@Article{info:doi/10.2196/59792,
author="He, Rosemary
and Sarwal, Varuni
and Qiu, Xinru
and Zhuang, Yongwen
and Zhang, Le
and Liu, Yue
and Chiang, Jeffrey",
title="Generative AI Models in Time-Varying Biomedical Data: Scoping Review",
journal="J Med Internet Res",
year="2025",
month="Mar",
day="10",
volume="27",
pages="e59792",
keywords="generative artificial intelligence",
keywords="artificial intelligence",
keywords="time series",
keywords="electronic health records",
keywords="electronic medical records",
keywords="systematic reviews",
keywords="disease trajectory",
keywords="machine learning",
keywords="algorithms",
keywords="forecasting",
abstract="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. ",
doi="10.2196/59792",
url="https://www.jmir.org/2025/1/e59792"
}


@Article{info:doi/10.2196/60077,
author="Finnegan, Harriet
and Mountford, Nicola",
title="25 Years of Electronic Health Record Implementation Processes: Scoping Review",
journal="J Med Internet Res",
year="2025",
month="Mar",
day="3",
volume="27",
pages="e60077",
keywords="electronic health record system",
keywords="EHR",
keywords="electronic medical record",
keywords="EMR",
keywords="scoping review",
keywords="process",
keywords="implementation",
abstract="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. ",
doi="10.2196/60077",
url="https://www.jmir.org/2025/1/e60077",
url="http://www.ncbi.nlm.nih.gov/pubmed/40053758"
}


@Article{info:doi/10.2196/60512,
author="Song, Mingming
and Elson, Joel
and Bastola, Dhundy",
title="Digital Age Transformation in Patient-Physician Communication: 25-Year Narrative Review (1999-2023)",
journal="J Med Internet Res",
year="2025",
month="Jan",
day="16",
volume="27",
pages="e60512",
keywords="health communication",
keywords="health IT",
keywords="patient empowerment",
keywords="shared decision-making",
keywords="patient-physician relationship",
keywords="trust",
abstract="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. ",
doi="10.2196/60512",
url="https://www.jmir.org/2025/1/e60512"
}


@Article{info:doi/10.2196/60189,
author="Klein, Dave
and Montgomery, Aisha
and Begale, Mark
and Sutherland, Scott
and Sawyer, Sherilyn
and McCauley, L. Jacob
and Husbands, Letheshia
and Joshi, Deepti
and Ashbeck, Alan
and Palmer, Marcy
and Jain, Praduman",
title="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",
journal="J Med Internet Res",
year="2025",
month="Jan",
day="15",
volume="27",
pages="e60189",
keywords="longitudinal studies",
keywords="cohort studies",
keywords="health disparities",
keywords="minority populations",
keywords="vulnerable populations",
keywords="precision medicine",
keywords="biomedical research",
keywords="decentralization",
keywords="digital health technology",
keywords="database management system",
abstract="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. ",
doi="10.2196/60189",
url="https://www.jmir.org/2025/1/e60189"
}


@Article{info:doi/10.2196/59027,
author="Liu, Shiyu
and Ma, Jingru
and Sun, Meichen
and Zhang, Chao
and Gao, Yujing
and Xu, Jinghong",
title="Mapping the Landscape of Digital Health Intervention Strategies: 25-Year Synthesis",
journal="J Med Internet Res",
year="2025",
month="Jan",
day="13",
volume="27",
pages="e59027",
keywords="digital health interventions",
keywords="intervention strategies",
keywords="behavior change",
keywords="mHealth",
keywords="eHealth",
keywords="randomized controlled trial",
abstract="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. ",
doi="10.2196/59027",
url="https://www.jmir.org/2025/1/e59027",
url="http://www.ncbi.nlm.nih.gov/pubmed/39804697"
}


@Article{info:doi/10.2196/60443,
author="van den Broek-Altenburg, M. Eline
and Atherly, J. Adam",
title="The Paradigm Shift From Patient to Health Consumer: 20 Years of Value Assessment in Health",
journal="J Med Internet Res",
year="2025",
month="Jan",
day="10",
volume="27",
pages="e60443",
keywords="value assessment",
keywords="cost-effectiveness",
keywords="quality-adjusted life-years",
keywords="QALY",
keywords="health consumer",
keywords="health technology",
keywords="value based",
keywords="digital health",
keywords="patient centered",
keywords="preferences",
keywords="health economics",
doi="10.2196/60443",
url="https://www.jmir.org/2025/1/e60443",
url="http://www.ncbi.nlm.nih.gov/pubmed/39793021"
}


@Article{info:doi/10.2196/59024,
author="Shen, Yun
and Yu, Jiamin
and Zhou, Jian
and Hu, Gang",
title="Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review",
journal="J Med Internet Res",
year="2025",
month="Jan",
day="9",
volume="27",
pages="e59024",
keywords="electronic health record",
keywords="electronic medical record",
keywords="medical research",
keywords="interoperability",
keywords="eHealth",
keywords="systematic review",
keywords="real-world evidence",
keywords="artificial intelligence",
abstract="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. ",
doi="10.2196/59024",
url="https://www.jmir.org/2025/1/e59024"
}


@Article{info:doi/10.2196/58637,
author="Austin, A. Jodie
and Lobo, H. Elton
and Samadbeik, Mahnaz
and Engstrom, Teyl
and Philip, Reji
and Pole, D. Jason
and Sullivan, M. Clair",
title="Decades in the Making: The Evolution of Digital Health Research Infrastructure Through Synthetic Data, Common Data Models, and Federated Learning",
journal="J Med Internet Res",
year="2024",
month="Dec",
day="20",
volume="26",
pages="e58637",
keywords="real-world data",
keywords="digital health research",
keywords="synthetic data",
keywords="common data models",
keywords="federated learning",
keywords="university-industry collaboration",
doi="10.2196/58637",
url="https://www.jmir.org/2024/1/e58637",
url="http://www.ncbi.nlm.nih.gov/pubmed/39705072"
}


@Article{info:doi/10.2196/60312,
author="Ogundiya, Oluwadamilola
and Rahman, Jasmine Thahmina
and Valnarov-Boulter, Ioan
and Young, Michael Tim",
title="Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review",
journal="J Med Internet Res",
year="2024",
month="Dec",
day="19",
volume="26",
pages="e60312",
keywords="digital health",
keywords="digital medical education",
keywords="health education",
keywords="medical education",
keywords="mobile phone",
keywords="artificial intelligence",
keywords="AI",
abstract="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. ",
doi="10.2196/60312",
url="https://www.jmir.org/2024/1/e60312"
}


@Article{info:doi/10.2196/59888,
author="Dobson, Rosie
and Whittaker, Robyn
and Abroms, C. Lorien
and Bramley, Dale
and Free, Caroline
and McRobbie, Hayden
and Stowell, Melanie
and Rodgers, Anthony",
title="Don't Forget the Humble Text Message: 25 Years of Text Messaging in Health",
journal="J Med Internet Res",
year="2024",
month="Dec",
day="17",
volume="26",
pages="e59888",
keywords="text messaging",
keywords="messaging",
keywords="SMS",
keywords="texting",
keywords="mHealth",
keywords="mobile health",
doi="10.2196/59888",
url="https://www.jmir.org/2024/1/e59888"
}


@Article{info:doi/10.2196/63391,
author="Spethmann, Sebastian
and Hindricks, Gerhard
and Koehler, Kerstin
and Stoerk, Stefan
and Angermann, E. Christiane
and B{\"o}hm, Michael
and Assmus, Birgit
and Winkler, Sebastian
and M{\"o}ckel, Martin
and Mittermaier, Mirja
and Lelgemann, Monika
and Reuter, Daniel
and Bosch, Ralph
and Albrecht, Alexander
and von Haehling, Stephan
and Helms, M. Thomas
and Sack, Stefan
and Bekfani, Tarek
and Gr{\"o}schel, Wolfgang Jan
and Koehler, Magdalena
and Melzer, Christoph
and Wintrich, Jan
and Zippel-Schultz, Bettina
and Ertl, Georg
and Vogelmeier, Claus
and Dagres, Nikolaos
and Zernikow, Jasmin
and Koehler, Friedrich",
title="Telemonitoring for Chronic Heart Failure: Narrative Review of the 20-Year Journey From Concept to Standard Care in Germany",
journal="J Med Internet Res",
year="2024",
month="Dec",
day="4",
volume="26",
pages="e63391",
keywords="telemedicine",
keywords="e-counseling",
keywords="heart decompensation",
keywords="Europe",
keywords="patient care management",
abstract="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. ",
doi="10.2196/63391",
url="https://www.jmir.org/2024/1/e63391"
}


@Article{info:doi/10.2196/59585,
author="Hall, A. Jeffrey",
title="Ten Myths About the Effect of Social Media Use on Well-Being",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="25",
volume="26",
pages="e59585",
keywords="social media",
keywords="well-being",
keywords="health promotion",
keywords="depressive disorder",
keywords="depression",
keywords="anxiety",
keywords="adolescent",
keywords="mental health",
doi="10.2196/59585",
url="https://www.jmir.org/2024/1/e59585"
}


@Article{info:doi/10.2196/57612,
author="Yi, Siyan
and Yam, Yan Esabelle Lo
and Cheruvettolil, Kochukoshy
and Linos, Eleni
and Gupta, Anshika
and Palaniappan, Latha
and Rajeshuni, Nitya
and Vaska, Gopal Kiran
and Schulman, Kevin
and Eggleston, N. Karen",
title="Perspectives of Digital Health Innovations in Low- and Middle-Income Health Care Systems From South and Southeast Asia",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="25",
volume="26",
pages="e57612",
keywords="digital health innovations",
keywords="public health",
keywords="South and Southeast Asia",
keywords="health care challenges",
keywords="low- and middle-income countries",
keywords="LMICs",
keywords="global health",
keywords="health AI",
keywords="artificial intelligence",
keywords="public health responses",
keywords="global health contexts",
keywords="digital health",
doi="10.2196/57612",
url="https://www.jmir.org/2024/1/e57612"
}


@Article{info:doi/10.2196/58933,
author="Piera-Jim{\'e}nez, Jordi
and Carot-Sans, Gerard
and Ramiro-Pareta, Marina
and Nogueras, Mercedes Maria
and Folguera-Profit{\'o}s, J{\'u}lia
and R{\'o}denas, Pepi
and Jim{\'e}nez-Rueda, Alba
and de Pando Navarro, Thais
and Mira Palacios, Antoni Josep
and Fajardo, Carles Joan
and Ustrell Campillo, Joan
and Vela, Emili
and Monterde, David
and Valero-Bover, Dami{\`a}
and Bonet, Tara
and Tarras{\'o}-Urios, Guillermo
and Cantenys-Sab{\`a}, Roser
and Fabregat-Fabregat, Pau
and G{\'o}mez Oliveros, Beatriz
and Berd{\'u}n, Jes{\'u}s
and Michelena, Xabier
and Cano, Isaac
and Gonz{\'a}lez-Colom, Rub{\`e}n
and Roca, Josep
and Solans, Oscar
and Pontes, Caridad
and P{\'e}rez-Sust, Pol",
title="A 25-Year Retrospective of Health IT Infrastructure Building: The Example of the Catalonia Region",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="18",
volume="26",
pages="e58933",
keywords="health ITs",
keywords="eHealth",
keywords="integrated care",
keywords="open platforms",
keywords="interoperability",
keywords="Catalonia",
keywords="digitalization",
keywords="health care structure",
keywords="health care delivery",
keywords="integrated pathway",
keywords="integrated treatment plan",
keywords="process management",
doi="10.2196/58933",
url="https://www.jmir.org/2024/1/e58933",
url="http://www.ncbi.nlm.nih.gov/pubmed/39556831"
}


@Article{info:doi/10.2196/59225,
author="Owen, David
and Lynham, J. Amy
and Smart, E. Sophie
and Pardi{\~n}as, F. Antonio
and Camacho Collados, Jose",
title="AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="15",
volume="26",
pages="e59225",
keywords="mental health",
keywords="depression",
keywords="anxiety",
keywords="schizophrenia",
keywords="social media",
keywords="natural language processing",
keywords="narrative review",
abstract="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. ",
doi="10.2196/59225",
url="https://www.jmir.org/2024/1/e59225"
}


@Article{info:doi/10.2196/60057,
author="Kaczmarczyk, Robert
and Wilhelm, Isabelle Theresa
and Roos, Jonas
and Martin, Ron",
title="Decoding the Digital Pulse: Bibliometric Analysis of 25 Years in Digital Health Research Through the Journal of Medical Internet Research",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="15",
volume="26",
pages="e60057",
keywords="digital health",
keywords="JMIR publication analysis",
keywords="network analysis",
keywords="artificial intelligence",
keywords="AI",
keywords="large language models",
keywords="eHealth",
keywords="Claude 3 Opus",
keywords="digital",
keywords="digital technology",
keywords="digital intervention",
keywords="machine learning",
keywords="natural language processing",
keywords="NLP",
keywords="deep learning",
keywords="algorithm",
keywords="model",
keywords="analytics",
keywords="practical model",
keywords="pandemic",
keywords="postpandemic era",
keywords="mobile phone",
abstract="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. ",
doi="10.2196/60057",
url="https://www.jmir.org/2024/1/e60057"
}


@Article{info:doi/10.2196/59556,
author="Gutman, Barak
and Shmilovitch, Amit-Haim
and Aran, Dvir
and Shelly, Shahar",
title="Twenty-Five Years of AI in Neurology: The Journey of Predictive Medicine and Biological Breakthroughs",
journal="JMIR Neurotech",
year="2024",
month="Nov",
day="8",
volume="3",
pages="e59556",
keywords="neurology",
keywords="artificial intelligence",
keywords="telemedicine",
keywords="clinical advancements",
keywords="mobile phone",
doi="10.2196/59556",
url="https://neuro.jmir.org/2024/1/e59556"
}


@Article{info:doi/10.2196/60441,
author="Fajnerova, Iveta
and Hejtm{\'a}nek, Luk{\'a}{\vs}
and Sedl{\'a}k, Michal
and Jablonsk{\'a}, Mark{\'e}ta
and Francov{\'a}, Anna
and Stopkov{\'a}, Pavla",
title="The Journey From Nonimmersive to Immersive Multiuser Applications in Mental Health Care: Systematic Review",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="7",
volume="26",
pages="e60441",
keywords="digital health",
keywords="mental health care",
keywords="clinical interventions",
keywords="multiuser",
keywords="immersive",
keywords="virtual reality",
keywords="VR",
keywords="app",
keywords="mental health",
keywords="online tools",
keywords="synthesis",
keywords="mobile phone",
keywords="PRISMA",
abstract="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. ",
doi="10.2196/60441",
url="https://www.jmir.org/2024/1/e60441"
}


@Article{info:doi/10.2196/60025,
author="Raman, Raghu
and Singhania, Monica
and Nedungadi, Prema",
title="Advancing the United Nations Sustainable Development Goals Through Digital Health Research: 25 Years of Contributions From the Journal of Medical Internet Research",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="4",
volume="26",
pages="e60025",
keywords="sustainable development goal",
keywords="topic modeling",
keywords="public health",
keywords="surveillance",
keywords="gender equality",
keywords="non-communicable disease",
keywords="social media",
keywords="COVID-19",
keywords="SARS-CoV-2",
keywords="coronavirus",
keywords="machine learning",
keywords="artificial intelligence",
keywords="AI",
keywords="digital health",
doi="10.2196/60025",
url="https://www.jmir.org/2024/1/e60025"
}


@Article{info:doi/10.2196/59791,
author="Barker, Wesley
and Chang, Wei
and Everson, Jordan
and Gabriel, Meghan
and Patel, Vaishali
and Richwine, Chelsea
and Strawley, Catherine",
title="The Evolution of Health Information Technology for Enhanced Patient-Centric Care in the United States: Data-Driven Descriptive Study",
journal="J Med Internet Res",
year="2024",
month="Oct",
day="28",
volume="26",
pages="e59791",
keywords="interoperability",
keywords="e-prescribing",
keywords="electronic public health reporting",
keywords="patient access to health information",
keywords="electronic health records",
keywords="health IT",
abstract="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. ",
doi="10.2196/59791",
url="https://www.jmir.org/2024/1/e59791",
url="http://www.ncbi.nlm.nih.gov/pubmed/39466303"
}


@Article{info:doi/10.2196/58936,
author="K{\"o}hler, Charlotte
and Bartschke, Alexander
and F{\"u}rstenau, Daniel
and Schaaf, Thorsten
and Salgado-Baez, Eduardo",
title="The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research",
journal="J Med Internet Res",
year="2024",
month="Oct",
day="25",
volume="26",
pages="e58936",
keywords="consumer devices",
keywords="smartwatches",
keywords="value-based health care",
keywords="monitoring",
keywords="nudging",
keywords="predicting",
keywords="mobile phone",
doi="10.2196/58936",
url="https://www.jmir.org/2024/1/e58936",
url="http://www.ncbi.nlm.nih.gov/pubmed/39356287"
}


@Article{info:doi/10.2196/62691,
author="Fiordelli, Maddalena",
title="Transitioning Perspectives in Digital Health Through Phenomenology Integration",
journal="J Med Internet Res",
year="2024",
month="Oct",
day="23",
volume="26",
pages="e62691",
keywords="eHealth",
keywords="digital health",
keywords="phenomenology",
keywords="phenomenological",
keywords="participatory",
keywords="health communication",
keywords="health information",
keywords="active listening",
keywords="lived experience",
doi="10.2196/62691",
url="https://www.jmir.org/2024/1/e62691"
}


@Article{info:doi/10.2196/58987,
author="Hu, Jing
and Li, Chong
and Ge, Yanlei
and Yang, Jingyi
and Zhu, Siyi
and He, Chengqi",
title="Mapping the Evolution of Digital Health Research: Bibliometric Overview of Research Hotspots, Trends, and Collaboration of Publications in JMIR (1999-2024)",
journal="J Med Internet Res",
year="2024",
month="Oct",
day="17",
volume="26",
pages="e58987",
keywords="JMIR",
keywords="bibliometric analysis",
keywords="ehealth",
keywords="digital health",
keywords="medical informatics",
keywords="health informatics",
keywords="open science",
keywords="publishing",
abstract="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. ",
doi="10.2196/58987",
url="https://www.jmir.org/2024/1/e58987"
}


@Article{info:doi/10.2196/60081,
author="You, Guan-Ting Jacqueline
and Leung, I. Tiffany
and Pandita, Deepti
and Sakumoto, Matthew",
title="Primary Care Informatics: Vitalizing the Bedrock of Health Care",
journal="J Med Internet Res",
year="2024",
month="Oct",
day="15",
volume="26",
pages="e60081",
keywords="health care delivery",
keywords="primary care",
keywords="primary health care",
keywords="primary prevention",
keywords="quality of health care",
keywords="holistic care",
keywords="holistic medicine",
keywords="people-centric care",
keywords="person-centric care",
keywords="medical informatics applications",
keywords="primary care informatics",
keywords="medical informatics",
keywords="health informatics",
keywords="information science",
keywords="data science",
doi="10.2196/60081",
url="https://www.jmir.org/2024/1/e60081"
}


@Article{info:doi/10.2196/58888,
author="Wilkes, Matt
and Kramer, Annabel
and Pugmire, Juliana
and Pilkington, Christopher
and Zaniello, Benjamin
and Zahradka, Nicole",
title="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",
journal="J Med Internet Res",
year="2024",
month="Oct",
day="11",
volume="26",
pages="e58888",
keywords="telemedicine",
keywords="implementation science",
keywords="hospital-to-home transition",
keywords="remote patient monitoring",
keywords="digital health",
keywords="transition of care",
keywords="accuracy",
keywords="acceptability",
doi="10.2196/58888",
url="https://www.jmir.org/2024/1/e58888",
url="http://www.ncbi.nlm.nih.gov/pubmed/39331537"
}


@Article{info:doi/10.2196/62790,
author="Portz, Jennifer
and Moore, Susan
and Bull, Sheana",
title="Evolutionary Trends in the Adoption, Adaptation, and Abandonment of Mobile Health Technologies: Viewpoint Based on 25 Years of Research",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="27",
volume="26",
pages="e62790",
keywords="technology adoption",
keywords="mobile health",
keywords="SMS text messaging",
keywords="mobile apps",
keywords="wearables",
keywords="social media",
doi="10.2196/62790",
url="https://www.jmir.org/2024/1/e62790",
url="http://www.ncbi.nlm.nih.gov/pubmed/39331463"
}


@Article{info:doi/10.2196/59939,
author="Robinson, Athena
and Flom, Megan
and Forman-Hoffman, L. Valerie
and Histon, Trina
and Levy, Monique
and Darcy, Alison
and Ajayi, Toluwalase
and Mohr, C. David
and Wicks, Paul
and Greene, Carolyn
and Montgomery, M. Robert",
title="Equity in Digital Mental Health Interventions in the United States: Where to Next?",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="24",
volume="26",
pages="e59939",
keywords="Digital Mental Health Interventions",
keywords="mental health",
keywords="health equity",
keywords="access to health care",
keywords="health plan implementations",
doi="10.2196/59939",
url="https://www.jmir.org/2024/1/e59939",
url="http://www.ncbi.nlm.nih.gov/pubmed/39316436"
}


@Article{info:doi/10.2196/63367,
author="Liu, Lu
and Wang, Xiu-Ling
and Cheng, Nuo
and Yu, Fu-Min
and Li, Hui-Jun
and Mu, Yang
and Yuan, Yonghui
and Dong, Jia-Xin
and Wu, Yu-Dan
and Gong, Da-Xin
and Wang, Shuang
and Zhang, Guang-Wei",
title="Development Trends and Prospects of Technology-Based Solutions for Health Challenges in Aging Over the Past 25 Years: Bibliometric Analysis",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="20",
volume="26",
pages="e63367",
keywords="bibliometrics",
keywords="CiteSpace",
keywords="VOSviewer",
keywords="visualization",
keywords="aging health",
keywords="technological innovations",
keywords="tech-based",
keywords="technology-based",
keywords="technology",
keywords="health challenges",
keywords="challenges",
keywords="trends",
keywords="older adults",
keywords="older adult",
keywords="ageing",
keywords="aging",
keywords="elder",
keywords="elderly",
keywords="older person",
keywords="older people",
keywords="gerontology",
keywords="geriatric",
keywords="geriatrics",
keywords="remote",
keywords="remote monitoring",
keywords="monitoring",
keywords="surveillance",
keywords="artificial intelligence",
keywords="AI",
keywords="AI-driven",
keywords="innovation",
keywords="innovations",
keywords="health management",
keywords="telemedicine",
keywords="remote care",
abstract="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. ",
doi="10.2196/63367",
url="https://www.jmir.org/2024/1/e63367",
url="http://www.ncbi.nlm.nih.gov/pubmed/39238480"
}


@Article{info:doi/10.2196/58198,
author="Fitzpatrick, Skye
and Crenshaw, O. Alexander
and Donkin, Victoria
and Collins, Alexis
and Xiang, Angela
and Earle, A. Elizabeth
and Goenka, Kamya
and Varma, Sonya
and Bushe, Julianne
and McFadden, Tara
and Librado, Andrea
and Monson, Candice",
title="We Have Spent Time, Money, and Effort Making Self-Help Digital Mental Health Interventions: Is Anyone Going to Come to the Party?",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="19",
volume="26",
pages="e58198",
keywords="online interventions",
keywords="self-help",
keywords="digital interventions",
keywords="mental health",
keywords="psychotherapy",
keywords="intervention desirability",
doi="10.2196/58198",
url="https://www.jmir.org/2024/1/e58198"
}


@Article{info:doi/10.2196/58704,
author="Elliot, J. Alex
and Hughes, E. Helen
and Harcourt, E. Sally
and Smith, Sue
and Loveridge, Paul
and Morbey, A. Roger
and Bains, Amardeep
and Edeghere, Obaghe
and Jones, R. Natalia
and Todkill, Daniel
and Smith, E. Gillian",
title="From Fax to Secure File Transfer Protocol: The 25-Year Evolution of Real-Time Syndromic Surveillance in England",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="17",
volume="26",
pages="e58704",
keywords="epidemiology",
keywords="population surveillance",
keywords="sentinel surveillance",
keywords="public health surveillance",
keywords="bioterrorism",
keywords="mass gathering",
keywords="pandemics",
doi="10.2196/58704",
url="https://www.jmir.org/2024/1/e58704"
}


@Article{info:doi/10.2196/59497,
author="Liang, Ya-Ting
and Wang, Charlotte
and Hsiao, Kate Chuhsing",
title="Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="11",
volume="26",
pages="e59497",
keywords="accelerometer",
keywords="association",
keywords="behavioral study",
keywords="classification",
keywords="digital biomarkers",
keywords="digital health",
keywords="physical activity",
keywords="prediction",
keywords="statistical method",
keywords="wearable",
abstract="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. ",
doi="10.2196/59497",
url="https://www.jmir.org/2024/1/e59497"
}


@Article{info:doi/10.2196/59711,
author="Wang, Zhaoxin
and Yang, Wenwen
and Li, Zhengyu
and Rong, Ze
and Wang, Xing
and Han, Jincong
and Ma, Lei",
title="A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="10",
volume="26",
pages="e59711",
keywords="acute stroke",
keywords="artificial intelligence",
keywords="AI",
keywords="machine learning",
keywords="deep learning",
keywords="stroke lesion segmentation and classification",
keywords="stroke prediction",
keywords="stroke prognosis",
abstract="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. ",
doi="10.2196/59711",
url="https://www.jmir.org/2024/1/e59711"
}


@Article{info:doi/10.2196/58939,
author="Hall, L. Charlotte
and G{\'o}mez Bergin, D. Aislinn
and Rennick-Egglestone, Stefan",
title="Research Into Digital Health Intervention for Mental Health: 25-Year Retrospective on the Ethical and Legal Challenges",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="9",
volume="26",
pages="e58939",
keywords="digital mental health intervention",
keywords="research ethics",
keywords="compliance",
keywords="regulation",
keywords="digital health",
keywords="mobile health",
keywords="mhealth",
keywords="intervention",
keywords="interventions",
keywords="mental health",
keywords="retrospective",
keywords="ethical",
keywords="legal",
keywords="challenge",
keywords="challenges",
doi="10.2196/58939",
url="https://www.jmir.org/2024/1/e58939"
}


@Article{info:doi/10.2196/59089,
author="Ferguson, M. Jacqueline
and Van Campen, James
and Slightam, Cindie
and Greene, Liberty
and Heyworth, Leonie
and Zulman, M. Donna",
title="Evaluation of the Veterans Health Administration's Digital Divide Consult for Tablet Distribution and Telehealth Adoption: Cohort Study",
journal="J Med Internet Res",
year="2024",
month="Sep",
day="9",
volume="26",
pages="e59089",
keywords="veterans",
keywords="health care access",
keywords="video-based care",
keywords="telehealth",
keywords="barriers to care",
keywords="telemedicine",
abstract="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. ",
doi="10.2196/59089",
url="https://www.jmir.org/2024/1/e59089",
url="http://www.ncbi.nlm.nih.gov/pubmed/39250183"
}


@Article{info:doi/10.2196/59013,
author="Goeldner, Moritz
and Gehder, Sara",
title="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",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="29",
volume="26",
pages="e59013",
keywords="digital health application",
keywords="DiGA",
keywords="data-driven analysis",
keywords="clinical evidence",
keywords="health economics",
keywords="positive care effect",
keywords="medical benefit",
keywords="patient-relevant structural and procedural improvements",
keywords="pSVV",
keywords="digital health care act",
abstract="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 f{\"u}r 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 {\texteuro}200 to {\texteuro}700 ({\texteuro}1=US \$1.07), averaging at a median of {\texteuro}514 for a 3-month DiGA prescription. Following negotiations or arbitration board decisions, prices typically see a 50\% reduction, settling at a median of {\texteuro}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. ",
doi="10.2196/59013",
url="https://www.jmir.org/2024/1/e59013"
}


@Article{info:doi/10.2196/58726,
author="Suffoletto, Brian",
title="Deceptively Simple yet Profoundly Impactful: Text Messaging Interventions to Support Health",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="27",
volume="26",
pages="e58726",
keywords="SMS intervention",
keywords="behavior",
keywords="intervention",
keywords="review",
keywords="text messaging",
keywords="SMS",
keywords="interventions",
keywords="behaviors",
keywords="behaviour",
keywords="behaviours",
keywords="effectiveness",
keywords="development",
keywords="impact",
keywords="narrative review",
keywords="physical activity",
keywords="diet",
keywords="weight loss",
keywords="mental health",
keywords="substance use",
keywords="meta-analysis",
keywords="chatbot",
keywords="chatbots",
keywords="large language model",
keywords="LLM",
keywords="large language models",
keywords="mobile phone",
doi="10.2196/58726",
url="https://www.jmir.org/2024/1/e58726",
url="http://www.ncbi.nlm.nih.gov/pubmed/39190427"
}


@Article{info:doi/10.2196/57848,
author="Osman, Sagda
and Churruca, Kate
and Ellis, A. Louise
and Luo, Dan
and Braithwaite, Jeffrey",
title="The Unintended Consequences of Telehealth in Australia: Critical Interpretive Synthesis",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="27",
volume="26",
pages="e57848",
keywords="telehealth",
keywords="telemedicine",
keywords="unintended consequences",
keywords="digital health",
keywords="eHealth",
keywords="critical interpretive synthesis",
keywords="review methodology",
keywords="literature review",
keywords="Australia",
abstract="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. ",
doi="10.2196/57848",
url="https://www.jmir.org/2024/1/e57848",
url="http://www.ncbi.nlm.nih.gov/pubmed/39190446"
}


@Article{info:doi/10.2196/59358,
author="Shi, Lin-Hong Jenny
and Sit, Wing-Shan Regina",
title="Impact of 25 Years of Mobile Health Tools for Pain Management in Patients With Chronic Musculoskeletal Pain: Systematic Review",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="16",
volume="26",
pages="e59358",
keywords="mHealth",
keywords="mobile health",
keywords="mobile app",
keywords="chronic musculoskeletal pain",
keywords="pain management",
keywords="patient compliance",
keywords="adherence",
keywords="usability",
keywords="feasibility",
keywords="acceptability",
keywords="PRISMA",
abstract="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 ",
doi="10.2196/59358",
url="https://www.jmir.org/2024/1/e59358"
}


@Article{info:doi/10.2196/58950,
author="Meyer, Annika
and Streichert, Thomas",
title="Twenty-Five Years of Progress---Lessons Learned From JMIR Publications to Address Gender Parity in Digital Health Authorships: Bibliometric Analysis",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="9",
volume="26",
pages="e58950",
keywords="digital health",
keywords="medical informatics, authorship",
keywords="gender distribution",
keywords="diversity",
keywords="bibliometric",
keywords="scientometric",
keywords="algorithmic bias reduction",
keywords="gender gap",
keywords="JMIR Publications",
keywords="authorships",
keywords="author",
keywords="authors",
keywords="bibliometric analysis",
keywords="equality",
keywords="comparison",
keywords="gender representation",
keywords="journal",
keywords="journals",
keywords="article",
keywords="articles",
keywords="Web of Science",
keywords="control group",
keywords="comparative analysis",
keywords="statistical analysis",
keywords="gender",
abstract="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. ",
doi="10.2196/58950",
url="https://www.jmir.org/2024/1/e58950"
}


@Article{info:doi/10.2196/59005,
author="Sendra-Portero, Francisco
and Lorenzo-{\'A}lvarez, Roc{\'i}o
and Rudolphi-Solero, Teodoro
and Ruiz-G{\'o}mez, Jos{\'e} Miguel",
title="The Second Life Metaverse and Its Usefulness in Medical Education After a Quarter of a Century",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="6",
volume="26",
pages="e59005",
keywords="medical education",
keywords="medical students",
keywords="postgraduate",
keywords="computer simulation",
keywords="virtual worlds",
keywords="metaverse",
doi="10.2196/59005",
url="https://www.jmir.org/2024/1/e59005"
}


@Article{info:doi/10.2196/59066,
author="Hersh, William",
title="A Quarter-Century of Online Informatics Education: Learners Served and Lessons Learned",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="6",
volume="26",
pages="e59066",
keywords="distance education",
keywords="online learning",
keywords="asynchronous education",
keywords="biomedical and health informatics",
keywords="learning",
keywords="biomedical",
keywords="health informatics",
keywords="education",
keywords="educational",
keywords="educational technology",
keywords="online program",
keywords="online course",
keywords="teaching",
keywords="students",
doi="10.2196/59066",
url="https://www.jmir.org/2024/1/e59066"
}


@Article{info:doi/10.2196/59826,
author="Ortiz, Abigail
and Mulsant, H. Benoit",
title="Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry?",
journal="J Med Internet Res",
year="2024",
month="Aug",
day="5",
volume="26",
pages="e59826",
keywords="digital phenotype",
keywords="digital phenotyping",
keywords="prediction",
keywords="predictions",
keywords="mental health",
keywords="mental illness",
keywords="mental illnesses",
keywords="mental disorder",
keywords="mental disorders",
keywords="US National Institute of Mental Health",
keywords="NIMH",
keywords="psychiatry",
keywords="psychiatrist",
keywords="psychiatrists",
doi="10.2196/59826",
url="https://www.jmir.org/2024/1/e59826"
}


@Article{info:doi/10.2196/58764,
author="Lokker, Cynthia
and McKibbon, Ann K.
and Afzal, Muhammad
and Navarro, Tamara
and Linkins, Lori-Ann
and Haynes, Brian R.
and Iorio, Alfonso",
title="The McMaster Health Information Research Unit: Over a Quarter-Century of Health Informatics Supporting Evidence-Based Medicine",
journal="J Med Internet Res",
year="2024",
month="Jul",
day="31",
volume="26",
pages="e58764",
keywords="health informatics",
keywords="evidence-based medicine",
keywords="information retrieval",
keywords="evidence-based",
keywords="health information",
keywords="Boolean",
keywords="natural language processing",
keywords="NLP",
keywords="journal",
keywords="article",
keywords="Health Information Research Unit",
keywords="HiRU",
doi="10.2196/58764",
url="https://www.jmir.org/2024/1/e58764"
}


@Article{info:doi/10.2196/58846,
author="Sweeting, Anna
and Warncken, A. Katie
and Patel, Martyn",
title="The Role of Assistive Technology in Enabling Older Adults to Achieve Independent Living: Past and Future",
journal="J Med Internet Res",
year="2024",
month="Jul",
day="30",
volume="26",
pages="e58846",
keywords="assistive technology",
keywords="older adults",
keywords="users",
keywords="aging",
keywords="aging in place",
keywords="UK",
keywords="cocreation",
keywords="research trial",
keywords="independent living",
keywords="North Norfolk",
keywords="disability",
keywords="injury",
keywords="tool",
keywords="use",
keywords="design",
keywords="barrier",
doi="10.2196/58846",
url="https://www.jmir.org/2024/1/e58846"
}