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

Use and User Demographics of mHealth (494) Mobile Health (mhealth) (5035) mHealth for Wellness, Behavior Change and Prevention (4200) Behavior Change (1053) Prevention and Health Promotion (2196)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71625, first published .
Person using phone and tablet for weight management app feedback

Health Motivation as a Predictor of mHealth Engagement Across BMI: Cross-Sectional Survey

Health Motivation as a Predictor of mHealth Engagement Across BMI: Cross-Sectional Survey

Authors of this article:

Shao-Hsuan Chang1, 2 Author Orcid Image ;   Lung-Kun Yeh2, 3 Author Orcid Image ;   Daishi Chen4 Author Orcid Image ;   Kae-Kuen Hu5 Author Orcid Image ;   Mei-Ching Yu6 Author Orcid Image ;   Ching-Mao Chang7, 8 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Shokr E. Effectiveness of artificial intelligence mobile app-guided prevention and treatment protocols on cancer patients and their impact on healthcare workers’ competence. BMC Medical Informatics and Decision Making 2026;26(1) View
  2. 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