Treatment burden as a predictor of self-management adherence within the primary care population.

Purpose: We aimed to (1) describe the amount of treatment burden experienced in the primary care population diagnosed with chronic conditions and (2) examine if cumulative and task-specific treatment burden were predictors of medication, exercise, and dietary adherence in patients diagnosed with chronic conditions.

Design: We conducted a prospective, descriptive, cross-sectional study.

Methods: We enrolled 149 men and women from a single primary care clinic. Participants completed self-report surveys with data collected between September 2019 and December 2019. Our primary statistical analyses consisted of multivariate regression modeling.

Results: The sample experience a moderate amount of treatment burden (M = 38.22; SD = 31.83). We found strong, negative correlations between both cumulative and task-specific burden in relation to medication, exercise, and dietary adherence (p < .001). Significant multivariate models (p < .001), controlling for sample demographics, demonstrated cumulative treatment burden predicted medication adherence, whereas task-specific burden predicted medication, exercise, and dietary adherence outcomes, with model effect sizes ranging from moderate (0.20) to large (0.54).

Conclusions: Results demonstrate higher levels of cumulative and task-specific treatment burden predict medication, exercise, and dietary adherence within a sample diagnosed with various chronic conditions. These findings indicate the potential for using treatment burden screening in the clinical setting to identify individuals at risk for poor self-management adherence. Treatment burden screening also enables the provider to determine areas of high burden affecting self-management adherence in order to design an effective treatment plan using targeted interventions, resources, or education to reduce patient burden in order to improve adherence.