SCHIZOPHRENIA RESEARCH | 卷:192 |
Automated analysis of written narratives reveals abnormalities in referential cohesion in youth at ultra high risk for psychosis | |
Article | |
Gupta, Tina1  Hespos, Susan J.1  Horton, William S.1  Mittal, Vijay A.1,2,3,4  | |
[1] Northwestern Univ, Dept Psychol, 2029 Sheridan Rd, Chicago, IL 60208 USA | |
[2] Northwestern Univ, Dept Psychiat, Chicago, IL 60208 USA | |
[3] Northwestern Univ, Inst Policy Res, Chicago, IL 60208 USA | |
[4] Northwestern Univ, Dept Med Social Sci, Chicago, IL 60208 USA | |
关键词: UHR; Coh-Metrix; Referential cohesion; Written narratives; Symptoms; Cognition; | |
DOI : 10.1016/j.schres.2017.04.025 | |
来源: Elsevier | |
【 摘 要 】
Schizophrenia and at-risk populations are suggested to exhibit referential cohesion deficits in language production (e.g., producing fewer pronouns or nouns that clearly link to concepts from previous sentences). Much of this work has focused on transcribed speech samples, while no work to our knowledge has examined referential cohesion in written narratives among ultra high risk (UHR) youth using Coh-Metrix, an automated analysis tool. In the present study, written narratives from 84 individuals (UHR = 41, control = 43) were examined. Referential cohesion variables and relationships with symptoms and relevant cognitive variables were also investigated. Findings reveal less word stem overlap in narratives produced by UHR youth compared to controls, and correlations with symptom domains and verbal learning. The present study highlights the potential usefulness of automated analysis of written narratives in identifying at-risk youth and these data provide critical information in better understanding the etiology of psychosis. As writing production is commonly elicited in educational contexts, markers of aberrant cohesion in writing represent significant potential for identifying youth who could benefit from further screening, and utilizing software that is easily accessible and free may provide utility in academic and clinical settings. (C) 2017 Elsevier B.V. All rights reserved.
【 授权许可】
Free
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