The Identification of Pretreatment Trajectories of Alcohol Use and Their Relationship to Treatment Outcome in Men and Women With Alcohol Use Disorder. (5th November 2019)

• Record Type: Journal Article
• Authors: Stasiewicz, Paul R.; Bradizza, Clara M.; Ruszczyk, Melanie U.; Lucke, Joseph F.; Zhao, Junru; Linn, Braden; Slosman, Kim S.; Dermen, Kurt H.
• Is Part Of: Alcoholism. Volume 43:Number 12(2019)
• Page Start: 2637
• Page End: 2648
• Publication Date: 2019-11-05
• Subjects: Pretreatment Change -- Alcohol Use Disorder -- Alcohol -- Treatment -- Behavior Change; Alcoholism -- Periodicals; Alcoholism -- Periodicals; Alcoolisme; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.861005
• DOI: 10.1111/acer.14216
• Languages: English
• ISSNs: 0145-6008

Abstract

Abstract : 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. Abstract : A subset of individuals entering treatment for AUD change their drinking prior to the first treatment session. Using finite mixture modeling we identified three pretreatment trajectory classes. All classes demonstrated pretreatment change in number of days abstinent per week, but differed on the amount of change, when the change began, and rate of change. This trajectory classification was predictive of within‐treatment change in drinking and post‐treatment drinking outcomes. Findings have implications for tailoring treatments and analyses of AUD clinical trials.