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When Will He Talk? An Evidence-Based Tutorial for Measuring Progress Toward Use of Spoken Words in Preverbal Children With Autism Spectrum Disorder.

ABSTRACT: Purpose Professionals face substantial challenges determining whether and when children with autism spectrum disorder (ASD) who are not yet using spoken words will use spoken language as their primary means of communication. This tutorial provides speech-language pathologists with practical guidance on how to measure expressive language predictors for progress monitoring and making intervention decisions for children with ASD who are preverbal. Method This tutorial is a repackaging effort that seeks to make the research accessible to clinicians wishing to implement evidence-based practice. Results We describe intentional communication, consonant inventory in communication acts, and responding to joint attention as particularly valuable prelinguistic skills to measure. We explain how and when to efficiently assess progress using published assessments periodically and using brief (5-min) communication samples for more frequent progress monitoring. Conclusions Communication samples can be used to show how a child performs within a therapeutic setting during teaching (treatment data) and outside of the therapeutic setting (generalization probe data). Both types of data are critical for determining whether the child is exhibiting progress and which aspects of intervention are facilitating progress toward use of spoken words. These recommendations also balance the evidence for best practices for progress monitoring and the demands on clinicians' time and effort. To encourage the measurement of prelinguistic skills of children with ASD who are preverbal in clinical practice, we include (a) example data collection documents, (b) examples with hypothetical data and interpretation, and (c) guidance on communication sampling procedures. Supplemental Material https://doi.org/10.23641/asha.13557836.

SUBMITTER: McDaniel J

PROVIDER: S-EPMC8740598 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The central symptom of autism spectrum disorder (ASD) is deficiency in social communication, which is generally viewed as being caused by pragmatic impairment (PI). PI is difficulty in using language appropriately in social situations. Studies have confirmed that PI is the result of neurological, cognitive, linguistic, and sensorimotor dysfunctions involving intricately intertwined factors. To elucidate the whole picture of this impairment, an approach from a multifaceted perspective fusing those factors is necessary. To this end, comprehensive PI mapping is a must, since no comprehensive mapping has yet been developed. The aim of this research is to present a model of annotation scheme development and corpus construction to efficiently visualize and quantify for statistical investigation occurrences of PI, which enables comprehensive mapping of PI in the spoken language of Japanese ASD individuals. We constructed system networks (lexicogrammatical option systems speakers make choices from) in the theoretical framework of Systemic Functional Linguistics, from which we developed an annotation scheme to comprehensively cover PI. Since system network covers all possible lexicogrammatical choices in linguistic interaction, it enables a comprehensive view of where and in what lexicogrammar PI occurs. Based on this annotation scheme, we successfully developed the Corpus of ASD + Typically Developed Spoken Language consisting of texts from 1,187 audiotaped tasks performed by 186 ASD and 106 typically developed subjects, accommodating approximately 1.07 million morphemes. Moreover, we were successful in the automatization of the annotation process by machine learning, accomplishing a 90 percent precision rate. We exemplified the mapping procedure with a focus on the spoken use of negotiating particles. Our model corpus is applicable to any language by incorporating our method of constructing the annotation scheme, and would give impetus to defining PI from a cross-linguistic point of view, which is needed because PI of ASD reflects cross-linguistic differences.

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When Will He Talk? An Evidence-Based Tutorial for Measuring Progress Toward Use of Spoken Words in Preverbal Children With Autism Spectrum Disorder.

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