부산대학교 도서관

Objective: Up to 37% of patients with anorexia nervosa score above cut‐off on autism screening measures. These individuals typically have poorer outcomes from standard eating disorder interventions and could therefore benefit from adaptations. Accurately identifying these individuals is important for improving autism referral processes and clinical pathway decisions. This study's aim was to identify subscales of questionnaires measuring constructs associated with either autism or eating disorders that, when combined with traditional autism screening measures, would improve the ability to identify women with restrictive eating disorders who might benefit from a full autism assessment. Method: One hundred and sixty women with restrictive eating disorders, with (n = 42) or without (n = 118) an autism diagnosis completed a battery of questionnaires. Using conditional stepwise binary logistic regression, we attempted to improve the autism spectrum quotient 10 item's (AQ‐10) ability to discriminate between autistic and non‐autistic women in a restrictive eating disorder sample. Results: In a binary logistic regression model, the AQ‐10 reliably discriminated between autistic and non‐autistic women with an accuracy rate of 85% but had relatively low (69%) sensitivity, reflecting a high rate of false negatives. Adding three subscales to the model (Glasgow Sensory Questionnaire Auditory, Camouflaging Autistic Traits Questionnaire Compensation and Toronto Alexithymia Scale Externally Orientated Thinking) significantly improved its differentiating ability (accuracy = 88%, sensitivity = 76%, specificity = 92%). Conclusions: We have identified three subscales that, when used in combination with the AQ‐10, may help clinicians understand the pattern of autistic traits in their patients with a restrictive eating disorder. This can inform clinical decisions about whether to refer for a full autism assessment and whether to adapt standard eating disorder treatments to accommodate autistic traits. Future studies are needed to test the model in samples where participants have undergone a full autism assessment. Highlights: In a restrictive eating disorder sample, the AQ‐10 accurately identified 85% of autistic women, but had a sensitivity of only 69%, indicating that it leads to many false negatives.Adding questions about auditory sensitivity, social compensation and externally orientated thinking, in combination with the AQ‐10, led to an improved autism screening model (sensitivity = 76%, specificity = 92%).The model indicates additional autistic characteristics that when supplemented with the AQ‐10 could improve autism screening tools for a restrictive eating disorder population. [ABSTRACT FROM AUTHOR]