Background Medication adherence is frequently suboptimal in adults with chronic diseases, resulting in negative consequences. Motivational interviewing (MI) is a collaborative conversational style for strengthening a person's motivation and commitment… Click to show full abstract
Background Medication adherence is frequently suboptimal in adults with chronic diseases, resulting in negative consequences. Motivational interviewing (MI) is a collaborative conversational style for strengthening a person's motivation and commitment to change. We aimed to assess whether MI interventions are effective to enhance medication adherence in adults with chronic diseases and to explore the effect of individual MI intervention characteristics. Methods We searched electronic databases and reference lists of relevant articles to find randomized controlled trials (RCTs) that assessed MI intervention effectiveness on medication adherence in adults with chronic diseases. A random-effects model was used to estimate a pooled MI intervention effect size and its heterogeneity (I 2 ). We also explored the effects of individual MI characteristics on MI intervention effect size using a meta-regression with linear mixed model. Results : Nineteen RCTs were identified, and 16 were included in the meta-analysis. The pooled MI intervention effect size was 0.12 [95% confidence interval (CI) = (0.05, 0.20), I 2 = 1%]. Interventions that were based on MI only [β = 0.183, 95% CI = (0.004, 0.362)] or those in which interventionists were coached during intervention implementation [β = 0.465, 95% CI = (0.028, 0.902)] were the most effective. MI interventions that were delivered solely face to face were more effective than those that were delivered solely by phone [β = 0.270, 95% CI = (0.041, 0.498)]. Conclusions This synthesis of RCTs suggests that MI interventions might be effective at enhancing of medication adherence in adults treated for chronic diseases. Further research is however warranted, as the observed intervention effect size was small.
               
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