Psychology ETDs

Publication Date

9-12-2014

Abstract

Introduction: Previous studies have found associations between alcohol use and having heavy-drinking social networks. This association is thought to be caused by (1) social influence, where ones social network influences his or her drinking, and (2) social selection, where an individual forms relationships with individuals who drink at similar levels. These processes are reciprocal and, when acting simultaneously, create a feedback loop with non-linear dynamics. Computer simulations have allowed complex systems to be modeled in many scientific fields; however, this method has not yet been used to study the dynamic associations between social networks and alcohol use. Method: The present study used computer simulations to model changes in drinking and social networks. Stochastic actor-based social networks were simulated using RSiena. Social ties between actors and drinking statuses evolved over time according to stochastic Markov processes. Social influence and social selection were each manipulated at three levels (none, medium, and high). Results: Correlations between actor drinking statuses and the percentage of heavy drinkers with whom actors shared social ties were approximately zero when neither social selection nor social influence were present, were positive but small when either social influence or social selection were medium or high, and were significantly higher when social selection and social influence were both present. Two individual-level manipulations, reducing the target actor's heavy drinking and reducing the target actor's susceptibility to social influence, reduced heavy drinking over time for the individual targeted for intervention. Reducing target actors' heavy drinking also reduced the heavy drinking of other actors not targeted for intervention. Discussion: Simulations of social networks offer a novel method for modeling dynamic associations between drinking and social relationships. These methods may be used to replicate findings from real-world populations and can help generate novel hypotheses involving nonlinear processes that can inform real-world prevention and treatment efforts.

Degree Name

Psychology

Level of Degree

Doctoral

Department Name

Psychology

First Committee Member (Chair)

Caudell, Thomas

Second Committee Member

Tonigan, J Scott

Third Committee Member

Witkiewitz, Katie

Sponsors

National Institute on Alcohol Abuse and Alcoholism

Language

English

Keywords

alcohol, complex systems, dynamic systems, simulation, social network analysis

Document Type

Dissertation

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