Health behavior and disease self-management indicators in patients with cardiovascular diseases using a health app: Findings from an RCT - Sonia Lippke; Luisa Korte; Vinayak Anand Kumar; Andreas Fach; Tiara Ratz (AIMS Public Health)
BackgroundPrevention of acute cardiovascular events in patients with cardiovascular disease (CVD) requires promoting health-protective behaviors (e.g., physical activity) and reducing health-compromising behaviors (e.g., sitting). Digital interventions addressing health behavior offer great potential. Based on a multiple behavior change theory, an intervention in the form of a digital health application (app) was evaluated in a pilot trial, testing the following hypotheses (H): H1: Health behaviors (physical activity, sitting) and disease self-management (self-care maintenance, self-care confidence) are closely related; H2: changes in health behaviors and disease self-management indicators over time (T0 to T1) are more pronounced in the intervention group (IG, app users) than in the control group (CG); H3: within the IG, changes in systolic and diastolic blood pressure indicate a positive trajectory.MethodsA 12-week randomized controlled trial (RCT) was conducted with two measurement points. The IG received an app addressing self-management and health behavior change. A total of N = 40 CVD patients were randomized equally to the CG (45% women; mean age = 60.6 years) and the IG (35% women; mean age = 61.5 years).ResultsFindings support H1 with correlations between behaviors (r = −0.66–0.79) and disease self-management (r = −0.06–0.70). H2 was also partially supported, with significant improvements over time in self-management indicators, especially self-care maintenance, in the IG (Eta² = 0.35; p < 0.001). H3 could not be confirmed as no significant changes were found.ConclusionsThis study provides evidence that an app addressing different behavior change techniques (BCTs) can help to manage CVD by promoting health-protective behaviors and preventing health-compromising behaviors. Taking different behaviors into account may increase the effectiveness of behavioral intervention, thereby improving individual and public health. Replications with larger samples and more objective measures are needed.