101
Views
0
CrossRef citations to date
0
Altmetric
Short Report

Predicting progress in Picture Exchange Communication System (PECS) use by children with autism

&
Received 16 Dec 2009, Accepted 08 Apr 2010, Published online: 10 Jun 2010
 

Abstract

Background: The Picture Exchange Communication System (PECS) is a widely used communication intervention for non-verbal children with autism spectrum disorder. Findings for the benefits of PECS have almost universally been positive, although there is very limited information about the characteristics of PECS users that determine the amount of progress that they are likely to make.

Aims: To explore the utility of using children's developmental age to predict the subsequent degree of progress using PECS.

Methods & Procedures: In a retrospective study, 23 non-verbal 5- and 6-year-old children with autism spectrum disorder attending a special school were assessed to determine their highest level of PECS ability. They were then allocated to one of two groups depending on whether or not they had mastered PECS phase III. All participants had been assessed using the Psycho-Educational Profile—Revised (PEP-R) on entry to the school and before being introduced to PECS. Total developmental age scores were examined to determine whether they accurately predicted membership of the two PECS ability groups.

Outcomes & Results: All the 16 children who had mastered PECS phase III had total developmental age scores of 16 months or above, whilst six of the seven children who had not progressed beyond phase III scored below 16 months—the other child had a score of 16 months.

Conclusions & Implications: The assessment of the developmental level of potential PECS users may provide valuable predictive information for speech-and-language therapists and other professionals in relation to the likely degree of progress and in setting realistic and achievable targets.

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

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.