Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis


Autoria(s): Mota, Natalia B.; Vasconcelos, Nivaldo A. P.; Lemos, Nathalia; Pieretti, Ana C.; Filho, Osame Kinouchi; Cecchi, Guillermo A.; Copelli, Mauro; Ribeiro, Sidarta
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

14/10/2013

14/10/2013

2012

Resumo

Background: Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. Methodology/Principal Findings: To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. Conclusions/Significance: The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.

FINEP [01.06.1092.00]

FINEP

CNPq Universal [481506/2007-1]

CNPq Universal

CNPq

CNPq

Capes

CAPES

ad Associacao Alberto Santos Dumont para Apoio a Pesquisa (AASDAP)

a'd Associacao Alberto Santos Dumont para Apoio a Pesquisa (AASDAP)

Identificador

PLOS ONE, SAN FRANCISCO, v. 7, n. 4, supl. 1, Part 2, pp. 1-12, APR 9, 2012

1932-6203

http://www.producao.usp.br/handle/BDPI/34363

10.1371/journal.pone.0034928

http://dx.doi.org/10.1371/journal.pone.0034928

Idioma(s)

eng

Publicador

PUBLIC LIBRARY SCIENCE

SAN FRANCISCO

Relação

PLOS ONE

Direitos

openAccess

Copyright PUBLIC LIBRARY SCIENCE

Palavras-Chave #STRUCTURED CLINICAL INTERVIEW #RELIABILITY #NETWORKS #MULTIDISCIPLINARY SCIENCES
Tipo

article

original article

publishedVersion