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dc.contributor.authorPintos, Andrea Stephanie
dc.contributor.authorHui, Christy Lai-Ming
dc.contributor.authorDe Deyne, Simon
dc.contributor.authorCheung, Charlton
dc.contributor.authorKo, Wai Tung
dc.contributor.authorNam, Suen Yi
dc.contributor.authorChan, Sherry Kit-Wa
dc.contributor.authorChang, Wing-Chung
dc.contributor.authorLee, Edwin Ho-Ming
dc.contributor.authorLo, Alison Wai-Fan
dc.contributor.authorLo, Tak-Lam
dc.contributor.authorElvevåg, Brita
dc.contributor.authorChen, Eric Yu-Hai
dc.date.accessioned2023-02-23T07:43:46Z
dc.date.available2023-02-23T07:43:46Z
dc.date.issued2022-08-24
dc.description.abstractThe underpinnings of language deviations in psychotic symptoms (eg, formal thought disorder, delusions) remain unclear. We examined whether the semantic networks underlying word associations are useful predictors of clinical outcomes in psychosis. Fifty-one patients with schizophrenia and other psychotic disorders and 51 matched healthy controls generated words in a Cantonese continued word association task. Patterns of word associations were examined using semantic similarity metrics derived from word embeddings (fastText) and the structure of individual semantic networks. A longitudinal design—baseline and 6 months later—enabled investigation of the relationship of changes in semantic associations in patients who were in an acute psychotic state at baseline compared to clinical stabilization 6 months later. The semantic similarity measure increased over time in patients, while it remained stable in controls. Moreover, the change in semantic similarity over time correlated with the changes in patients’ formal thought disorder symptoms. There were differences in individual semantic networks between the groups at both time points. Patients had less structured networks on average, as evidenced by a smaller network diameter and clustering coeffcient, and smaller average shortest path lengths. The identifcation of several state-like semantic measures that change over time with patients’ mental states allows for nuanced comparison with clinical measures. Semantic measures are complex. Semantic similarity was a state-like measure that changed over time with mental state in psychotic disorders, whereas individual semantic network parameters were trait-like and stable over time.en_US
dc.identifier.citationPintos, Hui, De Deyne, Cheung, Ko, Nam, Chan, Chang, Lee, Lo, Lo, Elvevåg, Chen. A Longitudinal Study of Semantic Networks in Schizophrenia and other Psychotic Disorders Using the Word Association Task. Schizophrenia Bulletin Open. 2022;3(1)en_US
dc.identifier.cristinIDFRIDAID 2103202
dc.identifier.doi10.1093/schizbullopen/sgac054
dc.identifier.issn2632-7899
dc.identifier.urihttps://hdl.handle.net/10037/28597
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.relation.journalSchizophrenia Bulletin Open
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0en_US
dc.rightsAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)en_US
dc.titleA Longitudinal Study of Semantic Networks in Schizophrenia and other Psychotic Disorders Using the Word Association Tasken_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)