Deceptive Empathy in Large Language Model Responses to Suicide-Related Disclosures

Key Findings

• — 20 prompts (50 sampled from the CLPsych 2019 r/SuicideWatch dataset; two licensed psychotherapists each chose 20 high-risk posts; 20 kept after consensus) were sent once each to 8 free-tier systems (ChatGPT 5.2, Gemini 2.5 Flash, Claude Haiku 4.5, DeepSeek V3.2, Perplexity, Grok 3, Llama 4, Mistral): 160 outputs, 1 excluded as Spanish, 159 evaluable.
• — Deceptive empathy was present in 96/159 responses (60.4%); between-model differences chi-square(7)=84.35, P<.001, Cramer V=0.73.
• — Per model (Table 1): DeepSeek V3.2 20/20, Claude Haiku 4.5 20/20, Mistral 20/20, ChatGPT 5.2 12/20 (60.0%), Gemini 2.5 Flash 11/20 (55.0%), Perplexity 9/20 (45.0%), Llama 4 4/19 (21.1%), Grok 3 0/20 (the paper says Grok 3 refused all prompts).
• — Coding by 3 independent coders with a prespecified rubric; Fleiss kappa 0.66 before consensus adjudication.
• — Limitations stated by the authors: small clinician-selected prompt set, single-turn, one collection window, free-tier systems only; the authors note that avoiding deceptive empathy by refusing every disclosure still fails to provide clinically appropriate crisis engagement.

Methodology Notes

Not peer reviewed (JMIR Preprints, under review at JMIR AI). Text read via r.jina rendering of the JMIR Preprints PDF (11 pages); the abstract was also read from Crossref (3,229 chars) for both versions. Inconsistency inside the document: the abstract says prompts were submitted in February 2026 while the methods text says January 2026 (and that the posts were chosen in January 2026). Two preprint versions exist (99710, April; 105273, June) with the same numbers; the later version only adds label prefixes in the abstract.

Sources