Using Speech to Monitor Symptom Severity in Arabic Speaking Patients With Schizophrenia

NCT ID: NCT05563818

Last Updated: 2023-09-22

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 57 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-11-09
• Study Completion Date: 2022-12-20

Brief Summary

Brief Summary:

Definition: A short description of the clinical study, including a brief statement of the clinical study's hypothesis, written in language intended for the lay public.

Limit: 5000 characters. The purpose of this study is to investigate the relationship between speech features and severity of positive and negative clinical symptoms in Arabic speaking patients with schizophrenia. Individuals will be invited to participate in this study because (1) they have a confirmed clinical diagnosis of schizophrenia; (2) they plan to receive routine clinical care for schizophrenia at one of the four participating sites; (3) they speak Arabic as a first language.

Participants must be between the ages of 18-65 years. Participation will involve seven visits consisting of one baseline visit and six monthly follow-up visits. All participants will continue to receive routine clinical care.

Participation in this research will involve providing speech samples using standardized tasks collected using an electronic device. Additionally, study team members will assess positive and negative symptoms of schizophrenia using validated questionnaires.

Detailed Description

Speech disorganization is a key feature of schizophrenia. The development of computerized tools to assess speech disorganization is rapidly growing in schizophrenia research. Several early studies showed that changes in speech distinguish schizophrenia patients from healthy controls and assist in differential diagnostics and relapse prevention (1). The Winterlight app can be used for speech collection and assessment and uses speech-based artificial intelligence to identify vocal biomarkers capable of detecting changes in cognitive/clinical symptoms.

Symptom rating scales remain the primary mode of assessing the nature and severity of schizophrenia and the magnitude of any change over time. The Positive and Negative Symptom Scale (PANSS) is a 30-item rating scale that was developed to measure the symptom severity of patients with schizophrenia and assess their dimensions (2). It has been widely used in clinical trials of schizophrenia and is considered as the "gold standard" for the assessment of antipsychotic treatment efficacy.

The goal of this study is to test the hypothesis that quantitative measures derived from speech samples acquired using the Winterlight application will be associated with positive and negative symptom subscores as assessed by the PANSS.

The investigators will use speech-based artificial intelligence methods to identify aspects of voice and language that are related to schizophrenia symptoms in Arabic-speaking patients.

Data collected may be used to evaluate:

1. The relationship between speech measures and PANSS subscores at baseline.

2. The relationship between changes in speech measures and changes in positive symptoms over time.

3. The relationship between changes in speech measures and changes in negative symptoms over time.

4. The ability for speech measures to be used to predict psychotic relapse in individuals with schizophrenia.

5. The feasibility of predicting relapse based on speech and sociodemographic variables.

Conditions

Schizophrenia

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Arabic-speaking individuals with schizophrenia

Approximately 56-60 Arabic-speaking individuals with a DSM-5 diagnosis of schizophrenia

WinterLight Mobile Phone Speech Analysis

Intervention Type: OTHER

N/A- observational study

Interventions

WinterLight Mobile Phone Speech Analysis

N/A- observational study

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

1. Aged 18 - 65 years

2. Confirmed clinical diagnosis of schizophrenia as per the DSM-5 criteria, at any stage of disease.

3. Planned to receive routine clinical care for schizophrenia in the study site for the next 6 months.

4. Arabic is first language

Exclusion Criteria

1. Illiterate.

2. Catatonic schizophrenia subtype.

3. Neurological disorder or major health problem.

4. Severe substance use disorder using DSM-5 criteria.

5. Risk to self or others.

6. Patient with any speech disorder or treated/planned to be treated with any medication known to impact speech (e.g. first-generation antipsychotics)

7. Patient or family member is unable to provide consent to participate in the study.

8. Participation in another clinical study.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 65 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Winterlight Labs

INDUSTRY

Sponsor Role: collaborator

Hikma Pharmaceuticals LLC

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Mustapha University Hospital

Algiers, , Algeria

Ain Shams Hospital

Cairo, , Egypt

Mental Health Hub

Amman, , Jordan

Jeddah Psychiatry Hospital

Jeddah, , Saudi Arabia

Countries

Algeria; Egypt; Jordan; Saudi Arabia

References

de Boer JN, Brederoo SG, Voppel AE, Sommer IEC. Anomalies in language as a biomarker for schizophrenia. Curr Opin Psychiatry. 2020 May;33(3):212-218. doi: 10.1097/YCO.0000000000000595.

Reference Type: BACKGROUND

PMID: 32049766 (View on PubMed)

Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13(2):261-76. doi: 10.1093/schbul/13.2.261.

Reference Type: BACKGROUND

PMID: 3616518 (View on PubMed)

Other Identifiers

HIK-WL-SCZ-2021-01

Identifier Type: -

Identifier Source: org_study_id