INVESTIGATING THE CO-EVOLUTION OF INDIVIDUAL AND NETWORK-LEVEL RECOVERY CAPITAL: A DYNAMIC SOCIAL NETWORK ANALYSIS TESTING NETWORK COHESION AND EXCHANGE THEORIES

Historically, treatment professionals, researchers, and policymakers widely regarded substance use disorders (SUDs) as acute conditions that patients could “recover” from after a single treatment. Recent efforts have redefined recovery as a lifelong, dynamic process that involves improvements in multiple domains over time. Thus, recovery capital frameworks and theory have gained momentum as a way to operationalize recovery from SUDs. Recovery capital is a multifaceted framework with theoretical underpinnings in the social capital literature that provides a way of conceptualizing and measuring the complexities of the recovery process. While the literature on recovery capital has grown significantly since its conception, the extant research has focused on investigating recovery capital at the individual-level and not on how it is developed contextually. The current longitudinal study sought to advance understanding of how recovery capital is developed using social network analysis while testing network cohesion, social exchange, and generalized exchange theories. Stochastic Actor Oriented Modeling was conducted on individuals recovering from SUDs (N = 627) residing in 42 recovery homes. Findings indicated that while cohesion, social exchanges, and generalized exchanges were prevalent across various types of networks, these network-level effects had no influences on changes in the individual-level of recovery capital. However, a dyadic-level effect was found, indicating that residents’ individual-level recovery capital increased when they were directly connected to those rich in recovery capital. Additionally, compared to men, women had slower increases in their recovery capital over time. The theoretical and practical implications and recommendations for future research are discussed