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Record W4403305374 · doi:10.52843/cassyni.xtl1cx

Health of Autistic Women: State of the Field and Future Directions

2024· preprint· en· W4403305374 on OpenAlexaffabout
Laura Hull, Felicity Sedgewick, Imene Zoulikha Kassous, Orla C. Putnam, Clare Harrop, Yani Hamdani, Miriam Harmens

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Toronto
FundersNational Center for Advancing Translational SciencesHealth Resources and Services Administration
KeywordsField (mathematics)State (computer science)PsychologyPolitical scienceComputer scienceMathematics

Abstract

fetched live from OpenAlex

At least 1% of the world’s population is autistic, meaning that they experience and process the world around them in ways which are different to the non-autistic majority. Historically, the focus of research and the image of autism has very much been male. Changes to the diagnostic conceptualisation of autism in the last 20 years, however, has led to an increase in the diagnosis of autism in women and girls, and the recognition that they may have different life experiences and support needs than autistic men. Having been ignored, overlooked, and at times actively silenced, much less is known about autistic women than their male counterparts. The study of autistic women is still in its infancy, but suggests that there are a wide range of differences which are only just beginning to be understood in terms of how autism interacts with gender - including those who are transgender, non-binary, or have other gender identities. This special collection from Women’s Health will explore what is known about the physical, mental, social, and emotional wellbeing of autistic women, encompassing original research, reviews, and perspectives from autistic women. Health of Autistic Women: State of the Field and Future Directions At least 1% of the world’s population is autistic, meaning that they experience and process the world around them in ways which are different to the non-autistic majority. Historically, the focus of research and the image of autism has very much been male. Changes to the diagnostic conceptualisation of autism in the last 20 years, however, has led to an increase in the diagnosis of autism in women and girls, and the recognition that they may have different life experiences and support needs than autistic men. Having been ignored, overlooked, and at times actively silenced, much less is known about autistic women than their male counterparts. The study of autistic women is still in its infancy, but suggests that there are a wide range of differences which are only just beginning to be understood in terms of how autism interacts with gender - including those who are transgender, non-binary, or have other gender identities. This special collection from Women’s Health will explore what is known about the physical, mental, social, and emotional wellbeing of autistic women, encompassing original research, reviews, and perspectives from autistic women. Researching autism in the Global South (MENA region): to what extent is Western autism research inclusive to the Global South? How autistic adults priorities for autism research differ by gender: a mixed methods study Background: Recent studies suggest that the funding breakdown of autism research in the United States may not align with stakeholder priorities. Furthermore, the majority of stakeholder-engaged research involves parents of autistic individuals rather than autistic adults themselves, who may have differing perspectives on research and funding priorities. Women and non-binary adults have been historically underrepresented in autism research. **Objectives**: The goal of the current study was to examine the autism research priorities of a group of autistic adults, with a particular focus on how these priorities are influenced by one's gender identity. **Design**: A concurrent mixed-methods design was used for this study. **Methods**: Seventy-one autistic adults (n = 18 men, n = 29 women, n = 24 non-binary adults) completed an online survey regarding the current funding landscape for autism research. Participants ranked the main research topics of the Interagency Autism Coordinating Committee (IACC) and identified top-priority research areas through free-text responses. Response themes were analyzed using content analysis and compared with the existing topic rankings. **Results**: Overall rankings of IACC research areas had a near inverse relationship with the amount of funding per research area. Main themes of stakeholder-generated research topics included "Characterization," "Societal Change," "Well-Being Trauma," "Diagnosis Healthcare," and "Accessibility Services." There was a relatively high overlap between topics identified by the IACC and by the stakeholder-generated topics. Subtle but important differences in topics arose based on gender, with women and non-binary adults identifying topics that were not identified by autistic men. **Conclusion**: Unique priorities generated by those typically excluded from autism research development underscore the importance of co-creating research with underrepresented stakeholders impacted by this work. The current study echoes the growing movement in the field of autism research to center autistic perspectives at every stage of research, including the establishment of funding priorities. Roadblocks and detours on pathways to a clinical diagnosis of autism for girls and women Background: Autism is not always considered for girls and women until later along their clinical diagnostic pathways. Misdiagnosis or late diagnosis can pose significant disadvantages with respect to accessing timely health and autism-related services and supports. Understanding what contributes to roadblocks and detours along clinical pathways to an autism diagnosis can shed light on missed opportunities for earlier recognition. **Objective**: Our objective was to examine what contributed to roadblocks, detours, and missed opportunities for earlier recognition and clinical diagnosis of autism for girls and women. **Design**: We conducted a qualitative secondary analysis using data from a Canadian primary study that examined the health and healthcare experiences of autistic girls and women through interviews and focus groups. **Methods**: Transcript data of 22 girls and women clinically diagnosed with autism and 15 parents were analysed, drawing on reflexive thematic analysis procedures. Techniques included coding data both inductively based on descriptions of roadblocks and detours and deductively based on conceptualizations of sex and gender. Patterns of ideas were categorized into themes and the ‘story’ of each theme was refined through writing and discussing analytic memos, reflecting on sex and gender assumptions, and creating a visual map of clinical pathways. **Results**: Contributing factors to roadblocks, detours, and missed opportunities for earlier recognition and diagnosis were categorized as follows: (1) age of pre-diagnosis ‘red flags’ and ‘signals’; (2) ‘non-autism’ mental health diagnoses first; (3) narrow understandings of autism based on male stereotypes; and (4) unavailable and unaffordable diagnostic services. **Conclusion**: Professionals providing developmental, mental health, educational, and/or employment supports can be more attuned to nuanced autism presentations. Research in collaboration with autistic girls and women and their childhood caregivers can help to identify examples of nuanced autistic features and how context plays a role in how these are experienced and navigated. Autistic women's diagnostic experiences: Interactions with identity and impacts on well-being **Objective:** There has been suggestion that current diagnostic instruments are not sufficient for detecting and diagnosing autism in women, and research suggests that a lack of diagnosis could negatively impact autistic women’s well-being and identity. This study aimed to explore the well-being and identity of autistic women at three points of their diagnostic journey: self-identifying or awaiting assessment, currently undergoing assessment or recently diagnosed, and more than a year post-diagnosis. **Methods:** Mixed-methods were used to explore this with 96 women who identified as autistic and within one of these three groups. Participants completed an online questionnaire, and a sub-sample of 24 of these women participated in a semi-structured interview. **Results:** Well-being was found to differ significantly across groups in three domains: satisfaction with health, psychological health, and environmental health. Validation was found to be a central issue for all autistic women, which impacted their diagnosis, identity, and well-being. The subthemes of don’t forget I’m autistic; what now?; having to be the professional; and no one saw me were also identified. **Conclusion:** These results suggest that autistic women’s well-being and identity differ in relation to their position on the diagnostic journey in a non-linear manner. We suggest that training on the presentation of autism in women for primary and secondary healthcare professionals, along with improved diagnostic and support pathways for autistic adult women could go some way to support well-being.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.004
Science and technology studies0.0030.007
Scholarly communication0.0060.011
Open science0.0020.004
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0150.003

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.

Opus teacher head0.021
GPT teacher head0.332
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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