JMIR mHealth and uHealth (May 2024)

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

  • Cyd K Eaton,
  • Emma McWilliams,
  • Dana Yablon,
  • Irem Kesim,
  • Renee Ge,
  • Karissa Mirus,
  • Takeera Sconiers,
  • Alfred Donkoh,
  • Melanie Lawrence,
  • Cynthia George,
  • Mary Leigh Morrison,
  • Emily Muther,
  • Gabriela R Oates,
  • Meghana Sathe,
  • Gregory S Sawicki,
  • Carolyn Snell,
  • Kristin Riekert

DOI
https://doi.org/10.2196/49024
Journal volume & issue
Vol. 12
pp. e49024 – e49024

Abstract

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Abstract BackgroundMobile health (mHealth) interventions have immense potential to support disease self-management for people with complex medical conditions following treatment regimens that involve taking medicine and other self-management activities. However, there is no consensus on what discrete behavior change techniques (BCTs) should be used in an effective adherence and self-management–promoting mHealth solution for any chronic illness. Reviewing the extant literature to identify effective, cross-cutting BCTs in mHealth interventions for adherence and self-management promotion could help accelerate the development, evaluation, and dissemination of behavior change interventions with potential generalizability across complex medical conditions. ObjectiveThis study aimed to identify cross-cutting, mHealth-based BCTs to incorporate into effective mHealth adherence and self-management interventions for people with complex medical conditions, by systematically reviewing the literature across chronic medical conditions with similar adherence and self-management demands. MethodsA registered systematic review was conducted to identify published evaluations of mHealth adherence and self-management interventions for chronic medical conditions with complex adherence and self-management demands. The methodological characteristics and BCTs in each study were extracted using a standard data collection form. ResultsA total of 122 studies were reviewed; the majority involved people with type 2 diabetes (28/122, 23%), asthma (27/122, 22%), and type 1 diabetes (19/122, 16%). mHealth interventions rated as having a positive outcome on adherence and self-management used more BCTs (mean 4.95, SD 2.56) than interventions with no impact on outcomes (mean 3.57, SD 1.95) or those that used >1 outcome measure or analytic approach (mean 3.90, SD 1.93; P ConclusionsTo support adherence and self-management in people with complex medical conditions, mHealth tools should purposefully incorporate effective and developmentally appropriate BCTs. A cross-cutting approach to BCT selection could accelerate the development of much-needed mHealth interventions for target populations, although mHealth intervention developers should continue to consider the unique needs of the target population when designing these tools.