The theory of planned behavior (TPB) states that behavioral intention is the best predictor of actual behavior change. However, intention explains only a portion of the variance in behavior. Of specific interest is the question of which moderating or mediating variables can be leveraged to aid health promotion interventions utilizing the tenets of behavioral economics (delay discounting and commitment contracts) in the intention–behavior pathway. Impulsivity has been postulated to fill this role and may be applied to multiple behaviors. We aim to determine if impulsivity moderates the association between intention and actual behavior in the TPB, to discover what other variables may moderate or mediate this association, and to apply the findings to future studies in the field of behavioral economics. To this end, a systematic review was conducted using the PubMed, PsychINFO, and Embase online databases. Eligible studies in peer-reviewed journals published prior to November 2021 were selected. Thirty-three studies were included in the final review, examining physical activity, diet, preventive health, mental health, addiction, and medication adherence behaviors. Three main concepts emerged: (1) impulsivity moderates the association between intention and behavior change; (2) self-efficacy moderates the association between intention and behavior change; and (3) planning and self-efficacy contribute to moderated mediation. This review demonstrates a gap in the literature regarding the application of the TPB to the intention–behavior pathway for health behaviors. Future studies in behavioral economics may leverage the variables of impulsivity, self-efficacy, and planning to predict follow-through in this area and to develop targeted change initiatives.
Background: Medication nonadherence affects health care costs, morbidity, and mortality. Concepts from behavioral economics can guide the development of interventions to improve medication adherence. Objective: To measure the relative effectiveness of 2 behavioral economic-based incentive structures to improve medication adherence. Methods: This randomized controlled trial compared adherence among participants taking antihypertensive or antihyperlipidemic medications randomized to usual care (UC), guaranteed pay-out (GPO) incentives, or lottery incentives. Daily adherence was measured over a 90-day period using electronic caps (Medication Event Monitoring System [MEMS]). The GPO group received $30 up-front in a virtual account, with $0.50 deducted for each missed dose. Lottery group participants were eligible for a weekly $50 drawing, but only if they had taken their medication as prescribed all week. An electronic survey assessed self-reported adherence. Statistical analysis included descriptive statistics, paired t tests, ANOVA, and Pearson’s correlations. Results: In all, 36 participants were randomized (UC, n = 11; GPO, n = 14; lottery, n = 11). Mean percentage (±SD) of days adherent during the incentive period was highest in the lottery group (96% ± 5%), followed by the GPO group (94% ± 9%) and the UC group (94% ± 9%). There were no statistically significant differences among groups (P > 0.05). MEMS-measured adherence was not significantly correlated with a patient’s self-reported adherence (P > 0.05) at baseline but was correlated at 90-day follow-up (P < 0.001). Conclusions: Although no statistically significant differences in adherence were demonstrated in this small sample of highly adherent participants, larger studies in a more diverse population or with other medications might show otherwise.