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Impact of Conversational and Animation Features of a Mental Health App Virtual Agent on Depressive Symptoms and User Experience Among College Students: Randomized Controlled Trial

Impact of Conversational and Animation Features of a Mental Health App Virtual Agent on Depressive Symptoms and User Experience Among College Students: Randomized Controlled Trial

The analysis aimed for 80% power to detect effects at P=.05 with 4 groups and 2 time points, based on previous effect sizes [47]. Results indicated a required minimum sample of 136 participants. Multimedia Appendix 1 provides detailed information. We sought to recruit ≥25% (170 minimum) over the minimum to account for attrition and data exclusions.

Stephanie Six, Elizabeth Schlesener, Victoria Hill, Sabarish V Babu, Kaileigh Byrne

JMIR Ment Health 2025;12:e67381

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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

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

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

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

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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Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study

Statistical significance was set at P The final cohort included 1821 patients with 2800 notes (Table 2). The average age was 66.7 (SD 17.2) years; 978 (54.3%) out of 1821 patients were female. The racial and ethnic composition of the sample was 3.8% (69/1821) Black or African American, 6.3% (115/1821) Hispanic, 1.9% (35/1821) Asian, and 80.7% (1471/1821) White. The three most common medications used were omeprazole, furosemide, and lisinopril. The most common ICD code stem was I50.

Daniel Sumsion, Elijah Davis, Marta Fernandes, Ruoqi Wei, Rebecca Milde, Jet Malou Veltink, Wan-Yee Kong, Yiwen Xiong, Samvrit Rao, Tara Westover, Lydia Petersen, Niels Turley, Arjun Singh, Stephanie Buss, Shibani Mukerji, Sahar Zafar, Sudeshna Das, Valdery Moura Junior, Manohar Ghanta, Aditya Gupta, Jennifer Kim, Katie Stone, Emmanuel Mignot, Dennis Hwang, Lynn Marie Trotti, Gari D Clifford, Umakanth Katwa, Robert Thomas, M Brandon Westover, Haoqi Sun

JMIR Med Inform 2025;13:e64113

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