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This paper is in the following e-collection/theme issue:

Anxiety and Stress Disorders (1608) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3201) Machine Learning (3165) Ecological Momentary Assessment (EMA) (506)

Published on in Vol 12 (2025)

This is a member publication of National University of Singapore

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67210, first published .
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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

Authors of this article:

Nur Hani Zainal1 Author Orcid Image ;   Hui Han Tan1 Author Orcid Image ;   Ryan Yee Shiun Hong1 Author Orcid Image ;   Michelle Gayle Newman2 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Basterfield C, Newman M. Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder. Journal of Anxiety Disorders 2025;110:102978 View
  2. Ahn G, Li C, Liang A, Choi W, Ahn S, Roberts C, Gabrieli J. Large Language Model Few-Shot Learning for Predicting Individual Treatment Response to Smartphone-Based Mindfulness in Autistic Adults With Anxiety: Secondary Analysis of a Randomized Controlled Trial. JMIR AI 2026;5:e89054 View
  3. Herrera L, Roca P. Toward precision mindfulness: Predicting mindfulness outcomes after Mindfulness-Based Stress Reduction using interpretable machine learning. Behaviour Research and Therapy 2026:105140 View

Conference Proceedings

  1. Chahar R, Dubey A. 2025 5th International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT). Mental Health Disorder Classification using RF-PSO: a Hybrid Machine Learning Approach View