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自闭症谱系障碍的行为学研究方法。

Ethological approach to autism spectrum disorders.

作者信息

Pegoraro Luiz F L, Setz Eleonore Z F, Dalgalarrondo Paulo

机构信息

Department of Psychiatry and Pediatric Research Center, University of Campinas, Brazil.

Department of Animal Biology, University of Campinas, Brazil.

出版信息

Evol Psychol. 2014 Mar 26;12(1):223-44. doi: 10.1177/147470491401200116.

DOI:10.1177/147470491401200116
PMID:25299761
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10481087/
Abstract

The purpose of the study was to develop a new ethogram for the assessment of children and adolescents with autism spectrum disorders (ASD) and intellectual developmental disorder (IDD) and to test whether this instrument accurately distinguishes ASD participants (n = 61) from IDD participants (n = 61). An ethogram with 88 behavior elements was generated, including body postures, verbalizations, facial expressions, motor stereotypies, head postures, gaze behavior, gestures, and interpersonal distance. Significant differences were detected between both groups in classic ASD behaviors; in behaviors that are deficient in ASD according to established theoretical models, such as symbolic play, gaze direction, gaze following, and use of mental state language; in atypical behaviors that have also been described previously in ethological studies with ASD; and in the nonspecific behaviors of ASD, such as walk, look own body, explore, and cry. The predictive success of a diagnosis of ASD in the logistic regression model with the ethogram's factors was 98.4%. The results suggest that this ethogram is a powerful and useful tool for both the detailed study of the social behaviors of autistic children and adolescents, and for discriminating ASD and IDD.

摘要

本研究的目的是开发一种用于评估自闭症谱系障碍(ASD)和智力发育障碍(IDD)儿童及青少年的新行为图谱,并测试该工具能否准确区分ASD参与者(n = 61)和IDD参与者(n = 61)。生成了一个包含88个行为要素的行为图谱,包括身体姿势、言语表达、面部表情、运动刻板行为、头部姿势、注视行为、手势和人际距离。在经典的ASD行为方面,两组之间检测到显著差异;在根据既定理论模型ASD中缺乏的行为方面,如象征性游戏、注视方向、注视跟随和心理状态语言的使用;在先前动物行为学研究中也描述过的ASD非典型行为方面;以及在ASD的非特异性行为方面,如行走、看自己的身体、探索和哭泣。在包含行为图谱因素的逻辑回归模型中,ASD诊断的预测成功率为98.4%。结果表明,这种行为图谱对于深入研究自闭症儿童和青少年的社会行为以及区分ASD和IDD都是一种强大且有用的工具。

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