Background: Few studies have focused on behavioral changes that occur prior to entering treatment for an alcohol use disorder (AUD). In 2 studies (Psychol Addict Behav, 27, 2013, 1159 J Stud Alcohol, 66, 2005, 369), pretreatment reductions in alcohol use were associated with better treatment outcomes. Identifying patterns of pretreatment change has the potential to inform clinical decision making.Methods: This study sought to identify pretreatment change trajectories in individuals seeking outpatient treatment for AUD (N = 205) using finite mixture modeling based on changes in number of days abstinent per week (NDA).Results: The analysis identified 3 pretreatment trajectory classes. Class 1 (High Abstinence-Minimal Increase; HA-MI) (n = 64; 31.2%) reported a high level of pretreatment NDA with minimal change during an 8-week pretreatment interval. Class 2 (Low Abstinence-Steady Increase; LA-SI) (n = 73; 35.6%) reported a low level of pretreatment NDA followed by a steady increase beginning 2 weeks prior to the phone screen. Class 3 (Nonabstinent-Accelerated Increase; NA-AI) (n = 68; 33.2%) reported no or very low levels of pretreatment NDA but demonstrated an increase following the phone screen. With regard to within-treatment change, Class 1 demonstrated the least and Class 3 demonstrated the most change in NDA. From baseline to 6-month follow-up, Class 3 added 2.31 abstinent days per week, Class 2 added 0.69 days, and Class 1 added 0.63 days. The increase in NDA for Class 3 was significantly different from the other 2 classes; however, Class 3 reported fewer overall days abstinent at 6-month follow-up.Conclusions: Study results have clinical and research implications including recommended changes to treatment protocols and research designs. Understanding the impact of pretreatment trajectories of alcohol use on within-treatment and posttreatment outcomes may provide important information about adapting treatment to increase efficiency and effectiveness.

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Purpose: Patients of substance use disorder (SUD), who successfully complete the treatment programs recommended by their therapists, have better health outcomes than the vast majority who drop out in the middle. We investigated the contribution of race and gender of both patients and therapists to address the cause of treatment noncompletion and gaps in knowledge. Method: Data collected from 11 SUD treatment outpatient programs, comprising 2,230 patients and 69 therapists, were analyzed to understand the effect of therapist–patient profile matching on treatment completion success rate. Results: Of the overall completion rate of 23%, White-male therapists had the highest rate (ranging from 20.4% to 50.0%) followed by White-female therapists (13.9% and 31.2%) dependent on patients’ race or gender. Non-White female and male therapists alike had varied but lesser completion rate. Discussion: Our studies recommend research and practice implementing performance-based practice measures with appropriate patient–therapist matching for better SUD-treatment outcomes.

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