Mobile Health Behavior Change Techniques to Support Treatment Adherence and Self-Management of Cystic Fibrosis and Similar Conditions Involving Complex Medical Regimens: A Systematic Review (Preprint)
Authors: Eaton Cyd , 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 , Sathe Meghana , Sawicki Gregory , Snell Carolyn , Riekert Kristin 
Published: June 2023

BACKGROUND

People with rare diseases want to use technology to support their disease self-management but are seldom the target population for technology developers. Cystic fibrosis (CF) is a rare, multisystemic medical condition and CF management is complex and burdensome for many people with CF. People with CF have noted that existing apps do not provide the necessary functionality to address their unique CF management needs. mHealth solutions may facilitate self-management and adherence behaviors in CF but, because it is a rare disease, little is known about which mHealth-based behavior change techniques are most effective. Examining other chronic medical conditions’ mHealth literature may inform and accelerate the development of an effective CF mHealth intervention for CF management.

OBJECTIVE

To identify mHealth-based behavior change techniques to incorporate in an effective mHealth adherence and self-management intervention for people with CF by systematically reviewing the literature in CF and other chronic medical conditions with similarities to CF.

METHODS

A registered systematic review was conducted to identify published evaluations of mHealth adherence and self-management interventions for CF and chronic medical conditions similar to CF. Methodological characteristics and behavior change techniques in each study were extracted using a standard data collection form.

RESULTS

122 studies were reviewed; only 6 included people with CF. The CF studies had small samples and were primarily descriptive. mHealth interventions rated as having a positive outcome on adherence/self-management used more behavior change techniques (M=4.95, SD=2.56) compared to interventions with no impact on outcomes (M=3.57, SD=1.95) or used >1 outcome measure or analytic approach (M=3.90, SD=1.93; P=.02). The following behavior change techniques were associated with positive outcomes: Self-monitoring outcomes of behavior (66%), feedback on outcomes of behavior (58%), self-monitoring of behavior (58%), feedback on behavior (49%), credible source (41%), and goal setting (behavior; 24%). In adult-only samples, prompts/cues were associated with positive outcomes (76%). In adolescent/young adult samples, information about health consequences (25%), problem-solving (25%), and material reward-behavior (50%) were associated with positive outcomes.

CONCLUSIONS

To support CF adherence and self-management, mHealth tools should purposefully incorporate effective and developmentally appropriate behavior change techniques. Researchers investigating behavior change interventions for other rare disease should consider using our systematic review approach to methodically incorporate literature from other medical conditions with complex self-management needs and speed up the development of much needed mHealth interventions for their target populations. Future CF mHealth researchers should empirically evaluate the efficacy of mHealth behavior change techniques identified in this review.

CLINICALTRIAL

PROSPERO CRD42021224407