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Applications of Self-Driving Vehicles in an Aging Population
JMIR Form Res 2025;9:e66180
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Consumer-Grade Neurofeedback With Mindfulness Meditation: Meta-Analysis
We conducted 2 different approaches, trim-and-fill, which corrects for publication bias in small samples, and 3-parameter selection models which explicitly model the proportion of studies below a p-threshold. We considered applying p-curve approaches, but they require at least 3 significant findings which was not the case for multiple models.
A PRISMA flow diagram is shown in Figure 2 (PRISMA checklist provided in Multimedia Appendix 2).
J Med Internet Res 2025;27:e68204
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Background characteristics of nursing home residents in both the experimental and control groups who completed the semistructured interviews after the 4-week intervention.
a Significance level set at P
b Chi-square test with Yates continuity correction.
c Not applicable.
d GDS: Global Deterioration Scale.
JMIR Form Res 2025;9:e56586
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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).
JMIR Cardio 2025;9:e67956
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Evaluating User Experience and Satisfaction in a Concussion Rehabilitation App: Usability Study
JMIR Form Res 2025;9:e67275
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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).
JMIR Hum Factors 2025;12:e69873
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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].
JMIR AI 2025;4:e67144
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