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

Reviews in AI (32) Artificial Intelligence (2297) Applications of AI (323)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46779, first published .
Predicting Adherence to Behavior Change Support Systems Using Machine Learning: Systematic Review

Predicting Adherence to Behavior Change Support Systems Using Machine Learning: Systematic Review

Predicting Adherence to Behavior Change Support Systems Using Machine Learning: Systematic Review

Authors of this article:

Akon Obu Ekpezu1 Author Orcid Image ;   Isaac Wiafe2 Author Orcid Image ;   Harri Oinas-Kukkonen1 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

  1. Ekpezu A, Wiafe I, Oinas-Kukkonen H. Persuasive software features as antecedents to perceived compliance within physical activity behavior change support systems. Behaviour & Information Technology 2025;44(12):2949 View
  2. Ekpezu A, Wiafe I, Atsakpo E, Oinas-Kukkonen H. Designing to promote compliance: the role of prompt types in a persuasive virtual reality environment. Behaviour & Information Technology 2025:1 View
  3. Lu H, Alhaskawi A, Dong Y, Zou X, Zhou H, Ezzi S, Kota V, Hasan Abdulla Hasan Abdulla M, Abdalbary S. Patient Autonomy in Medical Education: Navigating Ethical Challenges in the Age of Artificial Intelligence. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2024;61 View
  4. Shen Y, Wu X. Advances in implementation strategies for treatment adherence in schizophrenia: a narrative review. Frontiers in Psychiatry 2026;17 View
  5. Greco G, Petrelli A, Poli L, Fischetti F, Cataldi S. Machine Learning in Adapted Physical Activity: Clinical Applications, Monitoring, and Implementation Pathways for Personalized Exercise in Chronic Conditions: A Narrative Review. Journal of Functional Morphology and Kinesiology 2026;11(1):106 View