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

• Published in: JMIR mHealth and uHealth 2024-05, Vol.12, p.e49024-e49024
• Main Authors: Eaton, Cyd K, McWilliams, Emma, Yablon, Dana, Kesim, Irem, Ge, Renee, Mirus, Karissa, Sconiers, Takeera, Donkoh, Alfred, Lawrence, Melanie, George, Cynthia, Morrison, Mary Leigh, Muther, Emily, Oates, Gabriela R, Sathe, Meghana, Sawicki, Gregory S, Snell, Carolyn, Riekert, Kristin
• Format: Article
• Language: English
• Subjects: Behavior; Behavior Therapy - instrumentation; Behavior Therapy - methods; Behavior Therapy - standards; Behavior Therapy - statistics & numerical data; Bias; Chronic Disease - psychology; Chronic Disease - therapy; Chronic illnesses; Cystic fibrosis; Exercise; Humans; Intervention; Patient compliance; Physical fitness; Rare diseases; Self-Management - methods; Self-Management - psychology; Self-Management - statistics & numerical data; Smartphones; Systematic review; Taxonomy; Telemedicine; Telemedicine - methods; Telemedicine - standards; Telemedicine - statistics & numerical data; Text messaging; Treatment Adherence and Compliance - psychology; Treatment Adherence and Compliance - statistics & numerical data
• ISSN: 2291-5222; 2291-5222
• DOI: 10.2196/49024

Mobile 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. This 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. A 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. A 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=.02). The following BCTs were associated with positive outcomes: self-monitoring outcomes of behavior (39/59, 66%), feedback on outcomes of behavior (34/59, 58%), self-monitoring of behavior (34/59, 58%), feedback on behavior (29/59, 49%), credible source (24/59, 41%), and goal setting (behavior; 14/59, 24%). In adult-only samples, prompts and cues were associated with positive outcomes (34/45, 76%). In adolescent and young adult samples, information about health consequences (1/4, 25%), problem-solving (1/4, 25%), and material reward (behavior; 2/4, 50%) were associated with positive outcomes. In interventions explicitly targeting medicine taking, prompts and cues (2