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Evaluating network-level predictors of behavior change among injection networks enrolled in the HPTN 037 randomized
Laramie R Smith1, Steffanie A Strathdee1, David Metzger2
1Division of Global Public Health, University of California San Diego, UCSD School of Medicine, 9500 Gilman Drive #0507, La Jolla, CA, 92093-0507, USA.
Background:
Little 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.
Methods:
A 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.
Results:
At 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).
Conclusions:
Network-level factors offer insights into ways injection networks might be leveraged to promote combination prevention efforts.
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