B - 15 Additional Insights of the Factor Structure of the Autism Spectrum Adaptive Scale Questionnaire.

Abstract

Autism spectrum condition(s) (ASC) a neurodevelopmental disorder with limited research on the etiological basis. Thus, diagnoses are given based on an individual's behavior. However, the process of receiving a diagnosis can be difficult to procure. Having an accurate self-report scale for diagnosing ASC is important, and current scales have limitations. This study aims to assess the factor structure of a new scale developed by the authors, the Autism Spectrum Adaptive Scale Questionnaire (ASAS-Q). 994 adult volunteers with and without history of ASC were recruited via Research Match (391 with autism, 594 without autism). We ran an Exploratory Factor Analysis (EFA), which suggested three factors. Using a loading value cutoff of above 0.4, items that either did not load onto any factor or cross loaded were deleted. The final analysis converged in six iterations. Finally, we ran a reliability analysis to test the internal consistency. In its current experimental form, ASAS-Q has 38 items. Bartlett's tests of sphericity was significant (χ2 (780) = 24860.18, p = 0.000) and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy indicated a high relationship among variables (KMO = 0.97). These tests indicated that a factor analytic model was acceptable for this dataset. Cronbach's Alpha indicated that the ASAS-Q has excellent internal consistency overall (α= 0.97) as well as among each of the three subscales: (1) (α= 0.87), (2) (α= 0.90), and (3) (α= 0.94). These findings indicate that the ASAS-Q may serve as a useful new self-report scale for diagnosing ASC in adults.