Affiliation:
1. Alcohol Research Group, Public Health Institute, Emeryville, CA, USA
Abstract
This study tests a socioecological model of relapse and recovery using latent class growth mixture modeling to identify neighborhood, social network and individual-level predictors of alcohol dependence trajectories among a large, longitudinal sample of problem drinkers recruited from substance use treatment settings. We identified four distinct alcohol dependence trajectories: Stable Recovery/Low (Class 1); Relapsing/Rising (Class 2); Late Recovery/Declining (Class 3); and Chronic/High (Class 4). Neighborhood context (poverty and density of bars), social network characteristics (less involvement with Alcoholics Anonymous [AA], continued affiliation with heavy drinkers), and individual predisposing (psychiatric severity) and need (returning to treatment) characteristics each distinguished individuals in the Relapsing/Rising class from individuals in the Stable Recovery/Low class. Social network characteristics (AA involvement and continued affiliation with heavy drinkers) were the primary distinguishing factors for individuals in the Chronic/High class compared to the Late Recovery/Declining class. Study findings can be used to promote recovery and help prevent relapse by: guiding development of community-level interventions to improve social and physical environments; identifying potentially modifiable factors (social network support for sobriety, participation in self-help) to reduce negative consequences among problem drinkers who remain in high-risk neighborhoods; and contributing to ongoing discussions about new and continued licensing of alcohol outlets and regulation of alcohol sales to prevent alcohol problems in high-risk areas and among high-risk people.
Subject
Psychiatry and Mental health
Cited by
10 articles.
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