Testing a theory-driven factor structure of the autism-spectrum quotient

The Autism-Spectrum Quotient (AQ) is a popular instrument used to assess the degree to which individuals exhibit features of autism spectrum conditions (ASC). The current study aimed to develop a theory-driven factor structure of the AQ that would fit as well across samples as the 12 previously proposed factor structures, all of which, except for the original Baron-Cohen model, had been developed on the basis of exploratory factor analysis (EFA) or principal component analysis. We first proposed a six-factor solution: (1) social anhedonia; (2) interest in details/patterns; (3) imagination ability; (4) desire for predictability/routine; (5) social cognition; and (6) social discourse convention. We tested the six-factor structure and made final item selections (27 items) with EFA using data from college students (n = 503). Then, we empirically tested alternative factor structure models in three other independent samples (ns = 503; 1263; 1641) using confirmatory factor analysis. Results indicated that our model fit as well, if not better, than all of the other models across samples, regardless of parameter estimation methods and software packages. Overall, the theory-driven replicable six-factor structure that we report holds the potential to be used to measure the six domains of features that we identified in the AQ. Lay Summary: Questionnaire measures of autism spectrum conditions have typically been used to measure approximately four broad dimensions. Our study suggests that the Autism-Spectrum Quotient can be used to measure six more narrowly defined dimensions: social anhedonia, interest in details/patterns, imagination ability, desire for predictability/routine, social cognition, and social discourse convention. Additional work is needed to develop measures of a much wider variety of autism spectrum features.