circumference, high-density lipoprotein cholesterol, and total cholesterol. Further analysis of the feature selection in the RF model revealed that incorporating all features leads to optimal model performance.ConclusionsML algorithms, especially RF algorithm, improve the accuracy of MASLD identification, and the global and local interpretation of the RF model results enables us to intuitively understand how various features affect the chances of MASLD in patients with hypertension and pre-hypertension.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-21T01:52:27Z
      DOI: 10.1177/20552076241233135
      Issue No: Vol. 10 (2024)
       
  • Objectives for algorithmic decision-making systems in childhood asthma:
           Perspectives of children, parents, and physicians

    • Authors: Omar Masrour, Johan Personnic, Flore Amat, Rola Abou Taam, Blandine Prevost, Guillaume Lezmi, Apolline Gonsard, Nadia Nathan, Alexandra Pirojoc, Christophe Delacourt, Stéphanie Wanin, David Drummond
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesTo identify with children, parents and physicians the objectives to be used as parameters for algorithmic decision-making systems (ADMSs) adapting treatments in childhood asthma.MethodsWe first conducted a qualitative study based on semi-structured interviews to explore the objectives that children aged 8–17 years, their parents, and their physicians seek to achieve when taking/giving/prescribing a treatment for asthma. Following the grounded theory approach, each interview was independently coded by two researchers; reconciled codes were used to assess code frequency, categories were defined, and the main objectives identified. We then conducted a quantitative study based on questionnaires using these objectives to determine how children/parents/physicians ranked these objectives and whether their responses were aligned.ResultsWe interviewed 71 participants (31 children, 30 parents and 10 physicians) in the qualitative study and identified seven objectives associated with treatment uptake and five objectives associated with treatment modalities. We included 291 participants (137 children, 137 parents, and 17 physicians) in the quantitative study. We found little correlation between child, parent, and physician scores for each of the objectives. Each child's asthma history influenced the choice of scores assigned to each objective by the child, parents, and physician.ConclusionThe identified objectives are quantifiable and relevant to the management of asthma in the short and long term. They can therefore be incorporated as parameters for future ADMS. Shared decision-making seems essential to achieve consensus among children, parents, and physicians when choosing the weight to assign to each of these objectives.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-21T01:51:48Z
      DOI: 10.1177/20552076241227285
      Issue No: Vol. 10 (2024)
       
  • Enhancing digital health services: A machine learning approach to
           personalized exercise goal setting

    • Authors: Ji Fang, Vincent CS Lee, Hao Ji, Haiyan Wang
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundThe utilization of digital health has increased recently, and these services provide extensive guidance to encourage users to exercise frequently by setting daily exercise goals to promote a healthy lifestyle. These comprehensive guides evolved from the consideration of various personalized behavioral factors. Nevertheless, existing approaches frequently neglect the users’ dynamic behavior and the changing in their health conditions.ObjectiveThis study aims to fill this gap by developing a machine learning algorithm that dynamically updates auto-suggestion exercise goals using retrospective data and realistic behavior trajectory.MethodsWe conducted a methodological study by designing a deep reinforcement learning algorithm to evaluate exercise performance, considering fitness-fatigue effects. The deep reinforcement learning algorithm combines deep learning techniques to analyze time series data and infer user's exercise behavior. In addition, we use the asynchronous advantage actor-critic algorithm for reinforcement learning to determine the optimal exercise intensity through exploration and exploitation. The personalized exercise data and biometric data used in this study were collected from publicly available datasets, encompassing walking, sports logs, and running.ResultsIn our study, we conducted the statistical analyses/inferential tests to compare the effectiveness of machine learning approach in exercise goal setting across different exercise goal-setting strategies. The 95% confidence intervals demonstrated the robustness of these findings, emphasizing the superior outcomes of the machine learning approach.ConclusionsOur study demonstrates the adaptability of machine learning algorithm to users’ exercise preferences and behaviors in exercise goal setting, emphasizing the substantial influence of goal design on service effectiveness.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-20T11:36:56Z
      DOI: 10.1177/20552076241233247
      Issue No: Vol. 10 (2024)
       
  • Validity of a video-analysis-based app to detect prefrailty or frailty
           plus sarcopenia syndromes in community-dwelling older adults: Diagnostic
           accuracy study

    • Authors: Alessio Montemurro, Juan J Rodríguez-Juan, María del Mar Martínez-García, Juan D Ruiz-Cárdenas
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesSarcopenia and frailty have been associated with an increased risk of suffering health-related adverse events but the combination of both conditions results in worse health-related outcomes than either condition alone. Since both syndromes are reversible states, their early detection is fundamental. This study aims to validate a video analysis-based App to detect the presence of frailty or prefrailty plus sarcopenia syndromes and to analyze its construct validity with health-related risk factors.MethodsA total of 686 community-dwelling older adults (median-age: 72, 59% female) were enrolled. Muscle power generated during a sit-to-stand test using the App and calf circumference were considered the index test. The reference standards were the EWGSOP2 criteria (five-chair stand test plus appendicular skeletal mass or skeletal muscle index) and Fried's frailty phenotype. Area under the curve (AUC), sensitivity, specificity, positive and negative predictive values (PPV and NPV) were calculated.ResultsThe prevalence of both syndromes varied from 2.9% to 7.2% depending on the diagnostic criteria used for sarcopenia assessment. Excellent-to-outstanding AUC values were observed (range 0.80–0.92). Sensitivity and specificity ranged from 75% to 100% and 81.7% to 87.2%, respectively. PPV and NPV ranged from 12.1% to 37.5% and 97.9% to 100%, respectively. Individuals diagnosed by the App showed an increased risk of polypharmacy, depression, comorbidities, falls, hospitalization, low socioeconomical and educational levels, and smoking and poor self-perceived health compared to their healthy counterparts.ConclusionsThis App seems to be reliable to detect the simultaneous presence of both syndromes in community-dwelling older adults. Individuals diagnosed by the App showed more odds to have health-related risk factors.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-20T11:36:37Z
      DOI: 10.1177/20552076241232878
      Issue No: Vol. 10 (2024)
       
  • Enhancing elderly care: Efficient and reliable real-time fall detection
           algorithm

    • Authors: Yue Wang, Tiantai Deng
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      Background and ObjectiveFalls pose a significant risk to public health, especially for the elderly population, and could potentially result in severe injuries or even death. A reliable fall detection system is urgently needed to recognise and promptly alert to falls effectively. A vision-based fall detection system has the advantage of being non-invasive and affordable compared with another popular approach using wearable sensors. Nevertheless, the present challenge lies in the algorithm's limited on-device operating speed due to extremely high computational demands, and the high computational demands are usually essential to improve the performance for the complex scene. Therefore, it is crucial to address the above challenge in computational power and complex scenes.MethodsThis article presents the implementation of a real-time fall detection algorithm with low computational costs using a single webcam. The suggested method optimises precision and efficiency by synthesising the strengths of background subtraction and the human pose estimation model BlazePose. The biomechanical features, derived from body key points identified by BlazePose, are utilised in a random forest model for classifying fall events.ResultsThe proposed algorithm achieves 89.99% accuracy and 29.7 FPS with a laptop CPU on the UR Fall Detection dataset and the Le2i Fall Detection dataset. The algorithm shows great generalisation and robustness in different scenarios.ConclusionDue to the low computational power of the system, the findings also suggest the potential for implementing the system in small-scale medical monitoring equipment, which maximises its practical value in digital health.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-20T11:05:35Z
      DOI: 10.1177/20552076241233690
      Issue No: Vol. 10 (2024)
       
  • Diagnosing postoperative lymph node metastasis in thyroid cancer with
           multimodal radiomics and clinical features

    • Authors: Xin Fan, Han Zhang, Zhengshi Wang, Xiaoying Zhang, Shanshan Qin, Jiajia Zhang, Fan Hu, Mengdie Yang, Jingjing Zhang, Fei Yu
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      PurposeThis study aims to evaluate the diagnostic value of texture analysis for lymph node metastasis after thyroid cancer surgery.MethodsWe retrospectively analyzed patients who underwent positron emission tomography/computed tomography (PET/CT) examination before 131I treatment at Shanghai Tenth People's Hospital between 2017 and 2020. Clinical follow-up results were used as the criterion for determining the presence of lymph node metastasis. The study included 119 patients, who were then randomly divided into training and test groups in a 7:3 ratio. Regions of interest were identified, and radiomics features were extracted using LIFEx 7.3.0. Mann–Whitney U test and LASSO regression were employed to screen radiomics parameters for modeling. Subsequently, a nomogram model was built by combining radscore and clinical features. SPSS 26.0 software was utilized for statistical analysis, and p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-20T11:05:15Z
      DOI: 10.1177/20552076241233244
      Issue No: Vol. 10 (2024)
       
  • A randomized controlled pilot study of a cognitive–behavioral video game
           intervention for the promotion of active aging

    • Authors: Patricia Otero, Tania Cotardo, Vanessa Blanco, Ángela J. Torres, Miguel A. Simón, Ana M. Bueno, Fernando L. Vázquez
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundDue to the accessibility barriers of in-person programs for active aging, the development of programs that use innovative technologies is needed. Video games can be an engaging tool for disseminating active aging interventions.ObjectiveThe objective of this pilot study was to analyze the feasibility of a cognitive–behavioral intervention to promote active aging administered through a video game.MethodsFifty-five participants (63.6% women, mean age = 53.0 years) were randomly assigned to a cognitive–behavioral intervention to promote active aging administered through an interactive multimedia online video game with a complementary app (CBI-V; n = 29) or to a control group that received nonspecific online information (CG; n = 26).ResultsOnly 3.6% of the participants dropped out of the study (6.9% in CBI-V and 0.0% in CG; without significant differences between groups). The mean number of modules completed was 7.6 (SD = 0.9) out of 8 in the CBI-V and 7.9 (SD = 0.5) in the control group (CG), without significant between-group differences. In the CBI-V, the mean total time dedicated to the game was 516.8 min (SD = 94.3), including 143.2 min (SD = 31.6) of cognitive training tasks, and the mean of completed tasks was 206.2 (SD = 33.7) out of 259. Participants were highly engaged (M = 39.9, SD = 8.6) and satisfied (M = 25.8, SD = 4.5) with the intervention. After the intervention, the CBI-V group significantly improved on SF-36 dimensions of General Health (p = .0386), Vitality (p = .0283), Social Functioning (p = .0130), and Physical Summary Index (p = .0370) compared to the CG, with medium effect sizes (d = 0.56–0.75).ConclusionsThe results demonstrate the feasibility of the video game intervention to promote active aging and encourage conducting a large-scale randomized controlled trial.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-20T11:04:55Z
      DOI: 10.1177/20552076241233139
      Issue No: Vol. 10 (2024)
       
  • Exploring how health-related advertising interference contributes to the
           development of cyberchondria: A stressor–strain–outcome approach

    • Authors: Xinmiao Zhang, Han Zheng, Yueliang Zeng, Jiayi Zou, Lin Zhao
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesCyberchondria is increasingly recognized as the dark side of digital health, given the pervasive use of the internet as a main source of health information in people's daily lives. While previous studies have identified many factors contributing to cyberchondria, there is a dearth of research on the impact of health-related advertisements. Therefore, this study adopts the stressor–strain–outcome (SSO) model to investigate how health-related advertising interference is directly and indirectly related to cyberchondria.MethodsTo empirically validate the proposed research model, we conducted an online survey with 437 internet users with medical information seeking experience in China. Structural equation modeling (SEM) was employed to analyze the survey data.ResultsOur findings revealed a positive, direct association between health-related advertising interference and cyberchondria. Meanwhile, advertising interference was positively related to both information overload and information irrelevance, with the former further predicting cyberchondria. Moreover, doctor–patient communication weakened the positive effect of information overload on cyberchondria.ConclusionsThe study not only theoretically contributes to the literature by theorizing the relationship between health-related advertising interference and cyberchondria but also practically underlines the pivotal role of effective doctor–patient communication in reducing the development of cyberchondria.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-20T11:04:26Z
      DOI: 10.1177/20552076241233138
      Issue No: Vol. 10 (2024)
       
  • Advancing equity in challenging times: A qualitative study of telehealth
           expansion and changing patient–provider relationships in primary care
           settings during the COVID-19 pandemic

    • Authors: Monisa Aijaz, Valerie A Lewis, Genevra F Murray
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThe patient–provider relationship is critical for achieving high-quality care and better health outcomes. During the COVID-19 pandemic, primary care practices rapidly transitioned to telehealth. While telehealth provided critical access to services for many, not all patients could optimally utilize it, raising concerns about its potential to exacerbate inequities in patient–provider relationships. We investigated technical and workforce-related barriers to accessing telehealth and the impacts on patient–provider relationships for vulnerable populations.MethodsQualitative, semi-structured interviews from May 2021 to August 2021 with 31 individuals (medical directors, physicians, and medical assistants) working at 20 primary care practices in Massachusetts, North Carolina, and Texas. Thematic analysis to better understand how barriers to using telehealth complicated patient–provider relationships.ResultsInterviewees shared challenges for providers and patients that had a negative effect on patient–provider relationships, particularly for vulnerable patients, including older adults, lower socio-economic status patients, and those with limited English proficiency. Providers faced logistical challenges and disruptions in team-based care, reducing care coordination. Patients experienced technological challenges that made accessing and engaging in telehealth difficult. Interviewees shared challenges for patient–provider relationships as commonly used telephone-only telehealth reduced channels for non-verbal communication.ConclusionThis study indicates that barriers to virtual interaction with patients compared to in-person care likely led to weaker personal relationships that may have longer-term effects on engagement with and trust in the healthcare system, particularly among vulnerable patient groups. Additional support and resources should be available to primary care providers to optimize telehealth utilization.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-19T11:58:52Z
      DOI: 10.1177/20552076241233148
      Issue No: Vol. 10 (2024)
       
  • Clinical decision support system using a machine learning model to assist
           simultaneous cardiopulmonary auscultation: Open-label randomized
           controlled trial

    • Authors: Takanobu Hirosawa, Tetsu Sakamoto, Yukinori Harada, Kazuki Tokumasu, Taro Shimizu
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundThe utility of a clinical decision support system using a machine learning (ML) model for simultaneous cardiac and pulmonary auscultation is unknown.ObjectiveThis study aimed to develop and evaluate an ML system's utility for cardiopulmonary auscultation.MethodsFirst, we developed an ML system for cardiopulmonary auscultation, using cardiopulmonary sound files from our previous study. The technique involved pre-processing, feature extraction, and classification through several neural network layers. After integration, the output class was categorized as “normal,” “abnormal,” or “undetermined.” Second, we evaluated the ML system with 24 junior residents in an open-label randomized controlled trial at a university hospital. Participants were randomly assigned to the ML system group (intervention) or conventional auscultation group (control). During training, participants listened to four cardiac and four pulmonary sounds, all of which were correctly classified. Then, participants classified a series of 16 simultaneous cardiopulmonary sounds. The control group auscultated the sounds using noise-cancelling headphones, while the intervention group did so by watching recommendations from the ML system.ResultsThe total scores for correctly identified normal or abnormal cardiopulmonary sounds in the intervention group were significantly higher than those in the control group (366/384 [95.3%] vs. 343/384 [89.3%], P = 0.003). The cardiac test score in the intervention group was better (111/192 [57.8%] vs. 90/192 [46.9%], P = 0.04); there was no significant difference in pulmonary auscultation.ConclusionsThe ML-based system improved the accuracy of cardiopulmonary auscultation for junior residents. This result suggests that the system can assist early-career physicians in accurate screening.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-19T11:15:05Z
      DOI: 10.1177/20552076241233689
      Issue No: Vol. 10 (2024)
       
  • Performance of ChatGPT on Stage 1 of the Taiwanese medical licensing exam

    • Authors: Chao-Hsiung Huang, Han-Jung Hsiao, Pei-Chun Yeh, Kuo-Chen Wu, Chia-Hung Kao
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      IntroductionSince its release by OpenAI in November 2022, numerous studies have subjected ChatGPT to various tests to evaluate its performance in medical exams. The objective of this study is to evaluate ChatGPT's accuracy and logical reasoning across all 10 subjects featured in Stage 1 of Senior Professional and Technical Examinations for Medical Doctors (SPTEMD) in Taiwan, with questions that encompass both Chinese and English.MethodsIn this study, we tested ChatGPT-4 to complete SPTEMD Stage 1. The model was presented with multiple-choice questions extracted from three separate tests conducted in February 2022, July 2022, and February 2023. These questions encompass 10 subjects, namely biochemistry and molecular biology, anatomy, embryology and developmental biology, histology, physiology, microbiology and immunology, parasitology, pharmacology, pathology, and public health. Subsequently, we analyzed the model's accuracy for each subject.ResultIn all three tests, ChatGPT achieved scores surpassing the 60% passing threshold, resulting in an overall average score of 87.8%. Notably, its best performance was in biochemistry, where it garnered an average score of 93.8%. Conversely, the performance of the generative pre-trained transformer (GPT)-4 assistant on anatomy, parasitology, and embryology was not as good. In addition, its scores were highly variable in embryology and parasitology.ConclusionChatGPT has the potential to facilitate not only exam preparation but also improve the accessibility of medical education and support continuous education for medical professionals. In conclusion, this study has demonstrated ChatGPT's potential competence across various subjects within the SPTEMD Stage 1 and suggests that it could be a helpful tool for learning and exam preparation for medical students and professionals.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-16T08:21:42Z
      DOI: 10.1177/20552076241233144
      Issue No: Vol. 10 (2024)
       
  • Digital therapeutics in the hospital for suicide crisis – content and
           design recommendations from young people and hospital staff

    • Authors: Demee Rheinberger, Rachel Baffsky, Lauren McGillivray, Daniel Z Q Gan, Mark Larsen, Michelle Torok
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveHospital emergency departments lack the resources to adequately support young people who present for suicidal crisis. Digital therapeutics could fill this service gap by providing psychological support without creating additional burden on hospital staff. However, existing research on what is needed for successful integration of digital therapeutics in hospital settings is scant. Thus, this study sought to identify key considerations for implementing digital therapeutics to manage acute suicidal distress in hospitals.MethodParticipants were 17 young people who recently presented at the hospital for suicide-related crisis, and 12 hospital staff who regularly interacted with young people experiencing mental ill-health in their day-to-day work. Interviews were conducted via videoconference. Framework analysis and reflexive thematic analysis were used to interpret the data obtained.ResultsQualitative insights were centred around three major themes: hospital-specific content, therapeutic content, and usability. Digital therapeutics were seen as a useful means for facilitating hospital-based assessment and treatment planning, and for conducting post-discharge check-ins. Therapeutic content should be focused on helping young people self-manage suicide-related distress while they wait for in-person services. Features to promote usability, such as the availability of customisable features and the use of inclusive design or language, should be considered in the design of digital therapeutics.ConclusionsDigital therapeutics in hospital settings need to benefit both patients and staff. Given the unique context of the hospital setting and acute nature of suicidal distress, creating specialty digital therapeutics may be more viable than integrating existing ones.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-15T07:09:47Z
      DOI: 10.1177/20552076241230072
      Issue No: Vol. 10 (2024)
       
  • Determining design criteria for indoor positioning system projects in
           hospitals: A design science approach

    • Authors: Johannes Wichmann, Thomas Paetow, Michael Leyer, Bisrat Aweno, Kurt Sandkuhl
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesIndoor navigation systems (indoor positioning systems) can improve orientation for patients in hospitals and help employees to track assets. Many hospitals would like to implement indoor positioning systems but do not know how. To support them in doing this, and to gain knowledge about the requirements for indoor positioning system implementation, our research identifies the design criteria relevant to indoor positioning system implementation projects.MethodsA design science research process is built to design and evaluate an artifact. For this, five indoor positioning system developers and five hospital IT management representatives from various hospitals and companies in Germany are interviewed. Further, controlled experiments are conducted in Germany, using an ultrasound-based indoor positioning system.ResultsWe determined and tested indoor positioning system functions, evaluated indoor positioning system performance criteria, and identified the operating conditions in hospitals. Our results show that indoor positioning system functions should provide a benefit to a hospital's daily operations, that some performance criteria are more important than others, and that operating conditions are important, e.g., radiation.ConclusionAs a theoretical contribution, we show how design science research can be applied to the context of indoor positioning systems in hospitals. In addition, we make a practical contribution in that our propositions can be used for future indoor positioning system developments.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-15T07:09:18Z
      DOI: 10.1177/20552076241229148
      Issue No: Vol. 10 (2024)
       
  • Patients with floaters: Answers from virtual assistants and large language
           models

    • Authors: Gloria Wu, Weichen Zhao, Adrial Wong, David A Lee
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      Objectives“Floaters,” a common complaint among patients of all ages, was used as a query term because it affects 30% of all people searching for eye care. The American Academy of Ophthalmology website's “floaters” section was used as a source for questions and answers (www.aao.org). Floaters is a visual obstruction that moves with the movement of the eye. They can be associated with retinal detachment, which can lead to vision loss. With the advent of large language model (LLM) chatbots ChatGPT, Bard versus virtual assistants (VA), Google Assistant, and Alexa, we analyzed their responses to “floaters.”MethodsUsing AAO.org, “Public & Patients,” and its related subsection, “EyeHealth A-Z”: Floaters and Flashes link, we asked four questions: (1) What are floaters' (2) What are flashes' (3) Flashes and Migraines' (4) Floaters and Flashes Treatment' to ChatGPT, Bard, Google Assistant, and Alexa. The American Academy of Ophthalmology (AAO) keywords were identified if they were highlighted. The “Flesch-Kincaid Grade Level” formula approved by the U.S. Department of Education, was used to evaluate the reading comprehension level for the responses.ResultsOf the chatbots and virtual assistants, Google Assistant is the only one that uses the term “ophthalmologist.” There is no mention of the urgency or emergency nature of floaters. AAO.org shows a lower reading level vs the LLMs and VA (p = .11). The reading comprehension levels of ChatGPT, Bard, Google Assistant, and Alexa are higher (12.3, 9.7, 13.1, 8.1 grade) vs the AAO.org (7.3 grade). There is a higher word count for LLMs vs VA (p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-15T06:58:38Z
      DOI: 10.1177/20552076241229933
      Issue No: Vol. 10 (2024)
       
  • Added value of video edutainment on android handsets in home visits to
           improve maternal and child health in Bauchi State, Nigeria: Secondary
           analysis from a cluster randomised controlled trial

    • Authors: Umaira Ansari, Khalid Omer, Amar Aziz, Yagana Gidado, Hadiza Mudi, Ibrahim Sabo Jamaare, Neil Andersson, Anne Cockcroft
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveA trial of evidence-based health promotion home visits to pregnant women and their spouses in northern Nigeria found significant improvements in maternal and child health outcomes. This study tested the added value for these outcomes of including video edutainment in the visits.MethodsIn total, 19,718 households in three randomly allocated intervention wards (administrative areas) received home visits including short videos on android handsets to spark discussion about local risk factors for maternal and child health; 16,751 households in three control wards received visits with only verbal discussion about risk factors. We compared outcomes between wards with and without videos in the visits, calculating the odds ratio (OR) and 95% confidence interval (95%CI) of differences, in bivariate and then multivariate analysis adjusting for socio-economic differences between the video and non-video wards.ResultsPregnant women from video wards were more likely than those from non-video wards to have discussed pregnancy and childbirth often with their husbands (OR 2.22, 95%CI 1.07–4.59). Male spouses in video wards were more likely to know to give more fluids and continued feeding to a child with diarrhoea (OR 1.61, 95%CI 1.21–2.13). For most outcomes there was no significant difference between video and non-video wards. The home visitors who shared videos considered they helped pregnant women and their spouses to appreciate the information about risk factors.ConclusionThe lack of added value of the videos in the context of a research study may reflect the intensive training of home visitors and the effective evidence-based discussions included in all the visits. Further research could rollout routine home visits with and without videos and test the impact of video edutainment added to home visits carried out in a routine service context.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-14T07:35:35Z
      DOI: 10.1177/20552076241228408
      Issue No: Vol. 10 (2024)
       
  • Sequencing conversational turns in peer interactions: An integrated
           approach for evidence-based conversational agent for just-in-time nicotine
           cravings intervention

    • Authors: Tavleen Singh, Michael Truong, Kirk Roberts, Sahiti Myneni
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundRisky health behaviors place an enormous toll on public health systems. While relapse prevention support is integrated with most behavior modification programs, the results are suboptimal. Recent advances in artificial intelligence (AI) applications provide us with unique opportunities to develop just-in-time adaptive behavior change solutions.MethodsIn this study, we present an innovative framework, grounded in behavioral theory, and enhanced with social media sequencing and communications scenario builder to architect a conversational agent (CA) specialized in the prevention of relapses in the context of tobacco cessation. We modeled peer interaction data (n = 1000) using the taxonomy of behavior change techniques (BCTs) and speech act (SA) theory to uncover the socio-behavioral and linguistic context embedded within the online social discourse. Further, we uncovered the sequential patterns of BCTs and SAs from social conversations (n = 339,067). We utilized grounded theory-based techniques for extracting the scenarios that best describe individuals’ needs and mapped them into the architecture of the virtual CA.ResultsThe frequently occurring sequential patterns for BCTs were comparison of behavior and feedback and monitoring; for SAs were directive and assertion. Five cravings-related scenarios describing users’ needs as they deal with nicotine cravings were identified along with the kinds of behavior change constructs that are being elicited within those scenarios.ConclusionsAI-led virtual CAs focusing on behavior change need to employ data-driven and theory-linked approaches to address issues related to engagement, sustainability, and acceptance. The sequential patterns of theory and intent manifestations need to be considered when developing effective behavior change CAs.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-14T07:02:39Z
      DOI: 10.1177/20552076241228430
      Issue No: Vol. 10 (2024)
       
  • Beliefs, experiences and concerns of using artificial intelligence in
           healthcare: A qualitative synthesis

    • Authors: Carol-Ann Fazakarley, Maria Breen, Ben Thompson, Paul Leeson, Victoria Williamson
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveArtificial intelligence (AI) is a developing field in the context of healthcare. As this technology continues to be implemented in patient care, there is a growing need to understand the thoughts and experiences of stakeholders in this area to ensure that future AI development and implementation is successful. The aim of this study was to conduct a literature search of qualitative studies exploring the opinions of stakeholders such as clinicians, patients, and technology experts in order to establish the most common themes and ideas that have been presented in this research.MethodsA literature search was conducted of existing qualitative research on stakeholder beliefs about the use of AI use in healthcare. Twenty-one papers were selected and analysed resulting in the development of four key themes relating to patient care, patient–doctor relationships, lack of education and resources, and the need for regulations.ResultsOverall, patients and healthcare workers are open to the use of AI in care and appear positive about potential benefits. However, concerns were raised relating to the lack of empathy in interactions of AI tools, and potential risks that may arise from the data collection needed for AI use and development. Stakeholders in the healthcare, technology, and business sectors all stressed that there was a lack of appropriate education, funding, and guidelines surrounding AI, and these concerns needed to be addressed to ensure future implementation is safe and suitable for patient care.ConclusionUltimately, the results found in this study highlighted that there was a need for communication between stakeholder in order for these concerns to be addressed, mitigate potential risks, and maximise benefits for patients and clinicians alike. The results also identified a need for further qualitative research in this area to further understand stakeholder experiences as AI use continues to develop.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-12T05:57:57Z
      DOI: 10.1177/20552076241230075
      Issue No: Vol. 10 (2024)
       
  • Factors influencing how informal caregivers of people with multiple
           sclerosis access and use a curated intervention website: Analysis from an
           RCT

    • Authors: Tanya Packer, Nichole Austin, Michelle Lehman, Sara L Douglas, Matthew Plow
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveHealthcare consumers and providers are increasingly turning to digital solutions, such as curated websites. Knowing who accesses/benefits from these may improve design and development. This study investigated website usage of informal caregivers of people with multiple sclerosis and shifts in outcome plausibly associated with usage.MethodsSecondary analysis of data from a randomized clinical trial of 148 caregivers compared effectiveness of a website + tele-coaching to a website only intervention for caregivers. Groupwise differences in means/proportions were tested using t-tests and chi-square. Modified Poisson regression with a robust variance estimator and ordinal logistic regression tested the relationship between group and likelihood of website log-in. Ordinal logistic regression models examined whether caregiver characteristics were associated with website use. Generalized estimating equations (GEE) with an autoregressive correlation structure modeled the relationship between website usage and outcomes.ResultsFemales were more likely to access the website than males (60% vs. 43%; p = 0.05). Though not statistically significant, a possible association (POR: .85, 95% CI: .69, 1.03) between caregiver burden and website access emerged; caregivers experiencing highest levels of burden appeared less likely to engage. Usage patterns differed by treatment arm: the website-only group accessed the Caring for yourself topic significantly more (61.67% vs. 38.33%: p = .04) with similar, but insignificant, trends for other topics.ConclusionsClinicians can be confident referring females with moderate levels of burden to website-based interventions. By contrast, male caregivers and those experiencing high levels of burden may be less likely to access these resources, pointing to the need for alternative interventions.Trial RegistrationClinicaltrials.gov, registration number: NCT0466208.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-09T07:12:41Z
      DOI: 10.1177/20552076241228403
      Issue No: Vol. 10 (2024)
       
  • Differences in risk of generalized anxiety disorder according to physical
           activity type in Korea adolescents: The Korea youth risk behavior
           web-based survey, 2020–2021

    • Authors: Jhinyi Shin, Kihyuk Lee
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThis study aimed to analyze the association between the types of physical activity (PA) and the level of generalized anxiety disorder (GAD) in Korean adolescents.MethodsThis study analyzed data from the Korea Youth Risk Behavior Web-based Survey (KYRBS) for, 2020–2021. The dependent variable was the level of generalized anxiety disorder-7 (GAD-7). The GAD-7 scores were divided into four levels: normal, mild, moderate, and severe. The independent variables were moderate PA, vigorous PA, and strength exercises. Sex, school grade, body mass index, stress, depression, suicidal thoughts, violent victimization, drinking, smoking, substance abuse, sleep satisfaction, and sedentary time were selected as confounding variables.ResultsThe independent variable and all confounding variables showed significant differences with the level of GAD-7 (all p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-08T07:04:56Z
      DOI: 10.1177/20552076231225572
      Issue No: Vol. 10 (2024)
       
  • The design of the Deaf in Touch Everywhere (DITE)TM mobile application
           with Deaf and interpreter communities in Malaysia

    • Authors: Vee Yee Chong, Chong Chun Yong, Jennifer Ng, Dhaanyah Thanabalasingam, Jessica L Watterson, Uma Devi Palanisamy
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundIneffective communication with Deaf individuals in healthcare settings has led to poor outcomes including miscommunication, waste, and errors. To help address these challenges, we developed a mobile app, Deaf in Touch Everywhere (DITETM) which aims to connect the Deaf community in Malaysia with a pool of off-site interpreters through secure video conferencing.ObjectivesThe aims of this study were to (a) assess the feasibility and acceptability of measuring unified theory of acceptance and use of technology (UTAUT) constructs for DITETM with the Deaf community and Malaysian sign language (BIM) interpreters and (b) seek input from Deaf people and BIM interpreters on DITETM to improve its design.MethodsTwo versions of the UTAUT questionnaire were adapted for BIM interpreters and the Deaf community. Participants were recruited from both groups and asked to test the DITE app features over a 2-week period. They then completed the questionnaire and participated in focus group discussions to share their feedback on the app.ResultsA total of 18 participants completed the questionnaire and participated in the focus group discussions. Ratings of performance expectancy, effort expectancy, facilitating conditions and behavioural intention were high across both groups, and suggestions were provided to improve the app. High levels of engagement suggest that measurement of UTAUT constructs with these groups (through a modified questionnaire) is feasible and acceptable.ConclusionsThe process of engaging end users in the design process provided valuable insights and will help to ensure that the DITETM app continues to address the needs of both the Deaf community and BIM interpreters in Malaysia.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-07T09:05:03Z
      DOI: 10.1177/20552076241228432
      Issue No: Vol. 10 (2024)
       
  • Digital learning about patients: An online survey of German medical
           students investigating learning strategies for family medical video
           consultations

    • Authors: Franziska Särchen, Susanne Springborn, Achim Mortsiefer, Jan Ehlers
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveTraining in video consultations is seldom included in the curriculum for future physicians. Exploration of preferred teaching methods and learning objectives in this context among medical students remains limited. This study addresses this research gap by conducting a survey among medical students in Germany to assess their educational requirements concerning video consultations and patient-centred distance learning.MethodsThis quantitative study employed an online questionnaire designed for German medical students, following the guidelines of the International Association for Health Professions Education. The study primarily focused on discerning the didactic preferences related to patient-centred digital teaching regarding family medical video consultations. We provided a detailed explanation of a concrete learning concept, a family medical synchronous distance learning seminar. Subsequently, we surveyed students to gauge their needs, expectations, and evaluations of this concept. The collected data were subjected to descriptive analysis.ResultsThe analysis revealed that students aspire to offer video consulting services to their patients in the future (sample size (n) = 369, median (med) = 68 of 101 Likert scale points, interquartile range (IQR) = 53.75), despite having limited knowledge in this area (n = 353, med = 21, IQR = 33.25). To acquire expertise in telehealth, students favor blended learning models (n = 331, med = 76, IQR = 50). They also recognize the benefits of distance learning, particularly for students with family responsibilities or those who must travel long distances to their learning institutions,. The presented distance seminar concept resonated with them (n = 278, med = 72.5, IQR = 50.5), surpassing five other digital learning models in preference. Furthermore, they expressed a desire for its continued implementation beyond the Coronavirus SARS-CoV-2 pandemic (n = 188, med = 77.5, IQR = 44.75).ConclusionsThe deficiency in medical school education regarding video consultations requires attention. This issue could be resolved by integrating one of the five distance learning concepts outlined in this article.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-06T05:03:12Z
      DOI: 10.1177/20552076241230070
      Issue No: Vol. 10 (2024)
       
  • Effectiveness of digital games promoting young people's mental health: A
           review of reviews

    • Authors: Clara Vié, Kyllian Govindin-Ramassamy, Dimitri Thellier, David Labrosse, Ilaria Montagni
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesDigital games are a popular form of entertainment for youth. They are often used as a therapy for psychological problems, a mental health promotion intervention, and a preventative measure. Systematic reviews and meta-analyses have been conducted to assess the effectiveness of mental health-related digital games. However, a synthesis considering all evaluation results to inform their development is missing.MethodsWe performed a review of reviews to synthetize results of previous research to describe the impact of digital games on the mental health of young people aged
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-06T04:51:33Z
      DOI: 10.1177/20552076231220814
      Issue No: Vol. 10 (2024)
       
  • Rule-based expert system for the diagnosis of maternal complications
           during pregnancy: For low resource settings

    • Authors: Birhan Meskelu Gebremariam, Genet Tadese Aboye, Abebaw Aynewa Dessalegn, Gizeaddis Lamesgin Simegn
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesMaternal complications are health challenges linked to pregnancy, encompassing conditions like gestational diabetes, maternal sepsis, sexually transmitted diseases, obesity, anemia, urinary tract infections, hypertension, and heart disease. The diagnosis of common pregnancy complications is challenging due to the similarity in signs and symptoms with general pregnancy indicators, especially in settings with scarce resources where access to healthcare professionals, diagnostic tools, and patient record management is limited. This paper presents a rule-based expert system tailored for diagnosing three prevalent maternal complications: preeclampsia, gestational diabetes mellitus (GDM), and maternal sepsis.MethodsThe risk factors associated with each disease were identified from various sources, including local health facilities and literature reviews. Attributes and rules were then formulated for diagnosing the disease, with a Mamdani-style fuzzy inference system serving as the inference engine. To enhance usability and accessibility, a web-based user interface has been also developed for the expert system. This interface allows users to interact with the system seamlessly, making it easy for them to input relevant information and obtain accurate disease diagnose.ResultsThe proposed expert system demonstrated a 94% accuracy rate in identifying the three maternal complications (preeclampsia, GDM, and maternal sepsis) using a set of risk factors. The system was deployed to a custom-designed web-based user interface to improve ease of use.ConclusionsWith the potential to support health services provided during antenatal care visits and improve pregnant women's health outcomes, this system can be a significant advancement in low-resource setting maternal healthcare.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-02T05:16:19Z
      DOI: 10.1177/20552076241230073
      Issue No: Vol. 10 (2024)
       
  • Multi-task localization of the hemidiaphragms and lung segmentation in
           portable chest X-ray images of COVID-19 patients

    • Authors: Daniel I Morís, Joaquim de Moura, Shahab Aslani, Joseph Jacob, Jorge Novo, Marcos Ortega
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundThe COVID-19 can cause long-term symptoms in the patients after they overcome the disease. Given that this disease mainly damages the respiratory system, these symptoms are often related with breathing problems that can be caused by an affected diaphragm. The diaphragmatic function can be assessed with imaging modalities like computerized tomography or chest X-ray. However, this process must be performed by expert clinicians with manual visual inspection. Moreover, during the pandemic, the clinicians were asked to prioritize the use of portable devices, preventing the risk of cross-contamination. Nevertheless, the captures of these devices are of a lower quality.ObjectivesThe automatic quantification of the diaphragmatic function can determine the damage of COVID-19 on each patient and assess their evolution during the recovery period, a task that could also be complemented with the lung segmentation.MethodsWe propose a novel multi-task fully automatic methodology to simultaneously localize the position of the hemidiaphragms and to segment the lung boundaries with a convolutional architecture using portable chest X-ray images of COVID-19 patients. For that aim, the hemidiaphragms’ landmarks are located adapting the paradigm of heatmap regression.ResultsThe methodology is exhaustively validated with four analyses, achieving an 82.31% [math] 2.78% of accuracy when localizing the hemidiaphragms’ landmarks and a Dice score of 0.9688 [math] 0.0012 in lung segmentation.ConclusionsThe results demonstrate that the model is able to perform both tasks simultaneously, being a helpful tool for clinicians despite the lower quality of the portable chest X-ray images.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-02T05:15:34Z
      DOI: 10.1177/20552076231225853
      Issue No: Vol. 10 (2024)
       
  • Internet hospital response to the COVID-19 pandemic in a tertiary hospital
           in China: Perspectives based on a mixed-methods

    • Authors: Xiaolong Wu, Yulin Kuang, Yonglin Guo, Ji Wu, Li Xiao
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThis study aimed to summarize the characteristics of the Internet hospital services of the Seventh Affiliated Hospital of Sun Yat-sen University (SAHSYSU), describe diagnosis and treatment patterns in each department, determine SAHSYSU Internet hospital's role in pandemic control, and explore development strategies in non-pandemic situations.MethodsMixed-methods was used in this study. Qualitative organizational behavior analysis was conducted on hospital meeting records and semi-structured interview records to determine the research analysis indicators. We quantitatively analyzed online consultation record data of SAHSYSU Internet hospital from January to December 2020, and conduct classification analysis on departmental case studies using K-means clustering algorithm.Results29,944 patient data items were retrieved. Internet hospital services synchronized with COVID-19 pandemic development in China and Guangdong province. The service volume peaked during the period of January to March, which coincided with the height of the pandemic. Out of the total visits, 58.90% were conducted during office hours while 41.10% were conducted during non-office hours. The majority of the patients came from Guangdong (19.67%) and Hubei (9.09%) provinces. The cluster analysis identified three clusters, each with different change rates and magnitudes of change for various departments.ConclusionInternet hospitals complemented conventional medical services, providing crucial medical care during the COVID-19 pandemic. Internet hospitals are the future trend of medical services and should be improved based on each department's treatment characteristics.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-01T07:14:43Z
      DOI: 10.1177/20552076241228418
      Issue No: Vol. 10 (2024)
       
  • “No man is an island”: How Chinese netizens use deliberate metaphors
           to provide “depression sufferers” with social support

    • Authors: Youping Jing, Guiying Jiang
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveOnline social support provides a way to positively influence depression sufferers. In the present study, we aim to analyze how social support in Chinese online depression communities is communicated through the lens of deliberate metaphor theory (DMT) to deepen the understanding of the under-researched complicated, emotionally laden, and culture-related concepts of this experience.MethodsWe collected data (n = 3546 comments) from the Warm Supporting section of the Depression Super Topic, a major Chinese online depression community on Weibo. The data were analyzed using a metaphorical analysis with the Metaphor Identification Procedure Vrije Universiteit and a thematic analysis.ResultsOur findings identify two themes: deliberate metaphors (DMs) of depression and DMs of social environment for depression sufferers. The former conceptualizes future expectations without depression (as rosy images; victorious battles; the beaten black dog); disorder (as subtle objects; subjective initiative events); depression sufferers (as valuable objects; important roles); and present life with depression (as optional events; spiritual practices; fragile objects). The latter conceptualizes social connection (as solid objects; nonessentials); individuals in the social environment (as energetic objects; vicious roles); and prejudice (as colored objects).ConclusionsThe findings suggest that DMs as important online social support resources, helping to express empathy and normalize depression with more common-sense, and non-judgmental concepts. Additionally, in DMs, Chinese netizens navigate the intricate intersection of medical and moral perspectives on depression and its recovery, leveraging both aspects to offer comprehensive social support. “Confucian-based” elements are embedded in culture-related social support expressions in DMs. In practice, our findings contribute to tailored and appropriate health interventions for depression.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-01T05:27:22Z
      DOI: 10.1177/20552076241228521
      Issue No: Vol. 10 (2024)
       
  • Telemedicine in the age of the pandemics: The prospects of web-based
           remote patient monitoring systems for orthopaedic ambulatory care
           management in the developing economies

    • Authors: Uchechukwu Solomon Onyeabor, Wilfred Okwudili Okenwa, Okechukwu Onwuasoigwe, Omolade Ayoola Lasebikan, Thorsten Schaaf, Niels Pinkwart, Felix Balzer
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThe goal of this research was to demonstrate the efficacy of telemedicine via design, implementation and evaluation of a web-based remote patient monitoring system (WB-RPMS) across the tertiary/university teaching hospitals in a developing country Nigeria, as a tool to continue to expand access to an affordable and resilient tertiary healthcare system through the challenging times of the COVID-19 pandemic or any future disruptions.MethodsThis research employed an agile and human-centred design thinking philosophy, which saw the researchers iteratively collaborate with clinicians across the system development value chain. It also employed qualitative and quantitative research methods for new system evaluations. After the system's development, a 20-patient sample was randomly selected from members of the National Youth Service Corp to evaluate the WB-RPMS Patient Portal for usability and user experience through a survey based on the system usability scale. Again, the COREQ standards for reporting research result were adopted for this study.ResultsThe evaluation of the WB-RPMS Patient Portal by a select patient sample showed that 95.0% of the respondents believed that they would like to use the system frequently. It was also discovered that 90.0% of all respondents also indicated that they found the Patient Portal to be simple; 85.0% of the respondents believed and indicated that the WB-RPMS Patient Portal was easy to use.ConclusionsThe result of the usability evaluation of the developed WB-RPMS Patient Portal showed that it was well received by the select patient sample and by the clinicians who participated in the development process. In fact, the performance of the system shows that it has the potential to remotely support and sustain improved access to affordable healthcare for outpatients in developing countries even during times of uncertainties and disruptions as recently occasioned by COVID-19 pandemic.
      Citation: DIGITAL HEALTH
      PubDate: 2024-02-01T05:26:23Z
      DOI: 10.1177/20552076241226964
      Issue No: Vol. 10 (2024)
       
  • Development of a dental diet-tracking mobile app for improved
           caries-related dietary behaviours: Key features and pilot evaluation of
           quality

    • Authors: Charlene Enhui Goh, Kaiping Zheng, Wen Yong Chua, Thao Nguyen, Changshuo Liu, Chun Keat Koh, Gabriel Keng Yan Lee, Chong Meng Tay, Beng Chin Ooi, Mun Loke Wong
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveDiet significantly contributes to dental decay (caries) yet monitoring and modifying patients’ diets is a challenge for many dental practitioners. While many oral health and diet-tracking mHealth apps are available, few focus on the dietary risk factors for caries. This study aims to present the development and key features of a dental-specific mobile app for diet monitoring and dietary behaviour change to prevent caries, and pilot data from initial user evaluation.MethodsA mobile app incorporating a novel photo recognition algorithm and a localised database of 208,718 images for food item identification was developed. The design and development process were iterative and incorporated several behaviour change techniques commonly used in mHealth. Pilot evaluation of app quality was assessed using the end-user version of the Mobile Application Rating Scale (uMARS).ResultsUser feedback from the beta-testing of the prototype app spurred the improvement of the photo recognition algorithm and addition of more user-centric features. Other key features of the final app include real-time prompts to drive actionable behaviour change, goal setting, comprehensive oral health education modules, and visual metrics for caries-related dietary factors (sugar intake, meal frequency, etc.). The final app scored an overall mean (standard deviation) of 3.6 (0.5) out of 5 on the uMARS scale.ConclusionWe developed a novel diet-tracking mobile app tailored for oral health, addressing a gap in the mHealth landscape. Pilot user evaluations indicated good app quality, suggesting its potential as a useful clinical tool for dentists and empowering patients for self-monitoring and behavioural management.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-31T08:59:01Z
      DOI: 10.1177/20552076241228433
      Issue No: Vol. 10 (2024)
       
  • The German version of the mHealth App Usability Questionnaire (GER-MAUQ):
           Translation and validation study in patients with cardiovascular disease

    • Authors: Theodora Tacke, Pascal Nohl-Deryk, Neelam Lingwal, Lara Marie Reimer, Fabian Starnecker, Corina Güthlin, Ferdinand M Gerlach, Heribert Schunkert, Stephan Jonas, Angelina Müller
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveIn Germany, only a few standardized evaluation tools for assessing the usability of mobile Health apps exist so far. This study aimed to translate and validate the English patient version for standalone apps of the mHealth App Usability Questionnaire (MAUQ) into a German version.MethodsFollowing scientific guidelines for translation and cross-cultural adaptation, the patient version for standalone apps was forward and back-translated from English into German by an expert panel. In total, 53 participants who were recruited as part of the beta testing process of the recently developed mHealth app HerzFit, answered the questions of the German version of the MAUQ (GER-MAUQ) and the System Usability Scale. Subsequently, a descriptive as well as a psychometric analysis was performed to test validity and reliability.ResultsAfter conducting three cognitive interviews, five items were modified. The values for Cronbach alpha for the entire questionnaire and the three subscales (0.966, 0.814, 0.910, and 0.909) indicate strong internal consistency. The correlation analysis revealed that the scores of the GER-MAUQ, the subscales and the SUS were strongly correlated with each other. The correlation coefficient of the SUS and the GER-MAUQ overall score was r = 0.854, P 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-31T08:58:32Z
      DOI: 10.1177/20552076231225168
      Issue No: Vol. 10 (2024)
       
  • Exploration of vulnerability factors of digital hoarding behavior among
           university students and the moderating role of maladaptive perfectionism

    • Authors: Zeinab Zaremohzzabieh, Haslinda Abdullah, Seyedali Ahrari, Rusli Abdullah, Siti Maryam Md Nor
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      In light of the rapidly evolving digital landscape, there is an increasing need to explore digital hoarding behavior. This need is driven by concerns regarding its intricate psychological foundations and its impact on individuals within our technology-centric society. This research investigates the influence of various factors, including the fear of missing out, emotional attachment, information overload, and decision fatigue, on digital hoarding behaviors among university students in Iran. Additionally, the study examines the moderating role of maladaptive perfectionism in these relationships. The study involved 275 university students (mean age = 21.62 years; standard deviation = 2.28 years; 65.6% female) selected from four universities in Iran. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that the fear of missing out, emotional attachment, information overload, and decision fatigue significantly predict university students’ digital hoarding behavior. Moreover, the findings highlighted the moderating effect of maladaptive perfectionism on the association between emotional attachment and digital hoarding behavior. This suggests that individuals with higher levels of maladaptive perfectionism exhibit amplified digital hoarding tendencies when emotionally attached to their digital data. This study provides a deeper understanding of the relationship between psychological factors and digital hoarding tendencies. These findings have practical implications for educational institutions and mental health professionals, as they can help in developing targeted strategies and interventions to manage digital hoarding behavior in university freshmen and promote healthier digital habits.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-31T05:29:42Z
      DOI: 10.1177/20552076241226962
      Issue No: Vol. 10 (2024)
       
  • Navigating the infodemic: A qualitative study of university students’
           information strategies during the COVID-19 pandemic

    • Authors: Lieve Gies, Mayuri Gogoi, Christopher D. Bayliss, Manish Pareek, Adam Webb
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesWe aimed to study the strategies which university students developed for vetting information during the COVID-19 pandemic and associated infodemic.MethodsWe conducted semi-structured interviews with 34 students, using a piloted topic guide which explored several areas of pandemic experiences, including students’ use of media. Transcripts were analysed inductively following the thematic approach. Higher order themes were finalised following a coding exercise undertaken by two of the authors.ResultsParticipants were acutely aware of misinformation during the pandemic. They rated legacy news media (print and broadcast media with pre-Internet origins) higher than social media for reliable information about the pandemic. However, strikingly, not all legacy media were automatically trusted and not all social media were uniformly distrusted. Participants identified a set of mechanisms for establishing whether a piece of information was truthful and accurate. These mechanisms had four main focal points: (1) the source, (2) the message, (3) individual media literacy and (4) the trustworthiness of others. Despite possessing a critical awareness of misinformation, participants avoided posting anything in relation to the pandemic for fear of becoming the target of online abuse.ConclusionsIn addition to underscoring the role of media literacy, our research foregrounds the need to attend to the importance of fostering media confidence. We define media confidence as the ability of digital media users to challenge and interrogate questionable or inaccurate information safe in the knowledge that there are adequate regulatory mechanisms in place to curb abuse, trolling and intimidation.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-31T05:28:43Z
      DOI: 10.1177/20552076241228695
      Issue No: Vol. 10 (2024)
       
  • What is public trust in national electronic health record systems' A
           scoping review of qualitative research studies from 1995 to 2021

    • Authors: Kimon Papadopoulos, Viktor von Wyl, Felix Gille
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivePublic trust in national electronic health record systems is essential for the successful implementation within a healthcare system. Research investigating public trust in electronic health records is limited, leading to a lack of conceptual clarity. In response, the objective of this study is to gain a clearer understanding on the conceptualizations of public trust in electronic health records, which can support the implementation of national electronic health record systems.MethodsGuided by the PRISMA-ScR checklist, a scoping review of 27 qualitative studies on public trust in electronic health records found between January 2022 and June 2022 was conducted using an inclusive search method. In an iterative process, conceptual themes were derived describing the promoters and outcomes of public trust in electronic health records.ResultsFive major conceptual themes with 15 sub-themes were present across the literature. Comprehension, autonomy, and data protection promote public trust in electronic health record; while personal and system benefits are the outcomes once public trust in electronic health records exists. Additional findings highlight the pivotal role of healthcare actors for the public trust building process.ConclusionsThe results underscore comprehension, autonomy, and data protection as important themes that help ascertain and solidify public trust in electronic health records. As well, health system actors have the capacity to promote or hinder national electronic health record implementation, depending on their actions and how the public perceives those actions. The findings can assist researchers, policymakers, and other health system actors in attaining a better understanding of the intricacies of public trust in electronic health records.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-29T04:22:49Z
      DOI: 10.1177/20552076241228024
      Issue No: Vol. 10 (2024)
       
  • Comparison of digital recruitment strategies for Alzheimer's disease
           patients

    • Authors: Carlos Perez-Heydrich, Courtney Walker, Macie Pile, Yuri Agrawal
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesClinical trials studying Alzheimer's Disease (AD) face the challenge of recruiting participants with significant barriers to entering research studies. The objective of this study is to compare digital recruitment strategies’ ability to recruit older adults with cognitive impairment (CI).MethodsOlder adults with CI were recruited for a clinical trial studying vestibular therapy in reducing falls and improving balance and cognition in older adults with CI. Potential participants were recruited via two different digital recruitment methods, a direct messaging campaign using established patient records and a social media campaign. Potential participants then filled out surveys to determine eligibility for the study.ResultsThe direct messaging campaign contacted 3060 potential participants and the social media campaign resulted in 8265 instances of unique engagement. Of the number of people reached, the direct messaging campaign had a higher percentage of people who submitted the survey compared to the social media campaign (8.3% vs. 1.2%, p  0.05). Direct messaging recruitment proved more cost-effective at $21.74 per eligible participant compared to the social media campaign at $859.58 per eligible participant.ConclusionThis study found that direct messaging recruitment using established patient records was more cost-effective compared to social media recruitment for this clinical trial. In this sample size, similar demographics were reached by both recruitment methods. Future studies should continue to explore the use of social media and alternative methods to recruit representative participant populations for ongoing AD research.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-27T07:17:03Z
      DOI: 10.1177/20552076241229164
      Issue No: Vol. 10 (2024)
       
  • Acceptability of the Long-Term In-Home Ventilator Engagement virtual
           intervention for home mechanical ventilation patients during the COVID-19
           pandemic: A qualitative evaluation

    • Authors: Craig M. Dale, Munazzah Ambreen, Sohee Kang, Francine Buchanan, Regina Pizzuti, Andrea S. Gershon, Louise Rose, Reshma Amin
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundClinical management of ventilator-assisted individuals (VAIs) was challenged by social distancing rules during the COVID-19 pandemic. In May 2020, the Long-Term In-Home Ventilator Engagement (LIVE) Program was launched in Ontario, Canada to provide intensive digital care case management to VAIs. The purpose of this qualitative study was to explore the acceptability of the LIVE Program hosted via a digital platform during the COVID-19 pandemic from diverse perspectives.MethodsWe conducted a qualitative descriptive study (May 2020–April 2021) comprising semi-structured interviews with participants from eight home ventilation specialty centers in Ontario, Canada. We purposively recruited patients, family caregivers, and providers enrolled in LIVE. Content analysis and the theoretical concepts of acceptability, feasibility, and appropriateness were used to interpret findings.ResultsA total of 40 individuals (2 VAIs, 18 family caregivers, 20 healthcare providers) participated. Participants described LIVE as acceptable as it addressed a longstanding imperative to improve care access, ease of use, and training provided; feasible for triaging problems and sharing information; and appropriate for timeliness of provider responses, workflows, and perceived value. Negative perceptions of acceptability among healthcare providers concerned digital workload and fit with existing clinical workflows. Perceived benefits accorded to LIVE included enhanced physical and psychological safety in the home, patient–provider relations, and VAI engagement in their own care.ConclusionsStudy findings identify factors influencing the LIVE Program's acceptability by patients, family caregivers, and healthcare providers during pandemic conditions including enhanced access to care, ease of case management triage, and VAI safety. Findings may inform the implementation of digital health services to VAIs in non-pandemic circumstances.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-27T07:16:44Z
      DOI: 10.1177/20552076241228417
      Issue No: Vol. 10 (2024)
       
  • Personalized and longitudinal electronic informed consent in clinical
           trials: How to move the needle'

    • Authors: Evelien De Sutter, Liese Barbier, Pascal Borry, David Geerts, John P.A. Ioannidis, Isabelle Huys
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      Changes in the clinical trials landscape have been driven by advancements in digital technology. The use of electronic informed consent to inform research participants and to obtain their consent electronically has the potential to improve participant–researcher interactions over time, facilitate clinical trial participation, and increase efficiency in clinical trial conduct. A personalized electronic informed consent platform that enables long-term interactions with the research team could function as a tool to empower participant engagement in clinical trials. However, significant challenges persist impeding successful and widespread implementation. This Perspective provides insights into the opportunities and challenges for the implementation of electronic informed consent in clinical trials. It sets out key recommendations to promote the implementation of this innovative approach to the informed consent process, including the creation of uniform electronic informed consent platforms at regional and national level.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-24T12:29:55Z
      DOI: 10.1177/20552076231222361
      Issue No: Vol. 10 (2024)
       
  • The development and validation of a digital biomarker for remote
           assessment of Alzheimer's diseases risk

    • Authors: Joe Butler, Tamlyn J Watermeyer, Ellie Matterson, Emily G Harper, Mario Parra-Rodriguez
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundDigital cognitive assessment is becoming increasingly widespread in ageing research and care, especially since the COVID-19 pandemic. Remote online collection provides opportunities for ageing and dementia professionals to collect larger datasets, increase the diversity of research participants and patients and offer cost-effective screening and monitoring methods for clinical practice and trials. However, the reliability of self-administered at-home tests compared to their lab-based counterparts often goes unexamined, compromising the validity of adopting such measures.ObjectiveOur aim is to validate a self-administered web-based version of the visual short-term memory binding task (VSTMBT), a potential digital biomarker sensitive to Alzheimer's disease processes, suitable for use on personal devices.MethodsA final cross-sectional sample of 37 older-adult (51–77 years) participants without dementia completed our novel self-administered version of the VSTMBT, both at home on a personal device and in the lab, under researcher-controlled conditions.ResultsANOVA and Bayesian t-test found no significant differences between the task when it was remotely self-administered by participants at home compared to when it was taken under controlled lab conditions.ConclusionsThese results indicate the VSTMBT can provide reliable data when self-administered at-home using an online version of the task and on a personal device. This finding has important implications for remote screening and monitoring practices of older adults, as well as supporting clinical practices serving diverse patient communities. Future work will assess remote administration in older adults with cognitive impairment and diverse socio-economic and ethno-cultural backgrounds as well as a bench-to-bedside application.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-24T06:40:26Z
      DOI: 10.1177/20552076241228416
      Issue No: Vol. 10 (2024)
       
  • Analysis of digital capacity-related factors influencing health promotion
           participation and active aging of older adults residing in rural areas in
           South Korea: A structural equation model

    • Authors: Hocheol Lee, Hae Kweun Nam, Bo Zhao, Hee Ra Jeong, Subean Lim, Ayoung Chun, Min Kyoung Kim, Dong Hyun Kim, Myo Nyein Aung, Yuka Koyanagi, Eun Woo Nam
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThis study aimed to identify the correlation between digital capacity, health promotion participation, and active aging of older people living in rural areas in South Korea to assess the factors influencing participation in programs for health promotion and active aging.MethodsData were collected through a 1:1 face-to-face survey using a structured questionnaire from 13 February to 24 February 2023 during the older individuals’ visits in the senior citizen welfare centers and senior citizen centers in the region. The Measuring Digital Skills questionnaire used to assess the digital competence of South Korean individuals was employed in this study. To confirm the structural relationship between digital capacity and health promotion participation and active aging in the older population aged 65 years and older based on the collected data, a structural equation modeling analysis was performed.ResultsActive health promotion participation had a positive effect on active aging. The pathway that older adults in Korea can led to participation in health promotion and active aging in the current situation is not mainly through the digital competency whereas mobile internet skill showed positive influneces. ConclusionsIn the digital era and super-aged society, various programs are provided to older individuals to enhance the utilization of smartphones. However, education and programs for strengthening digital capacity should be organized to explain the advantages of digital use and to inform of the dangers of addiction to ensure healthy aging through social participation and exchange both online and offline.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-23T11:22:08Z
      DOI: 10.1177/20552076241226958
      Issue No: Vol. 10 (2024)
       
  • Macro-engagement in mHealth: Exploring user engagement beyond the screen

    • Authors: Camila Villegas Mejía, Danielle Remmerswaal, Rutger C.M.E. Engels, Geke D.S. Ludden, Marilisa Boffo
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      While digital technology holds great promise for health and well-being, some users feel sceptical about the time they spend online and how they use their mobile devices. This attitude could hamper uptake of digital health technologies and engagement with them. This study uses the concept of macro-engagement as a starting point to investigate how users of digital behaviour change interventions (DBCIs) engage with their behaviour change goals beyond the screens of their tools. Thirty semi-structured interviews were conducted with individuals who take part in behaviour change processes in different ways (i.e. mental health professionals, digital health experts and users of DBCIs). A qualitative analysis of their data through a grounded theory approach highlighted a wide array of offscreen behaviors and strategies that complement a behavior change process offscreen. Furthermore, implications for designing technology that encourages progressive non-reliance on DBCI usage are drawn out.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-23T11:21:49Z
      DOI: 10.1177/20552076231225591
      Issue No: Vol. 10 (2024)
       
  • Navigating the asthma network on Twitter: Insights from social network and
           sentiment analysis

    • Authors: Hening Pratiwi, Ria Benkő, Ikhwan Yuda Kusuma
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundAsthma is a condition in which the airways become inflamed and constricted, causing breathing difficulties, wheezing, coughing, and chest tightness. Social networks can have a substantial effect on asthma management and results. However, no studies of social networks addressing asthma have been undertaken.ObjectiveThe aim of this research was to identify the significant social network structures, key influencers, top topics, and sentiments of asthma-related Twitter conversations.MethodsAll the tweets collected for this study included the keyword “asthma” or were mentioned in or in replies to tweets that were performed. For this study, a random sample of Twitter data was collected using NodeXL Pro software between December 1, 2022, and January 29, 2023. The data collected includes the user's display name, Twitter handle, tweet text, and the tweet's publishing date and time. After being imported into the Gephi application, the NodeXL data were then shown using the Fruchterman-Reingold layout method. In our study, SNA (Social Network Analysis) metrics were utilized to identify the most popular subject using hashtags, sentiment-related phrases (positive, negative, or neutral), and top influencer by centrality measures (degree, betweenness).ResultsThe study collected 48,122 tweets containing the keyword “asthma” or mentioned in replies. News reporters and journalists emerged as top influencers based on centrality measures in Twitter conversations about asthma, followed by government and healthcare institutions. Education, trigger factors (e.g., cat exposure, diet), and associated conditions were highly discussed topics on asthma-related social media posts (e.g., sarscov2, copd). Our study's sentiment analysis revealed that there were 8427 phrases associated neutral comments (18%), 12,582 words reflecting positive viewpoints (26%), and 27,111 words reflecting negative opinions (56%).ConclusionThis study investigates the relevance of social media influencers, news reporters, health experts, health organizations, and the government in the dissemination and promotion of asthma-related education and awareness during public health information.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-23T05:51:15Z
      DOI: 10.1177/20552076231224075
      Issue No: Vol. 10 (2024)
       
  • Development of blood demand prediction model using artificial intelligence
           based on national public big data

    • Authors: Hi Jeong Kwon, Sholhui Park, Young Hoon Park, Seung Min Baik, Dong Jin Park
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveModern healthcare systems face challenges related to the stable and sufficient blood supply of blood due to shortages. This study aimed to predict the monthly blood transfusion requirements in medical institutions using an artificial intelligence model based on national open big data related to transfusion.MethodsData regarding blood types and components in Korea from January 2010 to December 2021 were obtained from the Health Insurance Review and Assessment Service and Statistics Korea. The data were collected from a single medical institution. Using the obtained information, predictive models were developed, including eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), and category boosting (CatBoost). An ensemble model was created using these three models.ResultsThe prediction performance of XGBoost, LGBM, and CatBoost demonstrated a mean absolute error ranging from 14.6657 for AB+ red blood cells (RBCs) to 84.0433 for A+ platelet concentrate (PC) and a root mean squared error ranging from 18.5374 for AB+ RBCs to 118.6245 for B+ PC. The error range was further improved by creating ensemble models, wherein the department requesting blood was the most influential parameter affecting transfusion prediction performance for different blood products and types. Except for the department, the features that affected the prediction performance varied for each product and blood type, including the number of RBC antibody screens, crossmatch, nationwide blood donations, and surgeries.ConclusionBased on blood-related open big data, the developed blood-demand prediction algorithm can efficiently provide medical facilities with an appropriate volume of blood ahead of time.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-18T12:19:47Z
      DOI: 10.1177/20552076231224245
      Issue No: Vol. 10 (2024)
       
  • Deep convolutional neural network and IoT technology for healthcare

    • Authors: Sobia Wassan, Hu Dongyan, Beenish Suhail, N.Z. Jhanjhi, Guanghua Xiao, Suhail Ahmed, Raja Kumar Murugesan
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundDeep Learning is an AI technology that trains computers to analyze data in an approach similar to the human brain. Deep learning algorithms can find complex patterns in images, text, audio, and other data types to provide accurate predictions and conclusions. Neuronal networks are another name for Deep Learning. These layers are the input, the hidden, and the output of a deep learning model. First, data is taken in by the input layer, and then it is processed by the output layer. Deep Learning has many advantages over traditional machine learning algorithms like a KA-nearest neighbor, support vector algorithms, and regression approaches. Deep learning models can read more complex data than traditional machine learning methods.ObjectivesThis research aims to find the ideal number of best-hidden layers for the neural network and different activation function variations. The article also thoroughly analyzes how various frameworks can be used to create a comparison or fast neural networks. The final goal of the article is to investigate all such innovative techniques that allow us to speed up the training of neural networks without losing accuracy.MethodsA sample data Set from 2001 was collected by www.Kaggle.com. We can reduce the total number of layers in the deep learning model. This will enable us to use our time. To perform the ReLU activation, we will make use of two layers that are completely connected. If the value being supplied is larger than zero, the ReLU activation will return 0, and else it will output the value being input directly.ResultsWe use multiple parameters to determine the most effective method to test how well our method works. In the next paragraph, we'll discuss how the calculation changes secret-shared Values. By adopting 19 train set features, we train our reliable model to predict healthcare cost's (numerical) target feature. We found that 0.89503 was the best choice because it gave us a good fit (R2) and let us set enough coefficients to 0. To develop our stable model with this Set of parameters, we require 26 iterations. We use an R2 of 0.89503, an MSE of 0.01094, an RMSE of 0.10458, a mean residual deviance of 0.01094, a mean absolute error of 0.07452, and a root mean squared log error of 0.07207. After training the model on the train set, we applied the same parameters to the test set and obtained an R2 of 0.90707, MSE of 0.01045, RMSE of 0.10224, mean residual deviation of 0.01045, MAE of 0.06954, and RMSE of 0.07051, validating our solution approach. The objective value of our secured model is higher than that of the scikit-learn model, although the former performs better on goodness-of-fit criteria. As a result, our protected model performs quite well, marginally outperforming the (very optimized) scikit-learn model. Using a backpropagation algorithm and stochastic gradient descent, deep Learning develops artificial neural systems with several interconnected layers. There may be hidden layers of neurons in the network that have the tanh, rectification, and max-out hyperparameters. Modern features like momentum training, dropout, active learning rate, rate annealed, and L1 or L2 regularization provide exceptional prediction performance. The worldwide model's parameters are multi-threadedly (asynchronously) trained on the data from that node, and the model-based data is then gradually augmented by model averaging over the entire network. The method is executed on a single-node, direct H2O cluster initiated by the operator. The operation is parallel despite there just being a single node involved. The number of threads may be adjusted in the settings menu under Preferences and General. The optimal number of threads for the system is used automatically. Successful predictions in the healthcare data sets are made using the H2O Deep Learning operator. There will be a classification done since its label is binomial. The Splitting Validation operator creates test and training datasets to evaluate the model. By default, the settings of the Deep Learning activator are used. To put it another way, we'll construct two hidden layers, each containing 50 neurons. The Accuracy measure is computed by linking the annotated Sample Set with a Performer (Binominal Classification) operator. Table 3 displays the Deep Learning Model, the labeled data, and the Performance Vector that resulted from the technique.ConclusionsDeep learning algorithms can be used to design systems that report data on patients and deliver warnings to medical applications or electronic health information if there are changes in the patient's health. These systems could be created using deep Learning. This helps verify that patients get the proper effective care at the proper time for each specific patient. A healthcare decision support system was presented using the Internet of Things and deep learning methods. In the proposed system, we examined the capability of integrating deep learning technology into automatic diagnosis and IoT capabilities for faster message exchange over the Internet. We have selected the suitable Neural Network structure (number of best-hidden layers and activation function classes) to construct the e-health system. In addition, the e-health system relied on data from doctors to understand the Neural Network. In the validation method, the total evaluation of the proposed healthcare system for diagnostics provides dependability under various patient conditions. Based on evaluation and simulation findings, a dual hidden layer of feed-forward NN and its neurons store the tanh function more effectively than other NN. To overcome challenges, this study will integrate artificial intelligence with IoT. This study aims to determine the NN's optimal layer counts and activation function variations.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-18T12:19:29Z
      DOI: 10.1177/20552076231220123
      Issue No: Vol. 10 (2024)
       
  • Barriers and facilitators of health professionals in adopting digital
           health-related tools for medication appropriateness: A systematic review

    • Authors: Daniela A. Rodrigues, Maria Roque, Ramona Mateos-Campos, Adolfo Figueiras, Maria Teresa Herdeiro, Fátima Roque
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveDigital health is described as the use and development of all types of digital technologies to improve health outcomes. It could be used to prevent medication errors, a priority for health systems worldwide. However, the adoption of such tools remains slow. This study aims to identify factors (attitudes, knowledge and beliefs) acting as barriers and/or facilitators reported by healthcare professionals (HCPs) for the adoption of digital health-related tools for medication appropriateness.MethodsA systematic review was performed by searching the literature in the MEDLINE PubMed, and EMBASE scientific databases for original articles regarding qualitative and quantitative data.ResultsFifteen articles were included and a total of 125 barriers and 108 facilitators were identified, consolidated and categorized into technical (n = 48), organizational (n = 12), economical (n = 4), user-related (n = 34), and patient-related (n = 8) components. The most often reported barriers and facilitators were technical component-related ones concerning the need for additional training (n = 6), the time consumed (n = 6), and the easy way of using or learning how to use the tools (n = 9), respectively. Regarding setting analysis, agreement with clinical decision recommendations and impact on the doctor–patient relationship were more valued in primary care, while the user interface and system design were in the hospital.ConclusionsThe barriers and facilitators identified in this study provide relevant information to developers and it can be used as a starting point for the designing of successful digital health-related tools, specifically related to medication appropriateness. Future research includes economic evaluation-focused studies and in-depth case studies of specific barriers and facilitators.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-18T07:28:02Z
      DOI: 10.1177/20552076231225133
      Issue No: Vol. 10 (2024)
       
  • Reliability of ChatGPT for performing triage task in the emergency
           department using the Korean Triage and Acuity Scale

    • Authors: Jae Hyuk Kim, Sun Kyung Kim, Jongmyung Choi, Youngho Lee
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundArtificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings.ObjectiveThis study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS).MethodsTwo hundred and two virtual patient cases were built. The gold standard triage classification for each case was established by an experienced ED physician. Three other human raters (ED paramedics) were involved and rated the virtual cases individually. The virtual cases were also rated by two different versions of the chat generative pre-trained transformer (ChatGPT, 3.5 and 4.0). Inter-rater reliability was examined using Fleiss’ kappa and intra-class correlation coefficient (ICC).ResultsThe kappa values for the agreement between the four human raters and ChatGPTs were .523 (version 4.0) and .320 (version 3.5). Of the five levels, the performance was poor when rating patients at levels 1 and 5, as well as case scenarios with additional text descriptions. There were differences in the accuracy of the different versions of GPTs. The ICC between version 3.5 and the gold standard was .520, and that between version 4.0 and the gold standard was .802.ConclusionsA substantial level of inter-rater reliability was revealed when GPTs were used as KTAS raters. The current study showed the potential of using GPT in emergency healthcare settings. Considering the shortage of experienced manpower, this AI method may help improve triaging accuracy.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-18T06:27:51Z
      DOI: 10.1177/20552076241227132
      Issue No: Vol. 10 (2024)
       
  • Gluten-free diet on video platforms: Retrospective infodemiology study

    • Authors: Chen Ye, Yuehui Fang, Yiyao Lian, Yuna He
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundVideo platform is an important approach for individuals to access and adopt health information. Online information on gluten-free diet (GFD) videos remains underinvestigated.MethodsGFD videos were identified by hashtag-based searching strategy. Videos' basic information, engagement metrics, and content were recorded. Mann-Kendall test was performed to examine time trends of submitting videos and engagement metrics. Video quality was evaluated by the DISCERN instrument and the HONcode.ResultsA total of 822 videos were included in the analysis, with the majority focusing on gluten-free food recipes. The number of videos related to GFD was showing an upward trend. Engagement metrics varied between platforms and video types, with non-recipe videos receiving higher user engagement. The average DISCERN score was 50.20 out of 80 and the average HONcode score was 1.93 out of 8. Videos submitted by health professionals demonstrated better quality compared to those submitted by patients or general users.ConclusionThere was a rise in the number of videos related to GFD on Chinese video platforms. The overall quality of these videos was poor, most of them were not rigorous enough. Highlighting using social media as a health information source has the potential risk of disseminating one-sided messages and misleading. Efforts should be made to enhance the transparency of advertisements and establish clear guidelines for information sharing on social media platforms.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-16T03:28:39Z
      DOI: 10.1177/20552076231224594
      Issue No: Vol. 10 (2024)
       
  • Designing technology to support greater participation of people living
           with dementia in daily and meaningful activities

    • Authors: Michael Wilson, Julie Doyle, Jonathan Turner, Ciaran Nugent, Dympna O’Sullivan
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundPeople living with dementia should be at the center of decision-making regarding their plans and goals for daily living and meaningful activities that help promote health and mental well-being. The human–computer interaction community has recently begun to recognize the need to design technologies where the person living with dementia is an active rather than a passive user of technology in the management of their care.MethodsData collection comprised semi-structured interviews and focus groups held with dyads of people with early-stage dementia (n = 5) and their informal carers (n = 4), as well as health professionals (n = 5). This article discusses findings from the thematic analysis of this qualitative data.ResultsAnalysis resulted in the construction of three main themes: (1) maintaining a sense of purpose and identity, (2) learning helplessness and (3) shared decision-making and collaboration. Within each of the three main themes, related sub-themes were also constructed.DiscussionThere is a need to design technologies for persons living with dementia/carer dyads that can support collaborative care planning and engagement in meaningful activities while also balancing persons living with dementia empowerment and active engagement in self-management with carer support.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-16T03:27:39Z
      DOI: 10.1177/20552076231222427
      Issue No: Vol. 10 (2024)
       
  • Usability study of SOSteniamoci: An internet-based intervention platform
           to support informal caregivers in Italy

    • Authors: Michelle Semonella, Gloria Marchesi, Gerhard Andersson, Rachel Dekel, Giada Pietrabissa, Noa Vilchinsky
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundProviding informal care can be experienced as stressful and lead to caregiver burden. Internet-based interventions, a specific form of eHealth, have proven to be a good option to support informal caregivers. SOSteniamoci, an internet-based intervention already tested in Lithuania, was translated and adapted for Italian caregivers.ObjectiveAs many novel eHealth solutions have been rejected by end-users due to usability problems, we aimed to evaluate the usability of the adapted platform, using a computer-based prototype.MethodsThe following methods and metrics were applied: 1. task analysis, using audio and video recordings that included three usability metrics: task completion rate, frequency of errors, and frequency of help requests; 2. the system usability scale (SUS); and 3. a semi-structured interview to collect additional data about the system's design and overall satisfaction.ResultsTen informal caregivers (60% female; age M = 47.8, SD = 15.21) provided insights and suggestions for increasing the usability of the platform. The platform was considered satisfactory, with a mean score on the SUS of 75 (SD = 13.07) out of 100. The task analysis measurements highlighted difficulties in how to log in to the platform, understanding what the intervention is about, and texting the therapist. The same difficulties were also mentioned during the post-experience interview. Thus, improvements were subsequently made to enhance users’ experience when navigating the platform. Finally, the platform overall was found to be intuitive and friendly, and the contents were appreciated.ConclusionTo maintain participants’ engagement and prevent drop-out, it is crucial to test the usability of internet-based interventions. Even though the platform proved to be user-friendly, intuitive and easy to use, several enhancements were implemented based on participants’ feedback. Thus, the usability of internet-based interventions should be tested, and end-users must be involved in the development process of such solutions.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-16T02:03:18Z
      DOI: 10.1177/20552076231225082
      Issue No: Vol. 10 (2024)
       
  • Interpretable machine learning for predicting chronic kidney disease
           progression risk

    • Authors: Jin-Xin Zheng, Xin Li, Jiang Zhu, Shi-Yang Guan, Shun-Xian Zhang, Wei-Ming Wang
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveChronic kidney disease (CKD) poses a major global health burden. Early CKD risk prediction enables timely interventions, but conventional models have limited accuracy. Machine learning (ML) enhances prediction, but interpretability is needed to support clinical usage with both in diagnostic and decision-making.MethodsA cohort of 491 patients with clinical data was collected for this study. The dataset was randomly split into an 80% training set and a 20% testing set. To achieve the first objective, we developed four ML algorithms (logistic regression, random forests, neural networks, and eXtreme Gradient Boosting (XGBoost)) to classify patients into two classes—those who progressed to CKD stages 3–5 during follow-up (positive class) and those who did not (negative class). For the classification task, the area under the receiver operating characteristic curve (AUC-ROC) was used to evaluate model performance in discriminating between the two classes. For survival analysis, Cox proportional hazards regression (COX) and random survival forests (RSFs) were employed to predict CKD progression, and the concordance index (C-index) and integrated Brier score were used for model evaluation. Furthermore, variable importance, partial dependence plots, and restrict cubic splines were used to interpret the models’ results.ResultsXGBOOST demonstrated the best predictive performance for CKD progression in the classification task, with an AUC-ROC of 0.867 (95% confidence interval (CI): 0.728–0.100), outperforming the other ML algorithms. In survival analysis, RSF showed slightly better discrimination and calibration on the test set compared to COX, indicating better generalization to new data. Variable importance analysis identified estimated glomerular filtration rate, age, and creatinine as the most important predictors for CKD survival analysis. Further analysis revealed non-linear associations between age and CKD progression, suggesting higher risks in patients aged 52–55 and 65–66 years. The association between cholesterol levels and CKD progression was also non-linear, with lower risks observed when cholesterol levels were in the range of 5.8–6.4 mmol/L.ConclusionsOur study demonstrated the effectiveness of interpretable ML models for predicting CKD progression. The comparison between COX and RSF highlighted the advantages of ML in survival analysis, particularly in handling non-linearity and high-dimensional data. By leveraging interpretable ML for unraveling risk factor relationships, contrasting predictive techniques, and exposing non-linear associations, this study significantly advances CKD risk prediction to enable enhanced clinical decision-making.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-16T01:56:59Z
      DOI: 10.1177/20552076231224225
      Issue No: Vol. 10 (2024)
       
  • Digital health and patient adherence: A qualitative study in older adults

    • Authors: Filipa Ferreira-Brito, Sérgio Alves, Tiago Guerreiro, Osvaldo Santos, Cátia Caneiras, Luís Carriço, Ana Verdelho
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      IntroductionComputer confidence and computer self-efficacy can impact an individual's perceived ease of use and usefulness of technology, ultimately determining adherence to digital healthcare services. However, few studies focus on assessing the impact of non-clinical factors on the efficacy and adherence to digital healthcare platforms.ObjectiveWe aimed to analyse the role of non-clinical factors (i.e. computer confidence and computer self-efficacy) in the interaction experience (IX) and the feasibility of a digital neuropsychological platform called NeuroVRehab.PT in a group of older adults with varying levels of computer confidence.MethodsEight older adults (70.63 ± 6.1 years) evaluated the platform, and data was collected using the Think-Aloud method and a semi-structured interview. Sessions were audio-recorded and analysed through an inductive-deductive informed Thematic Analysis protocol. This study was conducted according to the Consolidated Criteria for Reporting Qualitative Research guidelines.ResultsThree main themes were identified (Interaction Experience, Digital Literacy, and Attitudes toward NeuroVRehab.PT). Computer anxiety and fear of making errors were not uncommon, even among older adults who perceive themselves as confident in technology use, and negatively impacted IX. Moreover, some game elements (e.g. three-star system, progression bar) were not intuitive to all participants, leading to misleading interpretations. On the other hand, human support and the platform's realism seemed to impact participants’ IX positively.ConclusionsThis study shed light on the barriers raised by non-clinical factors in adopting and using digital healthcare services by older adults. Furthermore, a critical analysis of the platform's features that promote user adoption is done, and suggestions for overcoming limitations are presented.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-12T08:34:46Z
      DOI: 10.1177/20552076231223805
      Issue No: Vol. 10 (2024)
       
  • Technology adoption of electronic medical records in developing economies:
           A systematic review on physicians’ perspective

    • Authors: Karyl Claire Derecho, Rentor Cafino, Sarah Lizette Aquino-Cafino, Armando Isla, Jay Ar Esencia, Nove Joshua Lactuan, Jiddo Andrei G Maranda, Lemuel Clark P Velasco
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      Electronic Medical Records (EMRs) are a tool that could potentially improve the outcomes of patient care by providing physicians with access to up-to-date and accurate vital patient information. Despite this potential, EMR adoption in developing economies has been dilatory. This systematic review aims to synthesize the related literature on the adoption of EMRs in developing economies, with a focus on the perspective of physicians. With the aim to discern the key factors that impact EMR adoption as perceived by physicians and to offer guidance for future research on filling any gaps identified in the existing literature, this study utilized a systematic literature review by following the PRISMA guidelines. Out of 1160 initial articles, 21 were selected for analysis after eliminating duplicates and non-qualifying articles. Results show that common enablers of EMR adoption from physicians’ perspective were identified to be computer literacy, education, voluntariness, and the system functionality including its features and user interface, implying that the provision of proper interventions focusing on the aspects of the health information system has an impact in maximizing the utilization and capabilities of EMRs among healthcare providers. The most prevalent barriers include the lack of training and IT usage experience along with resistance to changes associated with respondents’ age and gender, the lack of time for learning complex EMR systems, and costs of the new technology. This indicates that a thorough planning and proper budget allocation is necessary prior to implementing and integrating EMR systems in healthcare institutions. From this synthesis of the common research conclusions, limitations, and recommendations from physicians’ perspective, the result of this systematic review is expected to shed light on the optimal technology adoption of EMRs and its contribution to the health care systems of developing economies.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-12T05:20:30Z
      DOI: 10.1177/20552076231224605
      Issue No: Vol. 10 (2024)
       
  • Providing compassionate care in a virtual context: Qualitative exploration
           of Canadian primary care nurses’ experiences

    • Authors: Geneviève Rouleau, Kelly Wu, Monica Parry, Lauralie Richard, Laura Desveaux
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveVirtual care presents a promising opportunity to create new communication channels and increase access to healthcare. However, concerns have been raised around the potential for unintended emotional distances created through virtual care environments that could strain patient–provider relationships. While compassionate care is an enabler of emotional connectivity and a core tenant of nursing, little is known about whether or how nurses have adapted their compassion skills into virtual interactions. These concerns are particularly relevant in primary care, where there is a focus on relational continuity (i.e. relationship-based, longitudinal care) and a broad uptake of virtual care. The aim of this study was to explore the meaning of compassionate virtual care and to uncover how nurses operationalized compassionate care through virtual interactions in primary care.MethodsWe used a qualitative interpretive descriptive lens to conduct semistructured interviews with primary care nurses (Ontario, Canada) who had provided virtual care (i.e. video visits, remote patient monitoring, or asynchronous messaging). We used a thematic approach to analyze the data.ResultsWe interviewed 18 nurse practitioners and two registered nurses. Participants described how: (1) compassionate care was central to nursing practice, (2) compassionate care was evolving through virtual nurse–patient interaction, and (3) nurses balanced practice with patients’ expectations while providing virtual compassionate care.ConclusionsThere is an opportunity to better align nurses’ understanding and operationalization of compassionate care in virtual primary care contexts. Exploring how compassionate care is operationalized in primary care settings is a necessary first step to building compassionate competencies across the nursing profession to support the continued virtual evolution of health service delivery.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-10T07:59:06Z
      DOI: 10.1177/20552076231224072
      Issue No: Vol. 10 (2024)
       
  • Proxy use of patient portals on behalf of children: Federally Qualified
           Health Centers as a case study

    • Authors: Patrick Dang, Arlette Chavez, Cecilia Pham, Mary Tipton, LeChauncy D Woodard, Omolola E Adepoju
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThis study examined the proxy use of patient portals for children in a large Federally Qualified Health Centers (FQHC) network in Texas.MethodsWe used de-identified individual-level data of patients, 0–18 years, who had 1+ visits between December 2018 and November 2020. Logistic regression was used to examine patient-, clinic-, and geographic-level factors associated with portal usage by an assumed proxy (i.e. parent or guardian).ResultsThe proxy portal usage rate increased from 28% in the pre-pandemic months (November 2018–February 2020) to 34% in the pandemic months (March–Nov 2020). Compared to patients 0–5 years, patients aged 6 to 18 years had lower odds of portal usage (6–10 OR: 0.77, p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-10T06:53:42Z
      DOI: 10.1177/20552076231224073
      Issue No: Vol. 10 (2024)
       
  • Digital therapeutics-based lumbar core exercise for patients with low back
           pain: A prospective exploratory pilot study

    • Authors: Seong Son, Byung Rhae Yoo, Yu Mi Jeong
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThis study aimed to implement a digital therapeutics-based approach based on motion detection technology and analyze the clinical results for patients with chronic low back pain (LBP).MethodsA prospective, single-arm clinical trial was conducted with 22 patients who performed mobile app-based sitting core twist exercise for 12 weeks. Clinical outcomes were assessed using the visual analog scale (VAS) for LBP, Oswestry Disability Index-Korean version (K-ODI), and EuroQol-5 dimension 5-level version (EQ-5D-5L) every 4 weeks after the initiation of treatment. Laboratory tests for factors associated with muscle metabolism, plain X-ray for evaluating sagittal balance, and magnetic resonance imaging for calculating cross-sectional area (CSA) of back muscles were performed at pretreatment and 12 weeks post-treatment.ResultsThe study population included 20 female patients with an average age of 45.77 ± 15.45 years. The clinical outcomes gradually improved throughout the study period in the VAS for LBP (from 6.05 ± 2.27 to 2.86 ± 1.86), K-ODI (from 16.18 ± 6.19 to 8.64 ± 5.58), and EQ-5D-5L (from 11.09 ± 3.24 to 7.23 ± 3.89) (p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-10T06:52:41Z
      DOI: 10.1177/20552076231218154
      Issue No: Vol. 10 (2024)
       
  • A randomized waitlist control trial of the Make the Connection® online
           program for caregivers of infants and young children: Study protocol

    • Authors: Sophie Barriault, Audrey-Ann Deneault, Samantha Kempe, Sheri Madigan, Anne Lovegrove, Gina Dimitropoulos, Rebecca Pillai Riddell, Nicole Racine
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundA positive child-caregiver relationship is one of the strongest determinants of child health and development, yet many caregivers report challenges in establishing a positive relationship with their child. For over 20 years, Make the Connection® (MTC), an evidence-based parenting program, has been delivered in-person by child-caring professionals to over 120,000 parents to improve positive parenting behaviours and attitudes. Recently, MTC has been adapted into a ‘direct to caregiver’ online platform to increase scalability and accessibility. The purpose of this study is to evaluate the effectiveness of the online modality of MTC in increasing parenting knowledge, attitudes, and the perceived relationship with their child, and to understand barriers and facilitators to its access.MethodsTwo hundred caregivers with children aged 0-3 years old will be recruited through Public Health agencies in Ontario, Canada. Participants will be randomly placed in the intervention or waitlist control group. Both groups will complete a battery of questionnaires at study enrolment and 8 weeks later. The intervention group will receive the MTC online program during the 8-week period, while the waitlist group will receive the program after an 8-week wait. The study questionnaires will address demographic information, caregivers’ relational attitudes towards their infant, self-competence in their caregiver role, depression, and caregiver stress, as well as caregivers’ and infants’ emotion regulation.DiscussionResults from this study will add critical knowledge to the development, scaling, and roll out of the MTC online program, thus increasing its capacity to reach a greater number of families.Trial registrationThe study was registered with ClinicalTrials.gov on 15 March 2023 (NCT05770414).
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-10T06:02:47Z
      DOI: 10.1177/20552076231221053
      Issue No: Vol. 10 (2024)
       
  • Corrigendum to “A hybrid forecasting technique for infection and death
           from the mpox virus”

    • Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.

      Citation: DIGITAL HEALTH
      PubDate: 2024-01-09T12:11:56Z
      DOI: 10.1177/20552076231224117
      Issue No: Vol. 10 (2024)
       
  • Toward telemedical diagnostics—clinical evaluation of a robotic
           examination system for emergency patients

    • Authors: Maximilian Berlet, Jonas Fuchtmann, Roman Krumpholz, Abdeldjallil Naceri, Daniela Macari, Christoph Jähne-Schon, Sami Haddadin, Helmut Friess, Hubertus Feussner, Dirk Wilhelm
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      IntroductionThe SARS-CoV-2 pandemic has affected global public healthcare for several years. Numerous medical professionals have been infected since the outbreak in 2019, resulting in a shortage of healthcare providers. Since traditional personal protective wear was insufficient to eliminate the virus transmission reliably, new strategies to avoid cross-infection were imperative while enabling high-quality medical care. In the project ProteCT, we investigated the potential of robotic-assisted examination in providing medical examination via a telemedical approach.Material and MethodsWe constructed a fully functional examination cabin equipped with cameras, microphones, screens and robotic arms to evaluate usability and perception. Therefore, we conducted a preliminary study with 10 healthy volunteers and 10 physicians to gain first insights and optimize the setup. In a second step, we performed telemedical examinations of actual patients from the local emergency department to compare the robotic approach with the classical method of measuring vital signs, auscultation, palpation and percussion.ResultsThe preliminary study identified basic requirements, such as the need for force-feedback and telemedical training for physicians. In the main study, acceptance was high and most patients indicated they would use a telemedical system again. Our setup enabled the physician to make the same diagnoses as by classic examination in the emergency department in most cases.DiscussionThe potential acceptance of a telemedical system such as ProteCT is high. Robotic telemedical approaches could complement future healthcare beyond the Corona pandemic to reach rural areas or even war zones. Moreover, the daily clinical use of robotic telemedicine could improve patients’ safety, the quality of perioperative management and the workflow in any medical facility.ConclusionThe development of telemedical and telerobotic systems is a multidisciplinary and complex challenge. However, acceptance of the proposed system was high among patients and physicians, indicating the potential use of similar systems for future healthcare.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-09T09:28:01Z
      DOI: 10.1177/20552076231225084
      Issue No: Vol. 10 (2024)
       
  • Profiles of digital health literacy among university students and its
           association with mental health during the COVID-19 pandemic: A latent
           profile analysis

    • Authors: Liangwen Ning, Zhou Zheng, Minghui Liu, Shang Gao, Xin Yang, Jiasi Bi, Xihe Yu, Dahai Yi
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveInvestigating the digital health literacy of university students can facilitate their effective acquisition of health information and adoption of appropriate protective behaviors. This study aims to explore the subtypes of digital health literacy among university students during the COVID-19 pandemic and their association with mental health outcomes.MethodsFrom 17 November to 14 December 2022, a stratified random sampling approach was used to conduct an online questionnaire survey on digital health literacy, fear of COVID-19, and depression status among students at Jilin University, China. A total of 1060 valid responses were obtained in the survey. Latent profile analysis identified subtypes of digital health literacy and linear regression analyses were used to examine the association of digital health literacy to the mental health outcome.ResultsThree latent profiles were identified: Profile 1—low digital health literacy (n = 66, 6.23%), Profile 2—moderate digital health literacy (n = 706, 66.60%), and Profile 3—high digital health literacy (n = 288, 27.17%). Results from linear regression demonstrated a negative correlation between digital health literacy and fear of COVID-19 (B = −2.954, P 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-09T06:00:58Z
      DOI: 10.1177/20552076231224596
      Issue No: Vol. 10 (2024)
       
  • Predicting delirium and the effects of medications in hospitalized
           COVID-19 patients using machine learning: A retrospective study within the
           Korean Multidisciplinary Cohort for Delirium Prevention (KoMCoDe)

    • Authors: So Hee Lee, Hyun Jung Hur, Sung Nyun Kim, Jang Ho Ahn, Du Hyun Ro, Arum Hong, Hye Yoon Park, Pyoeng Gyun Choe, Back Kim, Hye Youn Park
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveDelirium is commonly reported from the inpatients with Coronavirus disease 2019 (COVID-19) infection. As delirium is closely associated with adverse clinical outcomes, prediction and prevention of delirium is critical. We developed a machine learning (ML) model to predict delirium in hospitalized patients with COVID-19 and to identify modifiable factors to prevent delirium.MethodsThe data set (n = 878) from four medical centers was constructed. Total of 78 predictors were included such as demographic characteristics, vital signs, laboratory results and medication, and the primary outcome was delirium occurrence during hospitalization. For analysis, the extreme gradient boosting (XGBoost) algorithm was applied, and the most influential factors were selected by recursive feature elimination. Among the indicators of performance for ML model, the area under the curve of the receiver operating characteristic (AUROC) curve was selected as the evaluation metric.ResultsRegarding the performance of developed delirium prediction model, the accuracy, precision, recall, F1 score, and the AUROC were calculated (0.944, 0.581, 0.421, 0.485, 0.873, respectively). The influential factors of delirium in this model included were mechanical ventilation, medication (antipsychotics, sedatives, ambroxol, piperacillin/tazobactam, acetaminophen, ceftriaxone, and propacetamol), and sodium ion concentration (all p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-05T09:27:54Z
      DOI: 10.1177/20552076231223811
      Issue No: Vol. 10 (2024)
       
  • ‘It would help people to help me’: Acceptability of digital
           phenotyping among young people with visual impairment and their families

    • Authors: Bethany Higgins, Lee Jones, Kishan Devraj, Caroline Kilduff, Mariya Moosajee
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesTo explore the acceptability of an eHealth App for vision-related monitoring and symptom reporting among young people with a visual impairment and their parents.MethodsQualitative investigation using virtual semi-structured focus groups (via Zoom software) of seven young participants with a genetic eye disorder including inherited retinal disease and structural eye abnormalities (e.g. microphthalmia), and 7 parents; all recruited from ocular genetic clinics at Moorfields Eye Hospital. Audio transcripts were analysed using thematic analysis.ResultsData were coded into six key themes: (1) increased involvement in care, (2) opportunity for less hospital-centric care, (3) better representation of visual impairment in a real-world setting, (4) trust in a reputable service provider, (5) harnessing data for health purposes and (6) intended purpose of the app. Both young people and their families were accepting of an eHealth app and felt they would be empowered by greater involvement in their care plan, if privacy of the data was retained, and information was managed correctly. While parents endorsed the opportunity for mental health tracking, young people were hesitant towards its inclusion.ConclusionIn summary, there was overall acceptability of an eHealth app among young people with a visual impairment and their parents. These findings will help to maximise the effective integration of digital phenotyping when monitoring and supporting young people experiencing sight loss.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-05T09:25:22Z
      DOI: 10.1177/20552076231220804
      Issue No: Vol. 10 (2024)
       
  • Performance of ChatGPT incorporated chain-of-thought method in bilingual
           nuclear medicine physician board examinations

    • Authors: Yu-Ting Ting, Te-Chun Hsieh, Yuh-Feng Wang, Yu-Chieh Kuo, Yi-Jin Chen, Pak-Ki Chan, Chia-Hung Kao
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThis research explores the performance of ChatGPT, compared to human doctors, in bilingual, Mandarin Chinese and English, medical specialty exam in Nuclear Medicine in Taiwan.MethodsThe study employed generative pre-trained transformer (GPT-4) and integrated chain-of-thoughts (COT) method to enhance performance by triggering and explaining the thinking process to answer the question in a coherent and logical manner. Questions from the Taiwanese Nuclear Medicine Specialty Exam served as the basis for testing. The research analyzed the correctness of AI responses in different sections of the exam and explored the influence of question length and language proportion on accuracy.ResultsAI, especially ChatGPT with COT, exhibited exceptional capabilities in theoretical knowledge, clinical medicine, and handling integrated questions, often surpassing, or matching human doctor performance. However, AI struggled with questions related to medical regulations. The analysis of question length showed that questions within the 109–163 words range yielded the highest accuracy. Moreover, an increase in the proportion of English words in questions improved both AI and human accuracy.ConclusionsThis research highlights the potential and challenges of AI in the medical field. ChatGPT demonstrates significant competence in various aspects of medical knowledge. However, areas like medical regulations require improvement. The study also suggests that AI may help in evaluating exam question difficulty and maintaining fairness in examinations. These findings shed light on AI role in the medical field, with potential applications in healthcare education, exam preparation, and multilingual environments. Ongoing AI advancements are expected to further enhance AI utility in the medical domain.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-05T08:17:42Z
      DOI: 10.1177/20552076231224074
      Issue No: Vol. 10 (2024)
       
  • Clinical human activity recognition based on a wearable patch of combined
           tri-axial ACC and ECG sensors

    • Authors: Yanling Ren, Minqi Liu, Ying Yang, Ling Mao, Kai Chen
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundIn digital medicine, human activity recognition (HAR) can be used to track and assess a patient's progress throughout rehabilitation, enhancing the quality of life for the elderly and the disabled.MethodsA patch-type flexible sensor that integrated dynamic electrocardiogram (ECG) and acceleration signal (ACC) was used to record the signals of the various behavioral activities of 20 healthy volunteers and 25 patients with pneumoconiosis. Seven HAR tasks were then carried out on the data using four different deep learning methods (CNN, LSTM, CNN–LSTM and GRU).ResultsWhen ECG and ACC were obtained simultaneously, the overall accuracy rates of HAR for healthy group were 0.9371, 0.8829, 0.9843 and 0.9486 by the CNN, LSTM, CNN–LSTM and GRU models, respectively. In contrast, the overall accuracy rates of HAR for the pneumoconiosis patients’ group were 0.8850, 0.7975, 0.9425 and 0.8525 by the four corresponding models. The accuracy of HAR for both groups using all four models is higher than when only ACC signal is detected.ConclusionThe addition of the ECG signal significantly improves HAR outcomes in the group of healthy individuals, while having relatively less enhancing effects on the group of patients with pneumoconiosis. When ECG and ACC signals were combined, the increase in HAR accuracy was notable compared to cases where no ECG data was provided. These results suggest that the combination of ACC and ECG data can represent a novel method for the clinical application of HAR.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-05T01:44:59Z
      DOI: 10.1177/20552076231223804
      Issue No: Vol. 10 (2024)
       
  • ‘It's not everybody's snapshot. It's just an insight into that world’:
           A qualitative study of multiple perspectives towards understanding the
           mental health experience and addressing stigma in healthcare students
           through virtual reality

    • Authors: Raul Szekely, Oliver Mason, David Frohlich, Elizabeth Barley
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThe resurgence of virtual reality (VR) technologies has led to their increased use in contemporary healthcare education. One promising application is simulating the experiences of individuals with mental health conditions (MHCs) to reduce stigma among future healthcare professionals. This study set out to explore what those impacted by, or involved in, the education of healthcare students think about using VR in this way.MethodsOne individual interview and five focus groups were conducted with healthcare students (n = 7), healthcare educators (n = 6), and lived experience experts (n = 5). Before sharing their perspectives, participants familiarised themselves with VR equipment and immersive materials simulating MHCs. The constant comparative method and thematic analysis were used to analyse the data.ResultsParticipants recognised the acceptability and utility of VR for addressing mental health stigma in healthcare students, emphasising the immersive nature of this technology. However, some participants raised concerns about the limited insight VR could provide into the experiences of patients with the same MHCs and its potential emotional impact on users. Participants recommended the incorporation of interactive, realistic environments with a person-centred focus into future VR-based stigma reduction interventions while stressing the importance of providing healthcare students with opportunities for reflection and support.ConclusionsHealthcare students, healthcare educators, and lived experience experts highlighted both advantages and barriers associated with using VR to understand the experience of patients with MHCs. Furthermore, the recommendations put forward can inform the design, content, and delivery of VR-based stigma reduction interventions in healthcare education.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-04T08:09:06Z
      DOI: 10.1177/20552076231223801
      Issue No: Vol. 10 (2024)
       
  • Drivers and barriers of patients’ acceptance of video consultation
           in cancer care

    • Authors: Angelina Nurtsch, Martin Teufel, Lisa Maria Jahre, André Esber, Raya Rausch, Mitra Tewes, Christoph Schöbel, Stefan Palm, Martin Schuler, Dirk Schadendorf, Eva-Maria Skoda, Alexander Bäuerle
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundDue to digitization in the medical sector, many healthcare interactions are switched to online services. This study assessed the acceptance of video consultations (VCs) in cancer care, and determined drivers and barriers of acceptance.MethodsA cross-sectional online-based survey study was conducted in Germany from February 2022 to February 2023. Recruitment took place at oncology outpatient clinics, general practitioners, oncology practices and via cancer-related social media channels. Inclusion criteria were a cancer diagnosis, cancer treatment and internet access. Sociodemographic, medical data, eHealth-related data were acquired via an online assessment. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to determine the acceptance of VC and its predictors.ResultsOf N = 350 cancer patients, 56.0% (n = 196) reported high acceptance of VC, 28.0% (n = 98) stated moderate acceptance and 16.0% (n = 56) indicated low acceptance. Factors influencing acceptance were younger age (β = –.28, p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-04T08:08:26Z
      DOI: 10.1177/20552076231222108
      Issue No: Vol. 10 (2024)
       
  • Validity and reliability of the Chinese version of digital health
           readiness questionnaire among hypertension patients in rural areas of
           China

    • Authors: Linqi Xu, Tianzhuo Yu, Xin Leng, Tianyue Yu, Martijn Scherrenberg, Maarten Falter, Toshiki Kaihara, Sevda Ece Kizilkilic, Hanne Van Erum, Hanne Kindermans, Paul Dendale, Qian Tong, Feng Li
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      IntroductionDigital health has the potential to support health care in rural areas by overcoming the problems of distance and poor infrastructure, however, rural areas have extremely low use of digital health because of the lack of interaction with technology. There is no existing tool to measure digital health literacy in rural China. This study aims to test and validate the digital health readiness questionnaire for assessing digital readiness among patients in rural China.MethodsDue to the different Internet environments in China compared to Belgium, a cultural adaptation is needed to optimize the use of Digital Health Readiness Questionnaire in China. Then, a prospective single-center survey study was conducted in rural China among patients with hypertension. Confirmatory factor analysis was computed to test the measurement models.ResultsA total of 330 full questionnaires were selected and included in the analysis. The model-fit measures were used to assess the model's overall goodness of fit (Chi-square/degrees of freedom = 5.060, comparative fit index = 0.889, Tucker–Lewis index (TLI) = 0.869, root mean square error of approximation (RMSEA) = 0.111, standardized root mean square residual (SRMR) = 0.0880). TLI is a little bit lower than the borderline (more than 0.9) and RMSEA is higher than it (less than 0.08 means good model fit). We deleted two items 2 and 4 and the result shows a better goodness of fit (Chi-square/degrees of freedom = 4.897, comparative fit index = 0.914, TLI = 0.895, RMSEA = 0.109, SRMR = 0.0765)ConclusionTo increase applicability and generalizability in rural areas, it should be considered to use the calculation of only the parts Digital skills, Digital literacy and Digital health literacy which are equally applicable in a Belgian population as in a rural Chinese population.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-04T08:07:47Z
      DOI: 10.1177/20552076231216604
      Issue No: Vol. 10 (2024)
       
  • Do hospital data breaches affect health information technology
           investment'

    • Authors: Jinhyung Lee, Hyeyeong Kim, Sung J Choi
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectivesData breaches are a financial and operational threat to hospitals. In this study, we examine the association between a data breach and information technology capital and labor investment.MethodsIn this retrospective cohort study, we used American Hospital Association data from 2017 to 2019 and an unbalanced panel of hospitals with 6751 unique hospital-year observations. The breached group had 482 hospital-years, and the control group had 6269 hospital-years. We estimated the association between data breaches, information technology capital, and labor investment using the average treatment effect with propensity-score matching.ResultsFrom 2017 to 2019, hospitals experienced more hacking and information technology incidents but fewer thefts and losses. We found that hospital data breaches were associated with a 66% increase in employed information technology staff and a 57% increase in outsourced information technology staff. Breaches were not associated with information technology operating expenses and information technology capital expenses.ConclusionHigher information technology labor investment due to the remediation of data breaches is an added cost to the healthcare system. Hospitals and policymakers should consider initiatives to improve cybersecurity and protect patient data.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-03T08:09:17Z
      DOI: 10.1177/20552076231224164
      Issue No: Vol. 10 (2024)
       
  • Evaluation of information provided to patients by ChatGPT about chronic
           diseases in Spanish language

    • Authors: María Juliana Soto-Chávez, Marlon Mauricio Bustos, Daniel G. Fernández-Ávila, Oscar Mauricio Muñoz
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      IntroductionArtificial intelligence has presented exponential growth in medicine. The ChatGPT language model has been highlighted as a possible source of patient information. This study evaluates the reliability and readability of ChatGPT-generated patient information on chronic diseases in Spanish.MethodsQuestions frequently asked by patients on the internet about diabetes mellitus, heart failure, rheumatoid arthritis (RA), chronic kidney disease (CKD), and systemic lupus erythematosus (SLE) were submitted to ChatGPT. Reliability was assessed by rating responses as (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, (4) completely incorrect, and divided between “good” (1 and 2) and “bad” (3 and 4). Readability was evaluated with the adapted Flesch and Szigriszt formulas.ResultsAnd 71.67% of the answers were “good,” with none qualified as “completely incorrect.” Better reliability was observed in questions on diabetes and RA versus heart failure (p = 0.02). In readability, responses were “moderately difficult” (54.73, interquartile range (IQR) 51.59–58.58), with better results for CKD (median 56.1, IQR 53.5–59.1) and RA (56.4, IQR 53.7–60.7), than for heart failure responses (median 50.6, IQR 46.3–53.8).ConclusionOur study suggests that the ChatGPT tool can be a reliable source of information in spanish for patients with chronic diseases with different reliability for some of them, however, it needs to improve the readability of its answers to be recommended as a useful tool for patients.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-03T06:57:23Z
      DOI: 10.1177/20552076231224603
      Issue No: Vol. 10 (2024)
       
  • “Guttmann Cognitest®,” a digital solution for assessing cognitive
           performance in adult population: A feasibility and usability pilot study

    • Authors: Alba Roca-Ventura, Javier Solana-Sánchez, Eva Heras, Maria Anglada, Jan Missé, Encarnació Ulloa, Alberto García-Molina, Eloy Opisso, David Bartrés-Faz, Alvaro Pascual-Leone, Josep M. Tormos-Muñoz, Gabriele Cattaneo
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundAs the world population continues to age, the prevalence of neurological diseases, such as dementia, poses a significant challenge to society. Detecting cognitive impairment at an early stage is vital in preserving and enhancing cognitive function. Digital tools, particularly mHealth, offer a practical solution for large-scale population screening and prompt follow-up assessments of cognitive function, thus overcoming economic and time limitations.ObjectiveIn this work, two versions of a digital solution called Guttmann Cognitest® were tested.MethodsTwo hundred and one middle-aged adults used the first version (Group A), while 132 used the second one, which included improved tutorials and practice screens (Group B). This second version was also validated in an older age group (Group C).ResultsThis digital solution was found to be highly satisfactory in terms of usability and feasibility, with good acceptability among all three groups. Specifically for Group B, the system usability scale score obtained classifies the solution as the best imaginable in terms of usability.ConclusionsGuttmann Cognitest® has been shown to be effective and well-perceived, with a high potential for sustained engagement in tracking changes in cognitive function.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-03T06:56:45Z
      DOI: 10.1177/20552076231224246
      Issue No: Vol. 10 (2024)
       
  • Evaluating a smartphone-based symptom self-monitoring app for psychosis in
           China (YouXin): A non-randomised validity and feasibility study with a
           mixed-methods design

    • Authors: Xiaolong Zhang, Shôn Lewis, Lesley-Anne Carter, Xu Chen, Jiaojiao Zhou, Xingyu Wang, Sandra Bucci
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      BackgroundPsychosis causes a significant burden globally, including in China, where limited mental health resources hinder access to care. Smartphone-based remote monitoring offers a promising solution. This study aimed to assess the validity, feasibility, acceptability, and safety of a symptom self-monitoring smartphone app, YouXin, for people with psychosis in China.MethodsA pre-registered non-randomised validity and feasibility study with a mixed-methods design. Participants with psychosis were recruited from a major tertiary psychiatric hospital in Beijing, China. Participants utilised the YouXin app to self-monitor psychosis and mood symptoms for four weeks. Feasibility outcomes were recruitment, retention and outcome measures completeness. Active symptom monitoring (ASM) validity was tested against corresponding clinical assessments (PANSS and CDS) using Spearman correlation. Ten participants completed qualitative interviews at study end to explore acceptability of the app and trial procedures.ResultsFeasibility parameters were met. The target recruitment sample of 40 participants was met, with 82.5% completing outcome measures, 60% achieving acceptable ASM engagement (completing>33% of all prompts), and 33% recording sufficient passive monitoring data to extract mobility indicators. Five ASM domains (hallucinations, suspiciousness, guilt feelings, delusions, grandiosity) achieved moderate correlation with clinical assessment. Both quantitative and qualitative evaluation showed high acceptability of YouXin. Clinical measurements indicated no symptom and functional deterioration. No adverse events were reported, suggesting YouXin is safe to use in this clinical population.ConclusionsThe trial feasibility, acceptability and safety parameters were met and a powered efficacy study is indicated. However, refinements are needed to improve ASM validity and increase passive monitoring data completeness.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-03T06:56:04Z
      DOI: 10.1177/20552076231222097
      Issue No: Vol. 10 (2024)
       
  • Monitoring walking asymmetries and endpoint control in persons living with
           chronic stroke: Implications for remote diagnosis and telerehabilitation

    • Authors: Jiafeng Song, Elizabeth C Hardin
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveThe objective of this study was to assess the feasibility of monitoring and diagnosing compromised walking motion in the frontal plane, particularly in persons living with the chronic effects of stroke (PwCS). The study aimed to determine whether active control of walking in the frontal plane could be monitored and provide diagnostic insights into compensations made by PwCS during community living.MethodsThe study recruited PwCS with noticeable walking asymmetries and employed a monitoring method to assess frontal plane motion. Monitoring was conducted both within a single assessment and between assessments. The study aimed to uncover baseline data and diagnostic information about active control in chronic stroke survivors. Data were collected using sensors during 6 minutes of walking and compared between the paretic and non-paretic legs.ResultsThe study demonstrated the feasibility of monitoring frontal plane motion and diagnosing disturbed endpoint control (p 
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-03T05:41:56Z
      DOI: 10.1177/20552076231220450
      Issue No: Vol. 10 (2024)
       
  • Online public health promotion at the local level: An evaluation of four
           local authority-led marketing campaigns

    • Authors: Kristin Hanson, Anna-Marie Degas, Daniel Green, Antoine Al-Hosri, Tushna Vandrevala
      Abstract: DIGITAL HEALTH, Volume 10, Issue , January-December 2024.
      ObjectiveLocal authority-led online campaigns offer the possibility of targeted health promotion to connect local services and residents. This study assesses the evidence for medium (e.g., click-trhoughs) and high (off-line behaviour change) levels of public engagement with four local authority-led campaigns across a variety of public health promotions (sexual health, weight loss, and vaccination), online marketing approaches (social media marketing, search engine marketing, and programmatic marketing) and target demographics (language, gender, age, income, ethnicity) undertaken by a London borough local authority.MethodsEmploying quasi-experimental and observational study designs, engagement with local health services during the course of the campaigns was evaluated. The first three campaigns were evaluated based on an interrupted time series model of intervention assessment comparing outcome variables of interest during the campaign to periods before and after the campaign period. The results of the fourth campaign, an observational case-study, are discussed using descriptive statistics only.ResultsThe analyses of the high engagement data for two of the three campaigns statistically assessed clearly supported the effectiveness of the campaigns. While the effect of high engagement could not be determined in the other two campaigns, they provide data that may be useful in online campaign design.ConclusionsThe evidence assessed in this study across a variety of platforms, health promotion initiatives, and population targets suggests that local authority-led online marketing campaigns for health promotion may be useful for increasing participation in public health programmes.
      Citation: DIGITAL HEALTH
      PubDate: 2024-01-03T03:03:30Z
      DOI: 10.1177/20552076231220151
      Issue No: Vol. 10 (2024)
       
 
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  Subjects -> HEALTH AND SAFETY (Total: 1464 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (87 journals)
    - HEALTH AND SAFETY (686 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (358 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (112 journals)
    - PHYSICAL FITNESS AND HYGIENE (117 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH AND SAFETY (686 journals)                  1 2 3 4 | Last

Showing 1 - 200 of 203 Journals sorted alphabetically
16 de Abril     Open Access   (Followers: 1)
ACM Transactions on Computing for Healthcare     Hybrid Journal  
Acta Scientiarum. Health Sciences     Open Access   (Followers: 2)
Adultspan Journal     Hybrid Journal   (Followers: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 11)
Advances in Public Health     Open Access   (Followers: 33)
Adversity and Resilience Science : Journal of Research and Practice     Hybrid Journal   (Followers: 3)
African Health Sciences     Open Access   (Followers: 7)
African Journal of Health Professions Education     Open Access   (Followers: 7)
Afrimedic Journal     Open Access   (Followers: 3)
Ageing & Society     Hybrid Journal   (Followers: 40)
Aging and Health Research     Open Access   (Followers: 5)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 9)
AJOB Empirical Bioethics     Hybrid Journal   (Followers: 3)
Akademika     Open Access  
American Journal of Family Therapy     Hybrid Journal   (Followers: 8)
American Journal of Health Economics     Full-text available via subscription   (Followers: 26)
American Journal of Health Education     Hybrid Journal   (Followers: 36)
American Journal of Health Promotion     Hybrid Journal   (Followers: 23)
American Journal of Health Sciences     Open Access   (Followers: 11)
American Journal of Health Studies     Full-text available via subscription   (Followers: 16)
American Journal of Preventive Medicine     Hybrid Journal   (Followers: 33)
American Journal of Public Health     Full-text available via subscription   (Followers: 225)
American Journal of Public Health Research     Open Access   (Followers: 33)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 9)
Annali dell'Istituto Superiore di Sanità     Open Access  
Annals of Global Health     Open Access   (Followers: 10)
Annals of Health Law     Open Access   (Followers: 7)
Applied Biosafety     Hybrid Journal   (Followers: 2)
Applied Ergonomics     Hybrid Journal   (Followers: 18)
Apuntes Universitarios     Open Access   (Followers: 2)
Archives of Community Medicine and Public Health     Open Access   (Followers: 2)
Archives of Medicine and Health Sciences     Open Access   (Followers: 7)
Archives of Suicide Research     Hybrid Journal   (Followers: 13)
Archivos de Prevención de Riesgos Laborales     Open Access  
ASA Monitor     Full-text available via subscription   (Followers: 17)
Asia Pacific Journal of Counselling and Psychotherapy     Hybrid Journal   (Followers: 7)
Asia Pacific Journal of Health Management     Full-text available via subscription   (Followers: 4)
Asia-Pacific Journal of Public Health     Hybrid Journal   (Followers: 12)
Asian Journal of Gambling Issues and Public Health     Open Access   (Followers: 5)
Asian Journal of Medicine and Health     Open Access   (Followers: 1)
Asian Journal of Population Sciences     Open Access   (Followers: 8)
Asian Journal of Social Health and Behavior     Open Access   (Followers: 2)
Atención Primaria     Open Access   (Followers: 2)
Atención Primaria Práctica     Open Access   (Followers: 1)
Australasian Journal of Paramedicine     Open Access   (Followers: 9)
Australian Advanced Aesthetics     Full-text available via subscription   (Followers: 5)
Australian Family Physician     Full-text available via subscription   (Followers: 2)
Australian Indigenous HealthBulletin     Free   (Followers: 5)
Autism & Developmental Language Impairments     Open Access   (Followers: 18)
Bijzijn XL     Hybrid Journal  
Biograph-I : Journal of Biostatistics and Demographic Dynamic     Open Access   (Followers: 4)
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 7)
Biosafety and Health     Open Access  
Biosalud     Open Access  
Birat Journal of Health Sciences     Open Access  
BLDE University Journal of Health Sciences     Open Access   (Followers: 1)
BMC Oral Health     Open Access   (Followers: 5)
BMC Pregnancy and Childbirth     Open Access   (Followers: 20)
Brazilian Journal of Medicine and Human Health     Open Access  
British Journal of Health Psychology     Hybrid Journal   (Followers: 56)
Buletin Penelitian Kesehatan     Open Access  
Buletin Penelitian Sistem Kesehatan     Open Access  
Cadernos de Educação, Saúde e Fisioterapia     Open Access  
Cadernos de Saúde     Open Access  
Cambridge Quarterly of Healthcare Ethics     Hybrid Journal   (Followers: 13)
Canadian Family Physician     Partially Free   (Followers: 14)
Canadian Journal of Community Mental Health     Full-text available via subscription   (Followers: 16)
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 1)
Canadian Journal of Public Health     Hybrid Journal   (Followers: 30)
Cannabis and Cannabinoid Research     Hybrid Journal   (Followers: 2)
Carta Comunitaria     Open Access  
Case Reports in Women's Health     Open Access   (Followers: 4)
CASUS : Revista de Investigación y Casos en Salud     Open Access  
Central Asian Journal of Global Health     Open Access   (Followers: 2)
CES Medicina     Open Access  
CES Salud Pública     Open Access  
Child and Adolescent Obesity     Open Access   (Followers: 8)
Child's Nervous System     Hybrid Journal  
Childhood Obesity and Nutrition     Open Access   (Followers: 12)
Children     Open Access  
Chinese Journal of Physiology     Open Access   (Followers: 1)
CHRISMED Journal of Health and Research     Open Access   (Followers: 1)
Christian Journal for Global Health     Open Access   (Followers: 1)
Ciencia & Salud     Open Access  
Ciencia & Trabajo     Open Access  
Ciencia e Innovación en Salud     Open Access  
Ciencia y Cuidado     Open Access   (Followers: 1)
Ciencia y Salud     Open Access   (Followers: 1)
Ciencia, Tecnología y Salud     Open Access  
Cities & Health     Hybrid Journal   (Followers: 5)
Cleaner and Responsible Consumption     Open Access  
Clinical and Experimental Health Sciences     Open Access   (Followers: 1)
ClinicoEconomics and Outcomes Research     Open Access   (Followers: 1)
Clocks & Sleep     Open Access   (Followers: 2)
CME     Hybrid Journal   (Followers: 1)
Community Health     Open Access   (Followers: 6)
Conflict and Health     Open Access   (Followers: 8)
Contact (CTC)     Open Access   (Followers: 1)
Contraception and Reproductive Medicine     Open Access   (Followers: 2)
Cuaderno de investigaciones: semilleros andina     Open Access  
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 11)
Current Opinion in Environmental Science & Health     Hybrid Journal  
D Y Patil Journal of Health Sciences     Open Access   (Followers: 3)
Das österreichische Gesundheitswesen ÖKZ     Hybrid Journal   (Followers: 2)
Day Surgery Australia     Full-text available via subscription   (Followers: 2)
Design for Health     Hybrid Journal   (Followers: 1)
Digital Health     Open Access   (Followers: 10)
Disaster Medicine and Public Health Preparedness     Hybrid Journal   (Followers: 12)
Discover Social Science and Health     Open Access   (Followers: 17)
Diversity and Equality in Health and Care     Open Access   (Followers: 10)
Diversity of Research in Health Journal     Open Access   (Followers: 1)
Dramatherapy     Hybrid Journal   (Followers: 2)
Drogues, santé et société     Open Access   (Followers: 2)
Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi / Journal of Duzce University Health Sciences Institute     Open Access  
Early Childhood Research Quarterly     Hybrid Journal   (Followers: 26)
East African Journal of Public Health     Full-text available via subscription   (Followers: 3)
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity     Hybrid Journal   (Followers: 23)
EcoHealth     Hybrid Journal   (Followers: 6)
Education for Health     Open Access   (Followers: 9)
Egyptian Journal of Nutrition and Health     Open Access   (Followers: 8)
Egyptian Journal of Occupational Medicine     Open Access   (Followers: 6)
electronic Journal of Health Informatics     Open Access   (Followers: 7)
ElectronicHealthcare     Full-text available via subscription   (Followers: 2)
Emerging Trends in Drugs, Addictions, and Health     Open Access   (Followers: 2)
Ensaios e Ciência : Ciências Biológicas, Agrárias e da Saúde     Open Access  
Environmental Disease     Open Access   (Followers: 3)
Environmental Sciences Europe     Open Access   (Followers: 2)
Epidemics     Open Access   (Followers: 7)
EsSEX : Revista Científica     Open Access  
Estudios sociales : Revista de alimentación contemporánea y desarrollo regional     Open Access  
Ethics & Human Research     Hybrid Journal   (Followers: 4)
Ethics, Medicine and Public Health     Full-text available via subscription   (Followers: 8)
Ethiopian Journal of Health Development     Open Access   (Followers: 7)
Ethiopian Journal of Health Sciences     Open Access   (Followers: 6)
Ethnicity & Health     Hybrid Journal   (Followers: 17)
Eurasian Journal of Health Technology Assessment     Open Access   (Followers: 1)
EUREKA : Health Sciences     Open Access  
European Journal of Health Communication     Open Access  
European Journal of Investigation in Health, Psychology and Education     Open Access   (Followers: 5)
European Medical, Health and Pharmaceutical Journal     Open Access   (Followers: 2)
Evaluation & the Health Professions     Hybrid Journal   (Followers: 11)
Evidência - Ciência e Biotecnologia - Interdisciplinar     Open Access  
Exploratory Research in Clinical and Social Pharmacy     Open Access   (Followers: 4)
Expressa Extensão     Open Access  
F&S Reports     Open Access   (Followers: 2)
Face à face     Open Access  
Families, Systems, & Health     Full-text available via subscription   (Followers: 9)
Family & Community Health     Hybrid Journal   (Followers: 12)
Family Medicine and Community Health     Open Access   (Followers: 8)
Family Relations     Partially Free   (Followers: 12)
FASEB BioAdvances     Open Access   (Followers: 2)
Fatigue : Biomedicine, Health & Behavior     Hybrid Journal   (Followers: 3)
Finnish Journal of eHealth and eWelfare : Finjehew     Open Access  
Food and Public Health     Open Access   (Followers: 11)
Food Hydrocolloids for Health     Open Access  
Food Quality and Safety     Open Access   (Followers: 2)
Frontiers in Digital Health     Open Access   (Followers: 4)
Frontiers in Neuroergonomics     Open Access  
Frontiers in Public Health     Open Access   (Followers: 8)
Frontiers of Health Services Management     Partially Free   (Followers: 7)
Gaceta Sanitaria     Open Access   (Followers: 2)
Galen Medical Journal     Open Access  
Ganesha Journal     Open Access  
Gazi Sağlık Bilimleri Dergisi     Open Access  
Geospatial Health     Open Access   (Followers: 1)
Gestão e Desenvolvimento     Open Access  
Gesundheitsökonomie & Qualitätsmanagement     Hybrid Journal   (Followers: 7)
Giornale Italiano di Health Technology Assessment     Full-text available via subscription  
Global Advances in Health and Medicine     Open Access  
Global Challenges     Open Access   (Followers: 2)
Global Health : Science and Practice     Open Access   (Followers: 7)
Global Health Annual Review     Open Access   (Followers: 2)
Global Health Innovation     Open Access   (Followers: 4)
Global Health Journal     Open Access   (Followers: 2)
Global Health Promotion     Hybrid Journal   (Followers: 16)
Global Journal of Health Science     Open Access   (Followers: 6)
Global Journal of Public Health     Open Access   (Followers: 16)
Global Medical & Health Communication     Open Access   (Followers: 1)
Global Mental Health     Open Access   (Followers: 13)
Global Reproductive Health     Open Access   (Followers: 1)
Global Security : Health, Science and Policy     Open Access   (Followers: 1)
Global Transitions     Open Access   (Followers: 1)
Global Transitions Proceedings     Open Access   (Followers: 3)
Globalization and Health     Open Access   (Followers: 7)
Hacia la Promoción de la Salud     Open Access  
Hastane Öncesi Dergisi     Open Access  
Hastings Center Report     Hybrid Journal   (Followers: 7)
HCU Journal     Open Access  
HEADline     Hybrid Journal  
Health & Place     Hybrid Journal   (Followers: 23)
Health & Justice     Open Access   (Followers: 5)
Health : An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine     Hybrid Journal   (Followers: 21)
Health and Human Rights     Open Access   (Followers: 10)
Health and Social Care Chaplaincy     Hybrid Journal   (Followers: 10)
Health and Social Work     Hybrid Journal   (Followers: 64)
Health Behavior and Policy Review     Full-text available via subscription   (Followers: 5)
Health Behavior Research     Open Access   (Followers: 2)
Health Care Analysis     Hybrid Journal   (Followers: 13)
Health Equity     Open Access   (Followers: 4)

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