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使用自然语言样本和标准化测量预测 ASD 儿童的语言。

Predicting Language in Children with ASD Using Spontaneous Language Samples and Standardized Measures.

机构信息

Department of Psychological Sciences, University of Connecticut, Bousfield Psychology Building, 406 Babbidge Road Unit 1020, Storrs, CT, 06269, USA.

Speech, Language, and Hearing Sciences, University of Connecticut, Storrs, CT, USA.

出版信息

J Autism Dev Disord. 2023 Oct;53(10):3916-3931. doi: 10.1007/s10803-022-05691-z. Epub 2022 Aug 5.

Abstract

This longitudinal study examined the degree to which standardized measures of language and natural language samples predicted later language usage in a heterogeneous sample of children with autism spectrum disorder (ASD), and how this relationship is impacted by ASD severity and interventions. Participants with a diagnosis of ASD (N = 54, 41 males) completed standardized assessments of language and social functioning; natural language samples were transcribed from play-based interactions. Findings indicated that standardized language measures, natural language measures, and ADOS severity were each unique predictors of later lexical use. Intervention types also appeared to impact later language; in particular, participation in mainstream inclusion accounted for significant amounts of variance in children's mean length of utterance at T3.

摘要

本纵向研究考察了标准化语言测量和自然语言样本在多大程度上可以预测自闭症谱系障碍(ASD)儿童异质样本中随后的语言使用情况,以及这种关系如何受到 ASD 严重程度和干预措施的影响。54 名被诊断为 ASD 的参与者(41 名男性)完成了语言和社会功能的标准化评估;自然语言样本是从基于游戏的互动中转录的。研究结果表明,标准化语言测量、自然语言测量和 ADOS 严重程度都是随后词汇使用的独特预测因素。干预类型似乎也对后期语言产生影响;特别是,在主流融合中参与的程度解释了儿童在 T3 时的平均话语长度的显著差异。

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