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Motivation Theories and Constructs in Experimental Studies of Online Instruction: Systematic Review and Directed Content Analysis

Adam Gavarkovs, Erin Miller, Jaimie Coleman, Tharsiga Gunasegaran, Rashmi A Kusurkar, Kulamakan Kulasegaram, Melanie Anderson, Ryan Brydges

JMIR Med Educ 2025;11:e64179

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Implementation of an Integrated, Clinical Decision Support Tool at the Point of Antihypertensive Medication Refill Request to Improve Hypertension Management: Controlled Pre-Post Study

The baseline compliance proportion was higher in the intervention clinics compared to the control clinics (difference: 3.32%, 95% CI 0.5%-6.2%; P=.02). Across all clinics, there was no significant change in compliance proportions from the baseline to the intervention period (difference: 1.29%, 95% CI: −1.6% to 4.2%; P=.37). The DID estimate, reflecting the interaction between intervention group and time period, was not statistically significant (difference: 0.07%, 95% CI −4.0% to 4.1%; P=.97).

John Charles Matulis 3rd, Jason Greenwood, Michele Eberle, Benjamin Anderson, David Blair, Rajeev Chaudhry

JMIR Med Inform 2025;13:e70752

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A Web-Based Tool to Perform a Values Clarification for Stroke Prevention in Patients With Atrial Fibrillation: Design and Preliminary Testing Study

The overall SURE test, saying “yes” to all 4 components, was 61.2% (156/255) for the standard group, 66.5% (145/218) for the visual group, and 67% (134/200) for the visual+VC group (visual vs standard, odds ratio [OR] 1.26, 95% CI 0.86‐1.84; P=.23; visual+VC vs standard, OR 1.29, 95% CI 0.87‐1.90; P=.20).

Michael P Dorsch, Allen J Flynn, Kaitlyn M Greer, Sabah Ganai, Geoffrey D Barnes, Brian Zikmund-Fisher

JMIR Cardio 2025;9:e67956

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Evaluating User Experience and Satisfaction in a Concussion Rehabilitation App: Usability Study

Michael G Hutchison, Alex P Di Battista, Kyla L Pyndiura

JMIR Form Res 2025;9:e67275

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Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

Across all discrepancies, GPT-4o was significantly more effective in criteria filtering compared to the medical student (Mc Nemar test for paired proportions [30]: χ21=5.985; P=.015). However, in applying relevant criteria, GPT-4o performed worse than the medical students, though the difference was not statistically significant (Mc Nemar test: χ21=1.818; P=.178).

Vimig Socrates, Donald S Wright, Thomas Huang, Soraya Fereydooni, Christine Dien, Ling Chi, Jesse Albano, Brian Patterson, Naga Sasidhar Kanaparthy, Catherine X Wright, Andrew Loza, David Chartash, Mark Iscoe, Richard Andrew Taylor

JMIR Aging 2025;8:e69504

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A Novel Just-in-Time Intervention for Promoting Safer Drinking Among College Students: App Testing Across 2 Independent Pre-Post Trials

There was no significant effect of the study phase or incentives on any of the self-reported drinking outcomes, for the average number of days per week in the last month involving alcohol consumption (F2, 232=0.294, P=.75, η2=.003), typical weekend evening drink consumption in the last month (F2, 165=0.662, P=.52, η2=.008), the maximum number of drinks consumed in the last month (F2, 175=0.005, P=.99, η2=.00), or protective behavioral strategies (F2, 232=1.469, P=.23, η2=.013).

Philip I Chow, Jessica Smith, Ravjot Saini, Christina Frederick, Connie Clark, Maxwell Ritterband, Jennifer P Halbert, Kathryn Cheney, Katharine E Daniel, Karen S Ingersoll

JMIR Hum Factors 2025;12:e69873

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Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

The p-values of the AUROC scores are presented in Multimedia Appendix 1. As P Data cleaning and cohort selection with descriptive analysis were conducted using Stata version 16.1 (Stata Corp). We used Python version 3.8.10, along with the Monai framework version 1.2.0 (NVIDIA) and Pytorch version 2.0.0 (Facebook) to develop the deep learning models. Additionally, the AUROC score and its 95% CI were calculated using Fast De Long implementation from VMAF (Video Multimethod Assessment Fusion; Netflix) [43].

Mahmudur Rahman, Jifan Gao, Kyle A Carey, Dana P Edelson, Askar Afshar, John W Garrett, Guanhua Chen, Majid Afshar, Matthew M Churpek

JMIR AI 2025;4:e67144

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Association of Social Media Recruitment and Depression Among Racially and Ethnically Diverse Metabolic and Bariatric Surgery Candidates: Prospective Cohort Study

We performed all analyses using STATA (v.17.1, Stata Corp LP), with statistical significance set at a P value below 5%. Participant characteristics (N=380) stratified by recruitment method, social media (n=107), and nonsocial media (n=273) are presented in Table 1. Participants recruited through social media had a mean age of 47.27 (SD 1.02) years, whereas those in the nonsocial media group had a mean age of 47.38 (SD 0.73) years (P=.93).

Jackson M Francis, Sitapriya S Neti, Dhatri Polavarapu, Folefac Atem, Luyu Xie, Olivia Kapera, Matthew S Mathew, Elisa Marroquin, Carrie McAdams, Jeffrey Schellinger, Sophia Ngenge, Sachin Kukreja, Benjamin E Schneider, Jaime P Almandoz, Sarah E Messiah

JMIR Form Res 2025;9:e58916

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Digital Health Intervention on Awareness of Vaccination Against Influenza Among Adults With Diabetes: Pragmatic Randomized Follow-Up Study

The results indicated a nonsignificant association between the 2 variables (χ2(df=4)=4.98, P=.29). All expected cell frequencies were greater than 5, satisfying the assumption for the chi-square test. A total of 8431 users with diabetes self-reported influenza vaccination status in surveys (2) or (3). After 6 months, ratios of 71.0% (2489/3505) of group A reported getting vaccinated versus 71.9% (2207/3068) in group B and 70.5% (1310/1858) in group C (χ2(df=2)=1.30, P=.52) as presented in Table 3.

Yifat Fundoiano-Hershcovitz, Felix Lee, Catherine Stanger, Inbar Breuer Asher, David L Horwitz, Omar Manejwala, Jan Liska, David Kerr