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开发和验证一种阿拉伯语眼动追踪范式,用于在卡塔尔早期筛查和诊断自闭症谱系障碍。

Development and validation of an Arabic language eye-tracking paradigm for the early screening and diagnosis of autism spectrum disorders in Qatar.

机构信息

Neurological Disorders Research Center, Qatar Biomedical Research Institute, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

Center for Autism, Cleveland Clinic, Cleveland, Ohio, USA.

出版信息

Autism Res. 2023 Dec;16(12):2291-2301. doi: 10.1002/aur.3046. Epub 2023 Nov 27.

Abstract

Abnormal eye gaze is a hallmark characteristic of autism spectrum disorder (ASD). The primary aim of the present research was to develop an Arabic version of an objective measure of ASD, the "autism index" (AI), based on eye gaze tracking to social and nonsocial stimuli validated initially in the United States. The initial phase of this study included the translation of English language eye-tracking stimuli into stimuli appropriate for an Arabic-speaking culture. During the second phase, we tested it on a total of 144 children with ASD, and 96 controls. The AI had excellent internal consistency and test-retest reliability. Moreover, the AI showed good differentiation of ASD from control cases (AUC = 0.730, SE = 0.035). The AI was significantly positively correlated with SCQ total raw scores (r = 0.46, p < 0.001). ADOS-2 scores were only available in the ASD group and did not show a significant relationship with AI scores (r = 0.10, p = 0.348), likely due to the restricted range. The AI, when implemented using Arabic-translated stimuli in a Qatari sample, showed good diagnostic differentiation and a strong correlation with parent-reported ASD symptoms. Thus, the AI appears to have cross-cultural validity and may be useful as a diagnostic aide to inform clinical judgment and track ASD symptom levels as part of the evaluation process.

摘要

异常的目光注视是自闭症谱系障碍(ASD)的一个显著特征。本研究的主要目的是开发一种基于眼球追踪的自闭症客观测量方法的阿拉伯语版本,即“自闭症指数”(AI),该方法最初在美国经过验证,可用于评估社会和非社会刺激。本研究的初始阶段包括将英语眼动追踪刺激翻译成适合阿拉伯语文化的刺激。在第二阶段,我们对总共 144 名自闭症儿童和 96 名对照组进行了测试。AI 具有良好的内部一致性和重测信度。此外,AI 能够很好地区分自闭症和对照组(AUC=0.730,SE=0.035)。AI 与 SCQ 总分呈显著正相关(r=0.46,p<0.001)。ADOS-2 评分仅在自闭症组中可用,与 AI 评分无显著相关性(r=0.10,p=0.348),这可能是由于评分范围有限。当在卡塔尔样本中使用阿拉伯语翻译的刺激实施 AI 时,它显示出良好的诊断区分度,并与家长报告的自闭症症状强烈相关。因此,AI 似乎具有跨文化有效性,可作为一种诊断辅助工具,用于辅助临床判断和跟踪自闭症症状水平,作为评估过程的一部分。

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本文引用的文献

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Development of an Objective Autism Risk Index Using Remote Eye Tracking.利用远程眼动追踪技术开发客观自闭症风险指数
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