Physical health of autistic girls and women: a scoping review
Bibliographic record
Abstract
BACKGROUND: There is a growing recognition of sex and gender influences in autism. Increasingly, studies include comparisons between sexes or genders, but few have focused on clarifying the characteristics of autistic girls'/women's physical health. METHODS: A scoping review was conducted to determine what is currently known about the physical health of autistic girls/women. We screened 1112 unique articles, with 40 studies meeting the inclusion criteria. We used a convergent iterative process to synthesize this content into broad thematic areas. RESULTS: Autistic girls/women experience more overall physical health challenges compared to non-autistic girls/women and to autistic boys/men. Emerging evidence suggests increased prevalence of epilepsy in autistic girls/women compared to non-autistic girls/women and to autistic boys/men. The literature also suggests increased endocrine and reproductive health conditions in autistic girls/women compared to non-autistic girls/women. Findings regarding gastrointestinal, metabolic, nutritional, and immune-related conditions are preliminary and inconsistent. LIMITATIONS: The literature has substantial heterogeneity in how physical health conditions were assessed and reported. Further, our explicit focus on physical health may have constrained the ability to examine interactions between mental and physical health. The widely differing research aims and methodologies make it difficult to reach definitive conclusions. Nevertheless, in keeping with the goals of a scoping review, we were able to identify key themes to guide future research. CONCLUSIONS: The emerging literature suggests that autistic girls/women have heightened rates of physical health challenges compared to non-autistic girls/women and to autistic boys/men. Clinicians should seek to provide holistic care that includes a focus on physical health and develop a women's health lens when providing clinical care to autistic girls/women.
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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 | 0.009 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".