Speech disturbances in schizophrenia: Assessing cross-linguistic generalizability of NLP automated measures of coherence

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AJ4S7FNRZ" target="_blank" >RIV/00216208:11320/23:J4S7FNRZ - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135345352&doi=10.1016%2fj.schres.2022.07.002&partnerID=40&md5=bd6bc364c8a5f370b0d06e56c113e22a" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135345352&doi=10.1016%2fj.schres.2022.07.002&partnerID=40&md5=bd6bc364c8a5f370b0d06e56c113e22a</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.schres.2022.07.002" target="_blank" >10.1016/j.schres.2022.07.002</a>

Result language

angličtina

Original language name

Speech disturbances in schizophrenia: Assessing cross-linguistic generalizability of NLP automated measures of coherence

Original language description

"Introduction: Language disorders – disorganized and incoherent speech in particular - are distinctive features of schizophrenia. Natural language processing (NLP) offers automated measures of incoherent speech as promising markers for schizophrenia. However, the scientific and clinical impact of NLP markers depends on their generalizability across contexts, samples, and languages, which we systematically assessed in the present study relying on a large, novel, cross-linguistic corpus. Methods: We collected a Danish (DK), German (GE), and Chinese (CH) cross-linguistic dataset involving transcripts from 187 participants with schizophrenia (111DK, 25GE, 51CH) and 200 matched controls (129DK, 29GE, 42CH) performing the Animated Triangles Task. Fourteen previously published NLP coherence measures were calculated, and between-groups differences and association with symptoms were tested for cross-linguistic generalizability. Results: One coherence measure, i.e. second-order coherence, robustly generalized across samples and languages. We found several language-specific effects, some of which partially replicated previous findings (lower coherence in German and Chinese patients), while others did not (higher coherence in Danish patients). We found several associations between symptoms and measures of coherence, but the effects were generally inconsistent across languages and rating scales. Conclusions: Using a cumulative approach, we have shown that NLP findings of reduced semantic coherence in schizophrenia have limited generalizability across different languages, samples, and measures. We argue that several factors such as sociodemographic and clinical heterogeneity, cross-linguistic variation, and the different NLP measures reflecting different clinical aspects may be responsible for this variability. Future studies should take this variability into account in order to develop effective clinical applications targeting different patient populations. © 2022 The Authors"

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

"Schizophrenia Research"

ISSN

0920-9964

e-ISSN

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Volume of the periodical

259

Issue of the periodical within the volume

2023

Country of publishing house

US - UNITED STATES

Number of pages

12

Pages from-to

59-70

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85135345352