In addition to being interviewed by an AI assistant, the participants also had to fill out standardized rating scales for the nine most common psychiatric diagnoses. The results showed that the AI assistant's assessments were more consistent with the participants' actual diagnoses than the rating scales did.
The study included individuals with confirmed diagnoses for conditions such as depression, anxiety, obsessive-compulsive disorder, PTSD, ADHD, autism, eating disorders, substance use disorder and bipolar disorder, as well as a control group. All participants had an online interview with the AI assistant, Alba, which asked 15 - 20 open questions about their mental health and then proposed diagnoses based on DSM-5 - the internationally-used manual for psychiatric diagnosis.
The AI assistant achieved higher accuracy in eight of the nine diagnoses, and could differentiate more clearly between diagnoses that often overlap. For example, the conventional rating scales often gave similar readings for depression and anxiety, whereas Alba’s assessments could discern the conditions more clearly. The participants also described the user experience as positive - many perceived the AI assistant as empathic, relevant and supportive.
“An interview that can be done in a safe home environment before meeting a clinician has great value. The results point to a scalable, person-centred complement that can lighten the load for healthcare and provide a preliminary assessment, without replacing the psychologist or physician,” says Professor of Psychology Sverker Sikström, leader of the research team behind the study at Lund University and founder of the company, Talk To Alba.
Sikström S, Boehme RA, Mirström M, Agbotsoka T, Győri G, Lasota M, Tabesh M, Stille L, Garcia D.
Generative AI-assisted clinical interviewing of mental health.
Sci Rep. 2025 Oct 29;15(1):37737. doi: 10.1038/s41598-025-13429-x