New AI tool helps identify suicide-risk individuals

AI may help identify mental health disorders beyond suicide, including depression and anxiety, offering faster and more precise assessments.

AI tools using large language models detected suicide risk that standard assessments often miss by analysing speech patterns and future self-continuity.

Researchers at Touro University have found that an AI tool can identify suicide risk that standard diagnostic methods often miss. The study, published in the Journal of Personality Assessment, shows that LLMs can analyse speech to detect patterns linked to perceived suicide risk.

Current assessment methods, such as multiple-choice questionnaires, often fail to capture the nuances of an individual’s experience.

The study used Claude 3.5 Sonnet to analyse 164 participants’ audio responses, examining future self-continuity, a key factor linked to suicide risk. The AI detected subtle cues in speech, including coherence, emotional tone, and detail, which traditional tools overlooked.

While the research focused on perceived risk rather than actual suicide attempts, identifying individuals who feel at risk is crucial for timely intervention. LLM predictions could be used in hospitals, hotlines, or therapy sessions as a new tool for mental health professionals.

Beyond suicide risk, large language models may also help detect other mental health conditions such as depression and anxiety, providing faster, more nuanced insights into patients’ mental well-being and supporting early intervention strategies.

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