Derek J Dean1, Alayna T Samson2, Raeana Newberry3, Vijay A Mittal4. 1. University of Colorado Boulder, Department of Psychology and Neuroscience, Boulder, CO, USA; University of Colorado Boulder, Center for Neuroscience, Boulder, CO, USA. Electronic address: derek.dean@colorado.edu. 2. Children's Hospital Colorado, Denver, CO, USA. 3. University of Colorado Boulder, Department of Psychology and Neuroscience, Boulder, CO, USA. 4. Northwestern University, Department of Psychology, Evanston, IL, USA; Northwestern University, Department of Psychiatry, Chicago, IL, USA; Northwestern University, Institute for Policy Research, Evanston, IL, USA; Northwestern University, Medical Social Sciences, Chicago, IL, USA.
Abstract
BACKGROUND: Growing evidence suggests that movement abnormalities occur prior to the onset of psychosis. Innovations in technology and software provide the opportunity for a fine-tuned and sensitive measurement of observable behavior that may be particularly useful to detecting the subtle movement aberrations present during the prodromal period. METHODS: In the present study, 54 youth at ultrahigh risk (UHR) for psychosis and 62 healthy controls participated in structured clinical interviews to assess for an UHR syndrome. The initial 15min of the baseline clinical interview was assessed using Motion Energy Analysis (MEA) providing frame-by-frame measures of total movement, amplitude, speed, and variability of both head and body movement separately. RESULTS: Result showed region-specific group differences such that there were no differences in head movement but significant differences in body movement. Specifically, the UHR group showed greater total body movement and speed of body movements, and lower variation in body movement compared to healthy controls. However, there were no significant associations with positive, negative or disorganized symptom domains. CONCLUSION: This study represents an innovative perspective on gross motor function in the UHR group. Importantly, the automated approach used in this study provides a sensitive and objective measure of body movement abnormalities, potentially guiding novel assessment and prevention of symptom development in those at risk for psychosis. Published by Elsevier B.V.
BACKGROUND: Growing evidence suggests that movement abnormalities occur prior to the onset of psychosis. Innovations in technology and software provide the opportunity for a fine-tuned and sensitive measurement of observable behavior that may be particularly useful to detecting the subtle movement aberrations present during the prodromal period. METHODS: In the present study, 54 youth at ultrahigh risk (UHR) for psychosis and 62 healthy controls participated in structured clinical interviews to assess for an UHR syndrome. The initial 15min of the baseline clinical interview was assessed using Motion Energy Analysis (MEA) providing frame-by-frame measures of total movement, amplitude, speed, and variability of both head and body movement separately. RESULTS: Result showed region-specific group differences such that there were no differences in head movement but significant differences in body movement. Specifically, the UHR group showed greater total body movement and speed of body movements, and lower variation in body movement compared to healthy controls. However, there were no significant associations with positive, negative or disorganized symptom domains. CONCLUSION: This study represents an innovative perspective on gross motor function in the UHR group. Importantly, the automated approach used in this study provides a sensitive and objective measure of body movement abnormalities, potentially guiding novel assessment and prevention of symptom development in those at risk for psychosis. Published by Elsevier B.V.
Entities:
Keywords:
Gross motor; Motion energy analysis; Movement abnormalities; Psychosis; Ultrahigh risk
Authors: Michael T Compton; Francisco Fantes; Claire Ramsay Wan; Stephanie Johnson; Elaine F Walker Journal: Psychiatry Res Date: 2015-01-12 Impact factor: 3.222
Authors: Ana Caroline Lopes-Rocha; Cheryl Mary Corcoran; Julio Cesar Andrade; Leonardo Peroni; Natalia Mansur Haddad; Lucas Hortêncio; Mauricio Henriques Serpa; Martinus Theodorus van de Bilt; Wagner Farid Gattaz; Alexandre Andrade Loch Journal: Schizophrenia (Heidelb) Date: 2022-09-16