Automated analysis of free speech predicts psychosis onset in high-risk youths

BACKGROUND/OBJECTIVES: Psychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals. AIMS: In this proof-of-principle stud...

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Autores principales: Bedi, Gillinder, Carrillo, Facundo, Cecchi, Guillermo A., Fernández Slezak, Diego, Sigman, Mariano, Mota, Natália B., Ribeiro, Sidarta, Javitt, Daniel C., Copelli, Mauro, Corcoran, Cheryl M.
Formato: Artículo publishedVersion
Lenguaje:Inglés
Publicado: 2018
Materias:
Neurología
Esquizofrenia
Comunicación
Habla
Neuroscience
Schizophrenia
Acceso en línea:https://doi.org/10.1038/npjschz.2015.30
https://repositorio.utdt.edu/handle/20.500.13098/11075
Aporte de:
Repositorio Digital Universidad Torcuato Di Tella de Universidad Torcuato Di Tella
id I57-R16320.500.13098-11075
record_format dspace
institution Universidad Torcuato Di Tella
institution_str I-57
repository_str R-163
collection Repositorio Digital Universidad Torcuato Di Tella
language Inglés
orig_language_str_mv eng
topic Neurología
Esquizofrenia
Comunicación
Habla
Neuroscience
Schizophrenia
spellingShingle Neurología
Esquizofrenia
Comunicación
Habla
Neuroscience
Schizophrenia
Bedi, Gillinder
Carrillo, Facundo
Cecchi, Guillermo A.
Fernández Slezak, Diego
Sigman, Mariano
Mota, Natália B.
Ribeiro, Sidarta
Javitt, Daniel C.
Copelli, Mauro
Corcoran, Cheryl M.
Automated analysis of free speech predicts psychosis onset in high-risk youths
description BACKGROUND/OBJECTIVES: Psychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals. AIMS: In this proof-of-principle study, our aim was to test automated speech analyses combined with Machine Learning to predict later psychosis onset in youths at clinical high-risk (CHR) for psychosis. METHODS: Thirty-four CHR youths (11 females) had baseline interviews and were assessed quarterly for up to 2.5 years; five transitioned to psychosis. Using automated analysis, transcripts of interviews were evaluated for semantic and syntactic features predicting later psychosis onset. Speech features were fed into a convex hull classification algorithm with leave-one-subject-out cross-validation to assess their predictive value for psychosis outcome. The canonical correlation between the speech features and prodromal symptom ratings was computed. RESULTS: Derived speech features included a Latent Semantic Analysis measure of semantic coherence and two syntactic markers of speech complexity: maximum phrase length and use of determiners (e.g., which). These speech features predicted later psychosis development with 100% accuracy, outperforming classification from clinical interviews. Speech features were significantly correlated with prodromal symptoms. CONCLUSIONS: Findings support the utility of automated speech analysis to measure subtle, clinically relevant mental state changes in emergent psychosis. Recent developments in computer science, including natural language processing, could provide the foundation for future development of objective clinical tests for psychiatry.
format Artículo
publishedVersion
author Bedi, Gillinder
Carrillo, Facundo
Cecchi, Guillermo A.
Fernández Slezak, Diego
Sigman, Mariano
Mota, Natália B.
Ribeiro, Sidarta
Javitt, Daniel C.
Copelli, Mauro
Corcoran, Cheryl M.
author_facet Bedi, Gillinder
Carrillo, Facundo
Cecchi, Guillermo A.
Fernández Slezak, Diego
Sigman, Mariano
Mota, Natália B.
Ribeiro, Sidarta
Javitt, Daniel C.
Copelli, Mauro
Corcoran, Cheryl M.
author_sort Bedi, Gillinder
title Automated analysis of free speech predicts psychosis onset in high-risk youths
title_short Automated analysis of free speech predicts psychosis onset in high-risk youths
title_full Automated analysis of free speech predicts psychosis onset in high-risk youths
title_fullStr Automated analysis of free speech predicts psychosis onset in high-risk youths
title_full_unstemmed Automated analysis of free speech predicts psychosis onset in high-risk youths
title_sort automated analysis of free speech predicts psychosis onset in high-risk youths
publishDate 2018
url https://doi.org/10.1038/npjschz.2015.30
https://repositorio.utdt.edu/handle/20.500.13098/11075
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