Background: Online communities can provide social support for those recovering from opioid use disorder. However, advice-seekers on these platforms risk exposure to uncurated medical advice, potentially harming their health or recovery efforts. The objective of this analysis is to combine text annotation, social network analysis, and statistical modeling to identify advice-seekers on online social media for buprenorphine-naloxone use and study their characteristics. Methods: We collected 5,258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking (n=137) and not advice-seeking (n=65). We also annotated each posting user's medication use stage and quantified their connectedness using social network analysis. In order to analyze the relationship between advice-seeking with a user's social connectivity and medication use stage, we constructed four models which varied in explanatory variables. Results: The stepwise model (containing "total degree" (P=0.002), "using: inducting/tapering" (P<0.001), and "using: other" (P=0.01) as significant explanatory variables) outperformed all other models. We found that users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than users who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone. Conclusions: Our findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.
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