Title

Social Network Correlates of Methamphetamine, Heroin, and Cocaine Use in a Sociometric Network of Homeless Youth

Document Type

Article

Publication Date

2015

Organizational Units

Graduate School of Social Work

Abstract

Objective: Peer influence is one the most consistent correlates of drug use among youth. However, beyond the dyadic level, there is the possibility that peer influence alsofunctions at a more macro or group level, which calls for a better understanding of how positioning within larger social networks affects youth behaviors. Yet, whereas extant research among homeless youth indicates that having substance-using peers is associated with youth's own substance use, the issue of how peer influence operates in conjunction with network structure and position especially with regards to substance use is relatively unexplored. Method: Using Freeman's Event Based Approach, a sociometric network of 136 homeless youth (39.6% female; 38.1% African American; mean age 20.81 years) were recruited in 2008 at 1 drop-in agency in Los Angeles. Self-administered questionnaires and interviewer-administered social network interviews captured individual and network alters' risk behaviors. Network structure and position was assessed with UCINET and visualized with NetDraw. Logistic regressions assessed associations among substance use, adjacent peer substance use, and network position. Results: Youths' connections to specific substance-using peers and their overall position in the network exposed them to behaviors supportive of specific drugs. These results supported the general proposition that both peer and positional attributes affect substance use among homeless youth. Youth's position in the network exposed them to norms supportive of specific illicit drugs. Conclusions: These results underscore the importance of tailoring interventions to reduce drug use at the network level and of recognizing drug use as not only an individual problem but also a social problem. Limitations of this study include its small sample size, the lack of generalizability, and its focus on a finite set of variables.

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