Search Articles

View query in Help articles search

Search Results (1 to 10 of 3997 Results)

Download search results: CSV END BibTex RIS


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

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

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