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Digital Mental Health Interventions for Young People Aged 16-25 Years: Scoping Review

Digital Mental Health Interventions for Young People Aged 16-25 Years: Scoping Review

Data were analyzed in R using R version 4.3.2 (R Project for Statistical Computing). Summaries were computed for each study, including the country of publication, research method, and year of publication. Summary statistics were calculated for the length of studies in weeks and the follow-up length for studies that included a follow-up. Studies were labeled as including a follow-up if outcome measures were collected on any date after the poststudy outcomes were obtained.

Courtney Potts, Carmen Kealy, Jamie M McNulty, Alba Madrid-Cagigal, Thomas Wilson, Maurice D Mulvenna, Siobhan O'Neill, Gary Donohoe, Margaret M Barry

J Med Internet Res 2025;27:e72892

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation

Profile accuracy: H=high, M=medium, L=low. AUC: area under the curve; M: mixed; N: negative; P: positive; TPR: true-positive rate; TNR: true-negative rate. The above summary (Figure 2) presents results for all pilot study patients to show performance and overall results. However, the individual prognostic patient profile as used in IMPT clinical assessment provides clearly presented summary results for each patient.

Fredrick Zmudzki, Rob J E M Smeets, Jan S Groenewegen, Erik van der Graaff

JMIR Rehabil Assist Technol 2025;12:e65890

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Analyses were done with R (v4.2.2, R Foundation for Statistical Computing). This study was approved by the University of Otago Human Ethics Committee (reference: HD22/064). Participants were users of a commercially available app who consented to their anonymized data being used for research purposes through the app’s privacy policy. All data were deidentified before analysis. No compensation was provided for participation.

Michelle R Jospe, Martin Kendall, Susan M Schembre, Melyssa Roy

JMIR Form Res 2025;9:e65368