Translating basic behavioral and social science research to clinical application: the EVOLVE mixed methods approach

OBJECTIVE: To describe a mixed-methods approach to develop and test a basic behavioral science-informed intervention to motivate behavior change in 3 high-risk clinical populations. Our theoretically derived intervention comprised a combination of positive affect and self-affirmation (PA/SA), which we applied to 3 clinical chronic disease populations.

METHOD: We employed a sequential mixed methods model (EVOLVE) to design and test the PA/SA intervention in order to increase physical activity in people with coronary artery disease (post-percutaneous coronary intervention [PCI]) or asthma (ASM) and to improve medication adherence in African Americans with hypertension (HTN). In an initial qualitative phase, we explored participant values and beliefs. We next pilot tested and refined the intervention and then conducted 3 randomized controlled trials with parallel study design. Participants were randomized to combined PA/SA versus an informational control and were followed bimonthly for 12 months, assessing for health behaviors and interval medical events.

RESULTS: Over 4.5 years, we enrolled 1,056 participants. Changes were sequentially made to the intervention during the qualitative and pilot phases. The 3 randomized controlled trials enrolled 242 participants who had undergone PCI, 258 with ASM, and 256 with HTN (n = 756). Overall, 45.1% of PA/SA participants versus 33.6% of informational control participants achieved successful behavior change (p = .001). In multivariate analysis, PA/SA intervention remained a significant predictor of achieving behavior change (p < .002, odds ratio = 1.66), 95% CI [1.22, 2.27], controlling for baseline negative affect, comorbidity, gender, race/ethnicity, medical events, smoking, and age.

CONCLUSIONS: The EVOLVE method is a means by which basic behavioral science research can be translated into efficacious interventions for chronic disease populations.