arXiv — NLP / Computation & Language · · 3 min read

Self-Stigma Is Not a Monolith, but Generic Empathy Is: Persona-Conditioned LLM Support for People Who Use Drugs

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Computer Science > Computation and Language

arXiv:2606.23387 (cs)
[Submitted on 22 Jun 2026 (v1), last revised 25 Jun 2026 (this version, v2)]

Title:Self-Stigma Is Not a Monolith, but Generic Empathy Is: Persona-Conditioned LLM Support for People Who Use Drugs

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Abstract:Self-stigma predicts treatment avoidance and disengagement among people who use drugs (PWUD), yet conversational systems aiming to provide support typically treat self-stigma expression as a uniform signal. We present a three-phase, proof-of-concept study of a persona-aware approach to LLM support. Latent Profile Analysis (LPA) on indicator-level features from 1,174 self-stigma expressors on Reddit yields a four-persona typology validated against held-out behavioral and linguistic features. Sequential Bayesian and recurrent neural classifiers recover these personas from limited posting histories, substantially outperforming batch and few-shot LLM baselines (macro-F1 = 0.74 at 30 posts). Evaluation by eight clinical experts across three contemporary LLMs revealed a misalignment: persona-matched responses successfully achieved targeted behavioral shifts, yet raters holistically preferred the generic empathy of the persona-neutral baseline. Our findings suggest that holistic empathy judgments and clinically-aligned response design can pull in opposite directions, and that evaluating LLM-based stigma support requires rubrics capable of decomposing the two.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2606.23387 [cs.CL]
  (or arXiv:2606.23387v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2606.23387
arXiv-issued DOI via DataCite

Submission history

From: Layla Bouzoubaa [view email]
[v1] Mon, 22 Jun 2026 14:14:57 UTC (1,419 KB)
[v2] Thu, 25 Jun 2026 19:43:12 UTC (1,419 KB)
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