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Objective: The purpose of this study was to examine the problem of attrition in the treatment of substance use disorders. The authors analyzed the retention rates of 191 participants who were assigned to an episode of substance abuse treatment. Two types of attrition, the first due to participants withdrawing prematurely from treatment and the second due to participants failing to complete a posttest survey, were investigated. Relationships were found between severity of the substance use disorder and a tendency to withdraw prematurely from treatment. Though the study is far from perfect, the authors strongly believe that it confirms the importance of a rigorous alliance between therapist and client, especially for those likely to disengage early. Method: Participants provided a self-report assessment of their substance use patterns on a pretest survey, and also received a clinical assessment of psychosocial functioning. The scores from these two instruments were used to calculate an index quantifying the severity of substance use disorders. When scale data began to suggest that the severity of the disorder correlated with retention rates, the authors conducted more complex statistical analyses to determine which elements of the participants’ profile were most likely to predict attrition. Results: A significant finding of the study is that attrition can be predicted with some certainty. When the probability of premature disengagement is predicted, decisions can be made to direct participants to supportive environments that foster therapeutic alliance and increase readiness for treatment. In spite of being a reliable predictor of attrition, however, these variables explained only about 27% of variance in therapy outcomes. Conclusion: Recommendations for future research are made, including the need to highlight the importance of contextual factors, such as therapeutic alliance and motivational interviewing, on client retention. Future research could identify new predictors, and raise questions about others. Prospective studies should be theory-driven, should utilize measures of known reliability and validity, and should employ statistical methods appropriate to the hypothesis or theory under investigation.
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