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Semantic and Syntactic Computerized Analysis of Free Speech (ASESID)

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ClinicalTrials.gov Identifier: NCT03525054
Recruitment Status : Recruiting
First Posted : May 15, 2018
Last Update Posted : July 2, 2018
Sponsor:
Information provided by (Responsible Party):
University Hospital, Brest

Brief Summary:
Subtle speech disorganization could be predictive of a transition to schizophrenia of ultra-high-risk patients. The aim of our longitudinal multicenter cohort study is to identify specific linguistic markers of the psychotic transition to validate a french predictive model of this transition using computerized speech analysis techniques

Condition or disease
Psychotic Disorders Psychosis Schizophrenia and Related Disorders Schizophrenia Prodromal Diagnosis, Psychiatric

Detailed Description:

Different scales allow identification of patients at ultra-high-risk to develop psychosis. The current challenge is to identify a predictive marker of transition to schizophrenia. Language disorders, which reflect psyche, could be one of these markers. Computerized speech analysis techniques such as Latent Semantic Analysis (LSA) have already proven their reliability in schizophrenia. These techniques reveal subtle speech disorganization that would be predictive of a clinical transition of ultra-high-risk psychotic patients. A combination of semantic and syntactic analysis could accurately predict the psychotic transition. The aim of our longitudinal multicenter cohort study is to validate this predicitve model in french language as well as identifying specific linguistic markers of the psychotic transition.

The initial report including the CAARMS is completed with an audio recording from the initial medical interview. The recording will be transcribed and analyzed by computer following the method of lemmatization and vectorial analysis (LSA). An analysis of the grammatical function (number of words, rate of the various grammatical functions) will also be performed. This first analysis will emerge linguistic markers correlated to transition to psychosis that we will use to construct a predictive model for transition to schizophrenia.


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Study Type : Observational
Estimated Enrollment : 150 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Semantic and Syntactic Computerized Analysis of Free Speech
Actual Study Start Date : May 18, 2018
Estimated Primary Completion Date : May 18, 2022
Estimated Study Completion Date : May 18, 2022

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Schizophrenia




Primary Outcome Measures :
  1. Transition to schizophrenia [ Time Frame: 2 years ]
    Determined from the CAARMS scale (COMPREHENSIVE ASSESSMENT OF AT RISK MENTAL STATES)


Secondary Outcome Measures :
  1. Identification of patients at "ultra high risk " for developing schizophrenia [ Time Frame: Day 0 ]
    Determined from the CAARMS scale ( COMPREHENSIVE ASSESSMENT OF AT RISK MENTAL STATES)



Information from the National Library of Medicine

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Ages Eligible for Study:   15 Years to 30 Years   (Child, Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Help-seekers patients are recruited during two years from the early psychosis detection centers in Brest, France (CEVUP), Paris, France (CJAAD) and in Lausanne, Switzerland
Criteria

Inclusion Criteria:

  • Major and/or minor from 15 to 30 years old
  • Who alleged a suicidal gesture or idea or behavior that has repercussions in their emotional, social or professional life
  • Patient at risk 1, 2 or 3 according to the CAARMS score
  • If patients receive neuroleptic treatment that impairs cognitive abilities, a one-week wash-out period will be scheduled prior to assessment.

Exclusion Criteria:

  • History of psychosis
  • Risk of self-harm or violence not compatible with outpatient treatment
  • QI<70 (WAIS)
  • Neurological disorder or major health problem
  • Impossibility to interrupt neuroleptic treatment for one week
  • Refusal to participate

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03525054


Contacts
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Contact: Michel WALTER 02-98-01-51-57 michel.walter@chu-brest.fr
Contact: Christophe LEMEY christophe.lemey@chu-brest.fr

Locations
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France
CHRU de Brest Recruiting
Brest, France, 29609
Contact: Michel WALTER       michel.walter@chu-brest.fr   
CH de SAINT ANNE Not yet recruiting
Paris, France, 750144
Contact: Marie-Odile KREBS       mo.krebs@ch-saint-anne.fr   
Sponsors and Collaborators
University Hospital, Brest

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Responsible Party: University Hospital, Brest
ClinicalTrials.gov Identifier: NCT03525054     History of Changes
Other Study ID Numbers: ASESID (29BRC17.0198)
First Posted: May 15, 2018    Key Record Dates
Last Update Posted: July 2, 2018
Last Verified: April 2018

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No

Keywords provided by University Hospital, Brest:
Psychotic Disorders
Diagnosis, Psychiatric
Schizophrenia Prodromal
Ultra High Risk
Prediction Of Psychosis
Machine Learning
Automated Language Analysis
Semantic Coherence
Syntaxic Complexity

Additional relevant MeSH terms:
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Disease
Schizophrenia
Psychotic Disorders
Mental Disorders
Schizotypal Personality Disorder
Pathologic Processes
Schizophrenia Spectrum and Other Psychotic Disorders
Personality Disorders