The Influence of Multiple Peer Contexts on Status-Related Behaviors in Adolescence

The overall goal of this dissertation was to investigate the complex interplay between person-related factors (i.e., status and behaviors) and multiple contextual effects on status-related behaviors in adolescents. The behaviors of adolescents are clearly associated with the behaviors of their peers in multiple overlapping contexts. In each context, individual characteristics (e.g., popularity), group characteristics (e.g., the distribution of status in a classroom, mean levels of alcohol use, relational aggression norms), and their interactions play a role. On the outcome side, the story varies depending on whether one wishes to predict, for example, adolescents’ health-risk behaviors, their achievement of status, or the process of conformity to peers. Associations varied considerably, but in all studies the group co-facilitated individual influence. Interventions are therefore likely to benefit from targeting individuals within groups rather than individuals in isolation. Furthermore, the set of research questions across the six studies led to four noteworthy contributions to peer influence and sociometric research: (a) investigating peer influence effects in multiple peer contexts and including multiple individual and contextual characteristics simultaneously as interacting sources of influence, (b) improving the sociometric measurement of peer status, (c) using ecologically valid field experiments to determine specific peer influence effects, and (d) investigating multiple group composition effects simultaneously using a new methodological framework, the GAPIM (Kenny & Garcia, 2012). Unraveling associations between individual and group-level characteristics is a fascinating enterprise. Yet, it is also a challenging endeavor. Fortunately, this will be increasingly possible thanks to the further development of new methods and analyses, such as those used in our studies (e.g., Group Actor-Partner Interdependence Model) and others (e.g., Stochastic Actor-Based M