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Record W4394853151 · doi:10.1177/13623613241244548

“A perfect storm”: Autistic experiences of menopause and midlife

2024· article· en· W4394853151 on OpenAlexafffundabout
Miranda J. Brady, Christine Jenkins, Julie M. Turner‐Cobb, Rachel Moseley, Margaret Janse van Rensburg, Rose Matthews

Bibliographic record

VenueAutism · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMenopausePsychologyThematic analysisAutismDevelopmental psychologyFocus groupConversationQualitative researchMedicineSociologyCommunication

Abstract

fetched live from OpenAlex

Previous research indicates that menopause can be an extremely difficult transition for some autistic people. This study asks how autistic people experience menopause and how they can better access services, support and information; autistic Community Research Associates played an important role in each stage of the research. Online focus groups and interviews were conducted with 24 autistic participants who lived in Canada ( n = 13) or the United Kingdom ( n = 11) and had experience with the menopausal transition. Transcripts were coded and analysed by four team members using reflexive thematic analysis. Four themes and eight subthemes were identified: (1) Complexity, multiplicity and intensity of symptoms (0 subthemes); (2) Life experience and adversity converging at midlife (three subthemes); (3) The importance of knowledge and connection (two subthemes); and (4) Barriers to support and care (three subthemes). Limitations include a potential sample bias towards difficult experiences of menopause. The majority of our sample had a late diagnosis or discovery of autism, and their experiences might not generalize to wider autistic populations. This research may help autistic people prepare for menopause and recognize symptoms earlier. Hearing about the experiences of others may let autistic people who struggle with menopause know they are not alone. Lay abstract Previous studies report that menopause can be a very difficult transition for some autistic people. This study focuses on how autistic people experience menopause and what support and information might help them. Autistic Community Research Associates played an important role in the research and co-authored this article. We held four focus groups and eight interviews online with 24 autistic participants who lived in either Canada ( n = 13) or the United Kingdom ( n = 11). We analysed participant conversations using a method called reflexive thematic analysis. Participants described many intense challenges during menopause. Four themes and eight subthemes were identified across participant groups: (1) Complexity, multiplicity and intensity of symptoms (0 subthemes); (2) Life experience and adversity converging at midlife (three subthemes); (3) The importance of knowledge and connection (two subthemes); and (4) Barriers to support and care (three subthemes). The experiences of our participants may not be the same as other autistic people, and the study could have been more inclusive of diverse autistic groups. However, hearing about the experiences of others may provide reassurance to autistic people who struggle with menopause and let them know they are not alone.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.028
GPT teacher head0.310
Teacher spread0.282 · 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 designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2024
Admission routes3
Has abstractyes

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