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      Small Words That Matter: Linguistic Style and Conceptual Disorganization in Untreated First-Episode Schizophrenia

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          Abstract

          This study aimed to shed light on the linguistic style affecting the communication discourse in first-episode schizophrenia (FES) by investigating the analytic thinking index in relation to clinical scores of conceptual and thought disorganization (Positive and Negative Syndrome Scale, PANSS-P2 and Thought and Language Index, TLI). Using robust Bayesian modeling, we report three major findings: (1) FES subjects showed reduced analytic thinking, exhibiting a less categorical linguistic style than healthy control (HC) subjects (Bayes factor, BF 10 > 1000), despite using the same proportion of function and content words as HCs; (2) the lower the analytic thinking score, the higher the symptoms scores of conceptual disorganization (PANSS-P2, BF = 22.66) and global disorganization of thinking (TLI, BF 10 = 112.73); (3) the linguistic style is a better predictor of conceptual disorganization than the cognitive measure of processing speed in schizophrenia (SZ). These findings provide an objectively detectable linguistic style with a focus on Natural Language Processing Analytics of transcribed speech samples of patients with SZ that require no clinical judgment. These findings also offer a crucial insight into the primacy of linguistic structural disruption in clinically ascertained disorganized thinking in SZ. Our work contributes to an emerging body of literature on the psychopathology of SZ using a first-order lexeme-level analysis and a hypothesis-driven approach. At a utilitarian level, this has implications for improving educational and social outcomes in patients with SZ.

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          Most cited references66

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          How to grow a mind: statistics, structure, and abstraction.

          In coming to understand the world-in learning concepts, acquiring language, and grasping causal relations-our minds make inferences that appear to go far beyond the data available. How do we do it? This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of flexibly structured representations can address some of the deepest questions about the nature and origins of human thought: How does abstract knowledge guide learning and reasoning from sparse data? What forms does our knowledge take, across different domains and tasks? And how is that abstract knowledge itself acquired?
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            Psychological aspects of natural language. use: our words, our selves.

            The words people use in their daily lives can reveal important aspects of their social and psychological worlds. With advances in computer technology, text analysis allows researchers to reliably and quickly assess features of what people say as well as subtleties in their linguistic styles. Following a brief review of several text analysis programs, we summarize some of the evidence that links natural word use to personality, social and situational fluctuations, and psychological interventions. Of particular interest are findings that point to the psychological value of studying particles-parts of speech that include pronouns, articles, prepositions, conjunctives, and auxiliary verbs. Particles, which serve as the glue that holds nouns and regular verbs together, can serve as markers of emotional state, social identity, and cognitive styles.
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              Overlooking the obvious: a meta-analytic comparison of digit symbol coding tasks and other cognitive measures in schizophrenia.

              In focusing on potentially localizable cognitive impairments, the schizophrenia meta-analytic literature has overlooked the largest single impairment: on digit symbol coding tasks. To compare the magnitude of the schizophrenia impairment on coding tasks with impairments on other traditional neuropsychological instruments. MEDLINE and PsycINFO electronic databases and reference lists from identified articles. English-language studies from 1990 to present, comparing performance of patients with schizophrenia and healthy controls on coding tasks and cognitive measures representing at least 2 other cognitive domains. Of 182 studies identified, 40 met all criteria for inclusion in the meta-analysis. Means, standard deviations, and sample sizes were extracted for digit symbol coding and 36 other cognitive variables. In addition, we recorded potential clinical moderator variables, including chronicity/severity, medication status, age, and education, and potential study design moderators, including coding task variant, matching, and study publication date. Main analyses synthesized data from 37 studies comprising 1961 patients with schizophrenia and 1444 comparison subjects. Combination of mean effect sizes across studies by means of a random effects model yielded a weighted mean effect for digit symbol coding of g = -1.57 (95% confidence interval, -1.66 to -1.48). This effect compared with a grand mean effect of g = -0.98 and was significantly larger than effects for widely used measures of episodic memory, executive functioning, and working memory. Moderator variable analyses indicated that clinical and study design differences between studies had little effect on the coding task effect. Comparison with previous meta-analyses suggested that current results were representative of the broader literature. Subsidiary analysis of data from relatives of patients with schizophrenia also suggested prominent coding task impairments in this group. The 5-minute digit symbol coding task, reliable and easy to administer, taps an information processing inefficiency that is a central feature of the cognitive deficit in schizophrenia and deserves systematic investigation.
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                Author and article information

                Contributors
                Journal
                Schizophr Bull Open
                Schizophr Bull Open
                schizbullopen
                Schizophrenia Bulletin Open
                Oxford University Press (US )
                2632-7899
                January 2021
                15 March 2021
                15 March 2021
                : 2
                : 1
                : sgab010
                Affiliations
                [1 ] Robarts Research Institute , London, ON, Canada
                [2 ] Department of Psychiatry, University of Western Ontario , London, ON, Canada
                [3 ] Lawson Health Research Institute , London, ON, Canada
                [4 ] Department of Medical Biophysics, University of Western Ontario , London, ON, Canada
                [5 ] The Brain and Mind Institute, University of Western Ontario , London, ON, Canada
                Author notes
                To whom correspondence should be addressed; Robarts Research Institute, 1151 Richmond Street N, London, ON, Canada N6A 5B7; fax: 5199315789, e-mail: asilva43@ 123456uwo.ca
                Author information
                https://orcid.org/0000-0002-0388-4425
                https://orcid.org/0000-0002-4838-9567
                https://orcid.org/0000-0003-1640-7182
                Article
                sgab010
                10.1093/schizbullopen/sgab010
                8072135
                33937775
                8cad05a7-e063-4ec4-93f2-f4c657ddbbeb
                © The Author(s) 2021. Published by Oxford University Press on behalf of the University of Maryland's school of medicine, Maryland Psychiatric Research Center.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 26 April 2021
                Page count
                Pages: 10
                Funding
                Funded by: Canadian Institutes of Health Research, DOI 10.13039/501100000024;
                Award ID: 375104/2017
                Funded by: Academic Medical Organization of Southwestern Ontario Opportunities Fund;
                Funded by: Bucke Family Fund;
                Funded by: Chrysalis Foundation, DOI 10.13039/100002734;
                Categories
                Regular Articles
                AcademicSubjects/MED00800

                first-episode schizophrenia,formal thought disorder,speech–language impairment,natural language processing analytics,linguistic style

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