OBJECTIVE: Multiple studies have shown social network variables to mediate and predict drinking outcome, but, because of self-selection biases, these studies cannot reliably determine whether the influence is causal or correlational. The goal of this study was to evaluate evidence for a causal role for social network characteristics in determining long-term outcomes using state-of-the-art statistical methods. METHOD: Outpatient and aftercare clients enrolled inProject MATCH (N = 1,726) were assessed at intake and at 3, 6, 9, 12, and 15 months; the outpatient sample was also followed to 39 months. Generalized linear modeling with propensity stratification tested whether changes in social network ties (i.e., number of pro-abstainers and pro-drinkers) at Month 9 predicted percentage of days abstinent and drinks per drinking day at 15 and 39 months, covarying for Alcoholics Anonymous (AA) attendance at Month 9. RESULTS: An increase in the number of pro-drinkers predicted worse drinking outcomes, measured by percentage of days abstinent and drinks per drinking day, at Months 15 and 39 (p < .0001). An increase in the number of pro-abstainers predicted more percentage of days abstinent for both time periods (p < .01). The social network variables uniquely predicted 5%-12% of the outcome variance; AA attendance predicted an additional 1%-6%. CONCLUSIONS: Network composition following treatment is an important and plausibly causal predictor of alcohol outcome across 3 years, adjusting for multiple confounders. The effects are consistent across patients exhibiting a broad range of alcohol-related impairment. Results support the further development of treatments that promote positive social changes and highlight the need for additional research on the determinants of social network changes.
RCT Entities:
OBJECTIVE: Multiple studies have shown social network variables to mediate and predict drinking outcome, but, because of self-selection biases, these studies cannot reliably determine whether the influence is causal or correlational. The goal of this study was to evaluate evidence for a causal role for social network characteristics in determining long-term outcomes using state-of-the-art statistical methods. METHOD:Outpatient and aftercare clients enrolled in Project MATCH (N = 1,726) were assessed at intake and at 3, 6, 9, 12, and 15 months; the outpatient sample was also followed to 39 months. Generalized linear modeling with propensity stratification tested whether changes in social network ties (i.e., number of pro-abstainers and pro-drinkers) at Month 9 predicted percentage of days abstinent and drinks per drinking day at 15 and 39 months, covarying for Alcoholics Anonymous (AA) attendance at Month 9. RESULTS: An increase in the number of pro-drinkers predicted worse drinking outcomes, measured by percentage of days abstinent and drinks per drinking day, at Months 15 and 39 (p < .0001). An increase in the number of pro-abstainers predicted more percentage of days abstinent for both time periods (p < .01). The social network variables uniquely predicted 5%-12% of the outcome variance; AA attendance predicted an additional 1%-6%. CONCLUSIONS: Network composition following treatment is an important and plausibly causal predictor of alcohol outcome across 3 years, adjusting for multiple confounders. The effects are consistent across patients exhibiting a broad range of alcohol-related impairment. Results support the further development of treatments that promote positive social changes and highlight the need for additional research on the determinants of social network changes.
Authors: Scott W Henggeler; W Glenn Clingempeel; Michael J Brondino; Susan G Pickrel Journal: J Am Acad Child Adolesc Psychiatry Date: 2002-07 Impact factor: 8.829
Authors: Peter M Monti; Suzanne M Colby; Nadine R Mastroleo; Nancy P Barnett; Chad J Gwaltney; Timothy R Apodaca; Damaris J Rohsenow; Molly Magill; Aruna Gogineni; Michael J Mello; Walter L Biffl; William G Cioffi Journal: J Consult Clin Psychol Date: 2014-08-11