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.
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