Using Speech to Monitor Symptom Severity in Arabic Speaking Patients With Schizophrenia
Condition: Schizophrenia
MeSH terms: Schizophrenia
Study type: Observational

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.
    

Intervention name(s): WinterLight Mobile Phone Speech Analysis
Intervention type(s): Other
Intervention description(s): N/A- observational study
Observational model: Cohort
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        Participants will be recruited from four medical sites in the Middle East North Africa
        (MENA) region, which are located in Jordan, Saudi Arabia, Egypt, and Algeria.
      
Keywords: Schizophrenia; Schizophrenic Disorders; Mental Disorders; Speech; Voice; Language; Natural Language Processing; Behavioral Symptoms