Authors:Macarena Kruger, Andrea B. Goldschmidt, Adrian Ortega, Abigail Wharton, Danielle A. N. Chapa, Erin R. Stalvey, Isabel R. Rooper, Katrina T. Obleada, Graham C. Miller, Andrea K. Graham Abstract: Digital health interventions (DHIs) hold promise for improving the reach of mental health care for adolescents, particularly those from under-resourced communities who may face significant barriers to accessing in-person care. Yet, low engagement and uptake have challenged DHIs’ potency. Human-centered design (HCD) integrates end-users (i.e., future users of the DHI) into iterative design processes, thereby prioritizing their needs and preferences. Clinical scientists are increasingly embracing HCD, but often lack expertise in how to apply these methods in practice. We provide a template for creating a design session interview guide in a needs assessment, which is the first phase in our HCD process to design a DHI for dysregulated eating in adolescents. To create the guide, we first conducted a “needs assessment” within our team to identify important topic areas that required feedback from adolescents (“investigate”). We then consolidated these ideas into structured domains through a brainstorming process (“ideate”), which resulted in an initial draft of a design session guide (“prototype”). Next, we piloted the prototype with members of our team and a technology-savvy adolescent (“evaluate”) to refine it prior to administration with the target audience (“refine and develop”). Our internal needs assessment identified that we needed to learn adolescents’ preferences for technology (e.g., desired features), clinical content (e.g., areas for specialized support), delivery (e.g., coaching), and developmental relevance (e.g., focus on self-regulation). We organized these topics into six domains: dysregulated eating experiences and current help-seeking behaviors, major challenges that impact dysregulated eating, preferred intervention features and skills, preferences for coaching support, the potential role of sensors to assess activity behaviors, and preferred aesthetics and brand. We created relevant prompts within each domain, revised, and reordered them to elicit more comprehensive responses during administration. Next, we practiced administering the guide internally amongst our team, then with a non-participant adolescent volunteer. Using HCD, we created a semi-structured design session interview guide that will be administered in an upcoming needs assessment with adolescents and will continue to evolve as we learn from adolescents. This case example unpacks the process of creating and iterating a design session guide that could be applied across clinical domains. PubDate: 2025-04-17T00:00:00Z
Authors:Brittany McFeeley, Casey Nicastri, Taylor Krivanek, Kirk R. Daffner, Seth A. Gale Abstract: IntroductionWhen COVID-19 containment strategies were imposed in March 2020, we became interested in how these restrictions might interfere with brain-healthy behaviors of older adults who were either actively participating in or who had recently completed our telehealth behavior change intervention. Telehealth interventions have emerged as important tools for supporting brain health behaviors remotely, particularly among older adults. The objective of the current study was to assess how older adults with and without cognitive impairment were affected by COVID-19 restrictions and whether they were affected differently based on their active participation or recent completion of our Brain Health Champion (BHC) study and their cognitive status.MethodsBHC study 1.0 and 2.0 participants and their study partners were emailed in April and May of 2020 a link to five electronic surveys to collect qualitative and quantitative data on various health factors, including self-reports of pre-pandemic and current brain health behaviors (e.g., physical activity, Mediterranean diet adherence, social engagement, and cognitive stimulation), anxiety, sleep, and depression. The fifth survey was distributed to collect study feedback.ResultsTen out of 11 participants from Study 2.0 and 15 out of 30 participants from Study 1.0 completed the surveys. Results demonstrated that early pandemic restrictions negatively impacted all participants in physical activity (p PubDate: 2025-04-17T00:00:00Z
Authors:Corrado Gervasi, Erik Perego, Francesca Galli, Valter Torri, Massimo Castoldi, Emilio Bombardieri Abstract: IntroductionThe prevention of accidental falls in hospital is an important aspect of a healthcare management strategy, since they represent a relevant socio-economic problem. The Verso Vision System (VS) is an artificial intelligence-based system for accidental fall prevention and management, which uses computer vision algorithms to monitor environments and people in real time.MethodsThe efficacy of VS monitoring in terms of reduction of accidentals falls was retrospectively evaluated in a group of 362 hospitalized patients at Humanitas Gavazzeni Hospital.ResultsOf the 362 patients included in the analysis, 580 statistical units, 228 monitored with VS and 355 without VS were obtained splitting the observation of each patient based on the presence of VS monitoring and the Stratify score. The mean age of the 362 patients was 75.3 years and 150 were females (41.4%). The crude incidence rates per 1,000 person-time was 2.85 (95% CI 0.92–6.63, 5 accidental falls) and 6.65 (95% CI 3.72–10.96, 15 accidental falls) in the monitored with VS and unmonitored groups, respectively. At multivariable Poisson regression model, a statistically significant reduction of the risk of accidental falls was found in the monitored group compared to the unmonitored group [incidence rate ratio (IRR) 0.21, 95% CI 0.12–0.38, p PubDate: 2025-04-16T00:00:00Z
Authors:Deepika V, Praveen S. Jodalli, Avinash B R Abstract: Tobacco remains one of the leading global public health threats, causing over 8 million deaths worldwide each year. Existing tobacco cessation strategies must be complemented with innovative approaches to enhance their effectiveness. This paper is intended to review the state and success of chatbots and virtual assistants in the delivery of tobacco cessation counselling services. Comprehensive literature search was performed on various databases including PubMed, SCOPUS, EMBASE, COCHRANE Library, and ScienceDirect using relevant keywords concerning tobacco cessation as well as artificial intelligence. The review is limited to studies published between March 2015 and March 2024 examining only the role of chatbots and virtual assistants in smoking cessation. The analysis of 31 studies found that chatbots and virtual assistants deliver continuous support, personalized interaction, and increased accessibility, which collectively boost user engagement. Their anonymity from other means of online counselling has significantly increased the willingness of people who want to stop smoking. The development of information technology has led to the advent of AI-based chatbots and virtual assistants as a promising novel tool for the tobacco cessation process, providing personalized, adaptive, and scalable support to web-based users. Personalized approaches improve the chances of success in quitting smoking and represent a major advancement of cessation strategies. PubDate: 2025-04-16T00:00:00Z
Authors:Yuling Sang, Abhirup Banerjee, Marcel Beetz, Vicente Grau Abstract: Background12-lead electrocardiograms (ECGs) are a cornerstone for diagnosing and monitoring cardiovascular diseases (CVDs). They play a key role in detecting abnormalities such as arrhythmias and myocardial infarction, enabling early intervention and risk stratification. However, traditional analysis relies heavily on manual interpretation, which is time-consuming and expertise-dependent. Moreover, existing machine learning models often lack personalization, as they fail to integrate subject-specific anatomical and demographic information. Advances in deep generative models offer an opportunity to overcome these challenges by synthesizing personalized ECGs and extracting clinically relevant features for improved risk assessment.MethodsWe propose a conditional Variational Autoencoder (cVAE) framework to generate realistic, subject-specific 12-lead ECGs by incorporating demographic metadata, anatomical heart features, and ECG electrodes’ positions as conditioning factors. This allows for physiologically consistent and personalized ECG synthesis. Furthermore, we introduce a revised Cox proportional-hazards regression model that utilizes the latent embeddings learned by the cVAE to predict future CVD risk. This approach not only enhances the interpretability of ECG-derived risk factors but also demonstrates the potential of deep generative models in personalized cardiac assessment.ResultsOur model is trained and validated on the UK Biobank dataset and in silico simulation data. By incorporating heart position and electrodes’ positions, the generated ECGs demonstrate strong consistency with in silico simulations, providing insights into the relationship between cardiac anatomy and ECG morphology. Furthermore, our CVD risk prediction model achieves a C-index of 0.65, indicating that ECG signals, together with demographic and anatomical information, contain valuable prognostic information for stratifying subjects based on future cardiovascular risk.ConclusionThis work marks a significant advancement in ECG analysis by providing a conditional VAE framework that not only improves ECG generation but also enriches our understanding of the relationship between ECG patterns and subject-specific information. Importantly, our approach enables clinically significant information to be extracted from 12-lead ECGs, providing valuable insights for predicting future CVD risks. PubDate: 2025-04-16T00:00:00Z
Authors:Emily S. Rempel, Gianfranco Polizzi, Simeon Yates Abstract: IntroductionTraditional data and measures about health and well-being provide vital insights but do not provide context on the ways in which a community may want to see development in their local area. This article is based on a Participatory Action Research (PAR) project on well-being and data conducted with members of a community in Widnes, a town in the UK. We explore the usefulness of adapting a PAR methodology to develop a Participatory Data Stewardship (PDS) program at the community level.MethodsThrough repeated, semi-structured interviews, we tracked 15 Community Researchers' (CRs') experiences and perspectives of taking part in a PDS/PAR project. CRs were purposely recruited to primarily maximize diversity in gender, age, and socio-economic status, and interviewed before training, after training, and after fieldwork. We used thematic analysis to explore benefits and challenges, along with their expectations and experiences, at each stage of the project.ResultsFour main themes emerged from interviews with CRs on their expectations and experiences: (1) the role of CRs' motivation in taking part on their perceptions of project impact, (2) the role and development of confidence in CRs' perceptions of their own success, (3) the importance of community building through an appreciation of diversity, and (4) the value in developing CR agency by putting participatory process at each stage of the project.DiscussionThe findings illustrate that taking a PAR approach to the design of a PDS project around well-being and data shows potential for problematizing datafication through engaging local communities, developing their research skills, confidence and agency, and designing a data system that can empower community voice. This article addresses a gap in the literature on the feasibility of taking a PAR approach to the implementation of PDS. Future research should build on this study to explore the conditions for successful PAR in the context of other PDS projects. PubDate: 2025-04-16T00:00:00Z
Authors:Sára Imola Csuka, Barbara Horvát, Georgina Csordás, Csilla Lakatos, Tamás Martos Abstract: IntroductionA growing number of health technology solutions are designed for people with diabetes to ease disease self-management. However, according to some studies, technology can also bring dissatisfaction. According to the Motivation, Engagement, and Thriving in User Experience model, the use of technology is only beneficial if it is linked to the experience of autonomy. The study aimed to investigate the associations between health technology use and technology adoption motivation and associated health behavior of people with type 1 and type 2 diabetes.MethodsA cross-sectional questionnaire study was conducted on a sample of 315 patients with diabetes. The Technology Adoption Propensity Questionnaire was applied to assess general attitudes toward technology, the Autonomy and Competence in Technology Adoption Questionnaire for underlying motives of technology use, and the Summary of Diabetes Self-Care Activities tool for health behavior.ResultsThe results showed that technology use was predicted by proficiency (but not optimism) and lower levels of vulnerability and dependence. In addition, technology use predicted health behavior (diet and physical exercise) frequency. After refining the results further, among technology users, only autonomous motivation of technology use predicted health behavior, while controlled motivation had a slightly negative predictive effect on following the diet.DiscussionParticular attention should be paid to person-based health-related technology interventions for enhancing proficiency and reducing feelings of vulnerability and dependence on technologies. Ultimately, it is not the adoption of a technology per se, but the autonomous motivation for adoption that is associated with more favorable health behavior. PubDate: 2025-04-15T00:00:00Z
Authors:Elijah Moothedan, Micah Boyer, Stephanie Watts, Yassmeen Abdel-Aty, Satrajit Ghosh, Anaïs Rameau, Alexandros Sigaras, Olivier Elemento, Bridge2AI-Voice Consortium , Yael Bensoussan, Yael Bensoussan, Olivier Elemento, Anais Rameau, Alexandros Sigaras, Satrajit Ghosh, Maria Powell, Vardit Ravitsky, Jean Christophe Belisle-Pipon, David Dorr, Phillip Payne, Alistair Johnson, Ruth Bahr, Donald Bolser, Frank Rudzicz, Jordan Lerner-Ellis, Kathy Jenkins, Shaheen Awan, Micah Boyer, William Hersh, Andrea Krussel, Steven Bedrick, Toufeeq Ahmed Syed, Jamie Toghranegar, James Anibal, Duncan Sutherland, Enrique Diaz-Ocampo, Elizabeth Silberhoz, John Costello, Alexander Gelbard, Kimberly Vinson, Tempestt Neal, Lochana Jayachandran, Evan Ng, Selina Casalino, Yassmeen Abdel-Aty, Karim Hanna, Theresa Zesiewicz, Elijah Moothedan, Emily Evangelista, Samantha Salvi Cruz, Robin Zhao, Mohamed Ebraheem, Karlee Newberry, Iris De Santiago, Ellie Eiseman, JM Rahman, Stacy Jo, Anna Goldenberg Abstract: IntroductionBridge2AI-Voice, a collaborative multi-institutional consortium, aims to generate a large-scale, ethically sourced voice, speech, and cough database linked to health metadata in order to support AI-driven research. A novel smartphone application, the Bridge2AI-Voice app, was created to collect standardized recordings of acoustic tasks, validated patient questionnaires, and validated patient reported outcomes. Before broad data collection, a feasibility study was undertaken to assess the viability of the app in a clinical setting through task performance metrics and participant feedback.Materials & methodsParticipants were recruited from a tertiary academic voice center. Participants were instructed to complete a series of tasks through the application on an iPad. The Plan-Do-Study-Act model for quality improvement was implemented. Data collected included demographics and task metrics including time of completion, successful task/recording completion, and need for assistance. Participant feedback was measured by a qualitative interview adapted from the Mobile App Rating Scale.ResultsForty-seven participants were enrolled (61% female, 92% reported primary language of English, mean age of 58.3 years). All owned smart devices, with 49% using mobile health apps. Overall task completion rate was 68%, with acoustic tasks successfully recorded in 41% of cases. Participants requested assistance in 41% of successfully completed tasks, with challenges mainly related to design and instruction understandability. Interview responses reflected favorable perception of voice-screening apps and their features.ConclusionFindings suggest that the Bridge2AI-Voice application is a promising tool for voice data acquisition in a clinical setting. However, development of improved User Interface/User Experience and broader, diverse feasibility studies are needed for a usable tool.Level of evidence: 3. PubDate: 2025-04-15T00:00:00Z
Authors:Yasmin Youssef, Tu-Lan Vu-Han, Richard Trauth, Georg Osterhoff, David Alexander Back, Tobias Gehlen Abstract: BackgroundSocial media (SM) is increasingly used in the healthcare system and offers various benefits for patients such as accessible health information and communication with other patients and healthcare professionals. However, SM also poses risks, including the dissemination of medical misinformation and privacy concerns. This in turn can influence patients’ health-related decision-making and the patient-physician relationship. There is limited data regarding which SM orthopedic patients use and what benefits and risks of SM they perceive.MethodsAn online survey was conducted from April to December 2023 among orthopedic and trauma patients in five German orthopedic clinics. The questionnaire with 32 variables was designed to assess internet and SM usage patterns, platform preferences, and perceived benefits and risks. Statistical analysis was performed, including subgroup analyses.ResultsA total of 267 patients participated, with 82.0% reporting regular SM use. In total 45.9% of the patients used SM for general health questions and 51.3% for orthopedic-related questions. The most used information platforms were conventional websites, YouTube, Instagram, and messenger apps. A total of 45.9% used SM infrequently for general health questions, and 51.3% for orthopedic-related queries. Only 13.7% of patients agreed that SM helped in medical decision-making, and 31.1% felt confident in assessing the credibility of SM content. Additionally, 58.6% of patients were unsure about allowing physicians to present their cases on SM, and 62.3% were uncertain about posting their medical images.ConclusionAmong German orthopedic patients, the use of SM for health-related and gain of orthopedic information was low in the given study. While SM may offer valuable health information, their role in medical decision-making remains limited due to concerns over content credibility and privacy. Video-based content seems to achieve the best reach. Future research should explore these aspects longitudinally and across diverse populations to better understand and address the challenges and benefits of SM in healthcare. PubDate: 2025-04-14T00:00:00Z
Authors:Rudolf J. Schnetler, Venkat N. Vangaveti, Benjamin J. Crowley, Joshua K. Keogh, Trudie Harris, Dale Parker, Jane Watson, Teresa Edwards, Peter Westwood, Hudson Birden, Marina Daly, Kieran Keyes, Erik Biros, Andrew J. Mallett Abstract: BackgroundThe role of clinician-researchers in regional healthcare is challenging. Balancing patient care, academic research, and mentoring junior staff significantly burdens these dedicated professionals. Therefore, the Australian healthcare system must provide institutional support for improving clinicians' academic performance.MethodsThis paper describes two digital solutions implemented in a regional Australian Hospital and Health Service. The Audit, Quality, and Innovation Review panel simplifies the approval process using digital workflows for quality assurance and audit projects, and the Research Data Laboratory provides secure access to de-identified patient data and supports data analysis.DiscussionUnlike some countries, such as the US and UK, where financial incentives or established networks drive research integration, the Townsville Hospital and Health Service focuses on empowering clinicians to address local healthcare issues through research directly. This makes the Townsville Hospital and Health Service a standout example in Australian healthcare, highlighting the significance of specialised research infrastructure and data services for clinician-led audit projects and research. This digital health solutions approach is essential for closing the gap between research and practical application, ultimately leading to improved patient care. Importantly, as a service-embedded structure, this model may be more sustainable and effective than traditional models reliant on external funding or networks in regional settings. PubDate: 2025-04-14T00:00:00Z
Authors:Yanina Shraga, Helen Pushkarskaya, Orly Sarid Abstract: Informal mental healthcare groups often provide telephonic and text-based interventions to support communities affected by natural and man-made disasters. Operating outside formal regulations, these groups offer flexible and innovative care; documenting their practices is crucial for evaluating service quality. This paper presents a protocol of an international, informal Psychological First Aid (PFA) telephone-based initiative and a reflective account from a volunteering therapist. The initiative aimed to support Ukrainian civilians affected by the Russian-Ukrainian war through crisis intervention and resilience-building. Guided by PFA principles, theoretical first aid models, and evidence-based practices, the telephone interventions focused on reducing distress, providing moral support, and restoring functioning. A Russian-speaking therapist assisted 34 Ukrainian civilians, primarily addressing acute stress, anxiety, and panic attacks. Using an autoethnographic approach, this study integrates the therapist's retrospective reflections, cultural context, and professional learning to examine PFA implementation in a crisis setting. Individuals who received telephone-based PFA reported decreased distress and enhanced coping strategies, suggesting effectiveness. The initiative's three-year continuation illustrates its sustainability. The therapist's reflections highlight the importance of professional preparation, shared linguistic and cultural backgrounds, and a sense of purpose in delivering effective support. While limitations include the absence of standardized measures and potential self-selection and volunteer biases, this study demonstrates the feasibility of providing remote psychological first aid to civilians through informal international groups. Critically evaluating practices adopted by these informal organizations is essential for understanding their effectiveness, improving future implementation, and co-creating best practices for crisis intervention and support services that embrace “Care Without Address” models. PubDate: 2025-04-14T00:00:00Z
Authors:Yuting Liu, Haiyan Li Abstract: ObjectiveMobile health management service systems have rapidly emerged in today's digital age, providing a new way to manage personal health with great potential value. This study deeply explores the use behavior and influencing factors of mobile health management service systems for flight attendants in the context of the "Digital age".MethodsThe study mainly adopted the questionnaire survey method, used SPSS24.0 and AMOS24.0 software for data analysis, and used statistical methods such as factor analysis, regression analysis, and path analysis to verify the effectiveness of the model and explore the relationship between key variables.Results(1) The usage rate of the health management service system among flight attendants is not as high as expected, but the use rate of sports health monitoring applications reached 66.5%, and the daily frequency of use was as high as 25.52%, (2) Perceived ease of use and perceived usefulness have a positive and significant impact on intention to use, (3) Privacy concerns have a positive impact on intention to use Significant negative impact.ConclusionThe study points out that ease of use and usefulness are key factors in attracting flight attendants to use mobile health management service systems. System designers need to pay attention to this aspect. Flight attendants have a strong sense of privacy protection, and the system must provide a strong privacy protection mechanism to win trust. Therefore, system developers should strive to provide practical value, such as health advice and data tracking, to stimulate user enthusiasm. In addition, this article has certain limitations in the study of sample selection and the discussion of mediating relationships. Future research can be further improved in this regard. PubDate: 2025-04-14T00:00:00Z
Authors:Patrik Goncalves Rodrigues, Danieli Mayumi Kimura Leandro, Silvia Schoenau de Azevedo, Marcelo Jenné Mimica, Rafaela Fabri Rodrigues, Mauricio Magalhães, Bruno Fernandes dos Anjos, Gabriel Fernando Todeschi Variane Abstract: Mixed reality (MR) and augmented reality (AR) technologies bridge elements of the real and virtual worlds, emerging as tools that allow users to engage with digital cues to aid with tasks encountered in the physical environment. Thus, these holographic-based innovations are potential tools to support real-time patient care. The applications of MR and AR in neonatal care remain significantly underexplored. In the present article, we highlight the applications of MR and AR across medical procedures, physical examinations, medical diagnoses, and telemedicine, further underscoring their transformative potential within neonatal care. The use of MR and AR can be relevant across diverse economic and clinical landscapes, and in-depth research is required to evaluate the advantages of these tools in caring for neonates. PubDate: 2025-04-11T00:00:00Z
Authors:Joachim Eckerström, Sophie Mårtensson, Margaretha Larsson, Rajna Knez, Madeleine Ljudvåg, Samir El Alaoui, Karin Dahlström, Ylva Elvin Nowak, Terese Stenfors, Nitya Jayaram-Lindström, Marianne Kristiansson, Uno Fors, Karolina Sörman Abstract: BackgroundMultiple studies have shown that healthcare professionals often feel uncertain about when to inquire about intimate partner violence (IPV), the appropriate methods for doing so, and how to respond to the answers. Virtual patient (VP) cases are an interactive educational tool that can be effective for learning and training clinical reasoning skills. However, there is a lack of research on the use of VP in psychiatry education. This study aimed to investigate nursing students' experiences of using a VP as part of an educational module, integrated into their foundational training on IPV during their nursing education.MethodsThe study employed a mixed-methods approach, incorporating both quantitative and qualitative data. Participants (N = 62) completed an interactive educational module on IPV, in three consecutive parts: (a) a web-based education on IPV, (b) training with a VP, and (c) a seminar for follow-up discussions.ResultsThe VP platform was considered user-friendly and easy to navigate, although some participants found the instructions challenging. Participants perceived the VP as beneficial for learning about IPV and for practicing interactive patient dialogues. They appreciated the rich set of questions and the feedback provided, both by the experts in the field of IVP and by the VP itself. However, some participants noted that interacting with a VP on a screen was less emotional compared to real human interactions.ConclusionThe interactive educational module, integrated into the regular nursing program, was positively received by the students. Overall, the VP was considered beneficial for learning about IPV, easy to navigate, and provided a valuable opportunity for practice. PubDate: 2025-04-11T00:00:00Z
Authors:Miesa Gelchu, Geleta Chala, Gemechis Tuke, Gelgelo Wodessa, Angefa Ayele, Terefu Yambo, Anteneh Fikrie Abstract: BackgroundThe electronic medical record system is gradually being introduced in healthcare settings in high-income countries, but its adoption in low-resource settings like Ethiopia remains limited. There is a dearth of information regarding the readiness of health professionals to implement Electronic Medical Records system and the factors influencing this readiness, particularly in the study setting.ObjectiveThe study aimed to evaluate the readiness of healthcare professionals in Southern Oromia for the implementation of the electronic medical record system.MethodsA facility-based cross-sectional study was conducted using self-administered questionnaires among 384 health professionals from May 1–30, 2024, at public hospitals in the Borena and West Guji zones in southern Ethiopia. Epi Data version 4.6 and SPSS version 27.0 were used for data entry and analysis, respectively. The study used multivariable logistic regression to analyse factors influencing health professionals’ readiness to implement electronic medical record systems, assessing adjusted odds ratios with a 95% confidence interval and a p-value below 0.05, which is considered to declare statistical significance.ResultsHealth professionals, 60.4% [95% CI: (55.5–65.3%)] expressed readiness to utilize the Electronic Medical Record system. Factors associated with electronic medical record system readiness included younger age [AOR = 2.66, 95% CI: (1.06–6.67)], personal computer ownership [AOR = 3.54, 95% CI: (1.76–7.11)], adequate computer skills [AOR = 2.49, 95% CI: (1.41–4.39)], high computer literacy [AOR = 2.67, 95% CI: (1.53–4.66)], knowledge of electronic medical record system [AOR = 2.56, 95% CI: (1.53–4.29)], and a favorable attitude towards electronic medical record system [AOR = 2.77, 95% CI: (1.66–4.63)].ConclusionsThe study indicates that readiness for electronic medical record systems among health professionals is influenced by factors like younger age, computer ownership, skills, and positive attitudes. Interventions should target these factors, especially among older health professionals and those with limited digital literacy. PubDate: 2025-04-10T00:00:00Z
Authors:Muhammad K. Khan, Ambreen Liaqat, Ziyad A. Altokhais, Bader A. Alotaibi, Maryam Sadiq, Munazza Rehman, Zeeshan Ahsan Allana, Hasan N. Tahir Abstract: IntroductionThis systematic review and meta-analysis examine the effectiveness of smartphone and Web 2.0 interventions for weight management compared to traditional control interventions. The potential of smartphones and Web 2.0. technologies to transform health care and clinical intervention in the community are tremendous. This potential is incredibly increased by increasing adoption rates for smartphones and internet technologies.MethodologyTen randomized control trials published between 2015 and 2024 searched through PubMed and ScienceDirect were included. All studies with open access that assessed a smartphone or app intervention compared to a control group in randomized control trials, with weight-related body measures (i.e., body weight, BMI, waist circumference) and physical activity changes (steps/day) expressed in terms of mean and standard deviation performed in a population of adults were included. Review Manager software, version 5.4 (The Nordic Cochrane Centre, The Cochrane Collaboration) was used for statistical analysis.ResultsThe results of our study indicate that digital interventions, particularly those utilizing direct communication methods like text messages and social media, significantly promote weight loss and reduce waist circumference (mean difference of −2.12 and −2.81 for weight change and waist circumstances respectively). While reductions in body mass index (BMI) with mean difference of −0.53 were less pronounced, they still favored intervention groups. Subgroup analyses performed to find out the source of heterogeneity revealed that three-arm randomized control trials, studies with larger sample sizes, and interventions lasting around six months showed more consistent and significant effects whereas for sensitivity analysis no significant change in heterogeneity was observed for all parameters. High heterogeneity among studies suggests the need for standardized study designs and intervention protocols in future research.ConclusionsDespite limitations such as technological issues and engagement variability, these findings underscore the potential of digital health interventions in addressing the global burden of obesity and related non-communicable diseases. PubDate: 2025-04-10T00:00:00Z
Authors:Nhung H. Hoang, Zilu Liang Abstract: Sleep apnea is one of the most common sleep disorders, which, if left untreated, may have severe health consequences in the long term. Many sleep apnea patients remain non-diagnosed due to lacking access to medical tests. In recent years, portable and wearable sensors that measure blood oxygen saturation (SpO2) are becoming common and affordable for daily use, and they open the door for affordable and accessible sleep apnea screening in the context of everyday life. To learn about the advancement in SpO2-based sleep apnea screening, we conducted a survey of published studies. We searched databases including Springer, Science Direct, Web of Science, ACM Digital Library, and IEEE Xplore using the keywords “sleep apnea” AND (“SpO2” OR “blood oxygen saturation”) AND (“machine learning” OR “deep learning”). After screening 835 results, we included 31 publications for a full-text review. Analysis shows that SpO2-based sleep apnea screening studies consist of three main categories: (1) individual apnea events detection, (2) apnea-hypopnea index prediction, and (3) apnea severity classification. We found two significant research gaps: a lack of sufficient and diverse publicly available datasets, and the absence of standardized protocols for data collection, signal preprocessing, and model bench marking. Future research should focus on addressing these gaps to enhance the effectiveness and reliability of AI-driven sleep apnea screening methods using SpO2 signals. PubDate: 2025-04-09T00:00:00Z
Authors:Maram Al Alfi, Pedro Peris-Lopez, Carmen Camara Abstract: IntroductionThe electrocardiogram (ECG) is a highly secure biometric modality due to its intrinsic physiological characteristics, making it resilient to forgery and external attacks. This study presents a novel real-time biometric authentication system integrating Graph Convolutional Networks (GCN) with Mutual Information (MI) indices extracted from 12-lead ECG signals.MethodsThe MI index quantifies the statistical dependencies among ECG leads and is computed using entropy-based estimations. This index is used to construct a graph representation, where nodes correspond to ECG features and edges reflect their relationships based on MI values. The GCN model is trained on this graph, enabling it to learn complex patterns for user identification efficiently.ResultsExperimental results demonstrate that the proposed GCN-MI model achieves 100% accuracy with a 5-layer architecture at a k-fold of 75, outperforming conventional approaches that require less training data.DiscussionThis work introduces several innovations: the integration of MI indices enhances feature selection, improving model robustness and efficiency; the graph-based learning framework effectively captures both spatial and statistical relationships within ECG data, leading to higher classification accuracy; the proposed approach offers a scalable and real-time biometric authentication system suitable for applications in finance, healthcare, and personal device access. These findings highlight the practical value of the GCN-MI approach, setting a new benchmark in ECG-based biometric identification. PubDate: 2025-04-08T00:00:00Z
Authors:Oliver Meindl, Sarah Peuten, Xena Striebel, Henner Gimpel, Christoph Ostgathe, Werner Schneider, Tobias Steigleder Abstract: IntroductionPalliative care is based on the principle of multi-professional collaboration, which integrates diverse competencies and perspectives to provide holistic care and support for patients and their relatives. In palliative care teams, there is an intensive exchange of information and knowledge; however, current documentation and hospital information systems often fall short of meeting the specific demands for effective collaboration and dynamic communication in this field.MethodsThis action design research study is based on the three-and-a-half-year interdisciplinary research project PALLADiUM and aims to demonstrate the added value of knowledge-driven digitalization.Results and discussionOur study provides novel recommendations for digitally supported multi-professional collaboration tailored to the specific requirements of palliative care and similar fields. Based on the analytical distinction between ‘information’ and ‘knowledge,’ we present design recommendations for co-creative, knowledge-driven development processes and multi-professional collaboration support systems. We further illustrate how these recommendations have been implemented into a functional technical demonstrator and outline how our results could impact future digitalization initiatives in healthcare. PubDate: 2025-04-07T00:00:00Z
Open Access journal
[96 journals]
