The Theory of Mind (ToM) impairment is one of the best-studied theories explaining ASD. However, the severity in which such deficit may impact in other cognitive abilities remains largely unexplored. Scheuffgen et al. (2000) found that low‑functioning individuals with ASD (as measured by the Wechsler scales of intelligence) performed as well as TD controls in a simple Inspection Time (IT) task, known to correlate around -.50 with intelligence in TD individuals (Grudnik & Kranzler, 2001). Following the Minimal Cognitive Architecture model of intelligence (Anderson, 1992), the authors proposed that g (as measured with an IT task) remains intact in individuals with ASD, alongside a damaged ToM external module necessary to perform typically. A replication by Wallace et al. (2009) found this to be the case in low-, but not high-, functioning individuals with ASD, suggesting an increasing disparity between IT and intelligence with decreasing IQ.
Objectives:
In order to provide the appropriate level of education and support, it is paramount to know whether psychometric or cognitive tools accurately reveal the intellectual potential of low-functioning individuals with ASD and what variables may mediate any discrepancies. This study set out to explore the impact of ToM deficits on the discrepancy between cognitive and social psychometric intelligence measures in ASD. Furthermore, it was examined whether this discrepancy is specific to ASD or an expression of their global Intellectual Disability (ID).
Methods:
25 individuals with ASD+ID and 35 with ID alone (CA 8 to 19 years) completed the Coloured Progressive Matrices (CPM) and a visual IT task. Due to the severity of their intellectual impairment, materials for both tasks were adapted to match their ability levels. ToM measures consisted of the Penny Hiding Game, the updated Interactive and Active Sociability scales and the Vineland scales of adaptive behaviour. Lastly, they were assessed on the British Picture Vocabulary Scales (BPVS).
Results:
Overall, the ASD group performed faster on the IT task than the ID group even when IQ‑matched (14 ASD and 14 ID; z = 2.09, p = .04). CA was highly correlated with VIQ (from BPVS; r = -.72; p < .001) and PIQ (from CPM; r = -.81; p < .001) in the ID group but not in the ASD group. Supporting predictions, a discrepancy between crystallized (VIQ) and fluid measures of intelligence (IT) correlated moderate to highly with all social measures (including those measuring ToM; all p < .001) in the ASD group, but not in the ID group. Also, a strong directionality effect (higher PIQ than VIQ) was found in the ASD group.
Conclusions:
The findings suggest intact processing speed and potential intelligence in ASD, which is not tapped by socially mediated tools, or measures of crystallized intelligence, and supports previous studies where ASD individuals outperformed IQ‑matched ID individuals in the IT task. Furthermore, the strong directionality of the ASD group towards the PIQ in contrast to the ID group supports the strong differences between groups in terms of IQ profiles. This could have future implications in which ASD is assessed and conceptualized.
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