An Agent-Based Social Network Model of Binge Drinking Among Dutch Adults

Binge drinking is a complex social problem linked to an array of detrimental health effects. While binge drinking in youth has been analyzed extensively using traditional methods (e.g., regressions analyses), the adult population has received less attention, and recent work has exemplified the potential for simulations to help scholars and practitioners better understand the problem. In this paper, we used agent-based social network models to test a number of hypotheses on important aspects of binge drinking in a sample representative of the adult Dutch population. In particular, we found that a combination of simple social rules (choosing peers who are similar, being prompted to drink if at least a fraction of them drinks, and incorporating the context) was sufficient to correctly predict the behaviour of half of the binge drinkers and 4 out of 5 non binge drinkers. Furthermore, we used factorial analyses to examine the contribution and combination of hypotheses in predicting the behaviour of individuals, with results indicating that who we interact with may not matter so much as how we interact. Finally, we evaluated the potential for interventions that mediate interactions between people in order to reduce the prevalence of binge drinking and found that the impact of such interventions was non linear: moderate interventions would yield benefits, but stronger interventions may only be of limited further benefit.