The cognitive, affective, and behavioral expression of self-stigma among people who use drugs in online substance use communities

2026-06-23

AI Summary

This study presents the first systematic characterization of multidimensional expressions and temporal dynamics of online self-stigma among people who use drugs, integrating cognitive, affective, and behavioral dimensions. Analyzing 72,115 Reddit posts, the authors developed a ten-item coding framework and employed consensus-driven abductive coding, dual human annotation (Cohen’s κ = 0.72), and expert-validated large language model classification (κ = 0.73, F1 = 0.80) to identify self-stigma in 5.3% of posts, with 74% of users expressing it at least once. Behavioral indicators frequently preceded internalized core components, challenging conventional stage-based stigma models. Self-labeling (56.0%) and hopelessness (48.5%) were the most prevalent manifestations. While most indicators remained stable over time, pessimism significantly intensified longitudinally.

Abstract

Objectives: To develop a codebook for self-stigma across cognitive, affective, and behavioral domains, and to estimate the prevalence, co-occurrence, and temporal patterns of these indicators in Reddit posts by people who use drugs. Methods: We developed a ten-indicator codebook through consensus-based abductive coding spanning cognitive (self-labeling, pessimism/self-defeatism, deservingness/worthlessness), affective (shame, guilt/self-blame, despair/hopelessness), and behavioral (concealment, anticipated rejection, desire to quit, ambivalence) domains; two coders reached substantial agreement (Cohen's k = 0.72). We then scaled classification with a large language model validated against expert coding (k = 0.73, F1 = 0.80), analyzing 72,115 thread-initiating posts from 1,660 English-language users (2006-2025). Results: 3,838 posts (5.3%) from 1,228 users (74.0%) contained self-stigma; all ten indicators discriminated self-stigma posts (RR 3.6 to 86.2), led by self-labeling (56.0%) and despair/hopelessness (48.5%). Self-stigma was integrated: core and behavioral indicators were strongly associated at the user level (OR = 4.65, 95% CI 3.12-6.94, p < 0.001), and 87.0% of posts with behavioral indicators also contained a core indicator. Contrary to progressive models, behavioral indicators emerged earlier than core ones (desire to quit at median position 0.08 vs. shame at 0.38). Nine of ten indicators were stable across posting trajectories; only pessimism increased (OR = 1.62, 95% CI 1.25-2.10). Conclusion: Among people who use drugs online, self-stigma is an integrated phenomenon in which behavioral indicators rarely appear without internalized ones and often precede them. Most expressions remain stable over time, but pessimism about change deepens, marking a target for early digital intervention and showing that progressive stage models do not map directly onto textual disclosure.

Problem

• self-stigma
• substance use
• online communities
• cognitive-affective-behavioral domains
• temporal patterns

Innovation

• self-stigma
• large language model
• abductive coding
• temporal dynamics
• digital phenotyping