Complex Systems Science: Applications to Health Behavior.

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The proposed research combines perspectives from bioecological models of development with principles from the realist approach to evaluation. Specifically, the research will: (1) use complex social network methods (e.g., multilevel network analysis) to evaluate the dynamics between individual, social, and environmental determinants of health (e.g., substance use, risky sexual behavior, mental wellbeing); and (2) investigate complexities in social networks as they relate to intervention design in order to answer critical questions regarding the effective leverage of social networks to improve health outcomes. A well-established literature demonstrates that social networks and health are interrelated, such that networks impact the development of health behavior, and simultaneously, health behavior impacts the formation of social connections. Further, growing evidence indicates that peers can be effectively engaged in behavioral interventions. However, in order to fully harness the potential of social network methods to improve health outcomes, it is critically important to look beyond simple associations between networks and health, and network interventions and treatment outcomes, and begin explicitly investigating how these associations transfer across contexts, and through which underlying mechanisms these processes occur. As a result, the aim of the proposed research is two-fold. First, by integrating multilevel modeling techniques with social network methods, the research will answer complex questions regarding variation in health outcomes dependent on individual, social, and environmental factors. Specifically, the proposed research will apply and expand upon existing multilevel techniques for social network analysis in order to answer critical questions regarding when, for whom, to what extent, and under what circumstances social networks impact health. For example, the research will examine variation at the individual, peer, and school level to determine the ways through which these interdependent factors contribute to health inequities (e.g., substance use) among adolescents. Second, the proposed research aims to advance our understanding of network-based interventions by moving beyond simply investigating efficacy of these approaches, and instead focuses on parsing apart the underlying mechanisms through which network-based interventions impact health outcomes. For example, the research will apply and expand upon diffusion of innovation methods in order to determine for whom, in what way, and how these interventions impact health behavior change. In summary, the proposed research is nested within two complimentary approaches to behavioral health and intervention design; the bioecological theory of development, and the realist approach to evaluation. Through this framework, the research aims to uncover important variations in the relationship between social networks and health, while identifying novel intervention targets, and expanding our understanding of the mechanisms through which network interventions impact behavioral change. Lastly, the research uses a variety of existing datasets to accomplish the aforementioned goals.