%0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e59792 %T Generative AI Models in Time-Varying Biomedical Data: Scoping Review %A He,Rosemary %A Sarwal,Varuni %A Qiu,Xinru %A Zhuang,Yongwen %A Zhang,Le %A Liu,Yue %A Chiang,Jeffrey %+ Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, 300 Stein Plaza, Suite 560, Los Angeles, CA, 90095, United States, 1 310 825 5111, njchiang@g.ucla.edu %K generative artificial intelligence %K artificial intelligence %K time series %K electronic health records %K electronic medical records %K systematic reviews %K disease trajectory %K machine learning %K algorithms %K forecasting %D 2025 %7 10.3.2025 %9 Review %J J Med Internet Res %G English %X Background: Trajectory modeling is a long-standing challenge in the application of computational methods to health care. In the age of big data, traditional statistical and machine learning methods do not achieve satisfactory results as they often fail to capture the complex underlying distributions of multimodal health data and long-term dependencies throughout medical histories. Recent advances in generative artificial intelligence (AI) have provided powerful tools to represent complex distributions and patterns with minimal underlying assumptions, with major impact in fields such as finance and environmental sciences, prompting researchers to apply these methods for disease modeling in health care. Objective: While AI methods have proven powerful, their application in clinical practice remains limited due to their highly complex nature. The proliferation of AI algorithms also poses a significant challenge for nondevelopers to track and incorporate these advances into clinical research and application. In this paper, we introduce basic concepts in generative AI and discuss current algorithms and how they can be applied to health care for practitioners with little background in computer science. Methods: We surveyed peer-reviewed papers on generative AI models with specific applications to time-series health data. Our search included single- and multimodal generative AI models that operated over structured and unstructured data, physiological waveforms, medical imaging, and multi-omics data. We introduce current generative AI methods, review their applications, and discuss their limitations and future directions in each data modality. Results: We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and reviewed 155 articles on generative AI applications to time-series health care data across modalities. Furthermore, we offer a systematic framework for clinicians to easily identify suitable AI methods for their data and task at hand. Conclusions: We reviewed and critiqued existing applications of generative AI to time-series health data with the aim of bridging the gap between computational methods and clinical application. We also identified the shortcomings of existing approaches and highlighted recent advances in generative AI that represent promising directions for health care modeling. %M 40063929 %R 10.2196/59792 %U https://www.jmir.org/2025/1/e59792 %U https://doi.org/10.2196/59792 %U http://www.ncbi.nlm.nih.gov/pubmed/40063929 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60077 %T 25 Years of Electronic Health Record Implementation Processes: Scoping Review %A Finnegan,Harriet %A Mountford,Nicola %+ School of Business, Maynooth University, 3rd Floor TSI Building, Maynooth, Kildare, W23 X04D, Ireland, 353 17083609, harriet.finnegan.2017@mumail.ie %K electronic health record system %K EHR %K electronic medical record %K EMR %K scoping review %K process %K implementation %D 2025 %7 3.3.2025 %9 Review %J J Med Internet Res %G English %X Background: Electronic health record (EHR) systems have undergone substantial evolution over the past 25 years, transitioning from rudimentary digital repositories to sophisticated tools that are integral to modern health care delivery. These systems have the potential to increase efficiency and improve patient care. However, for these systems to reach their potential, we need to understand how the process of EHR implementation works. Objective: This scoping review aimed to examine the implementation process of EHRs from 1999 to 2024 and to articulate process-focused recommendations for future EHR implementations that build on this history of EHR research. Methods: We conducted a scoping literature review following a systematic methodological framework. A total of 5 databases were selected from the disciplines of medicine and business: EBSCO, PubMed, Embase, IEEE Explore, and Scopus. The search included studies published from 1999 to 2024 that addressed the process of implementing an EHR. Keywords included “EHR,” “EHRS,” “Electronic Health Record*,” “EMR,” “EMRS,” “Electronic Medical Record*,” “implemen*,” and “process.” The findings were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. The selected literature was thematically coded using NVivo qualitative analysis software, with the results reported qualitatively. Results: This review included 90 studies that described the process of EHR implementation in different settings. The studies identified key elements, such as the role of the government and vendors, the importance of communication and relationships, the provision of training and support, and the implementation approach and cost. Four process-related categories emerged from these results: compliance processes, collaboration processes, competence-development processes, and process costs. Conclusions: Although EHRs hold immense promise in improving patient care, enhancing research capabilities, and optimizing health care efficiency, there is a pressing need to examine the actual implementation process to understand how to approach implementation. Our findings offer 7 process-focused recommendations for EHR implementation formed from analysis of the selected literature. %M 40053758 %R 10.2196/60077 %U https://www.jmir.org/2025/1/e60077 %U https://doi.org/10.2196/60077 %U http://www.ncbi.nlm.nih.gov/pubmed/40053758 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60512 %T Digital Age Transformation in Patient-Physician Communication: 25-Year Narrative Review (1999-2023) %A Song,Mingming %A Elson,Joel %A Bastola,Dhundy %+ University of Nebraska at Omaha, 1110 S 67th Street, Omaha, NE, 68182, United States, 1 4025544899, dkbastola@unomaha.edu %K health communication %K health IT %K patient empowerment %K shared decision-making %K patient-physician relationship %K trust %D 2025 %7 16.1.2025 %9 Review %J J Med Internet Res %G English %X Background: The evolution of patient-physician communication has changed since the emergence of the World Wide Web. Health information technology (health IT) has become an influential tool, providing patients with access to a breadth of health information electronically. While such information has greatly facilitated communication between patients and physicians, it has also led to information overload and the potential for spreading misinformation. This could potentially result in suboptimal health care outcomes for patients. In the digital age, effectively integrating health IT with patient empowerment, strong patient-physician relationships, and shared decision-making could be increasingly important for health communication and reduce these risks. Objective: This review aims to identify key factors in health communication and demonstrate how essential elements in the communication model, such as health IT, patient empowerment, and shared decision-making, can be utilized to optimize patient-physician communication and, ultimately, improve patient outcomes in the digital age. Methods: Databases including PubMed, Web of Science, Scopus, PsycINFO, and IEEE Xplore were searched using keywords related to patient empowerment, health IT, shared decision-making, patient-physician relationship, and health communication for studies published between 1999 and 2023. The data were constrained by a modified query using a multidatabase search strategy. The screening process was supported by the web-based software tool Rayyan. The review methodology involved carefully designed steps to provide a comprehensive summary of existing research. Topic modeling, trend analysis, and synthesis were applied to analyze and evaluate topics, trends, and gaps in health communication. Results: From a total of 389 selected studies, topic modeling analysis identified 3 primary topics: (1) Patient-Physician Relationship and Shared Decision-Making, (2) Patient Empowerment and Education Strategies, and (3) Health Care Systems and Health IT Implementations. Trend analysis further indicated their frequency and prominence in health communication from 1999 to 2023. Detailed examinations were conducted using secondary terms, including trust, health IT, patient-physician relationship, and patient empowerment, derived from the main topics. These terms clarified the collective impact on improving health communication dynamics. The synthesis of the role of health IT in health communication models underscores its critical role in shaping patient-centered health care frameworks. Conclusions: This review highlights the significant contributions of key topics that should be thoroughly investigated and integrated into health communication models in the digital age. While health IT plays an essential role in promoting shared decision-making and patient empowerment, challenges such as usability, privacy concerns, and digital literacy remain significant barriers. Future research should prioritize evaluating these key themes and addressing the challenges associated with health IT in health communication models. Additionally, exploring how emerging technologies, such as artificial intelligence, can support these goals may provide valuable insights for enhancing health communication. %M 39819592 %R 10.2196/60512 %U https://www.jmir.org/2025/1/e60512 %U https://doi.org/10.2196/60512 %U http://www.ncbi.nlm.nih.gov/pubmed/39819592 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60189 %T Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study %A Klein,Dave %A Montgomery,Aisha %A Begale,Mark %A Sutherland,Scott %A Sawyer,Sherilyn %A McCauley,Jacob L %A Husbands,Letheshia %A Joshi,Deepti %A Ashbeck,Alan %A Palmer,Marcy %A Jain,Praduman %+ Vibrent Health, Inc, 4114 Legato Rd #900, Fairfax, VA, 22033, United States, 1 6784686545, aisha.montgomery@gmail.com %K longitudinal studies %K cohort studies %K health disparities %K minority populations %K vulnerable populations %K precision medicine %K biomedical research %K decentralization %K digital health technology %K database management system %D 2025 %7 15.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used. Objective: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health’s (NIH) All of Us Research Program (AOU). AOU is an ongoing national, multiyear study aimed to build a research cohort of 1 million participants that reflects the diversity of the United States, including minority, health-disparate, and other populations underrepresented in biomedical research (UBR). Methods: We collaborated with community members, health care provider organizations (HPOs), and NIH leadership to design, build, and validate a secure, feature-rich digital platform to facilitate multisite, hybrid, and remote study participation and multimodal data collection in AOU. Participants were recruited by in-person, print, and online digital campaigns. Participants securely accessed the DHRP via web and mobile apps, either independently or with research staff support. The participant-facing tool facilitated electronic informed consent (eConsent), multisource data collection (eg, surveys, genomic results, wearables, and electronic health records [EHRs]), and ongoing participant engagement. We also built tools for research staff to conduct remote participant support, study workflow management, participant tracking, data analytics, data harmonization, and data management. Results: We built a secure, participant-centric DHRP with engaging functionality used to recruit, engage, and collect data from 705,719 diverse participants throughout the United States. As of April 2024, 87% (n=613,976) of the participants enrolled via the platform were from UBR groups, including racial and ethnic minorities (n=282,429, 46%), rural dwelling individuals (n=49,118, 8%), those over the age of 65 years (n=190,333, 31%), and individuals with low socioeconomic status (n=122,795, 20%). Conclusions: We built a participant-centric digital platform with tools to enable engagement with individuals from different racial, ethnic, and socioeconomic backgrounds and other UBR groups. This DHRP demonstrated successful use among diverse participants. These findings could be used as best practices for the effective use of digital platforms to build and sustain cohorts of various study designs and increase engagement with diverse populations in health research. %M 39813673 %R 10.2196/60189 %U https://www.jmir.org/2025/1/e60189 %U https://doi.org/10.2196/60189 %U http://www.ncbi.nlm.nih.gov/pubmed/39813673 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e59027 %T Mapping the Landscape of Digital Health Intervention Strategies: 25-Year Synthesis %A Liu,Shiyu %A Ma,Jingru %A Sun,Meichen %A Zhang,Chao %A Gao,Yujing %A Xu,Jinghong %+ , School of Journalism and Communication, Beijing Normal University, No 19, Xinjiekouwai St, Haidian District, Beijing, China, Beijing, 100875, China, 86 15810320711, 123abctg@163.com %K digital health interventions %K intervention strategies %K behavior change %K mHealth %K eHealth %K randomized controlled trial %D 2025 %7 13.1.2025 %9 Review %J J Med Internet Res %G English %X Background: Digital health interventions have emerged as promising tools to promote health behavior change and improve health outcomes. However, a comprehensive synthesis of strategies contributing to these interventions is lacking. Objective: This study aims to (1) identify and categorize the strategies used in digital health interventions over the past 25 years; (2) explore the differences and changes in these strategies across time periods, countries, populations, delivery methods, and senders; and (3) serve as a valuable reference for future researchers and practitioners to improve the effectiveness of digital health interventions. Methods: This study followed a systematic review approach, complemented by close reading and text coding. A comprehensive search for published English academic papers from PubMed, Web of Science, and Scopus was conducted. The search employed a combination of digital health and intervention-related terms, along with database-specific subject headings and filters. The time span covered 25 years, from January 1, 1999, to March 10, 2024. Sample papers were selected based on study design, intervention details, and strategies. The strategies were identified and categorized based on the principles of Behavior Change Techniques and Behavior Strategies. Results: A total of 885 papers involving 954,847 participants met the eligibility criteria. We identified 173 unique strategies used in digital health interventions, categorized into 19 themes. The 3 most frequently used strategies in the sample papers were “guide” (n=492, 55.6%), “monitor” (n=490, 55.4%), and “communication” (n=392, 44.3%). The number of strategies employed in each paper ranged from 1 to 32. Most interventions targeted clients (n=844, 95.4%) and were carried out in hospitals (n=268, 30.3%). High-income countries demonstrated a substantially higher number and diversity of identified strategies than low- and middle-income countries, and the number of studies targeting the public (n=647, 73.1%) far exceeded those focusing on vulnerable groups (n=238, 26.9%). Conclusions: Digital health interventions and strategies have undergone considerable development over the past 25 years. They have evolved from simple approaches to sophisticated, personalized techniques and are trending toward multifaceted interventions, leveraging advanced technologies for real-time monitoring and feedback. Future studies should focus on rigorous evaluations, long-term effectiveness, and tailored approaches for diverse populations, and more attention should be given to vulnerable groups. %M 39804697 %R 10.2196/59027 %U https://www.jmir.org/2025/1/e59027 %U https://doi.org/10.2196/59027 %U http://www.ncbi.nlm.nih.gov/pubmed/39804697 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60443 %T The Paradigm Shift From Patient to Health Consumer: 20 Years of Value Assessment in Health %A van den Broek-Altenburg,Eline M %A Atherly,Adam J %+ University of Vermont, 111 Colchester Avenue, Burlington, VT, 05401, United States, 1 8026562722, eline.altenburg@med.uvm.edu %K value assessment %K cost-effectiveness %K quality-adjusted life-years %K QALY %K health consumer %K health technology %K value based %K digital health %K patient centered %K preferences %K health economics %D 2025 %7 10.1.2025 %9 Viewpoint %J J Med Internet Res %G English %X Health care is undergoing a “revolution,” where patients are becoming consumers and armed with apps, consumer review scores, and, in some countries, high out-of-pocket costs. Although economic analyses and health technology assessment (HTA) have come a long way in their evaluation of the clinical, economic, ethical, legal, and societal perspectives that may be impacted by new technologies and procedures, these approaches do not reflect underlying patient preferences that may be important in the assessment of “value” in the current value-based health care transition. The major challenges that come with the transformation to a value-based health care system lead to questions such as “How are economic analyses, often the basis for policy and reimbursement decisions, going to switch from a societal to an individual perspective?” and “How do we then assess (economic) value, considering individual preference heterogeneity, as well as varying heuristics and decision rules?” These challenges, related to including the individual perspective in cost-effectiveness analysis (CEA), have been widely debated. Cost-effectiveness measures treatments in terms of costs and quality-adjusted life-years (QALYs), where QALYs assume that a health state that is more desirable is more valuable, and therefore, value is equated with preference or desirability. QALYs have long been criticized for empirical and conceptual shortcomings. However, policy makers in many countries have used QALY measures to make health coverage decisions, although now, patients, and patient advocates, are questioning the valuation methodologies. This has led to the development of new approaches to valuing health, which are already starting to be used in the United States. This paper reviews 20-25 years of value assessment approaches in health and concludes with challenges and opportunities for value assessment methods in health in the years to come. %M 39793021 %R 10.2196/60443 %U https://www.jmir.org/2025/1/e60443 %U https://doi.org/10.2196/60443 %U http://www.ncbi.nlm.nih.gov/pubmed/39793021 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e59024 %T Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review %A Shen,Yun %A Yu,Jiamin %A Zhou,Jian %A Hu,Gang %+ Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 600 Yishan Road, Shanghai, 200233, China, 86 64369181 ext 8337, zhoujian@sjtu.edu.cn %K electronic health record %K electronic medical record %K medical research %K interoperability %K eHealth %K systematic review %K real-world evidence %K artificial intelligence %D 2025 %7 9.1.2025 %9 Review %J J Med Internet Res %G English %X Background: Electronic health records (EHRs) facilitate the accessibility and sharing of patient data among various health care providers, contributing to more coordinated and efficient care. Objective: This study aimed to summarize the evolution of secondary use of EHRs and their interoperability in medical research over the past 25 years. Methods: We conducted an extensive literature search in the PubMed, Scopus, and Web of Science databases using the keywords Electronic health record and Electronic medical record in the title or abstract and Medical research in all fields from 2000 to 2024. Specific terms were applied to different time periods. Results: The review yielded 2212 studies, all of which were then screened and processed in a structured manner. Of these 2212 studies, 2102 (93.03%) were included in the review analysis, of which 1079 (51.33%) studies were from 2000 to 2009, 582 (27.69%) were from 2010 to 2019, 251 (11.94%) were from 2020 to 2023, and 190 (9.04%) were from 2024. Conclusions: The evolution of EHRs marks an important milestone in health care’s journey toward integrating technology and medicine. From early documentation practices to the sophisticated use of artificial intelligence and big data analytics today, EHRs have become central to improving patient care, enhancing public health surveillance, and advancing medical research. %M 39787599 %R 10.2196/59024 %U https://www.jmir.org/2025/1/e59024 %U https://doi.org/10.2196/59024 %U http://www.ncbi.nlm.nih.gov/pubmed/39787599 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58637 %T Decades in the Making: The Evolution of Digital Health Research Infrastructure Through Synthetic Data, Common Data Models, and Federated Learning %A Austin,Jodie A %A Lobo,Elton H %A Samadbeik,Mahnaz %A Engstrom,Teyl %A Philip,Reji %A Pole,Jason D %A Sullivan,Clair M %+ Queensland Digital Health Centre, Centre for Health Services Research, The University of Queensland, Level 5, UQ Health Sciences Building, Fig Tree Cres, Brisbane, 4029, Australia, 61 7 3176 5530, j.austin1@uq.edu.au %K real-world data %K digital health research %K synthetic data %K common data models %K federated learning %K university-industry collaboration %D 2024 %7 20.12.2024 %9 Viewpoint %J J Med Internet Res %G English %X Traditionally, medical research is based on randomized controlled trials (RCTs) for interventions such as drugs and operative procedures. However, increasingly, there is a need for health research to evolve. RCTs are expensive to run, are generally formulated with a single research question in mind, and analyze a limited dataset for a restricted period. Progressively, health decision makers are focusing on real-world data (RWD) to deliver large-scale longitudinal insights that are actionable. RWD are collected as part of routine care in real time using digital health infrastructure. For example, understanding the effectiveness of an intervention could be enhanced by combining evidence from RCTs with RWD, providing insights into long-term outcomes in real-life situations. Clinicians and researchers struggle in the digital era to harness RWD for digital health research in an efficient and ethically and morally appropriate manner. This struggle encompasses challenges such as ensuring data quality, integrating diverse sources, establishing governance policies, ensuring regulatory compliance, developing analytical capabilities, and translating insights into actionable strategies. The same way that drug trials require infrastructure to support their conduct, digital health also necessitates new and disruptive research data infrastructure. Novel methods such as common data models, federated learning, and synthetic data generation are emerging to enhance the utility of research using RWD, which are often siloed across health systems. A continued focus on data privacy and ethical compliance remains. The past 25 years have seen a notable shift from an emphasis on RCTs as the only source of practice-guiding clinical evidence to the inclusion of modern-day methods harnessing RWD. This paper describes the evolution of synthetic data, common data models, and federated learning supported by strong cross-sector collaboration to support digital health research. Lessons learned are offered as a model for other jurisdictions with similar RWD infrastructure requirements. %M 39705072 %R 10.2196/58637 %U https://www.jmir.org/2024/1/e58637 %U https://doi.org/10.2196/58637 %U http://www.ncbi.nlm.nih.gov/pubmed/39705072 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60312 %T Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review %A Ogundiya,Oluwadamilola %A Rahman,Thahmina Jasmine %A Valnarov-Boulter,Ioan %A Young,Tim Michael %+ Queen Square Institute of Neurology, University College London, No/7 Queen Square, London, WC1N 3BG, United Kingdom, 44 203 1082781, t.young@ucl.ac.uk %K digital health %K digital medical education %K health education %K medical education %K mobile phone %K artificial intelligence %K AI %D 2024 %7 19.12.2024 %9 Review %J J Med Internet Res %G English %X Background: The last 25 years have seen enormous progression in digital technologies across the whole of the health service, including health education. The rapid evolution and use of web-based and digital techniques have been significantly transforming this field since the beginning of the new millennium. These advancements continue to progress swiftly, even more so after the COVID-19 pandemic. Objective: This narrative review aims to outline and discuss the developments that have taken place in digital medical education across the defined time frame. In addition, evidence for potential opportunities and challenges facing digital medical education in the near future was collated for analysis. Methods: Literature reviews were conducted using PubMed, Web of Science Core Collection, Scopus, Google Scholar, and Embase. The participants and learners in this study included medical students, physicians in training or continuing professional development, nurses, paramedics, and patients. Results: Evidence of the significant steps in the development of digital medical education in the past 25 years was presented and analyzed in terms of application, impact, and implications for the future. The results were grouped into the following themes for discussion: learning management systems; telemedicine (in digital medical education); mobile health; big data analytics; the metaverse, augmented reality, and virtual reality; the COVID-19 pandemic; artificial intelligence; and ethics and cybersecurity. Conclusions: Major changes and developments in digital medical education have occurred from around the start of the new millennium. Key steps in this journey include technical developments in teleconferencing and learning management systems, along with a marked increase in mobile device use for accessing learning over this time. While the pace of evolution in digital medical education accelerated during the COVID-19 pandemic, further rapid progress has continued since the resolution of the pandemic. Many of these changes are currently being widely used in health education and other fields, such as augmented reality, virtual reality, and artificial intelligence, providing significant future potential. The opportunities these technologies offer must be balanced against the associated challenges in areas such as cybersecurity, the integrity of web-based assessments, ethics, and issues of digital privacy to ensure that digital medical education continues to thrive in the future. %M 39700490 %R 10.2196/60312 %U https://www.jmir.org/2024/1/e60312 %U https://doi.org/10.2196/60312 %U http://www.ncbi.nlm.nih.gov/pubmed/39700490 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59888 %T Don’t Forget the Humble Text Message: 25 Years of Text Messaging in Health %A Dobson,Rosie %A Whittaker,Robyn %A Abroms,Lorien C %A Bramley,Dale %A Free,Caroline %A McRobbie,Hayden %A Stowell,Melanie %A Rodgers,Anthony %+ School of Population Health, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand, 64 93737599, r.dobson@auckland.ac.nz %K text messaging %K messaging %K SMS %K texting %K mHealth %K mobile health %D 2024 %7 17.12.2024 %9 Viewpoint %J J Med Internet Res %G English %X Since the early studies exploring the use of SMS text messaging for health intervention, text messaging has played a pivotal role in the advancement of mobile health. As an intervention modality, text messaging has provided vital learnings for the design and delivery of interventions, particularly in low-resource settings. Despite the advances in technology over the last 25 years, text messaging is still being used in largely the same way to deliver health information, behavior change interventions, and support. The strong, consistent evidence for the benefits of this type of intervention has made text messaging a routine part of health interventions around the world. Key to its success is its simplicity, alongside the benefit of being arguably the most accessible form of consumer digital health intervention. Text message interventions are well suited for public health interventions due to their low cost, vast reach, frequent use, high read rates, and ability to be tailored and personalized. Furthermore, the nature of text messaging interventions makes them ideal for the delivery of multilingual, culturally tailored interventions, which is important in the context of increasing cultural diversity in many countries internationally. Indeed, studies assessing text message–based health interventions have shown them to be effective across sociodemographic and ethnic groups and have led to their adoption into national-level health promotion programs. With a growing focus on artificial intelligence, robotics, sensors, and other advances in digital health, there is an opportunity to integrate these technologies into text messaging programs. Simultaneously, it is essential that equity remains at the forefront for digital health researchers, developers, and implementers. Ensuring digital health solutions address inequities in health experienced across the world while taking action to maximize digital inclusion will ensure the true potential of digital health is realized. Text messaging has the potential to continue to play a pivotal role in the delivery of equitable digital health tools to communities around the world for many years to come. Further new technologies can build on the humble text message, leveraging its success to advance the field of digital health. This Viewpoint presents a retrospective of text messaging in health, drawing on the example of text message–based interventions for smoking cessation, and presents evidence for the continued relevance of this mobile health modality in 2025 and beyond. %M 39689299 %R 10.2196/59888 %U https://www.jmir.org/2024/1/e59888 %U https://doi.org/10.2196/59888 %U http://www.ncbi.nlm.nih.gov/pubmed/39689299 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e63391 %T Telemonitoring for Chronic Heart Failure: Narrative Review of the 20-Year Journey From Concept to Standard Care in Germany %A Spethmann,Sebastian %A Hindricks,Gerhard %A Koehler,Kerstin %A Stoerk,Stefan %A Angermann,Christiane E %A Böhm,Michael %A Assmus,Birgit %A Winkler,Sebastian %A Möckel,Martin %A Mittermaier,Mirja %A Lelgemann,Monika %A Reuter,Daniel %A Bosch,Ralph %A Albrecht,Alexander %A von Haehling,Stephan %A Helms,Thomas M %A Sack,Stefan %A Bekfani,Tarek %A Gröschel,Jan Wolfgang %A Koehler,Magdalena %A Melzer,Christoph %A Wintrich,Jan %A Zippel-Schultz,Bettina %A Ertl,Georg %A Vogelmeier,Claus %A Dagres,Nikolaos %A Zernikow,Jasmin %A Koehler,Friedrich %+ Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité (DHZC), Chariteplatz 1, Berlin, 10117, Germany, 49 30450513142, Sebastian.spethmann@dhzc-charite.de %K telemedicine %K e-counseling %K heart decompensation %K Europe %K patient care management %D 2024 %7 4.12.2024 %9 Review %J J Med Internet Res %G English %X Background: Chronic heart failure (CHF) is a major cause of morbidity and mortality worldwide, placing a significant burden on health care systems. The concept of telemedicine for CHF was first introduced in the late 1990s, and since 2010, studies have demonstrated its potential to improve patient outcomes and reduce health care costs. Over the following decade, technological advancements and changes in health care policy led to the development of more sophisticated telemedicine solutions for CHF, including remote patient management through invasive or noninvasive telemonitoring devices, mobile apps, and virtual consultations. Years of public funding in Germany have generated evidence that remote patient management improves outcomes for patients with CHF, such as quality of life, and reduces hospital admissions. Based on these data, the Federal Joint Committee (Gemeinsamer Bundesausschuss; G-BA) decided, independently of the current European Society of Cardiology recommendations, to incorporate telemedicine as a standard digital intervention for high-risk patients with reduced left ventricular ejection fraction in Germany in 2020. Objective: This review aims to illustrate the journey from the initial concept through pioneering studies that led to telemedicine’s integration into standard care, and to share current experiences that have positioned Germany as a leader in cardiovascular telemedicine. Methods: We review and discuss existing literature and evidence on the development and implementation of telemonitoring for CHF in Germany over the past 20 years. Relevant studies, reports, and guidelines were identified through a comprehensive search of electronic databases, including PubMed, Google Scholar, and specialized journals focused on CHF telemonitoring. Results: Pioneering studies, such as the TIM-HF2 (Telemedical Interventional Management in Heart Failure II) and IN-TIME (Influence of Home Monitoring on Mortality and Morbidity in Heart Failure Patients with Impaired Left Ventricular Function) trials, demonstrated the effectiveness of remote patient management applications for patients with CHF in Germany and their applicability to current practices involving both invasive and noninvasive methods. Collaborations between researchers and technology developers overcame barriers, leading to sustainable improvements in patient care. Ongoing research on artificial intelligence applications for prioritizing and interpreting individual health data will continue to transform digital health care. Conclusions: The establishment of telemedical care for patients with HF across Europe is likely to benefit from experiences in Germany, where significant improvements have been achieved in the care of patients with HF. %M 39631073 %R 10.2196/63391 %U https://www.jmir.org/2024/1/e63391 %U https://doi.org/10.2196/63391 %U http://www.ncbi.nlm.nih.gov/pubmed/39631073 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59585 %T Ten Myths About the Effect of Social Media Use on Well-Being %A Hall,Jeffrey A %+ Department of Communication Studies, University of Kansas, Bailey Hall, 1440 Jayhawk Boulevard, Lawrence, KS, 66045, United States, 1 7858641082, hallj@ku.edu %K social media %K well-being %K health promotion %K depressive disorder %K depression %K anxiety %K adolescent %K mental health %D 2024 %7 25.11.2024 %9 Viewpoint %J J Med Internet Res %G English %X This viewpoint reviews the empirical evidence regarding the association between social media use and well-being, including life satisfaction and affective well-being, and the association between social media use and ill-being, including loneliness, anxiety, and depressive symptomology. To frame this discussion, this viewpoint will present 10 widely believed myths about social media, each drawn from popular discourse on the topic. In rebuttal, this viewpoint will offer a warranted claim supported by the research. The goal is to bring popular beliefs into dialogue with state-of-the-art quantitative social scientific evidence. It is the intention of this viewpoint to provide a more accurate and nuanced claim to challenge each myth. This viewpoint will bring attention to the importance of using rigorous scientific evidence to inform public debates about social media use and well-being, especially among adolescents and young adults. %M 39586087 %R 10.2196/59585 %U https://www.jmir.org/2024/1/e59585 %U https://doi.org/10.2196/59585 %U http://www.ncbi.nlm.nih.gov/pubmed/39586087 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57612 %T Perspectives of Digital Health Innovations in Low- and Middle-Income Health Care Systems From South and Southeast Asia %A Yi,Siyan %A Yam,Esabelle Lo Yan %A Cheruvettolil,Kochukoshy %A Linos,Eleni %A Gupta,Anshika %A Palaniappan,Latha %A Rajeshuni,Nitya %A Vaska,Kiran Gopal %A Schulman,Kevin %A Eggleston,Karen N %+ Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, #10-01, 12 Science Drive 2, Singapore, 117549, Singapore, 65 6516 6914, siyan@nus.edu.sg %K digital health innovations %K public health %K South and Southeast Asia %K health care challenges %K low- and middle-income countries %K LMICs %K global health %K health AI %K artificial intelligence %K public health responses %K global health contexts %K digital health %D 2024 %7 25.11.2024 %9 Viewpoint %J J Med Internet Res %G English %X Digital health innovations have emerged globally as a transformative force for addressing health system challenges, particularly in resource-constrained settings. The COVID-19 pandemic underscored the critical importance of these innovations for enhancing public health. In South and Southeast Asia, a region known for its cultural diversity and complex health care landscape, digital health innovations present a dynamic interplay of challenges and opportunities. We advocate for ongoing research built into system development and an evidence-based strategy focusing on designing and scaling national digital health infrastructures combined with a vibrant ecosystem or “marketplace” of local experiments generating shared experience about what works in which settings. As the global digital health revolution unfolds, the perspectives drawn from South and Southeast Asia—including the importance of local partnerships—may provide valuable insights for shaping future strategies and informing similar initiatives in low- and middle-income countries, contributing to effective digital health strategies across diverse global health contexts. %M 39586089 %R 10.2196/57612 %U https://www.jmir.org/2024/1/e57612 %U https://doi.org/10.2196/57612 %U http://www.ncbi.nlm.nih.gov/pubmed/39586089 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58933 %T A 25-Year Retrospective of Health IT Infrastructure Building: The Example of the Catalonia Region %A Piera-Jiménez,Jordi %A Carot-Sans,Gerard %A Ramiro-Pareta,Marina %A Nogueras,Maria Mercedes %A Folguera-Profitós,Júlia %A Ródenas,Pepi %A Jiménez-Rueda,Alba %A de Pando Navarro,Thais %A Mira Palacios,Josep Antoni %A Fajardo,Joan Carles %A Ustrell Campillo,Joan %A Vela,Emili %A Monterde,David %A Valero-Bover,Damià %A Bonet,Tara %A Tarrasó-Urios,Guillermo %A Cantenys-Sabà,Roser %A Fabregat-Fabregat,Pau %A Gómez Oliveros,Beatriz %A Berdún,Jesús %A Michelena,Xabier %A Cano,Isaac %A González-Colom,Rubèn %A Roca,Josep %A Solans,Oscar %A Pontes,Caridad %A Pérez-Sust,Pol %+ Catalan Health Service, Gran Via de les Corts Catalanes 587, Barcelona, 08007, Spain, 34 934643013, jpiera@catsalut.cat %K health ITs %K eHealth %K integrated care %K open platforms %K interoperability %K Catalonia %K digitalization %K health care structure %K health care delivery %K integrated pathway %K integrated treatment plan %K process management %D 2024 %7 18.11.2024 %9 Viewpoint %J J Med Internet Res %G English %X Over the past decades, health care systems have significantly evolved due to aging populations, chronic diseases, and higher-quality care expectations. Concurrently with the added health care needs, information and communications technology advancements have transformed health care delivery. Technologies such as telemedicine, electronic health records, and mobile health apps promise enhanced accessibility, efficiency, and patient outcomes, leading to more personalized, data-driven care. However, organizational, political, and cultural barriers and the fragmented approach to health information management are challenging the integration of these technologies to effectively support health care delivery. This fragmentation collides with the need for integrated care pathways that focus on holistic health and wellness. Catalonia (northeast Spain), a region of 8 million people with universal health care coverage and a single public health insurer but highly heterogeneous health care service providers, has experienced outstanding digitalization and integration of health information over the past 25 years, when the first transition from paper to digital support occurred. This Viewpoint describes the implementation of health ITs at a system level, discusses the hits and misses encountered in this journey, and frames this regional implementation within the global context. We present the architectures and use trends of the health information platforms over time. This provides insightful information that can be used by other systems worldwide in the never-ending transformation of health care structure and services. %M 39556831 %R 10.2196/58933 %U https://www.jmir.org/2024/1/e58933 %U https://doi.org/10.2196/58933 %U http://www.ncbi.nlm.nih.gov/pubmed/39556831 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59225 %T AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges %A Owen,David %A Lynham,Amy J %A Smart,Sophie E %A Pardiñas,Antonio F %A Camacho Collados,Jose %+ School of Computer Science and Informatics, Cardiff University, Abacws, Senghennydd Road, Cardiff, CF24 4AG, United Kingdom, 44 (0)29 2087 4812, owendw1@cardiff.ac.uk %K mental health %K depression %K anxiety %K schizophrenia %K social media %K natural language processing %K narrative review %D 2024 %7 15.11.2024 %9 Review %J J Med Internet Res %G English %X Background: Mental health disorders are currently the main contributor to poor quality of life and years lived with disability. Symptoms common to many mental health disorders lead to impairments or changes in the use of language, which are observable in the routine use of social media. Detection of these linguistic cues has been explored throughout the last quarter century, but interest and methodological development have burgeoned following the COVID-19 pandemic. The next decade may see the development of reliable methods for predicting mental health status using social media data. This might have implications for clinical practice and public health policy, particularly in the context of early intervention in mental health care. Objective: This study aims to examine the state of the art in methods for predicting mental health statuses of social media users. Our focus is the development of artificial intelligence–driven methods, particularly natural language processing, for analyzing large volumes of written text. This study details constraints affecting research in this area. These include the dearth of high-quality public datasets for methodological benchmarking and the need to adopt ethical and privacy frameworks acknowledging the stigma experienced by those with a mental illness. Methods: A Google Scholar search yielded peer-reviewed articles dated between 1999 and 2024. We manually grouped the articles by 4 primary areas of interest: datasets on social media and mental health, methods for predicting mental health status, longitudinal analyses of mental health, and ethical aspects of the data and analysis of mental health. Selected articles from these groups formed our narrative review. Results: Larger datasets with precise dates of participants’ diagnoses are needed to support the development of methods for predicting mental health status, particularly in severe disorders such as schizophrenia. Inviting users to donate their social media data for research purposes could help overcome widespread ethical and privacy concerns. In any event, multimodal methods for predicting mental health status appear likely to provide advancements that may not be achievable using natural language processing alone. Conclusions: Multimodal methods for predicting mental health status from voice, image, and video-based social media data need to be further developed before they may be considered for adoption in health care, medical support, or as consumer-facing products. Such methods are likely to garner greater public confidence in their efficacy than those that rely on text alone. To achieve this, more high-quality social media datasets need to be made available and privacy concerns regarding the use of these data must be formally addressed. A social media platform feature that invites users to share their data upon publication is a possible solution. Finally, a review of literature studying the effects of social media use on a user’s depression and anxiety is merited. %M 39546783 %R 10.2196/59225 %U https://www.jmir.org/2024/1/e59225 %U https://doi.org/10.2196/59225 %U http://www.ncbi.nlm.nih.gov/pubmed/39546783 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60057 %T Decoding the Digital Pulse: Bibliometric Analysis of 25 Years in Digital Health Research Through the Journal of Medical Internet Research %A Kaczmarczyk,Robert %A Wilhelm,Theresa Isabelle %A Roos,Jonas %A Martin,Ron %+ Eye Center—Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Killianstraße 5, Freiburg, 79106, Germany, 49 76127040020, theresa.wilhelm@uniklinik-freiburg.de %K digital health %K JMIR publication analysis %K network analysis %K artificial intelligence %K AI %K large language models %K eHealth %K Claude 3 Opus %K digital %K digital technology %K digital intervention %K machine learning %K natural language processing %K NLP %K deep learning %K algorithm %K model %K analytics %K practical model %K pandemic %K postpandemic era %K mobile phone %D 2024 %7 15.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: As the digital health landscape continues to evolve, analyzing the progress and direction of the field can yield valuable insights. The Journal of Medical Internet Research (JMIR) has been at the forefront of disseminating digital health research since 1999. A comprehensive network analysis of JMIR publications can help illuminate the evolution and trends in digital medicine over the past 25 years. Objective: This study aims to conduct a detailed network analysis of JMIR’s publications to uncover the growth patterns, dominant themes, and potential future trajectories in digital health research. Methods: We retrieved 8068 JMIR papers from PubMed using the Biopython library. Keyword metrics were assessed using accuracy, recall, and F1-scores to evaluate the effectiveness of keyword identification from Claude 3 Opus and Gemini 1.5 Pro in addition to 2 conventional natural language processing methods using key bidirectional encoder representations from transformers. Future trends for 2024-2026 were predicted using Claude 3 Opus, Google’s Time Series Foundation Model, autoregressive integrated moving average, exponential smoothing, and Prophet. Network visualization techniques were used to represent and analyze the complex relationships between collaborating countries, paper types, and keyword co-occurrence. Results: JMIR’s publication volume showed consistent growth, with a peak in 2020. The United States dominated country contributions, with China showing a notable increase in recent years. Keyword analysis from 1999 to 2023 showed significant thematic shifts, from an early internet and digital health focus to the dominance of COVID-19 and advanced technologies such as machine learning. Predictions for 2024-2026 suggest an increased focus on artificial intelligence, digital health, and mental health. Conclusions: Network analysis of JMIR publications provides a macroscopic view of the evolution of the digital health field. The journal’s trajectory reflects broader technological advances and shifting research priorities, including the impact of the COVID-19 pandemic. The predicted trends underscore the growing importance of computational technology in future health care research and practice. The findings from JMIR provide a glimpse into the future of digital medicine, suggesting a robust integration of artificial intelligence and continued emphasis on mental health in the postpandemic era. %M 39546778 %R 10.2196/60057 %U https://www.jmir.org/2024/1/e60057 %U https://doi.org/10.2196/60057 %U http://www.ncbi.nlm.nih.gov/pubmed/39546778 %0 Journal Article %@ 2817-092X %I JMIR Publications %V 3 %N %P e59556 %T Twenty-Five Years of AI in Neurology: The Journey of Predictive Medicine and Biological Breakthroughs %A Gutman,Barak %A Shmilovitch,Amit-Haim %A Aran,Dvir %A Shelly,Shahar %+ Department of Neurology, Rambam Medical Center, HaAliya HaShniya St 8, Haifa, 3109601, Israel, 972 4 777 3568, shahar.shell@technion.ac.il %K neurology %K artificial intelligence %K telemedicine %K clinical advancements %K mobile phone %D 2024 %7 8.11.2024 %9 Viewpoint %J JMIR Neurotech %G English %X Neurological disorders are the leading cause of physical and cognitive disability across the globe, currently affecting up to 15% of the world population, with the burden of chronic neurodegenerative diseases having doubled over the last 2 decades. Two decades ago, neurologists relying solely on clinical signs and basic imaging faced challenges in diagnosis and treatment. Today, the integration of artificial intelligence (AI) and bioinformatic methods is changing this landscape. This paper explores this transformative journey, emphasizing the critical role of AI in neurology, aiming to integrate a multitude of methods and thereby enhance the field of neurology. Over the past 25 years, integrating biomedical data science into medicine, particularly neurology, has fundamentally transformed how we understand, diagnose, and treat neurological diseases. Advances in genomics sequencing, the introduction of new imaging methods, the discovery of novel molecular biomarkers for nervous system function, a comprehensive understanding of immunology and neuroimmunology shaping disease subtypes, and the advent of advanced electrophysiological recording methods, alongside the digitalization of medical records and the rise of AI, all led to an unparalleled surge in data within neurology. In addition, telemedicine and web-based interactive health platforms, accelerated by the COVID-19 pandemic, have become integral to neurology practice. The real-world impact of these advancements is evident, with AI-driven analysis of imaging and genetic data leading to earlier and more accurate diagnoses of conditions such as multiple sclerosis, Parkinson disease, amyotrophic lateral sclerosis, Alzheimer disease, and more. Neuroinformatics is the key component connecting all these advances. By harnessing the power of IT and computational methods to efficiently organize, analyze, and interpret vast datasets, we can extract meaningful insights from complex neurological data, contributing to a deeper understanding of the intricate workings of the brain. In this paper, we describe the large-scale datasets that have emerged in neurology over the last 25 years and showcase the major advancements made by integrating these datasets with advanced neuroinformatic approaches for the diagnosis and treatment of neurological disorders. We further discuss challenges in integrating AI into neurology, including ethical considerations in data use, the need for further personalization of treatment, and embracing new emerging technologies like quantum computing. These developments are shaping a future where neurological care is more precise, accessible, and tailored to individual patient needs. We believe further advancements in AI will bridge traditional medical disciplines and cutting-edge technology, navigating the complexities of neurological data and steering medicine toward a future of more precise, accessible, and patient-centric health care. %R 10.2196/59556 %U https://neuro.jmir.org/2024/1/e59556 %U https://doi.org/10.2196/59556 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60441 %T The Journey From Nonimmersive to Immersive Multiuser Applications in Mental Health Care: Systematic Review %A Fajnerova,Iveta %A Hejtmánek,Lukáš %A Sedlák,Michal %A Jablonská,Markéta %A Francová,Anna %A Stopková,Pavla %+ Research Center for Virtual Reality in Mental Health and Neuroscience, National Institute of Mental Health, Topolová 748, Klecany, 250 67, Czech Republic, 420 283 088 478, Iveta.fajnerova@nudz.cz %K digital health %K mental health care %K clinical interventions %K multiuser %K immersive %K virtual reality %K VR %K app %K mental health %K online tools %K synthesis %K mobile phone %K PRISMA %D 2024 %7 7.11.2024 %9 Review %J J Med Internet Res %G English %X Background: Over the past 25 years, the development of multiuser applications has seen considerable advancements and challenges. The technological development in this field has emerged from simple chat rooms through videoconferencing tools to the creation of complex, interactive, and often multisensory virtual worlds. These multiuser technologies have gradually found their way into mental health care, where they are used in both dyadic counseling and group interventions. However, some limitations in hardware capabilities, user experience designs, and scalability may have hindered the effectiveness of these applications. Objective: This systematic review aims at summarizing the progress made and the potential future directions in this field while evaluating various factors and perspectives relevant to remote multiuser interventions. Methods: The systematic review was performed based on a Web of Science and PubMed database search covering articles in English, published from January 1999 to March 2024, related to multiuser mental health interventions. Several inclusion and exclusion criteria were determined before and during the records screening process, which was performed in several steps. Results: We identified 49 records exploring multiuser applications in mental health care, ranging from text-based interventions to interventions set in fully immersive environments. The number of publications exploring this topic has been growing since 2015, with a large increase during the COVID-19 pandemic. Most digital interventions were delivered in the form of videoconferencing, with only a few implementing immersive environments. The studies used professional or peer-supported group interventions or a combination of both approaches. The research studies targeted diverse groups and topics, from nursing mothers to psychiatric disorders or various minority groups. Most group sessions occurred weekly, or in the case of the peer-support groups, often with a flexible schedule. Conclusions: We identified many benefits to multiuser digital interventions for mental health care. These approaches provide distributed, always available, and affordable peer support that can be used to deliver necessary help to people living outside of areas where in-person interventions are easily available. While immersive virtual environments have become a common tool in many areas of psychiatric care, such as exposure therapy, our results suggest that this technology in multiuser settings is still in its early stages. Most identified studies investigated mainstream technologies, such as videoconferencing or text-based support, substituting the immersive experience for convenience and ease of use. While many studies discuss useful features of virtual environments in group interventions, such as anonymity or stronger engagement with the group, we discuss persisting issues with these technologies, which currently prevent their full adoption. %M 39509153 %R 10.2196/60441 %U https://www.jmir.org/2024/1/e60441 %U https://doi.org/10.2196/60441 %U http://www.ncbi.nlm.nih.gov/pubmed/39509153 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60025 %T Advancing the United Nations Sustainable Development Goals Through Digital Health Research: 25 Years of Contributions From the Journal of Medical Internet Research %A Raman,Raghu %A Singhania,Monica %A Nedungadi,Prema %+ Amrita School of Business, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, 690525, India, 91 9895028779, raghu@amrita.edu %K sustainable development goal %K topic modeling %K public health %K surveillance %K gender equality %K non-communicable disease %K social media %K COVID-19 %K SARS-CoV-2 %K coronavirus %K machine learning %K artificial intelligence %K AI %K digital health %D 2024 %7 4.11.2024 %9 Research Letter %J J Med Internet Res %G English %X %M 39496147 %R 10.2196/60025 %U https://www.jmir.org/2024/1/e60025 %U https://doi.org/10.2196/60025 %U http://www.ncbi.nlm.nih.gov/pubmed/39496147 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59791 %T The Evolution of Health Information Technology for Enhanced Patient-Centric Care in the United States: Data-Driven Descriptive Study %A Barker,Wesley %A Chang,Wei %A Everson,Jordan %A Gabriel,Meghan %A Patel,Vaishali %A Richwine,Chelsea %A Strawley,Catherine %+ Office of the Assistant Secretary for Technology Policy, US Department of Health and Human Services, 330 C St SW, Floor 7, Washington, DC, 20201, United States, 1 202 465 0597, meghan.gabriel@hhs.gov %K interoperability %K e-prescribing %K electronic public health reporting %K patient access to health information %K electronic health records %K health IT %D 2024 %7 28.10.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Health information technology (health IT) has revolutionized health care in the United States through interoperable clinical care data exchange, e-prescribing, electronic public health reporting, and electronic patient access to health information. Objective: This study aims to examine progress in health IT adoption and its alignment with the Office of the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health IT (ASTP's) mission to enhance health care through data access and exchange. Methods: This study leverages data on end users of health IT to capture trends in engagement in interoperable clinical care data exchange (ability to find, send, receive, and integrate information from outside organizations), e-prescribing, electronic public health reporting, and capabilities to enable patient access to electronic health information. Data were primarily sourced from the American Hospital Association Annual Survey IT Supplement (2008 to 2023), Surescripts e-prescribing use data (2008 to 2023), the National Cancer Institute’s Health Information National Trends Survey (2014 to 2022), and the National Center for Health Statistics’ National Electronic Health Records Survey (2009 to 2023). Results: Since 2009, there has been a 10-fold increase in electronic health record (EHR) use among hospitals and a 5-fold increase among physicians. This enabled the interoperable exchange of electronic health information, e- prescribing, electronic public health data exchange, and the means for patients and their caregivers to access crucial personal health information digitally. As of 2023, 70% of hospitals are interoperable, with many providers integrated within EHR systems. Nearly all pharmacies and 92% of prescribers possess e-prescribing capabilities, an 85%-point increase since 2008. In 2013, 40% of hospitals and one-third of physicians allowed patients to view their online medical records. Patient access has improved, with 97% of hospitals and 65% of physicians possessing EHRs that enable patients to access their online medical records. As of 2022, three-fourths of individuals report being offered access to patient portals, and over half (57%) report engaging with their health information through their patient portal. Electronic public health reporting has also seen an increase, with most hospitals and physicians actively engaged in key reporting types. Conclusions: Federal incentives have contributed to the widespread adoption of EHRs and broad digitization in health care, while efforts to promote interoperability have encouraged collaboration across health care entities. As a result, interoperable clinical care data exchange, e-prescribing, electronic public health reporting, and patient access to health information have grown substantially over the past quarter century and have been shown to improve health care outcomes. However, interoperability hurdles, usability issues, data security concerns, and inequitable patient access persist. Addressing these issues will require collaborative efforts among stakeholders to promote data standardization, implement governance structures, and establish robust health information exchange networks. %M 39466303 %R 10.2196/59791 %U https://www.jmir.org/2024/1/e59791 %U https://doi.org/10.2196/59791 %U http://www.ncbi.nlm.nih.gov/pubmed/39466303 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58936 %T The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research %A Köhler,Charlotte %A Bartschke,Alexander %A Fürstenau,Daniel %A Schaaf,Thorsten %A Salgado-Baez,Eduardo %+ Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Charitéplatz 1, Berlin, 10117, Germany, 49 30450631167, eduardo.salgado@charite.de %K consumer devices %K smartwatches %K value-based health care %K monitoring %K nudging %K predicting %K mobile phone %D 2024 %7 25.10.2024 %9 Viewpoint %J J Med Internet Res %G English %X We propose a categorization of smartwatch use in the health care sector into 3 key functional domains: monitoring, nudging, and predicting. Monitoring involves using smartwatches within medical treatments to track health data, nudging pertains to individual use for health purposes outside a particular medical setting, and predicting involves using aggregated user data to train machine learning algorithms to predict health outcomes. Each domain offers unique contributions to health care, yet there is a lack of nuanced discussion in existing research. This paper not only provides an overview of recent technological advancements in consumer smartwatches but also explores the 3 domains in detail, culminating in a comprehensive summary that anticipates the future value and impact of smartwatches in health care. By dissecting the interconnected challenges and potentials, this paper aims to enhance the understanding and effective deployment of smartwatches in value-based health care. %M 39356287 %R 10.2196/58936 %U https://www.jmir.org/2024/1/e58936 %U https://doi.org/10.2196/58936 %U http://www.ncbi.nlm.nih.gov/pubmed/39356287 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e62691 %T Transitioning Perspectives in Digital Health Through Phenomenology Integration %A Fiordelli,Maddalena %+ Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera italiana, Via Buffi 13, Lugano, 6900, Switzerland, 41 586664139, maddalena.fiordelli@usi.ch %K eHealth %K digital health %K phenomenology %K phenomenological %K participatory %K health communication %K health information %K active listening %K lived experience %D 2024 %7 23.10.2024 %9 Viewpoint %J J Med Internet Res %G English %X The evolution of digital health, from its early days as eHealth to its current expansive scope, reflects a significant transformation in health care delivery and management. This transition underscores the integration of digital technologies across the health continuum from prevention and diagnosis to treatment and rehabilitation. The emergence of digital health has introduced innovative solutions but also posed challenges, particularly in aligning technological advancements with health needs, human experiences, and ethical considerations. This position paper aims to explore the integration of phenomenology in digital health, advocating for a paradigm that emphasizes the centrality of human experience in the design and implementation of digital health solutions. It specifically seeks to address challenges related to relevance for individuals who “speak” different languages, ensuring long-term use, addressing digital and health literacy, coordinating various sources, and navigating ethical issues in the rapidly evolving digital health landscape. Drawing upon years of research and practical experience in communication technologies and health, this paper uses a reflective approach to examine the intersection of digital health and phenomenology. It reviews the historical development of digital health, identifies the challenges faced during its evolution, and discusses the potential of phenomenological methods to enhance user-centered design and ethical practices in digital health. The integration of phenomenology into digital health facilitates a deeper understanding of user experiences, enabling the development of more responsive and ethical digital health solutions. Participatory design models, informed by phenomenological perspectives, offer a pathway to bridge the gap between technological innovation and human-centric health care. The paper highlights successful practices in digital health development, including mobile apps for vaccination decision-making and platforms for managing chronic conditions, illustrating the benefits of a phenomenological approach. Transitioning perspectives in digital health through phenomenology integration represents a critical step toward realizing the full potential of digital technologies in health care. %M 39442170 %R 10.2196/62691 %U https://www.jmir.org/2024/1/e62691 %U https://doi.org/10.2196/62691 %U http://www.ncbi.nlm.nih.gov/pubmed/39442170 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58987 %T Mapping the Evolution of Digital Health Research: Bibliometric Overview of Research Hotspots, Trends, and Collaboration of Publications in JMIR (1999-2024) %A Hu,Jing %A Li,Chong %A Ge,Yanlei %A Yang,Jingyi %A Zhu,Siyi %A He,Chengqi %+ Rehabilitation Medicine Center, West China Hospital, Sichuan University, #37 Guoxue Alley, Wuhou District, Chengdu, 610041, China, 86 28 8542 2847, hxkfhcq2015@126.com %K JMIR %K bibliometric analysis %K ehealth %K digital health %K medical informatics %K health informatics %K open science %K publishing %D 2024 %7 17.10.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: While bibliometric studies of individual journals have been conducted, to the best of our knowledge, bibliometric mapping has not yet been utilized to analyze the literature published by the Journal of Medical Internet Research (JMIR). Objective: In celebration of the journal’s 25th anniversary, this study aimed to review the entire collection of JMIR publications from 1999 to 2024 and provide a comprehensive overview of the main publication characteristics. Methods: This study included papers published in JMIR during the 25-year period from 1999 to 2024. The data were analyzed using CiteSpace, VOSviewer, and the “Bibliometrix” package in R. Through descriptive bibliometrics, we examined the dynamics and trend patterns of JMIR literature production and identified the most prolific authors, papers, institutions, and countries. Bibliometric maps were used to visualize the content of published articles and to identify the most prominent research terms and topics, along with their evolution. A bibliometric network map was constructed to determine the hot research topics over the past 25 years. Results: This study revealed positive trends in literature production, with both the total number of publications and the average number of citations increasing over the years. And the global COVID-19 pandemic induced an explosive rise in the number of publications in JMIR. The most productive institutions were predominantly from the United States, which ranked highest in successful publications within the journal. The editor-in-chief of JMIR was identified as a pioneer in this field. The thematic analysis indicated that the most prolific topics aligned with the primary aims and scope of the journal. Currently and in the foreseeable future, the main themes of JMIR include “artificial intelligence,” “patient empowerment,” and “victimization.” Conclusions: This bibliometric study highlighted significant contributions to digital health by identifying key research trends, themes, influential authors, and collaborations. The findings underscore the necessity to enhance publications from developing countries, improve gender diversity among authors, and expand the range of research topics explored in the journal. %M 39419496 %R 10.2196/58987 %U https://www.jmir.org/2024/1/e58987 %U https://doi.org/10.2196/58987 %U http://www.ncbi.nlm.nih.gov/pubmed/39419496 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60081 %T Primary Care Informatics: Vitalizing the Bedrock of Health Care %A You,Jacqueline Guan-Ting %A Leung,Tiffany I %A Pandita,Deepti %A Sakumoto,Matthew %+ Department of Medicine, University of California San Francisco, 533 Parnassus Avenue, U127, San Francisco, CA, 94143, United States, 1 4154761000, matthew.sakumoto@ucsf.edu %K health care delivery %K primary care %K primary health care %K primary prevention %K quality of health care %K holistic care %K holistic medicine %K people-centric care %K person-centric care %K medical informatics applications %K primary care informatics %K medical informatics %K health informatics %K information science %K data science %D 2024 %7 15.10.2024 %9 Viewpoint %J J Med Internet Res %G English %X Primary care informatics (PCI) professionals address workflow and technology solutions in a wide spectrum of health, ranging from optimizing the experience of the individual patient in the clinic room to supporting the health of populations and augmenting the work of frontline primary care clinical teams. PCI overlaps uniquely with 2 disciplines with an impact on societal health—primary care and health informatics. Primary care is a gateway to health care access and aims to synthesize and coordinate numerous, complex elements of patients’ health and medical care in a holistic manner. However, over the past 25 years, primary care has become a specialty in crisis: in a post–COVID-19 world, workforce shortages, clinician burnout, and continuing challenges in health care access all contribute to difficulties in sustaining primary care. Informatics professionals are poised to change this trajectory. In this viewpoint, we aim to inform readers of the discipline of PCI and its importance in the design, support, and maintenance of essential primary care services. Although this work focuses on primary care in the United States, which includes general internal medicine, family medicine, and pediatrics (and depending on definition, includes specialties such as obstetrics and gynecology), many of the principles outlined can also be applied to comparable health care services and settings in other countries. We highlight (1) common global challenges in primary care, (2) recent trends in the evolution of PCI (personalized medicine, population health, social drivers of health, and team-based care), and (3) opportunities to move forward PCI with current and emerging technologies using the 4Cs of primary care framework. In summary, PCI offers important contributions to health care and the informatics field, and there are many opportunities for informatics professionals to enhance the primary care experience for patients, families, and their care teams. %M 39405512 %R 10.2196/60081 %U https://www.jmir.org/2024/1/e60081 %U https://doi.org/10.2196/60081 %U http://www.ncbi.nlm.nih.gov/pubmed/39405512 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58888 %T Hospital Is Not the Home: Lessons From Implementing Remote Technology to Support Acute Inpatient and Transitional Care in the Home in the United States and United Kingdom %A Wilkes,Matt %A Kramer,Annabel %A Pugmire,Juliana %A Pilkington,Christopher %A Zaniello,Benjamin %A Zahradka,Nicole %+ Best Buy Health, 2 Seaport Lane, Boston, MA, 02210, United States, 1 415 941 5734, matt.wilkes@bestbuy.com %K telemedicine %K implementation science %K hospital-to-home transition %K remote patient monitoring %K digital health %K transition of care %K accuracy %K acceptability %D 2024 %7 11.10.2024 %9 Viewpoint %J J Med Internet Res %G English %X The COVID-19 pandemic, patient preference, and economic opportunity are shifting acute care from the hospital to the home, supported by the transformation in remote monitoring technology. Monitoring patients with digital medical devices gives unprecedented insight into their physiology. However, this technology does not exist in a vacuum. Distinguishing pathology from physiological variability, user error, or device limitations is challenging. In a hospital, patients are monitored in a contrived environment. Monitoring at home instead captures activities of daily living alongside patients’ trajectory of disease and recovery. Both settings make for “noisy” data. However, we are familiar with hospital noise, accounting for it in our practice and perceptions of normal. Home monitoring as a diagnostic intervention introduces a new set of downstream consequences, dependent on device, cadence of collection, adherence, duration, alarm thresholds, and escalation criteria. We must accept greater ambiguity and contextualize vital signs. All devices balance accuracy with acceptability, so compromises are inevitable and perfect data should not be expected. Alarms must be specific as well as sensitive, balancing clinical risk with capacity for response. By setting expectations around data from the home, we can smooth the adoption of remote monitoring and accelerate the transition of acute care. %M 39331537 %R 10.2196/58888 %U https://www.jmir.org/2024/1/e58888 %U https://doi.org/10.2196/58888 %U http://www.ncbi.nlm.nih.gov/pubmed/39331537 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e62790 %T Evolutionary Trends in the Adoption, Adaptation, and Abandonment of Mobile Health Technologies: Viewpoint Based on 25 Years of Research %A Portz,Jennifer %A Moore,Susan %A Bull,Sheana %+ Division of General Internal Medicine, School of Medicine, University of Colorado, Mailstop B119, Aurora, CO, 80045, United States, 1 303 724 8856, jennifer.portz@CUAnschutz.edu %K technology adoption %K mobile health %K SMS text messaging %K mobile apps %K wearables %K social media %D 2024 %7 27.9.2024 %9 Viewpoint %J J Med Internet Res %G English %X Over the past quarter-century, mobile health (mHealth) technologies have experienced significant changes in adoption rates, adaptation strategies, and instances of abandonment. Understanding the underlying factors driving these trends is essential for optimizing the design, implementation, and sustainability of interventions using these technologies. The evolution of mHealth adoption has followed a progressive trajectory, starting with cautious exploration and later accelerating due to technological advancements, increased smartphone penetration, and growing acceptance of digital health solutions by both health care providers and patients. However, alongside widespread adoption, challenges related to usability, interoperability, privacy concerns, and socioeconomic disparities have emerged, necessitating ongoing adaptation efforts. While many mHealth initiatives have successfully adapted to address these challenges, technology abandonment remains common, often due to unsustainable business models, inadequate user engagement, and insufficient evidence of effectiveness. This paper utilizes the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework to examine the interplay between the academic and industry sectors in patterns of adoption, adaptation, and abandonment, using 3 major mHealth innovations as examples: health-related SMS text messaging, mobile apps and wearables, and social media for health communication. Health SMS text messaging has demonstrated significant potential as a tool for health promotion, disease management, and patient engagement. The proliferation of mobile apps and devices has facilitated a shift from in-person and in-clinic practices to mobile- and wearable-centric solutions, encompassing everything from simple activity trackers to advanced health monitoring devices. Social media, initially characterized by basic text-based interactions in chat rooms and online forums, underwent a paradigm shift with the emergence of platforms such as MySpace and Facebook. This transition ushered in an era of mass communication through social media. The rise of microblogging and visually focused platforms such as Twitter(now X), Instagram, Snapchat, and TikTok, along with the integration of live streaming and augmented reality features, exemplifies the ongoing innovation within the social media landscape. Over the past 25 years, there have been remarkable strides in the adoption and adaptation of mHealth technologies, driven by technological innovation and a growing recognition of their potential to revolutionize health care delivery. Each mobile technology uniquely enhances public health and health care by catering to different user needs. SMS text messaging offers wide accessibility and proven effectiveness, while mobile apps and wearables provide comprehensive functionalities for more in-depth health management. Social media platforms amplify these efforts with their vast reach and community-building potential, making it essential to select the right tool for specific health interventions to maximize impact and engagement. Nevertheless, continued efforts are needed to address persistent challenges and mitigate instances of abandonment, ensuring that mHealth interventions reach their full potential in improving health outcomes and advancing equitable access to care. %M 39331463 %R 10.2196/62790 %U https://www.jmir.org/2024/1/e62790 %U https://doi.org/10.2196/62790 %U http://www.ncbi.nlm.nih.gov/pubmed/39331463 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59939 %T Equity in Digital Mental Health Interventions in the United States: Where to Next? %A Robinson,Athena %A Flom,Megan %A Forman-Hoffman,Valerie L %A Histon,Trina %A Levy,Monique %A Darcy,Alison %A Ajayi,Toluwalase %A Mohr,David C %A Wicks,Paul %A Greene,Carolyn %A Montgomery,Robert M %+ Woebot Health, 535 Mission St Fl 14, San Francisco, CA, 94105, United States, 1 707 563 1759, scicomms@woebothealth.com %K Digital Mental Health Interventions %K mental health %K health equity %K access to health care %K health plan implementations %D 2024 %7 24.9.2024 %9 Viewpoint %J J Med Internet Res %G English %X Health care technologies have the ability to bridge or hinder equitable care. Advocates of digital mental health interventions (DMHIs) report that such technologies are poised to reduce the documented gross health care inequities that have plagued generations of people seeking care in the United States. This is due to a multitude of factors such as their potential to revolutionize access; mitigate logistical barriers to in-person mental health care; and leverage patient inputs to formulate tailored, responsive, and personalized experiences. Although we agree with the potential of DMHIs to advance health equity, we articulate several steps essential to mobilize and sustain meaningful forward progression in this endeavor, reflecting on decades of research and learnings drawn from multiple fields of expertise and real-world experience. First, DMHI manufacturers must build diversity, equity, inclusion, and belonging (DEIB) processes into the full spectrum of product evolution itself (eg, product design, evidence generation) as well as into the fabric of internal company practices (eg, talent recruitment, communication principles, and advisory boards). Second, awareness of the DEIB efforts—or lack thereof—in DMHI research trials is needed to refine and optimize future study design for inclusivity as well as proactively address potential barriers to doing so. Trials should incorporate thoughtful, inclusive, and creative approaches to recruitment, enrollment, and measurement of social determinants of health and self-identity, as well as a prioritization of planned and exploratory analyses examining outcomes across various groups of people. Third, mental health care advocacy, research funding policies, and local and federal legislation can advance these pursuits, with directives from the US Preventive Services Taskforce, National Institutes of Health, and Food and Drug Administration applied as poignant examples. For products with artificial intelligence/machine learning, maintaining a “human in the loop” as well as prespecified and adaptive analytic frameworks to monitor and remediate potential algorithmic bias can reduce the risk of increasing inequity. Last, but certainly not least, is a call for partnership and transparency within and across ecosystems (academic, industry, payer, provider, regulatory agencies, and value-based care organizations) to reliably build health equity into real-world DMHI product deployments and evidence-generation strategies. All these considerations should also extend into the context of an equity-informed commercial strategy for DMHI manufacturers and health care organizations alike. The potential to advance health equity in innovation with DMHI is apparent. We advocate the field’s thoughtful and evergreen advancement in inclusivity, thereby redefining the mental health care experience for this generation and those to come. %M 39316436 %R 10.2196/59939 %U https://www.jmir.org/2024/1/e59939 %U https://doi.org/10.2196/59939 %U http://www.ncbi.nlm.nih.gov/pubmed/39316436 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e63367 %T Development Trends and Prospects of Technology-Based Solutions for Health Challenges in Aging Over the Past 25 Years: Bibliometric Analysis %A Liu,Lu %A Wang,Xiu-Ling %A Cheng,Nuo %A Yu,Fu-Min %A Li,Hui-Jun %A Mu,Yang %A Yuan,Yonghui %A Dong,Jia-Xin %A Wu,Yu-Dan %A Gong,Da-Xin %A Wang,Shuang %A Zhang,Guang-Wei %+ Smart Hospital Management Department, The First Hospital of China Medical University, 155 Nanjingbei St, Shenyang, 110001, China, 86 024 83283350, gwzhang@cmu.edu.cn %K bibliometrics %K CiteSpace %K VOSviewer %K visualization %K aging health %K technological innovations %K tech-based %K technology-based %K technology %K health challenges %K challenges %K trends %K older adults %K older adult %K ageing %K aging %K elder %K elderly %K older person %K older people %K gerontology %K geriatric %K geriatrics %K remote %K remote monitoring %K monitoring %K surveillance %K artificial intelligence %K AI %K AI-driven %K innovation %K innovations %K health management %K telemedicine %K remote care %D 2024 %7 20.9.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: As the global population ages, we witness a broad scientific and technological revolution tailored to meet the health challenges of older adults. Over the past 25 years, technological innovations, ranging from advanced medical devices to user-friendly mobile apps, are transforming the way we address these challenges, offering new avenues to enhance the quality of life and well-being of the aging demographic. Objective: This study aimed to systematically review the development trends in technology for managing and caring for the health of older adults over the past 25 years and to project future development prospects. Methods: We conducted a comprehensive bibliometric analysis of literatures related to technology-based solutions for health challenges in aging, published up to March 18, 2024. The search was performed using the Web of Science Core Collection, covering a span from 1999 to 2024. Our search strategy was designed to capture a broad spectrum of terms associated with aging, health challenges specific to older adults, and technological interventions. Results: A total of 1133 publications were found in the Web of Science Core Collection. The publication trend over these 25 years showed a gradual but fluctuating increase. The United States was the most productive country and participated in international collaboration most frequently. The predominant keywords identified through this analysis included “dementia,” “telemedicine,” “older-adults,” “telehealth,” and “care.” The keywords with citation bursts included “telemedicine” and “digital health.” Conclusions: The scientific and technological revolution has significantly improved older adult health management, particularly in chronic disease monitoring, mobility, and social connectivity. The momentum for innovation continues to build, with future research likely to focus on predictive analytics and personalized health care solutions, further enhancing older adults’ independence and quality of life. %M 39238480 %R 10.2196/63367 %U https://www.jmir.org/2024/1/e63367 %U https://doi.org/10.2196/63367 %U http://www.ncbi.nlm.nih.gov/pubmed/39238480 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58198 %T We Have Spent Time, Money, and Effort Making Self-Help Digital Mental Health Interventions: Is Anyone Going to Come to the Party? %A Fitzpatrick,Skye %A Crenshaw,Alexander O %A Donkin,Victoria %A Collins,Alexis %A Xiang,Angela %A Earle,Elizabeth A %A Goenka,Kamya %A Varma,Sonya %A Bushe,Julianne %A McFadden,Tara %A Librado,Andrea %A Monson,Candice %+ York University, 4700 Keele St, Toronto, ON, M3J1P3, Canada, 1 4167362100 ext 66214, skyefitz@yorku.ca %K online interventions %K self-help %K digital interventions %K mental health %K psychotherapy %K intervention desirability %D 2024 %7 19.9.2024 %9 Viewpoint %J J Med Internet Res %G English %X Although efficacious psychotherapies exist, a limited number of mental health care providers and significant demand make their accessibility a fundamental problem. Clinical researchers, funders, and investors alike have converged on self-help digital mental health interventions (self-help DMHIs) as a low-cost, low-burden, and broadly scalable solution to the global mental health burden. Consequently, exorbitant financial and time-based resources have been invested in developing, testing, and disseminating these interventions. However, the public’s assumed desirability for self-help DMHIs by experts has largely proceeded without question. This commentary critically evaluates whether self-help DMHIs can, and will, reach their purported potential as a solution to the public burden of mental illness, with an emphasis on evaluating their real-world desirability. Our review finds that self-help DMHIs are often perceived as less desirable and credible than in-person treatments, with lower usage rates and, perhaps accordingly, clinical trials testing self-help DMHIs suffering from widespread recruitment challenges. We highlight two fundamental challenges that may be interfering with the desirability of, and engagement in, self-help DMHIs: (1) difficulty competing with technology companies that have advantages in resources, marketing, and user experience design (but may not be delivering evidence-based interventions) and (2) difficulty retaining (vs initially attracting) users. We discuss a range of potential solutions, including highlighting self-help DMHIs in public mental health awareness campaigns; public education about evidence-based interventions that can guide consumers to appropriate self-help DMHI selection; increased financial and expert support to clinical researchers for marketing, design, and user experience in self-help DMHI development; increased involvement of stakeholders in the design of self-help DMHIs; and investing in more research on ways to improve retention (versus initial engagement). We suggest that, through these efforts, self-help DMHIs may fully realize their promise for reducing the global burden of mental illness. %M 39298760 %R 10.2196/58198 %U https://www.jmir.org/2024/1/e58198 %U https://doi.org/10.2196/58198 %U http://www.ncbi.nlm.nih.gov/pubmed/39298760 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58704 %T From Fax to Secure File Transfer Protocol: The 25-Year Evolution of Real-Time Syndromic Surveillance in England %A Elliot,Alex J %A Hughes,Helen E %A Harcourt,Sally E %A Smith,Sue %A Loveridge,Paul %A Morbey,Roger A %A Bains,Amardeep %A Edeghere,Obaghe %A Jones,Natalia R %A Todkill,Daniel %A Smith,Gillian E %+ Real-time Syndromic Surveillance Team, UK Health Security Agency, 23 Stephenson Street, Birmingham, B2 4BH, United Kingdom, 44 1212329211, alex.elliot@ukhsa.gov.uk %K epidemiology %K population surveillance %K sentinel surveillance %K public health surveillance %K bioterrorism %K mass gathering %K pandemics %D 2024 %7 17.9.2024 %9 Viewpoint %J J Med Internet Res %G English %X The purpose of syndromic surveillance is to provide early warning of public health incidents, real-time situational awareness during incidents and emergencies, and reassurance of the lack of impact on the population, particularly during mass gatherings. The United Kingdom Health Security Agency (UKHSA) currently coordinates a real-time syndromic surveillance service that encompasses 6 national syndromic surveillance systems reporting on daily health care usage across England. Each working day, UKHSA analyzes syndromic data from over 200,000 daily patient encounters with the National Health Service, monitoring over 140 unique syndromic indicators, risk assessing over 50 daily statistical exceedances, and taking and recommending public health action on these daily. This English syndromic surveillance service had its origins as a small exploratory pilot in a single region of England in 1999 involving a new pilot telehealth service, initially reporting only on “cold or flu” calls. This pilot showed the value of syndromic surveillance in England, providing advanced warning of the start of seasonal influenza activity over existing laboratory-based surveillance systems. Since this initial pilot, a program of real-time syndromic surveillance has evolved from the single-system, -region, -indicator pilot (using manual data transfer methods) to an all-hazard, multisystem, automated national service. The suite of systems now monitors a wide range of syndromes, from acute respiratory illness to diarrhea to cardiac conditions, and is widely used in routine public health surveillance and for monitoring seasonal respiratory disease and incidents such as the COVID-19 pandemic. Here, we describe the 25-year evolution of the English syndromic surveillance system, focusing on the expansion and improvements in data sources and data management, the technological and digital enablers, and novel methods of data analytics and visualization. %M 39288377 %R 10.2196/58704 %U https://www.jmir.org/2024/1/e58704 %U https://doi.org/10.2196/58704 %U http://www.ncbi.nlm.nih.gov/pubmed/39288377 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59497 %T Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review %A Liang,Ya-Ting %A Wang,Charlotte %A Hsiao,Chuhsing Kate %+ Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, No.17, Xu-Zhou Rd, Taipei, 10055, Taiwan, 886 2 33668032, ckhsiao@ntu.edu.tw %K accelerometer %K association %K behavioral study %K classification %K digital biomarkers %K digital health %K physical activity %K prediction %K statistical method %K wearable %D 2024 %7 11.9.2024 %9 Review %J J Med Internet Res %G English %X Background: Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized. Objective: This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual’s free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks? Methods: This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers. Results: After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%). Conclusions: Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals’ overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings. %M 39259962 %R 10.2196/59497 %U https://www.jmir.org/2024/1/e59497 %U https://doi.org/10.2196/59497 %U http://www.ncbi.nlm.nih.gov/pubmed/39259962 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59711 %T A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review %A Wang,Zhaoxin %A Yang,Wenwen %A Li,Zhengyu %A Rong,Ze %A Wang,Xing %A Han,Jincong %A Ma,Lei %+ Nantong University, 9# Seyuan Road, Chongchuan District, Nantong, 226019, China, 86 18860970645, mlmyhero@163.com %K acute stroke %K artificial intelligence %K AI %K machine learning %K deep learning %K stroke lesion segmentation and classification %K stroke prediction %K stroke prognosis %D 2024 %7 10.9.2024 %9 Review %J J Med Internet Res %G English %X Background: Stroke is a leading cause of death and disability worldwide. Rapid and accurate diagnosis is crucial for minimizing brain damage and optimizing treatment plans. Objective: This review aims to summarize the methods of artificial intelligence (AI)–assisted stroke diagnosis over the past 25 years, providing an overview of performance metrics and algorithm development trends. It also delves into existing issues and future prospects, intending to offer a comprehensive reference for clinical practice. Methods: A total of 50 representative articles published between 1999 and 2024 on using AI technology for stroke prevention and diagnosis were systematically selected and analyzed in detail. Results: AI-assisted stroke diagnosis has made significant advances in stroke lesion segmentation and classification, stroke risk prediction, and stroke prognosis. Before 2012, research mainly focused on segmentation using traditional thresholding and heuristic techniques. From 2012 to 2016, the focus shifted to machine learning (ML)–based approaches. After 2016, the emphasis moved to deep learning (DL), which brought significant improvements in accuracy. In stroke lesion segmentation and classification as well as stroke risk prediction, DL has shown superiority over ML. In stroke prognosis, both DL and ML have shown good performance. Conclusions: Over the past 25 years, AI technology has shown promising performance in stroke diagnosis. %M 39255472 %R 10.2196/59711 %U https://www.jmir.org/2024/1/e59711 %U https://doi.org/10.2196/59711 %U http://www.ncbi.nlm.nih.gov/pubmed/39255472 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58939 %T Research Into Digital Health Intervention for Mental Health: 25-Year Retrospective on the Ethical and Legal Challenges %A Hall,Charlotte L %A Gómez Bergin,Aislinn D %A Rennick-Egglestone,Stefan %+ School of Health Sciences, Institute of Mental Health, University of Nottingham, University of Nottingham Innovation Park, Triumph Road, Nottingham, NG7 2TU, United Kingdom, 44 11582 ext 30926, stefan.egglestone@nottingham.ac.uk %K digital mental health intervention %K research ethics %K compliance %K regulation %K digital health %K mobile health %K mhealth %K intervention %K interventions %K mental health %K retrospective %K ethical %K legal %K challenge %K challenges %D 2024 %7 9.9.2024 %9 Viewpoint %J J Med Internet Res %G English %X Digital mental health interventions are routinely integrated into mental health services internationally and can contribute to reducing the global mental health treatment gap identified by the World Health Organization. Research teams designing and delivering evaluations frequently invest substantial effort in deliberating on ethical and legal challenges around digital mental health interventions. In this article, we reflect on our own research experience with digital mental health intervention design and evaluation to identify 8 of the most critical challenges that we or others have faced, and that have ethical or legal consequences. These include: (1) harm caused by online recruitment work; (2) monitoring of intervention safety; (3) exclusion of specific demographic or clinical groups; (4) inadequate robustness of effectiveness and cost-effectiveness findings; (5) adequately conceptualizing and supporting engagement and adherence; (6) structural barriers to implementation; (7) data protection and intellectual property; and (8) regulatory ambiguity relating to digital mental health interventions that are medical devices. As we describe these challenges, we have highlighted serious consequences that can or have occurred, such as substantial delays to studies if regulations around Software as a Medical Device (SaMD) are not fully understood, or if regulations change substantially during the study lifecycle. Collectively, the challenges we have identified highlight a substantial body of required knowledge and expertise, either within the team or through access to external experts. Ensuring access to knowledge requires careful planning and adequate financial resources (for example, paying public contributors to engage in debate on critical ethical issues or paying for legal opinions on regulatory issues). Access to such resources can be planned for on a per-study basis and enabled through funding proposals. However, organizations regularly engaged in the development and evaluation of digital mental health interventions should consider creating or supporting structures such as advisory groups that can retain necessary competencies, such as in medical device regulation. %M 39250796 %R 10.2196/58939 %U https://www.jmir.org/2024/1/e58939 %U https://doi.org/10.2196/58939 %U http://www.ncbi.nlm.nih.gov/pubmed/39250796 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59089 %T Evaluation of the Veterans Health Administration’s Digital Divide Consult for Tablet Distribution and Telehealth Adoption: Cohort Study %A Ferguson,Jacqueline M %A Van Campen,James %A Slightam,Cindie %A Greene,Liberty %A Heyworth,Leonie %A Zulman,Donna M %+ Center for Innovation to Implementation, Veterans Affairs Palo Alto Healthcare System, 795 Willow Road, MDP-152, Menlo Park, CA, 94025, United States, 1 (650) 493 5000, Jacqueline.Ferguson@va.gov %K veterans %K health care access %K video-based care %K telehealth %K barriers to care %K telemedicine %D 2024 %7 9.9.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Video telehealth offers a mechanism to help Veterans Health Administration (VHA) patients overcome health care access barriers; however, many veterans lack a suitable device and sufficient internet connectivity. To address disparities in technology access, VHA established a Connected Device Program that offers veterans loaned video-capable tablets and internet service. In 2020, VHA introduced a national Digital Divide Consult to facilitate and standardize referrals for this resource. Objective: We sought to evaluate the reach and impact of VHA’s Connected Device Program, leveraging Digital Divide Consult data to determine whether resources are supporting veterans with health care needs and access barriers. Methods: We examined the reach of VHA’s Connected Device Program using national secondary data from VHA’s electronic health records among 119,926 tablet recipients who received a tablet (April 1, 2020, to February 28, 2023) and 683,219 veterans from the general VHA population. We assessed changes in tablet recipients’ demographic and clinical characteristics before and after implementation of the Digital Divide Consult compared with the general VHA population. We examined the impact of tablets and the consult on adoption of telehealth (ie, video visit use and number of visits) adjusting for differences between tablet recipients and the general VHA population. Finally, we evaluated consult implementation by assessing the use of video-based services by tablet referral reason. Results: Common reasons for tablet referral included mental health diagnoses (50,367/79,230, 63.9%), distance from a VHA facility >30 miles (17,228/79,230, 21.7%), and social isolation (16,161/79,230, 20.4%). Moreover, 63.0% (49,925/79,230) of individuals who received a tablet after implementation of the Digital Divide Consult had a video visit in the first 6 months of tablet receipt. Some consult reasons were associated with a higher-than-average percentage of video telehealth use, including enrollment in evidence-based mental health programs (74.8% [830/1100] with video use), living >30 miles from a VHA facility (68.3% [10,557/17,228] with video use), and having a mental health diagnosis (68.1% [34,301/50,367] with video use). Tablet recipients had nearly 3 times the likelihood of having a video visit within a month once provided a tablet compared to the general VHA population, with an adjusted risk ratio of 2.95 (95% CI 2.91-2.99) before consult implementation and 2.73 (95% CI 2.70-2.76) after consult implementation. Analyses of telehealth adoption suggested that veterans receiving tablets for mental health care and evidence-based programs have higher rates of video visits, while those who are homebound or receiving tablets for hospice have higher rates of nonuse. Conclusions: This evaluation of VHA’s Connected Device Program suggests that tablets are facilitating video-based care among veterans with complex needs. Standardization of referrals through the Digital Divide Consult has created opportunities to identify groups of tablet recipients with lower telehealth adoption rates who might benefit from a targeted intervention. %M 39250183 %R 10.2196/59089 %U https://www.jmir.org/2024/1/e59089 %U https://doi.org/10.2196/59089 %U http://www.ncbi.nlm.nih.gov/pubmed/39250183 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59013 %T Digital Health Applications (DiGAs) on a Fast Track: Insights From a Data-Driven Analysis of Prescribable Digital Therapeutics in Germany From 2020 to Mid-2024 %A Goeldner,Moritz %A Gehder,Sara %+ Working Group for Data-Driven Innovation, Hamburg University of Technology, Am Schwarzenberg-Campus 4, Hamburg, 21073, Germany, 49 40428784777, moritz.goeldner@tuhh.de %K digital health application %K DiGA %K data-driven analysis %K clinical evidence %K health economics %K positive care effect %K medical benefit %K patient-relevant structural and procedural improvements %K pSVV %K digital health care act %D 2024 %7 29.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: This study aimed to analyze the rapidly evolving ecosystem of digital health applications (Digitale Gesundheitsanwendung; DiGAs) in Germany, spurred by the 2019 Digital Healthcare Act. With over 73 million people in Germany now having access to DiGAs, these prescribable digital health apps and web-based applications represent a substantial stride in health care modernization, supporting both patients and health care providers with digital solutions for disease management and care improvement. Objective: Through a data-driven approach, this research aimed to unpack the complexities of DiGA market dynamics, economic factors, and clinical evidence, offering insights into their impact over the past years. Methods: The analysis draws from a range of public data sources, including the DiGA directory, statutory health insurance reports, app store feedback, and clinical study results. Results: As of July 1, 2024, there are 56 DiGAs listed by the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte), divided into 35 permanently and 21 preliminarily listed applications. Our findings reveal that a majority of DiGAs extend beyond the intended 1-year period to achieve permanent listing, reflecting the extensive effort required to demonstrate clinical efficacy. Economic analysis uncovered a dynamic pricing landscape, with initial prices ranging from approximately €200 to €700 (€1=US $1.07), averaging at a median of €514 for a 3-month DiGA prescription. Following negotiations or arbitration board decisions, prices typically see a 50% reduction, settling at a median of €221. Prescription data offer valuable insights into DiGA acceptance, with total prescriptions jumping from around 41,000 in the first period to 209,000 in the latest reporting period. The analysis of the top 15 DiGAs, representing 82% of the total prescriptions, shows that these best-performing apps receive from a minimum of 8 to a maximum of 77 daily prescriptions, with native apps and early market entrants achieving higher rates. Clinical evidence from all 35 permanently listed DiGAs indicates a uniform preference for randomized controlled trials to validate primary end points, with no noteworthy use of alternative study designs encouraged in the Digital Healthcare Act and related regulations. Moreover, all evaluated DiGAs focused on medical benefits, with health status improvement as a key end point, suggesting an underuse of patient-relevant structural and procedural improvement in demonstrating health care impact. Conclusions: This study highlights the growth and challenges within the DiGA sector, suggesting areas for future research, such as the exploration of new study designs and the potential impact of patient-relevant structural and procedural improvements. For DiGA manufacturers, the strategic advantage of early market entry is emphasized. Overall, this paper underscores the evolving landscape of digital health, advocating for a nuanced understanding of digital health technology integration in Germany and beyond. %M 39208415 %R 10.2196/59013 %U https://www.jmir.org/2024/1/e59013 %U https://doi.org/10.2196/59013 %U http://www.ncbi.nlm.nih.gov/pubmed/39208415 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58726 %T Deceptively Simple yet Profoundly Impactful: Text Messaging Interventions to Support Health %A Suffoletto,Brian %+ Department of Emergency Medicine, Stanford University, 3145 Porter Drive Wing B, Palo Alto, CA, 94035, United States, 1 412 901 6892, suffbp@stanford.edu %K SMS intervention %K behavior %K intervention %K review %K text messaging %K SMS %K interventions %K behaviors %K behaviour %K behaviours %K effectiveness %K development %K impact %K narrative review %K physical activity %K diet %K weight loss %K mental health %K substance use %K meta-analysis %K chatbot %K chatbots %K large language model %K LLM %K large language models %K mobile phone %D 2024 %7 27.8.2024 %9 Viewpoint %J J Med Internet Res %G English %X This paper examines the use of text message (SMS) interventions for health-related behavioral support. It first outlines the historical progress in SMS intervention research publications and the variety of funds from US government agencies. A narrative review follows, highlighting the effectiveness of SMS interventions in key health areas, such as physical activity, diet and weight loss, mental health, and substance use, based on published meta-analyses. It then outlines advantages of text messaging compared to other digital modalities, including the real-time capability to collect information and deliver microdoses of intervention support. Crucial design elements are proposed to optimize effectiveness and longitudinal engagement across communication strategies, psychological foundations, and behavior change tactics. We then discuss advanced functionalities, such as the potential for generative artificial intelligence to improve user interaction. Finally, major challenges to implementation are highlighted, including the absence of a dedicated commercial platform, privacy and security concerns with SMS technology, difficulties integrating SMS interventions with medical informatics systems, and concerns about user engagement. Proposed solutions aim to facilitate the broader application and effectiveness of SMS interventions. Our hope is that these insights can assist researchers and practitioners in using SMS interventions to improve health outcomes and reducing disparities. %M 39190427 %R 10.2196/58726 %U https://www.jmir.org/2024/1/e58726 %U https://doi.org/10.2196/58726 %U http://www.ncbi.nlm.nih.gov/pubmed/39190427 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57848 %T The Unintended Consequences of Telehealth in Australia: Critical Interpretive Synthesis %A Osman,Sagda %A Churruca,Kate %A Ellis,Louise A %A Luo,Dan %A Braithwaite,Jeffrey %+ Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Rd, North Ryde, 2113, Australia, 61 (02) 9850 2400, sagda.osman@mq.edu.au %K telehealth %K telemedicine %K unintended consequences %K digital health %K eHealth %K critical interpretive synthesis %K review methodology %K literature review %K Australia %D 2024 %7 27.8.2024 %9 Review %J J Med Internet Res %G English %X Background: Despite more than 2 decades of telehealth use in Australia and the rapid uptake during the COVID-19 pandemic, little is known about its unintended consequences beyond its planned and intended outcomes. Objective: The aim of this review was to synthesize evidence on the unintended consequences of telehealth use in Australia to clarify its impact beyond its planned and intended outcomes. Methods: We conducted a search of 4 electronic databases: Ovid MEDLINE, Ovid Embase, EBSCO CINAHL, and Scopus. A critical interpretive synthesis approach was adopted for its flexibility and interpretive nature. We extracted data about study characteristics and the types and models of telehealth services. The extracted unintended consequences were coded and mapped into the domains and dimensions of the Australian Health Performance Framework. Results: Of the 4241 records identified by the search, 94 (2.22%) studies were eligible for data extraction and analysis. Of these 94 studies, 23 (24%) reported largely positive unintended consequences of telehealth associated with health status, while 6 (6%) noted a potential negative impact of telehealth on socioeconomic status. The findings of 4 (4%) of the 94 studies highlighted societal and financial consequences of telehealth beyond the health system. Almost all studies (93/94, 99%) reported unintended consequences under the 5 dimensions of the Australian Health Performance Framework. Conclusions: Our synthesis offers a framework for understanding the unintended consequences of the use of telehealth as an alternative to in-person care in Australia. While we have documented many unintended benefits of telehealth use, our findings also shed light on many challenges of delivering care via telehealth across different domains and dimensions. These findings hold significant practice and policy-making implications for ensuring safe and high-quality care delivery via telehealth. %M 39190446 %R 10.2196/57848 %U https://www.jmir.org/2024/1/e57848 %U https://doi.org/10.2196/57848 %U http://www.ncbi.nlm.nih.gov/pubmed/39190446 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59358 %T Impact of 25 Years of Mobile Health Tools for Pain Management in Patients With Chronic Musculoskeletal Pain: Systematic Review %A Shi,Jenny Lin-Hong %A Sit,Regina Wing-Shan %+ Department of Medicine, Jockey Club School of Public Health and Primary Care, Prince of Wales Hospital, The Chinese University of Hong Kong, 4/F, JC School of Public Health and Primary Care Building, Shatin, NT, Hong Kong, 999077, China, 852 25039406, reginasit@cuhk.edu.hk %K mHealth %K mobile health %K mobile app %K chronic musculoskeletal pain %K pain management %K patient compliance %K adherence %K usability %K feasibility %K acceptability %K PRISMA %D 2024 %7 16.8.2024 %9 Review %J J Med Internet Res %G English %X Background: Mobile technologies are increasingly being used in health care and public health practice for patient communication, monitoring, and education. Mobile health (mHealth) tools have also been used to facilitate adherence to chronic musculoskeletal pain (CMP) management, which is critical to achieving improved pain outcomes, quality of life, and cost-effective health care. Objective: The aim of this systematic review was to evaluate the 25-year trend of the literature on the adherence, usability, feasibility, and acceptability of mHealth interventions in CMP management among patients and health care providers. Methods: We searched the PubMed, Cochrane CENTRAL, MEDLINE, EMBASE, and Web of Science databases for studies assessing the role of mHealth in CMP management from January 1999 to December 2023. Outcomes of interest included the effect of mHealth interventions on patient adherence; pain-specific clinical outcomes after the intervention; and the usability, feasibility, and acceptability of mHealth tools and platforms in chronic pain management among target end users. Results: A total of 89 articles (26,429 participants) were included in the systematic review. Mobile apps were the most commonly used mHealth tools (78/89, 88%) among the included studies, followed by mobile app plus monitor (5/89, 6%), mobile app plus wearable sensor (4/89, 4%), and web-based mobile app plus monitor (1/89, 1%). Usability, feasibility, and acceptability or patient preferences for mHealth interventions were assessed in 26% (23/89) of the studies and observed to be generally high. Overall, 30% (27/89) of the studies used a randomized controlled trial (RCT), cohort, or pilot design to assess the impact of the mHealth intervention on patients’ adherence, with significant improvements (all P<.05) observed in 93% (25/27) of these studies. Significant (judged at P<.05) between-group differences were reported in 27 of the 29 (93%) RCTs that measured the effect of mHealth on CMP-specific clinical outcomes. Conclusions: There is great potential for mHealth tools to better facilitate adherence to CMP management, and the current evidence supporting their effectiveness is generally high. Further research should focus on the cost-effectiveness of mHealth interventions for better incorporating these tools into health care practices. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42024524634; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=524634 %M 39150748 %R 10.2196/59358 %U https://www.jmir.org/2024/1/e59358 %U https://doi.org/10.2196/59358 %U http://www.ncbi.nlm.nih.gov/pubmed/39150748 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58950 %T Twenty-Five Years of Progress—Lessons Learned From JMIR Publications to Address Gender Parity in Digital Health Authorships: Bibliometric Analysis %A Meyer,Annika %A Streichert,Thomas %+ Institute of Clinical Chemistry, Faculty of Medicine and University Hospital, University Hospital Cologne, Kerpener Str 62, Cologne, 50937, Germany, annika.meyer@uk-koeln.de %K digital health %K medical informatics, authorship %K gender distribution %K diversity %K bibliometric %K scientometric %K algorithmic bias reduction %K gender gap %K JMIR Publications %K authorships %K author %K authors %K bibliometric analysis %K equality %K comparison %K gender representation %K journal %K journals %K article %K articles %K Web of Science %K control group %K comparative analysis %K statistical analysis %K gender %D 2024 %7 9.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital health research plays a vital role in advancing equitable health care. The diversity of research teams is thereby instrumental in capturing societal challenges, increasing productivity, and reducing bias in algorithms. Despite its importance, the gender distribution within digital health authorship remains largely unexplored. Objective: This study aimed to investigate the gender distribution among first and last authors in digital health research, thereby identifying predicting factors of female authorship. Methods: This bibliometric analysis examined the gender distribution across 59,980 publications from 1999 to 2023, spanning 42 digital health journals indexed in the Web of Science. To identify strategies ensuring equality in research, a detailed comparison of gender representation in JMIR journals was conducted within the field, as well as against a matched sample. Two-tailed Welch 2-sample t tests, Wilcoxon rank sum tests, and chi-square tests were used to assess differences. In addition, odds ratios were calculated to identify predictors of female authorship. Results: The analysis revealed that 37% of first authors and 30% of last authors in digital health were female. JMIR journals demonstrated a higher representation, with 49% of first authors and 38% of last authors being female, yielding odds ratios of 1.96 (95% CI 1.90-2.03; P<.001) and 1.78 (95% CI 1.71-1.84; P<.001), respectively. Since 2008, JMIR journals have consistently featured a greater proportion of female first authors than male counterparts. Other factors that predicted female authorship included having female authors in other relevant positions and gender discordance, given the higher rate of male last authors in the field. Conclusions: There was an evident shift toward gender parity across publications in digital health, particularly from the publisher JMIR Publications. The specialized focus of its sister journals, equitable editorial policies, and transparency in the review process might contribute to these achievements. Further research is imperative to establish causality, enabling the replication of these successful strategies across other scientific fields to bridge the gender gap in digital health effectively. %M 39121467 %R 10.2196/58950 %U https://www.jmir.org/2024/1/e58950 %U https://doi.org/10.2196/58950 %U http://www.ncbi.nlm.nih.gov/pubmed/39121467 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59005 %T The Second Life Metaverse and Its Usefulness in Medical Education After a Quarter of a Century %A Sendra-Portero,Francisco %A Lorenzo-Álvarez,Rocío %A Rudolphi-Solero,Teodoro %A Ruiz-Gómez,Miguel José %+ Department of Radiology and Physical Medicine, Facultad de Medicina, Universidad de Málaga, Bvd. Luis Pasteur, 32. 20071, Málaga, 29071, Spain, 34 952131653, sendra@uma.es %K medical education %K medical students %K postgraduate %K computer simulation %K virtual worlds %K metaverse %D 2024 %7 6.8.2024 %9 Viewpoint %J J Med Internet Res %G English %X The immersive virtual world platform Second Life (SL) was conceived 25 years ago, when Philip Rosedale founded Linden Lab in 1999 with the intention of developing computing hardware that would allow people to immerse themselves in a virtual world. This initial effort was transformed 4 years later into SL, a universally accessible virtual world centered on the user, with commercial transactions and even its own virtual currency, which fully connects with the concept of the metaverse, recently repopularized after the statements of the chief executive officer of Meta (formerly Facebook) in October 2021. SL is considered the best known virtual environment among higher education professionals. This paper aimed to review medical education in the SL metaverse; its evolution; and its possibilities, limitations, and future perspectives, focusing especially on medical education experiences during undergraduate, residency, and continuing medical education. The concept of the metaverse and virtual worlds was described, making special reference to SL and its conceptual philosophy, historical evolution, and technical aspects and capabilities for higher education. A narrative review of the existing literature was performed, including at the same time a point of view from our teaching team after an uninterrupted practical experience of undergraduate and postgraduate medical education in the last 13 years with >4000 users and >10 publications on the subject. From an educational point of view, SL has the advantages of being available 24/7 and creating in the student the important feeling of “being there” and of copresence. This, together with the reproduction of the 3D world, real-time interaction, and the quality of voice communication, makes the immersive experiences unique, generating engagement and a fluid interrelation of students with each other and with their teachers. Various groups of researchers in medical education have developed experiences during these years, which have shown that courses, seminars, workshops and conferences, problem-based learning experiences, evaluations, teamwork, gamification, medical simulation, and virtual objective structured clinical examinations can be successfully carried out. Acceptance from students and faculty is generally positive, recognizing its usefulness for undergraduate medical education and continuing medical education. In the 25 years since its conception, SL has proven to be a virtual platform that connects with the concept of the metaverse, an interconnected, open, and globally accessible system that all humans can access to socialize or share products for free or using a virtual currency. SL remains active and technologically improved since its creation. It is necessary to continue carrying out educational experiences, outlining the organization, objectives, and content and measuring the actual educational impact to make SL a tool of more universal use. %M 39106480 %R 10.2196/59005 %U https://www.jmir.org/2024/1/e59005 %U https://doi.org/10.2196/59005 %U http://www.ncbi.nlm.nih.gov/pubmed/39106480 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59066 %T A Quarter-Century of Online Informatics Education: Learners Served and Lessons Learned %A Hersh,William %+ Department of Medical Informatics & Clinical Epidemiology, School of Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Biomedical Information Communication Center, Portland, OR, 97239, United States, 1 5034944563, hersh@ohsu.edu %K distance education %K online learning %K asynchronous education %K biomedical and health informatics %K learning %K biomedical %K health informatics %K education %K educational %K educational technology %K online program %K online course %K teaching %K students %D 2024 %7 6.8.2024 %9 Viewpoint %J J Med Internet Res %G English %X The value and methods of online learning have changed tremendously over the last 25 years. The goal of this paper is to review a quarter-century of experience with online learning by the author in the field of biomedical and health informatics, describing the learners served and the lessons learned. The author details the history of the decision to pursue online education in informatics, describing the approaches taken as educational technology evolved over time. A large number of learners have been served, and the online learning approach has been well-received, with many lessons learned to optimize the educational experience. Online education in biomedical and health informatics has provided a scalable and exemplary approach to learning in this field. %M 39106486 %R 10.2196/59066 %U https://www.jmir.org/2024/1/e59066 %U https://doi.org/10.2196/59066 %U http://www.ncbi.nlm.nih.gov/pubmed/39106486 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59826 %T Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry? %A Ortiz,Abigail %A Mulsant,Benoit H %+ Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 8th Floor, 250 College Street, Toronto, ON, M5T 1R8, Canada, 1 416 979 6948, benoit.mulsant@utoronto.ca %K digital phenotype %K digital phenotyping %K prediction %K predictions %K mental health %K mental illness %K mental illnesses %K mental disorder %K mental disorders %K US National Institute of Mental Health %K NIMH %K psychiatry %K psychiatrist %K psychiatrists %D 2024 %7 5.8.2024 %9 Viewpoint %J J Med Internet Res %G English %X Some models for mental disorders or behaviors (eg, suicide) have been successfully developed, allowing predictions at the population level. However, current demographic and clinical variables are neither sensitive nor specific enough for making individual actionable clinical predictions. A major hope of the “Decade of the Brain” was that biological measures (biomarkers) would solve these issues and lead to precision psychiatry. However, as models are based on sociodemographic and clinical data, even when these biomarkers differ significantly between groups of patients and control participants, they are still neither sensitive nor specific enough to be applied to individual patients. Technological advances over the past decade offer a promising approach based on new measures that may be essential for understanding mental disorders and predicting their trajectories. Several new tools allow us to continuously monitor objective behavioral measures (eg, hours of sleep) and densely sample subjective measures (eg, mood). The promise of this approach, referred to as digital phenotyping, was recognized almost a decade ago, with its potential impact on psychiatry being compared to the impact of the microscope on biological sciences. However, despite the intuitive belief that collecting densely sampled data (big data) improves clinical outcomes, recent clinical trials have not shown that incorporating digital phenotyping improves clinical outcomes. This viewpoint provides a stepwise development and implementation approach, similar to the one that has been successful in the prediction and prevention of cardiovascular disease, to achieve clinically actionable predictions in psychiatry. %M 39102686 %R 10.2196/59826 %U https://www.jmir.org/2024/1/e59826 %U https://doi.org/10.2196/59826 %U http://www.ncbi.nlm.nih.gov/pubmed/39102686 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58764 %T The McMaster Health Information Research Unit: Over a Quarter-Century of Health Informatics Supporting Evidence-Based Medicine %A Lokker,Cynthia %A McKibbon,K Ann %A Afzal,Muhammad %A Navarro,Tamara %A Linkins,Lori-Ann %A Haynes,R Brian %A Iorio,Alfonso %+ Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, CRL 137, Hamilton, ON, L8S 4K1, Canada, 1 2897883272, lokkerc@mcmaster.ca %K health informatics %K evidence-based medicine %K information retrieval %K evidence-based %K health information %K Boolean %K natural language processing %K NLP %K journal %K article %K Health Information Research Unit %K HiRU %D 2024 %7 31.7.2024 %9 Viewpoint %J J Med Internet Res %G English %X Evidence-based medicine (EBM) emerged from McMaster University in the 1980-1990s, which emphasizes the integration of the best research evidence with clinical expertise and patient values. The Health Information Research Unit (HiRU) was created at McMaster University in 1985 to support EBM. Early on, digital health informatics took the form of teaching clinicians how to search MEDLINE with modems and phone lines. Searching and retrieval of published articles were transformed as electronic platforms provided greater access to clinically relevant studies, systematic reviews, and clinical practice guidelines, with PubMed playing a pivotal role. In the early 2000s, the HiRU introduced Clinical Queries—validated search filters derived from the curated, gold-standard, human-appraised Hedges dataset—to enhance the precision of searches, allowing clinicians to hone their queries based on study design, population, and outcomes. Currently, almost 1 million articles are added to PubMed annually. To filter through this volume of heterogenous publications for clinically important articles, the HiRU team and other researchers have been applying classical machine learning, deep learning, and, increasingly, large language models (LLMs). These approaches are built upon the foundation of gold-standard annotated datasets and humans in the loop for active machine learning. In this viewpoint, we explore the evolution of health informatics in supporting evidence search and retrieval processes over the past 25+ years within the HiRU, including the evolving roles of LLMs and responsible artificial intelligence, as we continue to facilitate the dissemination of knowledge, enabling clinicians to integrate the best available evidence into their clinical practice. %M 39083765 %R 10.2196/58764 %U https://www.jmir.org/2024/1/e58764 %U https://doi.org/10.2196/58764 %U http://www.ncbi.nlm.nih.gov/pubmed/39083765 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58846 %T The Role of Assistive Technology in Enabling Older Adults to Achieve Independent Living: Past and Future %A Sweeting,Anna %A Warncken,Katie A %A Patel,Martyn %+ Older Peoples Medicine Department, Norfolk and Norwich University Hospital NHS Foundation Trust, Colney Lane, Norwich, NR4 7UY, United Kingdom, 44 01603286286 ext 4009, martyn.patel@nnuh.nhs.uk %K assistive technology %K older adults %K users %K aging %K aging in place %K UK %K cocreation %K research trial %K independent living %K North Norfolk %K disability %K injury %K tool %K use %K design %K barrier %D 2024 %7 30.7.2024 %9 Viewpoint %J J Med Internet Res %G English %X In this viewpoint, we present evidence of a marked increase in the use of assistive technology (AT) by older adults over the last 25 years. We also explain the way in which this use has expanded not only as an increase in terms of the total number of users but also by going beyond the typical scopes of use from its inception in 1999 to reach new categories of users. We outline our opinions on some of the key driving forces behind this expansion, such as population demographic changes, technological advances, and the promotion of AT as a means to enable older adults to achieve independent living. As well as our review of the evolution of AT over the past 25 years, we also discuss the future of AT research as a field and the need for harmonization of terminology in AT research. Finally, we outline how our experience in North Norfolk (notably the United Kingdom’s most old age–dependent district) suggests that cocreation may be the key to not only successful research trials in the field of AT but also to the successful sustained adoption of AT beyond its original scope of use. %M 39079115 %R 10.2196/58846 %U https://www.jmir.org/2024/1/e58846 %U https://doi.org/10.2196/58846 %U http://www.ncbi.nlm.nih.gov/pubmed/39079115