613
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Video self-modeling for reducing vocal stereotypy in children with autism spectrum disorder (ASD)

&
Pages 322-337 | Received 02 Jan 2015, Accepted 11 Sep 2015, Published online: 19 Oct 2015
 

ABSTRACT

Video self-modeling (VSM) is a promising intervention strategy for teaching a variety of novel skills to children with autism spectrum disorders (ASD). The present study provides preliminary effects of VSM on reducing the vocal stereotypy of children with ASD. Two children participated and experimental control was achieved using a multiple-baseline across subjects design. Results were highly encouraging with one of the participants who showed a large reduction of his vocal stereotypy. Also, the intervention gains were successfully generalized across stimuli, people, and settings and maintained at 2-month follow-up assessment. However, for the other participant, the intervention was interrupted prematurely as he showed stressful reactions in relation to the videos that were presented as part of the intervention. Possible mechanisms for the success of this procedure are discussed as well as implications for its use in educational settings and areas for further research.

Acknowledgements

A special thanks is extended to the children and their families who participated in this study as well as to the anonymous reviewers of the manuscript for their valuable comments. Moreover, we would like to thank all members of staff at the school for their assistance.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 336.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.