A Thematic Framework for Analyzing Large-scale Self-reported Social Media Data on Opioid Use Disorder Treatment Using Buprenorphine Product
Madhusudan Basak, Omar Sharif, Sarah E. Lord, Jacob T. Borodovsky,, Lisa A. Marsch, Sandra A. Springer, Edward Nunes, Charlie D. Brackett, Luke, J. ArchiBald, Sarah M. Preum

TL;DR
This study develops a thematic framework to analyze large-scale social media data on buprenorphine treatment for Opioid Use Disorder, revealing key information needs, misconceptions, and treatment challenges shared by users.
Contribution
The paper introduces a novel theme-based framework for analyzing social media data to characterize treatment information needs for buprenorphine in OUD, enabling large-scale qualitative insights.
Findings
High prevalence of psychological and physical effects reported during recovery
Complexities in accessing buprenorphine and medication management
Identification of misconceptions and information gaps among users
Abstract
Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine. Despite its popularity, individuals often report various information needs regarding buprenorphine treatment on social media platforms like Reddit. However, the key challenge is to characterize these needs. In this study, we propose a theme-based framework to curate and analyze large-scale data from social media to characterize self-reported treatment information needs (TINs). Methods: We collected 15,253 posts from r/Suboxone, one of the largest Reddit sub-community for buprenorphine products. Following the standard protocol, we first identified and defined five main themes from the data and then coded 6,000 posts based on these themes, where one post can be labeled with applicable one to three themes. Finally, we determined the most frequently appearing sub-themes (topics) for each…
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Taxonomy
TopicsHIV, Drug Use, Sexual Risk · Sentiment Analysis and Opinion Mining · Mental Health via Writing
