Abstract
Alcohol lapses are the modal outcome following treatment for alcohol use disorders, yet many alcohol researchers have encountered limited success in the prediction and prevention of relapse. One hypothesis is that lapses are unpredictable, but another possibility is the complexity of the relapse process is not captured by traditional statistical methods. Data from Project Matching Alcohol Treatments to Client Heterogeneity (Project MATCH), a multisite alcohol treatment study, were reanalyzed with 2 statistical methodologies: catastrophe and 2-part growth mixture modeling. Drawing on previous investigations of self-efficacy as a dynamic predictor of relapse, the current study revisits the self-efficacy matching hypothesis, which was not statistically supported in Project MATCH. Results from both the catastrophe and growth mixture analyses demonstrated a dynamic relationship between self-efficacy and drinking outcomes. The growth mixture analyses provided evidence in support of the original matching hypothesis: Individuals with lower self-efficacy who received cognitive behavior therapy drank far less frequently than did those with low self-efficacy who received motivational therapy. These results highlight the dynamical nature of the relapse process and the importance of the use of methodologies that accommodate this complexity when evaluating treatment outcomes.