Position-Specific HIV Risk in a Large Network of Homeless Youths

Abstract

Objectives To add to the body of evidence supporting the relationship between social network structures and health, this study examined interconnections among a sample of runaway and homeless youth (RHY) and how position in the aggregated network structure was associated with HIV risk. Methods Individual and social network data were collected from a sample of 136 RHY. A sociomatrix was generated, network visualization was accomplished with a “spring embedder,” and k-cores were examined. Multivariate logistic regression models assessed the associations between peripheral and non-peripheral network position and recent unprotected sex. Results Small numbers of nominations at the individual level aggregated into a large social network with a visible core, periphery (including isolates), and small clusters. Female youth were more likely to be located in the core as were youth who had been homeless for two years or more. Youth at the periphery of the network were less likely to report unprotected sex and had been homeless for a shorter duration. Conclusions Not only was HIV risk a function of risk-taking youth being connected to other risk-taking youth, but also risk was associated with position in the overall structure of the network. We provide suggestions for effective social network-based prevention programs, need for young women’s housing and health programs, as well as the likely added traction that housing-first programs will have with peripheral youth, for whom the pull of street life is less, which may help them to more successfully engage in the structures and opportunities of housing programs.

Project HOPE: Online Social Network Changes in an HIV Prevention Randomized Controlled Trial for African American and Latino Men Who Have Sex With Men

“…The sample size was n = 112. and is often plagued by errors because of recall bias among participants. 28 Network ties defined by friend status may lack some of the depth of content that other network studies use, such as "someone you go to for help or advice," but their accuracy is high. As a result, we can have confidence in the changes observed over time in these structures and any associations such changes may have with health behaviors.…”

Exploring the impact of network characteristics on substance use outcomes among homeless former foster youth

“…A measure of k-cores describes a subgroup of actors in a larger network, all of whom are connected to some minimum number (k) of other members in that subnetwork (Hanneman and Riddle 2005;Rice et al 2012). k-core identifies spaces of highly interconnected persons in a larger network.…”

“…Structural network theory has been used to describe the impact of network structure and node position on aspects of behavioral health, such as substance use (Borgatti and Halgin 2011), positing that it is not random (Christakis and Fowler 2009). Rice et al (2012) found that position in the overall network and individual connectivity to other homeless youth were significantly associated with engagement in certain risk behaviors. Similarly, it is likely that former foster youth occupy a unique location in the larger homeless network, and affiliation with one another may uniquely affect their engagement in certain risks behaviors.…”

Influence of “traveling” youth and substance use behaviors in the social networks of homeless youth

“…Finally, the EBA developed by Freeman and Webster (1994) provides a framework for creating boundaries based on individuals' shared activities or experiences. Freeman and Webster particularly aimed to sample individuals from natural settings, where ongoing interactions among regular attendees can occur while entry and exit are common (Rice et al, 2012). For homeless youth, drop-in centers are the lowest barrier service organizations that are most commonly utilized by street youth (Esparza, 2009;Gomez et al, 2010).…”