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

Wearables and MHealth Reviews (310) Medication Adherence (140) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) mHealth for Treatment Adherence (467)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49024, first published .
Cross-Cutting mHealth Behavior Change Techniques to Support Treatment Adherence and Self-Management of Complex Medical Conditions: Systematic Review

Cross-Cutting mHealth Behavior Change Techniques to Support Treatment Adherence and Self-Management of Complex Medical Conditions: Systematic Review

Cross-Cutting mHealth Behavior Change Techniques to Support Treatment Adherence and Self-Management of Complex Medical Conditions: Systematic Review

Authors of this article:

Cyd K Eaton1 Author Orcid Image ;   Emma McWilliams2 Author Orcid Image ;   Dana Yablon3 Author Orcid Image ;   Irem Kesim3 Author Orcid Image ;   Renee Ge3 Author Orcid Image ;   Karissa Mirus3 Author Orcid Image ;   Takeera Sconiers3 Author Orcid Image ;   Alfred Donkoh3 Author Orcid Image ;   Melanie Lawrence4 Author Orcid Image ;   Cynthia George5 Author Orcid Image ;   Mary Leigh Morrison4 Author Orcid Image ;   Emily Muther6 Author Orcid Image ;   Gabriela R Oates7 Author Orcid Image ;   Meghana Sathe8 Author Orcid Image ;   Gregory S Sawicki2 Author Orcid Image ;   Carolyn Snell2 Author Orcid Image ;   Kristin Riekert3 Author Orcid Image
Article Authors Cited by (8) Tweetations (3) Metrics

Journals

  1. Ekenberg M, Landin F, Wettermark B. A Cross-Sectional Study Identifying Medication Adherence Technologies (MATech) in Sweden Using Behavior Change Techniques. Patient Preference and Adherence 2024;Volume 18:2281 View
  2. Nagino K, Sung J, Midorikawa-Inomata A, Akasaki Y, Adachi T, Ebihara N, Fukuda K, Fukushima A, Fujio K, Okumura Y, Eguchi A, Fujimoto K, Shokirova H, Yee A, Morooka Y, Huang T, Hirosawa K, Nakao S, Kobayashi H, Inomata T. Minimal Clinically Important Differences With the Outcomes of the App-Based Japanese Allergic Conjunctival Diseases Quality of Life Questionnaire: Cross-Sectional Observational Study. JMIR Formative Research 2024;8:e60731 View
  3. Ganjali R, Ghorban Sabbagh M, Eslami S. A patient-centered interactive voice response system for supporting self-management in kidney transplantation: design and field testing. Frontiers in Digital Health 2025;6 View
  4. Kirchner-Krath J, Schmidt-Kraepelin M, Schmähl K, Schütz C, Morschheuser B, Sunyaev A. Behavior Change Support Systems for Self-Treating Procrastination: Systematic Search in App Stores and Analysis of Motivational Design Archetypes. Journal of Medical Internet Research 2025;27:e65214 View
  5. Sivakumar B, Ricupero M, Mahajan A, Jefferson K, Wenger J, Code J, Theodorou A, Arcand J. A mobile app intervention to support nutrition education for heart failure management: co-design, development and user-testing. BMC Nutrition 2025;11(1) View
  6. Pan Z, Li X, Yan Q, Zeng N. Application of Behavioral Science in Digital Therapeutics for Individuals With Prediabetes: Scoping Review. Journal of Medical Internet Research 2025;27:e78891 View
  7. Pu B, Huang K. Modeling the path to digital health intention: the mediating role of system expectation and health beliefs. Frontiers in Public Health 2025;13 View
  8. Sobrinho A, Rodrigues G, Oliveira G, Oliveira Gomes G, Júnior C. Everyday Digital Support to Promote Health and Literacy Among Older Adults: A 14-Week Randomized Digital Pilot Trial by Engagement Level (Preprint). JMIR Formative Research 2025 View