Capturing Motor Signs in Psychosis: How the New Technologies Can Improve Assessment and Treatment?
Motor signs are critical features of psychosis that remain underutilized in clinical practice. These signs, including social motor behaviors, mechanistically relevant motor signs, and other motor abnormalities, have demonstrated potential as biomarkers for early detection and intervention. However,...
| Published in: | Schizophrenia Bulletin Vol. 51; no. 4; pp. 845 - 852 |
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| Main Authors: | , |
| Format: | tables/charts Journal Article |
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Oxford University Press / USA
Jul2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186630334&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186630334 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 05867614 2CZ jtl: Schizophrenia Bulletin issn: 05867614 maglogo: N pubinfo: dt: Jul2025 vid: 51 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 186630334 186630334 186630334 10.1093/schbul/sbaf010 186630334 ppf: 845 ppct: 7 formats: tig: atl: Capturing Motor Signs in Psychosis: How the New Technologies Can Improve Assessment and Treatment? aug: au: Lozano-Goupil, Juliette Mittal, Vijay A affil: Department of Psychology, Northwestern University, Evanston, IL 60208, United States sug: subj: Psychotic Disorders Diagnosis Biological Markers Motor Skills Social Behavior Technology, Medical Psychotic Disorders Therapy Patient Assessment Early Diagnosis ab: Motor signs are critical features of psychosis that remain underutilized in clinical practice. These signs, including social motor behaviors, mechanistically relevant motor signs, and other motor abnormalities, have demonstrated potential as biomarkers for early detection and intervention. However, their application in clinical settings remains limited due to challenges such as cost, accessibility, and integration into clinical workflows. Recent advancements in related research fields, such as Human Movement Sciences and Affective Computing , offer promising solutions, enabling scalable and precise measurement of patients motor signs. In this editorial, we explore the spectrum of motor signs and highlight the evolving role of motor assessments in psychosis research. By examining traditional assessment methods alongside alternative and innovative tools, we underscore the potential of leveraging technology and methodology to bridge the gap between research and clinical application, ultimately advancing personalized care and improving outcomes. pubtype: Academic Journal doctype: tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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