Indigenous women’s experiences, symptomology and understandings of menopause: a scoping review
Bibliographic record
Abstract
BACKGROUND: Most women at some time in their life will experience menopause. Recent commentaries, however, have highlighted that menopause is a neglected area of both research and health- related support; this being especially the case for ethnic minorities and Indigenous women. Coupled with the World Health Organization's Global Plan of Action on Indigenous Health, which calls for global attention to the health of Indigenous Peoples, this makes it timely to undertake a scoping review of the literature on Indigenous women's experiences and understandings of menopause to identify themes and gaps across the contemporary literature. METHODS: Arksey and O'Malley's scoping review framework and PRISMA-ScR guidelines were utilised. A comprehensive search of eight electronic databases as well as grey literature from 2015 to 2025 identified 319 articles. After removing duplicates and applying inclusion criteria and exclusion criteria, 21 articles were included in the final review. RESULTS: Eleven of the studies were from India, three from United States of America, two from Canada and one study from each of the following countries: Aotearoa/New Zealand, Argentina, China, Colombia and Malaysia. Sixteen studies were quantitative and focused primarily on symptomology, age of menopause and impacts on health. Minimal qualitative research was evident. Themes included 1) menopause symptomology; 2) menopause and metabolic health; 3) age of menopause and associations with factors such as age of first menarche, age of marriage, nulliparity, and occupation; 4) menopause knowledge, which was limited for some Indigenous women, contributing to fear and anxiety; 5) symbolic and cultural meanings, which underpinned Indigenous women's understandings of menopause; 6) challenges in accessing person-centred and culturally sensitive healthcare and menopause support. CONCLUSIONS: The research question for this scoping review focused on exploring the global academic literature on Indigenous women's experiences, symptomology, and understandings of menopause. Culturally sensitive health education, improved healthcare access and more research which explores Indigenous worldviews and their impact on how menopause is understood and experienced are needed to support Indigenous women through menopause.
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".