AI chatbots struggle with subtle mental health cues

Driving the news: Mpathic built new clinician-led benchmarks for testing AI systems in high-risk conversations and evaluated six major models on suicide-related and eating disorder-related chats.

• Its suicide benchmark tested models across 300 multi-turn role plays, each 10–15 turns long, designed by 50 licensed clinicians.
• Its eating disorder benchmark tested whether models could detect, interpret and respond to disordered eating signals — including indirect cues framed as dieting, discipline, fitness or health optimization.

What they found: The models generally handled explicit suicide risk better than murkier cases.

• On the suicide benchmark, Anthropic's Claude Sonnet 4.5 had the highest score across safety and helpfulness, while OpenAI's GPT-5.2 "stood out for consistently avoiding harmful responses," Mpathic said.
• The chatbots all fared less well when it came to discussions around eating disorders, missing more subtle but critical clues, Mpathic said.

What they're saying: "Many of these systems do fairly well when the risk is very explicit," Mpathic co-founder and chief business officer Danielle Schlosser told Axios. "Almost all the models struggled with more nuanced risk signals."

• The quality of advice also tends to degrade during extended conversations, said Schlosser, who is also a licensed psychologist.

Reality check: Mpathic is a for-profit company paid to consult with the leading labs to improve model behavior in high-risk human conversations.

How it works: Unlike other evaluations based on a single prompt, Mpathic's mPACT benchmark measures performance based on longer conversations the chatbot has with trained psychologists.

• Licensed clinicians create test scenarios that include both explicit and subtle expressions of risk.
• Mpathic then evaluates the responses for helpful and harmful behaviors and assesses the models on how well they detect and interpret issues and the quality of their response.

Zoom out: The findings land as AI companies face growing pressure over chatbot safety.

• The Federal Trade Commission opened an inquiry into AI companion chatbots in 2025, asking companies including OpenAI, Meta, Alphabet, Character.AI, Snap and xAI about child and teen safety practices.

• Families of teens who died by suicide after chatbot interactions testified before Congress in 2025.
• Pennsylvania recently sued Character.AI, alleging some of its bots falsely presented themselves as licensed medical professionals.

Between the lines: One of the challenges comes in how AI models are trained. "In the spirit of trying to be helpful, the model usually wants to agree with the user," Schlosser said.

• But that gets problematic when a person's goal could harm them, such as someone who requests help planning a 500-calorie-per-day diet, for example.
• "Most people don't say 'I'm at risk' directly — they demonstrate it through subtle behaviors over time that are obvious to human clinicians," Mpathic CEO Grin Lord said in a statement.

Yes, but: Large language models are non-deterministic, which means they will give different answers to the same prompt, making it difficult to track the overall quality of responses.

• Models are also constantly being updated in ways that can change how they handle particular queries.

What we're watching: The models are getting better at handling obvious crises, but the tougher problem is whether they can stop being agreeable when a user's goal is dangerous.

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