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Health Care Professionals' Engagement With Digital Mental Health Interventions in the United Kingdom and China: Mixed Methods Study on Engagement Factors and Design Implications

Health Care Professionals' Engagement With Digital Mental Health Interventions in the United Kingdom and China: Mixed Methods Study on Engagement Factors and Design Implications

Many recent reviews have shown that low engagement is a ubiquitous problem among DMHIs [17-19]. Plus, user engagement is considerably lower in naturalistic settings than in empirical studies [19-21]. To illustrate this, a review of 59 off-the-shelf mental health apps reported a median uptake rate of 4.0% and a 15-day retention rate of only 3.9% [22].

Zheyuan Zhang, Sijin Sun, Laura Moradbakhti, Andrew Hall, Celine Mougenot, Juan Chen, Rafael A Calvo

JMIR Ment Health 2025;12:e67190

Patient and Clinician Perspectives on Alert-Based Remote Monitoring–First Care for Cardiovascular Implantable Electronic Devices: Semistructured Interview Study Within the Veterans Health Administration

Patient and Clinician Perspectives on Alert-Based Remote Monitoring–First Care for Cardiovascular Implantable Electronic Devices: Semistructured Interview Study Within the Veterans Health Administration

RM involves sending CIED data from a patient’s residence via a transmitter or smartphone app. Routine transmissions are usually sent every 90 days and can also be patient- or alert-initiated. RM is a Class 1, Level of Evidence A, professional society recommendation because of its many clinical outcome benefits [1,2]. These include reduced mortality [3-5], fewer hospitalizations [3,6], fewer inappropriate ICD shocks [7], as well as high patient satisfaction [8].

Allison Kratka, Thomas L Rotering, Scott Munson, Merritt H Raitt, Mary A Whooley, Sanket S Dhruva

JMIR Cardio 2025;9:e66215

Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG

Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG

This laborious process, which demands expertise and resources, faces a bottleneck in scaling up to meet the demand for a vast quantity of quality items. The challenge is particularly pronounced in medical education, where only a progress test administration in a year requires having 2400 multiple-choice items [2], showing the inefficiency of traditional methods in satisfying the needs of question banks in medical schools.

Yavuz Selim Kıyak, Andrzej A Kononowicz

JMIR Form Res 2025;9:e65726

Virtual Patients Using Large Language Models: Scalable, Contextualized Simulation of Clinician-Patient Dialogue With Feedback

Virtual Patients Using Large Language Models: Scalable, Contextualized Simulation of Clinician-Patient Dialogue With Feedback

We iteratively and rigorously engineered detailed “prompts” guiding GPT to emulate a diagnosis-focused or management-focused VP and provide feedback. To instantiate a specific VP, the interface accesses a 1-page case description. Narrative S1 in Multimedia Appendix 1 reports the full prompt and 1 case description. We selected as topics 2 common problems in ambulatory medicine: chronic cough (a diagnostic task) and diabetes (a management task).

David A Cook, Joshua Overgaard, V Shane Pankratz, Guilherme Del Fiol, Chris A Aakre

J Med Internet Res 2025;27:e68486

Changes in Physical Activity, Heart Rate, and Sleep Measured by Activity Trackers During the COVID-19 Pandemic Across 34 Countries: Retrospective Analysis

Changes in Physical Activity, Heart Rate, and Sleep Measured by Activity Trackers During the COVID-19 Pandemic Across 34 Countries: Retrospective Analysis

A threshold of 4 was chosen, as values beyond this range are typically considered extreme in statistical analysis, reducing the influence of outliers while retaining most of the data. This choice was particularly appropriate given that step count data often do not follow a normal distribution, necessitating a more flexible approach to outlier detection [32]. The number of steps ranged from 0 to 60,000 steps.

Bastien Wyatt, Nicolas Forstmann, Nolwenn Badier, Anne-Sophie Hamy, Quentin De Larochelambert, Juliana Antero, Arthur Danino, Vincent Vercamer, Paul De Villele, Benjamin Vittrant, Thomas Lanz, Fabien Reyal, Jean-François Toussaint, Lidia Delrieu

J Med Internet Res 2025;27:e68199

Environmental Impact of Physical Visits and Telemedicine in Nursing Care at Home: Comparative Life Cycle Assessment

Environmental Impact of Physical Visits and Telemedicine in Nursing Care at Home: Comparative Life Cycle Assessment

Telemedicine is often considered to be a promising solution for sustainable health care delivery as multiple reviews reported a reduction in travel-related emissions [9,10]. Savings were typically setting dependent and ranged anywhere between 0.7 and 372 kg of carbon dioxide equivalents (kg CO2eq) per consultation [10].

Egid M van Bree, Lynn E Snijder, Hans C Ossebaard, Evelyn A Brakema

J Med Internet Res 2025;27:e67538

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

(A) The 5-Cog battery (5-min cognitive assessment). (B) Decision support for a patient with a positive 5-Cog result. (C) Decision support for a patient with a negative 5-Cog result. EMR: electronic medical record. The United States Institute of Medicine (now the National Academy of Medicine) estimated a 17-year gap from when a clinical innovation is proven effective to when it is routinely implemented in clinical care [51].

Rachel Beth Rosansky Chalmer, Emmeline Ayers, Erica F Weiss, Nicole R Fowler, Andrew Telzak, Diana Summanwar, Jessica Zwerling, Cuiling Wang, Huiping Xu, Richard J Holden, Kevin Fiori, Dustin D French, Celeste Nsubayi, Asif Ansari, Paul Dexter, Anna Higbie, Pratibha Yadav, James M Walker, Harrshavasan Congivaram, Dristi Adhikari, Mairim Melecio-Vazquez, Malaz Boustani, Joe Verghese

JMIR Res Protoc 2025;14:e60471

Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis

Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis

Multiple notes can be written to describe the same identified chiropractic visit; for example, a resident chiropractor note and an attending chiropractor note may each contain data relevant to a single visit. We concatenated all notes linked to the same unique visit identifier on the same date of service (regardless of note author) to create a 1-to-1 relationship between visits and clinic notes. A unique character set was used as a delimiter to separate individual notes.

Brian C Coleman, Kelsey L Corcoran, Cynthia A Brandt, Joseph L Goulet, Stephen L Luther, Anthony J Lisi

JMIR Med Inform 2025;13:e66466

Digital Ergonomics of NavegApp, a Novel Serious Game for Spatial Cognition Assessment: Content Validity and Usability Study

Digital Ergonomics of NavegApp, a Novel Serious Game for Spatial Cognition Assessment: Content Validity and Usability Study

SC involves a range of cognitive functions, including the perception, organization, and use of location and object–based information to understand and navigate through physical or mental spaces [12-14]. When integrated, these processes facilitate complex spatial behaviors, such as solving mazes or tracing routes from point A to point B using landmarks or self-positioning as a reference [13].

Juan Pablo Sanchez-Escudero, David Aguillon, Stella Valencia, Mauricio A Garcia-Barrera, Daniel Camilo Aguirre-Acevedo, Natalia Trujillo

JMIR Serious Games 2025;13:e66167

Digital Health Resilience and Well-Being Interventions for Military Members, Veterans, and Public Safety Personnel: Environmental Scan and Quality Review

Digital Health Resilience and Well-Being Interventions for Military Members, Veterans, and Public Safety Personnel: Environmental Scan and Quality Review

Each DMHI was evaluated based on 2 quality rating scales: the A-MARS and the ARIA. A description of each is provided in the subsequent sections. The A-MARS [33] is a rating scale adapted from the MARS [34] and was used to review RBs and WBPs. The A-MARS was developed to evaluate health-related e-tools, with a specific expansion of the engagement subscale.

Rashell R Allen, Myrah A Malik, Carley Aquin, Lucijana Herceg, Suzette Brémault-Phillips, Phillip R Sevigny

JMIR Mhealth Uhealth 2025;13:e64098