RecruitingNCT07397975

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

Sponsor

Philipp Homan

Enrollment

360 participants

Start Date

Jan 29, 2026

Study Type

OBSERVATIONAL

Conditions

Psychotic Disorder

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

Min Age: 18 YearsMax Age: 65 Years

Inclusion Criteria16

Between 18 and 65 years old.
Subjects must be able to provide informed consent (IC).
Participants must have provided signed informed consent prior to enrollment.
Participants should not take prescription drugs regularly.
Native or equivalent fluency in speaking and understanding one of the following languages: English, German, Dutch, French, Czech or Turkish.
Ability to have access to a smartphone and be capable of using a mobile app for speech-based data collection.
Must be able to comply with the study schedule and procedures.
Between 18 and 65 years old.
Diagnoses include psychotic disorders (schizophrenia, schizoaffective disorder, schizophreniform disorder, acute psychosis, bipolar disorder with psychotic symptoms, psychosis not otherwise specified).
First visit must be during remission phase (baseline measurement).
Current positive symptoms rated 3 (mild) or lower on all of these Brief Psychiatric Symptom Scale (BPRS) items: hallucinatory behavior, unusual thought content, conceptual disorganization.
Must be able to comply with the study schedule and procedures.
Subjects must be able to provide IC.
Participants must have provided signed informed consent prior to enrollment.
Native or equivalent fluency in speaking and understanding one of the following languages: English, German, Dutch, French, Czech or Turkish.
Ability to have access to a smartphone and be capable of using a mobile app for speech-based data collection.

Exclusion Criteria8

Any history of major diseases (e.g., cardiovascular, neurological, metabolic, renal, hepatic, respiratory or speech disorders).
Recreational drug use or psychiatric disorders due to use of alcohol.
Depression, anxiety, or other psychiatric disorders.
Family history of depression, anxiety, or other psychiatric disorders.
Individuals who are not able or willing to understand the purpose and details of the study.
Severe comorbid speech disorders (aphasia or severe stuttering) that prevent adequate speech recording.
Individuals who are not able or willing to understand the purpose and details of the investigation.
Citizens with psychiatric or somatic comorbidity, drug- or alcohol abuse will be allowed to participate, so that the sample will reflect the general population of citizens with psychosis and the study's endpoints will be generalizable.

Interventions

OTHERWeekly 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.