Autism Spectrum Disorder Traits Predict Interoceptive Deficits and Eating Disorder Symptomatology in Children and Adolescents with Anorexia Nervosa—A Cross-Sectional Analysis: Italian Preliminary Data
Bibliographic record
Abstract
BACKGROUND: Anorexia Nervosa (AN) is a severe Feeding and Eating Disorder (FED) that is more prevalent in females, often manifesting during adolescence. Recent research highlights an elevated presence of comorbid Autism Spectrum Disorder (ASD) traits among individuals with AN, with specific expressions in females accounting for sensorial and interoceptive experiences. This study retrospectively explores the association between ASD traits, eating symptomatology, and interoceptive deficits in Italian female adolescents with AN. METHODS: A retrospective evaluation of female AN/Atypical AN patients (n = 52) aged 13-17 years was conducted at two university pediatric hospitals in Italy. The participants underwent neuropsychiatric assessments, including the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2), and measurement of ASD traits with the Autism-spectrum quotient (AQ), camouflaging ASD traits Questionnaire (CAT-Q), Toronto Alexithymia Scale (TAS-20), and FED-symptomatology-related measures. RESULTS: Overall, 9.6% of the participants exhibited an ADOS-2 clinical impression consistent with ASD. Higher scores in AQ and CAT-Q revealed ASD traits and camouflaging strategies. The interoceptive deficits positively correlated with the ASD traits, alexithymia, and camouflage, and TAS-Difficulty Identifying Feelings emerged as the sole predictor for interoceptive deficits. DISCUSSION: This Italian study preliminarily underscores the importance of recognizing ASD traits in the AN population, emphasizing early intervention strategies. The intersection of alexithymia and interoceptive deficits emerges as a crucial nexus between ASD and AN, with potential therapeutic implications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".