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Prescriptive Predictors of Mindfulness Ecological Momentary Intervention for Social Anxiety Disorder: Machine Learning Analysis of Randomized Controlled Trial Data

Prescriptive Predictors of Mindfulness Ecological Momentary Intervention for Social Anxiety Disorder: Machine Learning Analysis of Randomized Controlled Trial Data

Instead of relying on a conventional training-test set or nonnested k-fold cross-validation approaches, we used nested 10-fold cross-validation (10 F-CV) with 10 repetitions and grid-search [127]. Nested 10 F-CV provides more robust performance estimates for small sample sizes, maximizes data utilization, minimizes bias, and controls for overfitting more than the split train-test approach [128,129]. It subsets the dataset into 10 outer and 10 inner folds [130].

Nur Hani Zainal, Hui Han Tan, Ryan Yee Shiun Hong, Michelle Gayle Newman

JMIR Ment Health 2025;12:e67210

Correction: Use and Engagement With Low-Intensity Cognitive Behavioral Therapy Techniques Used Within an App to Support Worry Management: Content Analysis of Log Data

Correction: Use and Engagement With Low-Intensity Cognitive Behavioral Therapy Techniques Used Within an App to Support Worry Management: Content Analysis of Log Data

The authorship was previously published as: Paul Farrand1,2*, Ph D; Patrick J Raue3*, Ph D; Earlise Ward4*, Ph D; Dean Repper5*, MSc; Patricia Areán3*, Ph D The following author, equal contribution tag, ORCID, and associated affiliation have been added in the fifth position of the authorship: Jonathon Baker6*, MA (ORCID 0009 0000 9923 5042) Iona Mind Inc, Romford, United Kingdom The Authors' Contributions was revised from: PF, PA, and PJR conceptualized and designed the project with EW and DR providing theoretical

Paul Farrand, Patrick J Raue, Earlise Ward, Dean Repper, Jonathan Baker, Patricia Areán

JMIR Mhealth Uhealth 2025;13:e76573

Clinical Efficacy and Safety of the Herbal Prescription, HH333, in Preventing Recurrent Stroke in Patients With Ischemic Stroke Induced by Small-Vessel Disease: Protocol for Multicenter, Double-Blind, Randomized, Prospective, Pilot Clinical Trial

Clinical Efficacy and Safety of the Herbal Prescription, HH333, in Preventing Recurrent Stroke in Patients With Ischemic Stroke Induced by Small-Vessel Disease: Protocol for Multicenter, Double-Blind, Randomized, Prospective, Pilot Clinical Trial

The total scores on the Korean National Institutes of Health Stroke Scale (K-NIHSS), modified Rankin Scale (m RS), Korean Modified Barthel Index (K-m BI), and Korean Montreal Cognitive Assessment (K-Mo CA) will also be measured as exploratory endpoints at the same time as the secondary efficacy endpoints. The safety of HH333 will be assessed based on the presence of adverse events at the same time as the primary efficacy endpoints.

Han-Gyul Lee, Seungwon Kwon, Woo-Sang Jung, Sang-Kwan Moon, Cheol-Hyun Kim, Dong-Jun Choi

JMIR Res Protoc 2025;14:e70953

Epidemic Trends and Spatial Distribution Characteristics of Hepatitis B in China: Surveillance Study

Epidemic Trends and Spatial Distribution Characteristics of Hepatitis B in China: Surveillance Study

The formula for calculating the Moran’s I is as follows: In this formula, the incidence rate is represented by λ, the average incidence rate is represented by X, and the matrix of spatial weights is denoted as Wij, representing the proximity relationship between region i and region j. Local Moran’s I was used to conduct a local analysis of the distribution of hepatitis B cases in each region, and the local autocorrelation type was determined by visualizing the local autocorrelation map.

Xiaoxue Li, Jie Liang, Lanqing Ma, Shijie Shen, Xueying Han, Tao Sun, Heng Guo

JMIR Public Health Surveill 2025;11:e70888

Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation

Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation

WSens evaluates overall accuracy by considering the RSens of each region and its corresponding weight in the data set, which is calculated as follows: where k denotes the total number of regions, i denotes the index corresponding to each region, N denotes the total number of regions in the data set, and Ni denotes the count of instances for the i-th region.

Yaxi Luo, Meng Jiao, Neel Fotedar, Jun-En Ding, Ioannis Karakis, Vikram R Rao, Melissa Asmar, Xiaochen Xian, Orwa Aboud, Yuxin Wen, Jack J Lin, Fang-Ming Hung, Hai Sun, Felix Rosenow, Feng Liu

J Med Internet Res 2025;27:e69173