Effectiveness of behavior change techniques in eHealth-based cardiac rehabilitation in patients with coronary artery disease: A systematic review

Background: Participation in cardiac rehabilitation (CR) reduces risk of cardiovascular mortality, improves functional capacity and enhances quality of life in patients with coronary artery disease (CAD). eHealth-based CR can increase participation rates, but research into effective components is necessary. The objective of this systematic review was to identify effective behavior change techniques (BCTs) used in eHealth-based CR interventions. Methods: A search of four databases (CINAHL, PubMed, PsychINFO, and MEDLINE) was conducted until January 10, 2023. Randomized controlled trials investigating eHealth-based interventions for patients with CAD were included. Risk of bias was assessed using the Effective Public Healthcare Practice Project tool. BCTs were coded following the Behavior Change Taxonomy. A best-evidence synthesis was conducted to determine the effectiveness of BCTs, with ratings ranging from A (strong evidence indicating either a positive effect (+) or no effect (-)) to D (no data collected). Results: A total of 88 studies (25,007 participants) met the eligibility criteria. The interventions in these studies used 31 different BCTs. The most common BCTs were instructions on how to perform the behavior (k = 86), social support (k = 69) and and information about health consequences (k = 56). The evidence for action planning was rated as A+ for medication adherence and diet. Conversely, for systematically decreasing the number of prompts/cues sent during an intervention, the evidence was rated as A- for physical activity, medication adherence and smoking cessation. The evidence for feedback on behavior was rated as A+ for medication adherence and A- for smoking cessation. Conclusions: Action planning is effective as a BCT in eHealth-based CR, whereas reducing prompts/cues is not. Feedback on behavior may, depending on the behavior targeted, exert both positive and no effect, suggesting that BCT-behavior matching is important to optimize effectiveness of eHealth-based CR.