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From E-Patients to AI Patients: The Tidal Wave Empowering Patients, Redefining Clinical Relationships, and Transforming Care

From E-Patients to AI Patients: The Tidal Wave Empowering Patients, Redefining Clinical Relationships, and Transforming Care

In 2017, Jo PM joined JMIR Publications as a peer-reviewed, open access journal to advance the science of participatory care (also referred to as coproduction and co-design). Published papers mirror the 15-year shift in relationships between patients, their health information, and their providers. Health professionals often overestimate the risks of e-patients (patients and caregivers online) and underestimate their value [18].

Susan S Woods, Sarah M Greene, Laura Adams, Grace Cordovano, Matthew F Hudson

J Particip Med 2025;17:e75794


Exploring Ethics: Understanding the Role of Privacy Policies and Institutional Review Boards in Digital Health Companies

Exploring Ethics: Understanding the Role of Privacy Policies and Institutional Review Boards in Digital Health Companies

A recent paper described how studies involving sensitive data, when conducted without formal ethical review, can lead to public misinformation, erode trust in science, and undermine institutional credibility [4]. These concerns are especially relevant in digital health, where existing company practices and policies, such as internal review processes or general user agreements, may not sufficiently address the ethical complexities of data use, highlighting the need for more robust forms of oversight.

Jacqlyn L Yourell, Kelsey L McAlister, Clare C Beatty, Jennifer L Huberty

J Med Internet Res 2025;27:e70711


Leveraging Technology to Engage Supplemental Nutrition Assistance Program Consumers With Children at Farmers Markets: Qualitative Community-Engaged Approach to App Development

Leveraging Technology to Engage Supplemental Nutrition Assistance Program Consumers With Children at Farmers Markets: Qualitative Community-Engaged Approach to App Development

Mobile apps are a popular approach in translational science in behavioral health interventions [24,25], demonstrating some success in changing dietary patterns [26]. Effective dissemination, implementation, and translational science, however, hinges on community engagement, where the target population is engaged in all processes from problem identification to design and implementation of interventions [27].

Callie Ogland-Hand, Jillian Schulte, Owusua Yamoah, Kathryn Poppe, Timothy H Ciesielski, Regan Gee, Ana Claudia Zubieta, Darcy A Freedman

JMIR Form Res 2025;9:e70104


Benchmarking the Confidence of Large Language Models in Answering Clinical Questions: Cross-Sectional Evaluation Study

Benchmarking the Confidence of Large Language Models in Answering Clinical Questions: Cross-Sectional Evaluation Study

A wide array of LLMs is now accessible, including open-source models, offering solutions that cater to both the public and medical professionals [1,4]. The efficacy of these models has been demonstrated in a variety of tasks, albeit with some limitations [5,6]. For instance, LLMs, such as GPT, have shown promise in providing diagnostic assistance and answering medical queries [5,7-9].

Mahmud Omar, Reem Agbareia, Benjamin S Glicksberg, Girish N Nadkarni, Eyal Klang

JMIR Med Inform 2025;13:e66917


Stakeholders and Contextual Factors in the Implementation of Assistive Robotic Arms for Persons With Tetraplegia: Deductive Content Analysis of Focus Group Interviews

Stakeholders and Contextual Factors in the Implementation of Assistive Robotic Arms for Persons With Tetraplegia: Deductive Content Analysis of Focus Group Interviews

A link to a Microsoft Forms survey allowed the validation of the illustration map by each participant anonymously, where either the option “I agree with the visual summary” or the option “I do not agree with the visual summary,” followed by an open text field for feedback, could be chosen (Multimedia Appendices 10 and 11). The response rate for the validation was 77%, with 17 participants completing the survey.

Vera Fosbrooke, Marco Riguzzi, Anja M Raab

JMIR Rehabil Assist Technol 2025;12:e65759


Experience of Using Electronic Inhaler Monitoring Devices for Patients With Chronic Obstructive Pulmonary Disease or Asthma: Systematic Review of Qualitative Studies

Experience of Using Electronic Inhaler Monitoring Devices for Patients With Chronic Obstructive Pulmonary Disease or Asthma: Systematic Review of Qualitative Studies

A comprehensive search was conducted in 6 databases—Pub Med, Web of Science, CINAHL, Embase, Cochrane Library, and Psyc Info—to identify qualitative studies on the experiences of patients with COPD or asthma using EIMDs. Electronic monitoring equipment for inhalation devices was first reported in 1983 [28]. To maximize the inclusion of relevant reports, this search covered publications from January 1983 through July 2024.

Jilong Duan, Xia Chen, Di Fan, Haikun Jiang, Xue Zhang, Wenyue Zhang, Zhiping Liu, Hongyan Lu

JMIR Mhealth Uhealth 2025;13:e57645


Power-Assist Add-Ons for Older Adult Manual Wheelchair Users: Protocol for a Scoping Review

Power-Assist Add-Ons for Older Adult Manual Wheelchair Users: Protocol for a Scoping Review

Our review protocol has been registered on the Open Science Framework [13] and will be guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-Sc R) checklist extension for Scoping Reviews [14]. We will use the scoping review framework originally developed by Arksey and O’Malley [15] and incorporate additional refinements recommended by Levac et al [16].

Oladele Atoyebi, Andrew Wister, Johanne Mattie, Gloria Gutman, Habib Chaudhury, Carolyn Sparrey, O Yvette Jones, W Ben Mortenson, Eireann O’Dea, Sogol Haji Hosseini, Jaimie Borisoff

JMIR Res Protoc 2025;14:e56375


Quality and Misinformation About Health Conditions in Online Peer Support Groups: Scoping Review

Quality and Misinformation About Health Conditions in Online Peer Support Groups: Scoping Review

The review protocol was registered in January 2024 on the Open Science Framework Registries [39]. The PCC (Population, Concept, and Context) framework [37] was followed as a guide to construct the review objectives, search strategy, and eligibility criteria. Covidence systematic review software was used for all review stages [40]. The principal reviewer (BMT) and second reviewer (EP) developed the search strategy, with assistance from a university research librarian.

Bethan M Treadgold, Neil S Coulson, John L Campbell, Jeffrey Lambert, Emma Pitchforth

J Med Internet Res 2025;27:e71140


Providing Education and Training to Health Care Professionals to Address COVID-19 Health Disparities: Protocol for Implementation Project Using Reach, Effectiveness, Adoption, Implementation, and Maintenance Framework

Providing Education and Training to Health Care Professionals to Address COVID-19 Health Disparities: Protocol for Implementation Project Using Reach, Effectiveness, Adoption, Implementation, and Maintenance Framework

By using implementation science methods, an innovative and comprehensive educational protocol was developed for health care workers in Nebraska that integrates the training curriculum, evaluation metrics, and coaching support, allowing the translation of the training into actionable health care/community projects focused on addressing health disparities. This model has shown initial promise in terms of feasibility and uptake.

Adati Tarfa, Nada Fadul, Erica Stohs, Jeffrey Wetherhold, Mahelet Kebede, Nuha Mirghani, Muhammad Salman Ashraf

JMIR Res Protoc 2025;14:e60901


Patients’ Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study

Patients’ Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study

We (JG, SN, and CB) created a topic guide to generate open responses. We developed our guide using Krueger and Casey’s [49] approach to FG guides, Helfferich’s methods [50], the TAM [40,41], and the UTAUT [42]. Participants were asked the following questions: What factors would make you more or less likely to accept an AI system in medical care? What challenges do you see for a successful use of AI in medical care? Where do you see potential applications for AI in medical care, and where don’t?

Jana Gundlack, Carolin Thiel, Sarah Negash, Charlotte Buch, Timo Apfelbacher, Kathleen Denny, Jan Christoph, Rafael Mikolajczyk, Susanne Unverzagt, Thomas Frese

J Med Internet Res 2025;27:e70487