Examining the social and behavioral dynamics of substance use in a longitudinal network study in rural Appalachia

Addict Behav. 2024 May 9:156:108060. doi: 10.1016/j.addbeh.2024.108060. Online ahead of print.

Abstract

Background: Prior studies have shown that individuals and their peers often have similar substance use behaviors, but the mechanisms driving these similarities - particularly in rural settings, are not well understood. The primary objectives of this analysis are to (1) identify factors that contribute to relationship turnover and maintenance within a rural network of persons who use drugs (PWUD), (2) determine whether assimilation and/or homophily shape participants use of injection drugs, heroin, and stimulants (methamphetamine and cocaine), and (3) assess the extent that these mechanisms influence networks ties and/or behaviors and whether these effects vary across time.

Methods: Sociometric network data were collected from a cohort of PWUD in rural Eastern Kentucky at baseline (2008-2010) and at four follow-up visits conducted approximately semiannually. Stochastic actor-oriented models (SAOMS) were used to model network structure and participant behaviors as jointly dependent variables and to identify characteristics associated with the maintenance, dissolution, and formation of network ties and changes in drug use behaviors.

Results: Findings suggest (1) greater network stability over time for reciprocal and transitive relationships, (2) both homophily and assimilation played a greater role in shaping injection drug use (IDU) initiation and cessation than they did in shaping heroin and stimulant use, and (3) the importance of these mechanisms appeared consistent over time.

Conclusion: Given the stability of particular network structures and evidence of both homophily and assimilation with respect to drug-use behaviors, interventions that leverage social networks could be used to motivate health-promoting behaviors.

Keywords: Assimilation; Homophily; Injection drug use; Social network analysis; Stochastic actor-oriented model.