NCT07397975

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 360 (estimated)
• Sponsor: Philipp Homan · Academic / Other
• Sex: All
• Age: 18 Years – 65 Years
• Healthy volunteers: Accepted

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.

Detailed description

This project follows a prospective, exploratory, observational design with a non-randomized, two-arm structure, including a group of individuals with psychosis at risk of relapse and a healthy control group. As a multicenter, international research project, it will assess the usability and feasibility of speech data collection across 6 different languages (English, German, French, Dutch, Czech and Turkish) and healthcare systems, ensuring its applicability in diverse clinical environments. Speech and self-report data will be collected weekly for a year using a finalized smartphone application, ensuring consistency and feasibility in real-world clinical settings. The recordings will be securely transferred to an external platform for AI-based analysis, preventing any direct impact on clinical decision-making and maintaining the study's observational nature. To ensure data integrity and reliability, a Human-in-the-Loop (HITL) quality control process is implemented after each speech recording session: Initial Data Review: a designated reviewer (HITL1) checks the audio quality and accuracy of automated transcripts stored securely in the Trusted Secure Database (TSD) system in Norway. They correct transcription errors and flag anomalies such as poor audio quality to maintain data accuracy for analysis. Risk Assessment and Decision Suggestion: a second reviewer (HITL2) evaluates the data by: (i) assessing speech characteristics relevant to relapse risk based on raw response data and performance scores (e.g., story recall accuracy); (ii) providing an independent relapse risk estimate, without access to the automated AI-generated risk assessment, (iii) classify the participant as belonging to either the psychosis or healthy control group, and (iv) suggesting a clinical decision, which is recorded for research purposes but not shared with the treating clinician. Apart from this Fast Diagnostic Loop, where a clinical decision will be made, an exploratory component will be incorporated to identify and validate new speech markers associated with relapse. This New Marker Discovery Loop will involve the search of additional speech features associated with relapse beyond the standard markers. The goal is to discover novel speech markers that may improve our understanding of relapse mechanisms and potentially serve as predictive or diagnostic tools for future clinical use. For the 1-year follow-up period, participants will attend a total of three study visits. These visits will occur at the following time points: Visit 0: Baseline visit, Visit 1: 6 months post-baseline (±10 days), and Visit 2: 12 months post-baseline (±10 days). During these visits, participants from both groups will undergo assessments aiming to evaluate the usability and trustworthiness of the procedure and to assess various functional and quality-of-life outcomes.

Conditions

• Psychotic Disorder

Interventions

Type	Name	Description
OTHER	Weekly online speech assessments via a smartphone app collect speech and self-report data. Recordings are securely transferred and analyzed by an AI-based backend to calculate relapse risk scores.	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.

Timeline

• Start date: 2026-01-29
• Primary completion: 2029-01-31
• Completion: 2029-01-31
• First posted: 2026-02-09
• Last updated: 2026-02-09

Locations

7 sites across 6 countries: Czechia, Ireland, Netherlands, Norway, Switzerland, Turkey (Türkiye)