Simulating social network-based interventions for adolescent cigarette smoking.

Social network-based adolescent substance use interventions have demonstrated potential for reducing adolescent cigarette smoking. This approach is premised upon leveraging youths' social networks for the diffusion of peer influence. Determining which adolescents to select in network interventions for reducing smoking is a major consideration. We utilize a simulation approach that first estimates Stochastic Actor-Oriented models (SAOM) of adolescent smoking using data from two of the largest schools from the longitudinal saturation sample of the National Study of Adolescent to Adult Health (Add Health) (n = 3,154). We then conduct Agent-Based Simulation models which mimic the consequences of intervention strategies selecting adolescents in network positions and structures that are salient for smoking and the diffusion of peer influence within school-based networks, and we select adolescents smoking at different levels. Our findings indicate that selecting adolescents occupying central network positions yielded the greatest reductions in the number of smokers in a school, one year post intervention. Moreover, our findings indicate that in the school with the higher smoking prevalence, there was a beneficial network multiplier effect one year later, which resulted in more non-smokers than those smokers initially intervened upon. When examining the effects of varying the magnitude of peer influence, we find that targeting central positions in networks led to even greater decreases in smoking in schools with higher levels of peer influence. Our findings highlight interdependence and sensitivity of peer influence to network position and have implications for informing school-based network interventions for adolescent smoking.