Speech-based Assessment of Relapse Risk in People With Psychosis
A Prospective Multicenter Study for Relapse Risk Assessment Through Language Analysis in Individuals With Psychosis
Philipp Homan
360 participants
Jan 29, 2026
OBSERVATIONAL
Conditions
Summary
This observational, multinational study assesses the feasibility of speech and self-report data collection across six languages for Artificial Intelligence (AI)-driven relapse risk estimation in psychosis. Over 12 months, patients at risk of relapse and healthy controls will provide weekly speech recordings and self-report data for automated analysis. Risk scores will be stored but not shared with treating clinicians. Independent clinical evaluations ensure data quality and validation. The study lays the foundation for future Clinical Decision Support System (CDSS) research and explores novel speech markers for relapse prediction while minimizing participant burden.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
The intervention is a weekly online assessment of speech, to detect subtle characteristics of psychotic speech. These recordings are made through a speech data collection tool: a smartphone app with implemented tasks for the collection of behavioral response data (speech and self-report). Data is then transferred to a safe repository (TSD) to be analysed by an AI-based speech data analysis algorithm: a backend system will run the predictor code to calculate automatic relapse risk scores.
Locations(7)
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NCT07397975