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Nanyang Technological University, Singapore (NTU Singapore) and the Institute of Mental Health (IMH) have developed an artificial intelligence (AI) framework capable of identifying youths at high risk of psychosis from short samples of casual, spontaneous speech.

Psychosis is a severe mental health condition that typically emerges between adolescence and early adulthood, in which a person may experience hallucinations, delusions and disordered thinking.

This is the first reported study in Singapore to focus specifically on early psychosis risk among youths using large language models (LLMs), a form of artificial intelligence trained to analyze and generate human language.

The team of researchers believes the technology could eventually support primary care providers and community workers in identifying vulnerable youths before clinical symptoms escalate.

Early identification of individuals at ultra-high risk (UHR) of psychosis is challenging because youths in everyday life rarely articulate mental health struggles directly. Ultra-high risk of psychosis refers to a clinical state in which an individual shows early warning signs or risk factors that significantly increase the likelihood of developing psychosis.

For example, a depressed person may not explicitly state that they feel depressed. This is known as "non-disclosing speech," meaning language that does not contain any explicit mention of the mental health condition experienced by the speaker.

Therefore, evaluating whether AI can detect potential risk purely from casual, spontaneous conversation addresses a key hurdle in early intervention.

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