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Phenotypes of stigma expressed by people who use drugs on Reddit
Journal article   Peer reviewed

Phenotypes of stigma expressed by people who use drugs on Reddit

Layla Bouzoubaa, Elham Aghakhani and Rezvaneh Rezapour
Social science & medicine, v 390, 118889
Feb 2026
PMID: 41422691
Featured in Collection :   Research Supported by Drexel Libraries' OA Programs
url
https://doi.org/10.1016/j.socscimed.2025.118889View
Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2025CC BY-NC-ND V4.0 Restricted

Abstract

Stigma Substance use Social media Reddit Phenotypes Natural language processing Large language models
Rationale: Despite record-high overdose deaths in the U.S., most individuals meeting criteria for substance use disorder remain outside formal treatment systems. Stigma is a major contributor to this treatment gap yet remains difficult to study among people who use drugs (PWUD) who are not engaged in clinical care. Social media platforms like Reddit offer a valuable window into the lived experiences of stigma of this population through naturally occurring discourse. This study develops a comprehensive framework for identifying stigma expressions in social media discourse, identifies distinct patterns using computational methods, and examines how these patterns relate to established stigma theory. Methods: We analyzed over one million posts from six drug-related subreddits using mixed-methods. Large language models with human validation identified and classified stigma-related content across validated dimensions of narrativity, stigma experience, and psycholinguistic features. K-means clustering identified distinct stigma expression patterns (phenotypes), which were then characterized through comprehensive linguistic analysis. Results: Analysis of 1,033,619 posts identified 56, 446 stigma-containing posts and revealed a novel classification — Stigma Perceptions & Commentary (SPC) - which captures the broader discourse on stigma beyond personal experiences. Clustering analysis of these stigma posts plus 5495 non-stigma posts (61,941 total) revealed three distinct phenotypes: Internalized Stigma (34.5%), characterized by self-blame, high narrative agency, and avoidant coping; Public Stigma (38.9%), featuring discrimination from healthcare systems with mixed coping; and Righteous Indignation (26.6%), marked by analytical critique of systemic issues. Conclusion: These phenotypes align with theoretical models of self-stigma and demonstrates the potential of social media data to extend stigma research beyond clinical populations, offering insight into how PWUD experience and contest stigma in everyday discourse.

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Web of Science research areas
Public, Environmental & Occupational Health
Social Sciences, Biomedical
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