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Therapy for Childhood Apraxia of Speech Through a Dynamic Systems Lens: A Tutorial.

  • Published In: Journal of Speech, Language & Hearing Research, 2025, v. 68, n. 10. P. 4567 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lim, Jacqueline; McCabe, Patricia; Purcell, Alison 3 of 3

Abstract

Purpose: Dynamic Systems Theory (DST) has been used as a foundational lens through which to observe and understand child development and disorders. Childhood apraxia of speech (CAS) is a motor planning speech disorder that can be difficult to treat. This tutorial outlines how a DST framework can be used to understand the therapy process for children with CAS, thus aiding clinicians to provide more individualized and focused therapy for these children. Method: This tutorial will focus on three concepts from DST that may have relevance for CAS related therapy. These are: (a) multicausality, (b) variability, and (c) self-organization. This tutorial will describe DST and demonstrate its usefulness in understanding the therapy process in children with CAS through a case study that outlines how the application of a dynamic systems framework can enhance the clinical practice of speech-language pathologists. Conclusions: DST can be a useful theoretical framework to apply when attempting to understand the nature of a child's presentation of CAS. This can then be used to develop individualized and flexible treatment plans that help to support the child through developmental change. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Speech, Language & Hearing Research. 2025/10, Vol. 68, Issue 10, p4567
  • Document Type:Article
  • Subject Area:Psychology
  • Publication Date:2025
  • ISSN:1092-4388
  • DOI:10.1044/2025_JSLHR-25-00024
  • Accession Number:188657759
  • 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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