Alex S Cohen1, Brita Elvevåg. 1. aDepartment of Psychology, Louisiana State University, Baton Rouge, Louisiana, USA bPsychiatry Research Group, Department of Clinical Medicine, University of Tromsø cThe Norwegian Centre for Integrated Care and Telemedicine (NST), University Hospital of North Norway, Tromsø, Norway.
Abstract
PURPOSE OF REVIEW: Disturbances in communication are a hallmark feature of severe mental illnesses. Recent technological advances have paved the way for objectifying communication using automated computerized semantic, linguistic and acoustic analyses. We review recent studies applying various computer-based assessments to the natural language produced by adult patients with severe mental illness. RECENT FINDINGS: Automated computerized methods afford tools with which it is possible to objectively evaluate patients in a reliable, valid and efficient manner that complements human ratings. Crucially, these measures correlate with important clinical measures. The clinical relevance of these novel metrics has been demonstrated by showing their relationship to functional outcome measures, their in-vivo link to classic 'language' regions in the brain, and, in the case of linguistic analysis, their relationship to candidate genes for severe mental illness. SUMMARY: Computer-based assessments of natural language afford a framework with which to measure communication disturbances in adults with severe mental illnesses. Emerging evidence suggests that they can be reliable and valid, and overcome many practical limitations of more traditional assessment methods. The advancement of these technologies offers unprecedented potential for measuring and understanding some of the most crippling symptoms of some of the most debilitating illnesses known to humankind.
PURPOSE OF REVIEW: Disturbances in communication are a hallmark feature of severe mental illnesses. Recent technological advances have paved the way for objectifying communication using automated computerized semantic, linguistic and acoustic analyses. We review recent studies applying various computer-based assessments to the natural language produced by adult patients with severe mental illness. RECENT FINDINGS: Automated computerized methods afford tools with which it is possible to objectively evaluate patients in a reliable, valid and efficient manner that complements human ratings. Crucially, these measures correlate with important clinical measures. The clinical relevance of these novel metrics has been demonstrated by showing their relationship to functional outcome measures, their in-vivo link to classic 'language' regions in the brain, and, in the case of linguistic analysis, their relationship to candidate genes for severe mental illness. SUMMARY: Computer-based assessments of natural language afford a framework with which to measure communication disturbances in adults with severe mental illnesses. Emerging evidence suggests that they can be reliable and valid, and overcome many practical limitations of more traditional assessment methods. The advancement of these technologies offers unprecedented potential for measuring and understanding some of the most crippling symptoms of some of the most debilitating illnesses known to humankind.
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Authors: Katherine Holshausen; Philip D Harvey; Brita Elvevåg; Peter W Foltz; Christopher R Bowie Journal: Cortex Date: 2013-02-19 Impact factor: 4.027
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Authors: Alex S Cohen; Taylor Fedechko; Elana K Schwartz; Thanh P Le; Peter W Foltz; Jared Bernstein; Jian Cheng; Elizabeth Rosenfeld; Brita Elvevåg Journal: Community Ment Health J Date: 2019-06-01
Authors: Alex S Cohen; Elana Schwartz; Thanh Le; Tovah Cowan; Christopher Cox; Raymond Tucker; Peter Foltz; Terje B Holmlund; Brita Elvevåg Journal: World Psychiatry Date: 2020-02 Impact factor: 49.548
Authors: Alex S Cohen; Kyle R Mitchell; Gregory P Strauss; Jack J Blanchard; Robert W Buchanan; Deanna L Kelly; James Gold; Robert P McMahon; Heather A Adams; William T Carpenter Journal: Schizophr Res Date: 2017-01-25 Impact factor: 4.939
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