Nonnormality and divergence in posttreatment alcohol use: Reexamining the Project MATCH data "another way."

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.Keywords alcohol relapse; drinking trajectories; growth mixture modeling; catastrophe modeling; self-efficacy Alcohol relapse has been described as a discrete phenomenon and as a process of behavior change (Brownell, Marlatt, Lichtenstein, & Wilson, 1986;Miller, 1996). More recent conceptualizations of relapse have defined lapse as the initial setback (e.g., a discrete drinking episode) after a period of abstention, prolapse as a return to abstinence or moderate drinking goals, and relapse as a dynamic process of continual lapses and prolapses (e.g., Donovan, 1996;Witkiewitz & Marlatt, 2004). The characterization of the alcohol relapse process as a dynamic and "complex" phenomenon has been described by several authors (Brownell et al., 1986;Hufford, Witkiewitz, Shields, Kodya, & Caruso, 2003;Marlatt, 1996;Shiffman, 1989), yet the most commonly used statistical analyses to assess alcohol treatment outcomes (e.g., multiple regression, repeated measures analysis of variance [ NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript complexity in the observed data. For example, the use of a continuous linear model a unit change in some risk factor predicts a unit change in drinking behavior, but in reality an ostensibly insignificant change in risk often corresponds with sudden changes in drinking. Drawing from this clinical and empirical observation, we propose that the alcohol relapse process is best characterized as a nonlinear dynamical system, and we evaluate two methods for testing dynamical models of alcohol consumption following treatment.The complexity of the alcohol relapse process is easily observed by examining the betwee...

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