Objectives: It is well established that children with ASD may experience difficulties with language, however, many have only focused on identifying the specific areas of difficulties. To better inform language interventions, it is important to understand the underlying factors that influence specific language profiles. The inconsistency with English language structure, form, meaning, and usage creates a difficult medium for children with ASD to engage in communication, particularly if being driven by local features or set rules. The current study examined the role of cognitive biases on language development in ASD.
Methods: Children between 7 and 11 years of age with and without an ASD diagnosis (i.e., High-Functioning Autism, Asperger Syndrome) were included in the study. Two sets of measures were administered to assess cognitive biases. Weak Central Coherence measures included the Children’s Embedded Figures Test (CEFT; Witkin, Oltman, Raskin, & Karp, 1971) and the Sentence Completion Task (SCT; Booth & Happé, 2010). These measures provided an assessment of visual and linguistic local processing. Systemizing measures included the Systemizing Quotient- Child Version (SQ-C; Auyeung et al., 2009) and the Picture Sequencing Test (PST; Baron-Cohen, Leslie & Frith, 1986). These measures provided an assessment of rule-based processing. To evaluate children’s language profiles, the Core Language subtests of the Clinical Evaluation of Language Fundamentals – 4 (CELF-4; Semel, Wiig, & Secord, 2003) were administered. Parent-reported autism traits were evaluated using the Autism Spectrum Quotient – Child Version (ASQ). All tasks were administered in one session.
Results: Following the procedure used by Loth, Gomez, and Happé (2008), composite scores were created for local processing based on the CEFT and the SCT and for systemizing based on the SQ-C and the PST. Preliminary analyses suggest that there may be distinct underlying factors that influence language development in children with ASD. The Systemizing Composite was a significant predictor of core language abilities in children with HFA, R2 = .532, F(1, 7) = 7.968, p<.05. However, parent-reported autism traits were the only significant predictor of core language abilities in children with AS, R2 = .768, F(1, 9) = 32.959, p<.001. Further analyses will evaluate specific language components assessed within the core subtests of the CELF-4 (e.g., morphology, syntax, semantics).
Conclusions: The preliminary results suggest that children with HFA may be utilizing more systematic approaches in their linguistic abilities. Therefore it is important to include rule-based strategies in the intervention plans and curriculum for children with HFA.
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