using social cognitive theory to predict medication compliance behavior in patients with depression in southern united states in 2016 in a cross-sectional study

Introduction: depression is a major public health issue. one of the concerns in depression research and practice pertains to non-compliance to prescribed medications. the purpose of the study was to predict compliance with medication use for patients with depression using social cognitive theory (sct). based on this study it was envisaged that recommendations for interventions to enhance compliance for medication use could be developed for patients with depression. methods: the study was conducted using cross sectional design (n=148) in southern united states with a convenience sample of clinic-based depression patients with a 37-item valid and reliable questionnaire. sample size was calculated to be 148 using g*power (five predictors with a 0.80 power at the 0.05 alpha level and an estimated effect size of 0.10 with an inflation by 10% for missing data). social cognitive theory constructs of expectations, self-efficacy and self-efficacy in overcoming barriers, self-control, and environment were reified. data were analyzed using multiple linear regression and multiple logistic regression analyses. results: self-control for taking medication for depression (p=0.04), expectations for taking medication for depression (p=0.025), age (p<0.0001) and race (p=0.04) were significantly related to intent for taking medication for depression (adjusted r² = 0.183). in race, blacks had lower intent to take medication for depression. conclusion: social cognitive theory is weakly predictive with low explained variance for taking medication for depression. it needs to be bolstered by newer theories like integrative model or multi-theory model of health behavior change for designing educational interventions aimed at enhancing compliance to medication for depression.