Towards Improving the Mental Health of Autistic Women: Gender/Sex Differences in Co-Occurring Conditions and Contributors to Restricted Eating Disorders of Autistic Women
Bibliographic record
Abstract
This thesis explores the nature and underlying contributors to mental health problems in autistic women. Part 1 presents a systematic review and meta-analysis examining gender/sex differences in co-occurring neurodevelopmental and mental health conditions in autistic adults. It identified 33 studies reporting prevalence rates for various co-occurring conditions in autistic women and men. The female-to-male odds ratios and heterogeneity across studies were calculated for ‘any co-occurring psychiatric condition’ and 14 individual conditions. The meta-analyses revealed significant gender/sex differences in the prevalence rates of co-occurring conditions among autistic adults. These findings underscore the need for heightened clinical attention to co-occurring conditions in autistic individuals, particularly women, and have the potential to inform screening efforts and tailored treatments. Part 2 presents an empirical study focused on the role of interoceptive difficulty and alexithymia in restrictive eating disorders (REDs) among autistic women. A Confirmatory Factor Analysis (CFA) was conducted to identify the best-fitting factor model to represent the constructs of interoceptive difficulty and alexithymia, as measured by the Interoceptive Sensory Questionnaire (ISQ; Fiene et al., 2018) and the Toronto Alexithymia Scale (TAS; Bagby et al., 1994) across the sample. Identified factors were compared among (1) autistic women without REDs, (2) autistic women with REDs, (3) non-autistic women with REDs, and (4) women with REDs and high autistic traits. Interoceptive difficulty and certain facets of alexithymia were identified as potential risk factors for REDs in autistic women, which could inform the formulation and more tailored treatment for REDs in this population. Part 3 presents a critical appraisal of the research process and reflections on broader issues relevant to this thesis. I reflected on the research skills I developed and the insights I gained related to working with existing datasets, conceptualising abstract constructs, and conducting participatory research.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".