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Updated: Jul 16, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
Individual and social network factors that predict entry to drug treatment
Melissa A Davey1, Carl A Latkin, Wei Hua
1Department of Health, Behavior, and Society, Johns Hopkins University, Bloomberg School of Public Health, 1629 East Baltimore Street, Baltimore, MD 21231, USA. mdavey@jhsph.edu
Abstract:
Prospective data were analyzed to examine individual and social network characteristics that predict entry into drug treatment among a sample of 557 heroin and cocaine users. Entering treatment was associated with being HIV positive [AOR: 2.25, 95% CI: 1.33-3.81] and a history of drug treatment [AOR: 3.41, 95% CI: 2.19-5.31]. Individuals with a greater number of social network members who were in drug treatment [AOR: 1.29, 95% CI: 1.07-1.56] and fewer network members who smoked crack [AOR: 0.86, 95% CI: 0.75-0.99] were more likely to enter treatment. Social network-based interventions that promote successful outcomes in drug treatment are needed.
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