Evaluating network-level predictors of behavior change among injection networks enrolled in the HPTN 037 randomized controlled trial

- Prospectively examines network-level mechanisms injection risk.
- Factors affecting instability of network structure affected HIV risk.
- Network gender composition moderated intervention effect.

BackgroundLittle is known about ways network-level factors that may influence the adoption of combination prevention behaviors among injection networks, or how network-oriented interventions might moderate this behavior change process.MethodsA total of 232 unique injection risk networks in Philadelphia, PA, were randomized to a peer educator network-oriented intervention or standard of care control arm. Network-level aggregates reflecting the injection networks' baseline substance use dynamics, social interactions, and the networks exposure to gender- and structural-related vulnerabilities were calculated and used to predict changes in the proportion of network members adopting safer injection practices at 6-month follow-up.ResultsAt follow-up, safer injection practices were observed among 46.31% of a network's members on average. In contrast, 25.7% of networks observed no change. Controlling for the effects of the intervention, significant network-level factors influencing network-level behavior change reflected larger sized injection networks (b = 2.20, p = 0.013) with a greater proportion of members who shared needles (b = 0.29, p < 0.001) and engaged in poly drug use at baseline (b = 6.65, p = 0.021). Changes in a network's safer injection practices were also observed for networks with fewer new network members (b = −0.31, p = 0.008), and for networks whose members were proportionally less likely to have experienced incarceration (b = −0.20, p = 0.012) or more likely to have been exposed to drug treatment (b = 0.17, p = 0.034) in the 6-months prior to baseline. A significant interaction suggested the intervention uniquely facilitated change in safer injection practices among female-only networks (b = −0.32, p = 0.046).ConclusionsNetwork-level factors offer insights into ways injection networks might be leveraged to promote combination prevention efforts.