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精神分裂症患者手部和面部运动异常的仪器测量

An Instrumental Measure of Hand and Facial Movement Abnormalities in Patients With Schizophrenia.

作者信息

Wang Shu-Mei, Ouyang Wen-Chen, Hsu Hsiao-Man, Hsu Li-Ta

机构信息

Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.

Department of Geriatric Psychiatry, Jianan Psychiatric Center, Ministry of Health and Welfare, Tainan, Taiwan.

出版信息

Front Psychiatry. 2022 Mar 4;13:803661. doi: 10.3389/fpsyt.2022.803661. eCollection 2022.

Abstract

INTRODUCTION

Movement disorders have been suggested to be a cardinal component of schizophrenia. With increased research interests in this area, instrumental measures are needed. This study was to examine if the motion capture system was reliable in measuring hand and facial bradykinesia and dyskinesia and more sensitive to detecting movement differences between schizophrenia patients and healthy people than traditional rating scales.

METHODS

Sixteen schizophrenia patients and 20 control subjects were recruited. Hand and facial bradykinesia and dyskinesia were measured using the motion capture system and rated using the Extrapyramidal Symptom Rating Scale and the Abnormal Involuntary Movement Scale.

RESULTS

The system showed strong test-retest reliability and generated larger effect sizes of group differences than did the rating scales.

CONCLUSIONS

The results may support researchers and clinical practitioners to apply the system to sensitively measuring the hand and facial movement symptoms in schizophrenia patients, which contributes to gaining a deep understanding of movement issues in schizophrenia.

摘要

引言

运动障碍被认为是精神分裂症的一个主要组成部分。随着该领域研究兴趣的增加,需要一些仪器测量方法。本研究旨在检验动作捕捉系统在测量手部和面部运动迟缓及运动障碍方面是否可靠,以及与传统评分量表相比,在检测精神分裂症患者和健康人之间的运动差异时是否更敏感。

方法

招募了16名精神分裂症患者和20名对照受试者。使用动作捕捉系统测量手部和面部运动迟缓及运动障碍,并使用锥体外系症状评定量表和异常不自主运动量表进行评分。

结果

该系统显示出很强的重测信度,并且与评分量表相比,产生了更大的组间差异效应量。

结论

研究结果可能支持研究人员和临床医生应用该系统来敏感地测量精神分裂症患者的手部和面部运动症状,这有助于深入了解精神分裂症中的运动问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7180/8931260/adef410e7147/fpsyt-13-803661-g0001.jpg

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