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

Evaluation and Research Methodology for mHealth (261) mHealth for Wellness, Behavior Change and Prevention (3476) Machine Learning (2298) Digital Biomarkers and Digital Phenotyping (339) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (709) Data Science (406)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70987, first published .
Cluster-Based Predictive Modeling of User Ratings for Physical Activity Apps Using Mobile App Rating Scale (MARS) Dimensions: Model Development and Validation

Cluster-Based Predictive Modeling of User Ratings for Physical Activity Apps Using Mobile App Rating Scale (MARS) Dimensions: Model Development and Validation

Cluster-Based Predictive Modeling of User Ratings for Physical Activity Apps Using Mobile App Rating Scale (MARS) Dimensions: Model Development and Validation

Authors of this article:

Ayush Bhattacharya1 Author Orcid Image ;   Jose Fernando Florez-Arango1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Asante I, Norbi E, Ali M. Tracking subjective symptom improvement from patient narratives in mobile health: An observational natural language processing study. DIGITAL HEALTH 2026;12 View