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.
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.
Authors: Christopher W Kahler; Heather R Lachance; David R Strong; Susan E Ramsey; Peter M Monti; Richard A Brown Journal: Addict Behav Date: 2007-04-06 Impact factor: 3.913
Authors: D V Sheehan; Y Lecrubier; K H Sheehan; P Amorim; J Janavs; E Weiller; T Hergueta; R Baker; G C Dunbar Journal: J Clin Psychiatry Date: 1998 Impact factor: 4.384
Authors: Patrick McKiernan; Richard Cloud; David A Patterson; Silver Wolf Adelv Unegv Waya; Seana Golder; Karl Besel Journal: J Soc Work Pract Addict Date: 2011-08-16
Authors: Wave-Ananda Baskerville; Steven J Nieto; Diana Ho; Brandon Towns; Erica N Grodin; Caesar Li; Elizabeth Burnette; Suzanna Donato; Lara A Ray Journal: Alcohol Alcohol Date: 2021-01-04 Impact factor: 2.826
Authors: Braden K Linn; Paul R Stasiewicz; Junru Zhao; Joseph F Lucke; Melanie U Ruszczyk; Charles LaBarre; Clara M Bradizza Journal: J Stud Alcohol Drugs Date: 2021-09 Impact factor: 3.346
Authors: Erica N Grodin; Suzanna Donato; Han Du; ReJoyce Green; Spencer Bujarski; Lara A Ray Journal: Alcohol Alcohol Date: 2022-09-10 Impact factor: 3.913