Alexithymia As a Predictor of Dimensional Scales of Autism Symptoms
Objectives: The goal of this study was to explore the relationship between ASD symptoms and the related constructs of alexithymia, anxiety, and depression. Specifically, we hypothesized that alexithymia would remain a significant predictor of ASD symptoms even after controlling for anxiety and depression.
Methods: Participants were 23 adults diagnosed with ASD as well as 20 neurotypical controls. All participants completed a battery of questionnaires including the Toronto Alexithymia Scale (TAS-20), the Autism Spectrum Quotient (AQ), the Social Responsiveness Scale (SRS-2), the State-Trait Anxiety Inventory (STAI), and the Beck Depression Inventory (BDI). We used multiple regression analyses to predict autism symptoms (i.e., AQ and SRS-2 scores) using alexithymia, anxiety, depression, and categorical diagnosis as predictors.
Results: Multiple regression analyses indicated that both alexithymia and diagnosis were significant predictors of both AQ and SRS-2 scores when controlling for anxiety and depression. Furthermore, alexithymia emerged as a better predictor of dimensional ASD symptoms than categorical diagnosis. Additional Pearson correlations showed differing patterns between the study variables among the two diagnostic groups. In particular there appears to be different relationships between subscales of the TAS-20 and the SRS-2 in individuals with ASD.
Conclusions: Alexithymia appears to be a robust predictor of dimensional measures of autism symptoms, even when controlling for related anxiety and depression symptoms. This evidence emphasizes the connection between autism and alexithymia and suggests the importance of the assessment of alexithymia in both clinical and research settings.