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Expressive Language Profiles in a Clinical Screening Sample of Mandarin-Speaking Preschool Children With Autism Spectrum Disorder.

  • Published In: Journal of Speech, Language & Hearing Research, 2023, v. 66, n. 11. P. 4497 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Li, Li; Yi (Esther) Su; Wenwen Hou; Muyu Zhou; Yixiang Xie; Xiaobing Zou; Ming Li 3 of 3

Abstract

urpose: This cross-sectional study aimed to depict expressive language profiles and clarify lexical–grammatical interrelationships in Mandarin-speaking preschoolers with autism spectrum disorder (ASD) during the administration of the simplified Chinese Psychoeducational Profile–Third Edition screening. Method: We collected naturalistic language samples from 81 (74 boys, seven girls) 2- to 7-year-old (Mage = 55.6 months, SD = 15.17) Mandarin-speaking children with ASD in clinician–child interactions. The child participants were divided into five age subgroups with 12-month intervals according to their chronological age. Computer-assisted part-of-speech tagging, constituency analysis, and dependency analysis addressed the developmental trajectories of early lexical and grammatical growth in each age subgroup. Results: Significant within-ASD differences were observed in content words, function words, and lexical categories. Nouns and verbs were the predominant lexical categories, while noun types overwhelmed verb types in children over 3 years old. The grammatical development of 5- to 6-year-old Mandarinspeaking children with ASD was better than that of 3- to 4-year-old children. The trends of syntactic structures, grammatical relations, and grammatical complexity in each age group were similar. Conclusions: Mandarin-speaking preschoolers with ASD produce more lexicons with increasing age. They preserve the noun bias as a universal mechanism in early lexical learning. Moreover, their developmental trajectories of grammatical growth were comparable in each age subgroup. In addition, their lexicons and grammar were synchronically developed during early language acquisition. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Speech, Language & Hearing Research. 2023/11, Vol. 66, Issue 11, p4497
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2023
  • ISSN:1092-4388
  • DOI:10.1044/2023_JSLHR-23-00184
  • Accession Number:173573534
  • Copyright Statement:Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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