Towards identifying a method of screening for autism amongst women with restrictive eating disorders
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".