Towards identifying a method of screening for autism amongst women with restrictive eating disorders.

This research looked at better ways to identify autism in women with eating disorders like anorexia nervosa. Many women with eating disorders also have autism traits, but standard autism screening tools often miss them. The study found that adding questions about sensory sensitivity, masking behaviours, and difficulty identifying emotions improved detection from 69% to 76%. Better identification could help these women get appropriate support and treatment adaptations.

This study examined methods to better identify autism among women with restrictive eating disorders. Researchers found that up to 37% of women with anorexia nervosa score above autism screening thresholds, and these individuals typically have poorer treatment outcomes. The study tested 160 women (42 with autism diagnosis, 118 without) using various questionnaires. The standard autism screening tool (AQ-10) alone had 85% accuracy but missed many autistic women (69% sensitivity).

Adding three additional questionnaire subscales measuring sensory processing, camouflaging behaviours, and alexithymia improved accuracy to 88% and sensitivity to 76%. This enhanced screening approach could help clinicians better identify women who might benefit from autism assessment and adapted eating disorder treatments.

Clinicians should consider enhanced autism screening for women with restrictive eating disorders using additional measures of sensory processing, camouflaging, and alexithymia alongside standard tools. Early identification may improve treatment outcomes through adapted interventions.

Study requires validation with participants who have undergone full autism assessment rather than existing diagnoses. Sample size breakdown and demographic details not clearly specified. Generalizability beyond restrictive eating disorders unclear.

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.

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. 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%).

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.