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

Evaluation and Research Methodology for mHealth (251) mHealth for Wellness, Behavior Change and Prevention (3391) Digital Biomarkers and Digital Phenotyping (304) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (671) Data Science (374) Machine Learning (2173)

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
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Ayush Bhattacharya   1 , MS ;   Jose Fernando Florez-Arango   1 , MSc, MD, PhD

1 Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States

Corresponding Author:

  • Jose Fernando Florez-Arango, MSc, MD, PhD
  • Department of Population Health Sciences
  • Weill Cornell Medicine
  • 575 Lexington Ave, Room FP 1025
  • New York, NY 10022
  • United States
  • Phone: 1 6469622435
  • Email: jff4001@med.cornell.edu