Experience of menopause in aboriginal women: a systematic review
Bibliographic record
Abstract
Every woman experiences the menopause transition period in a very individual way. Menopause symptoms and management are greatly influenced by socioeconomic status in addition to genetic background and medical history. Because of their very unique cultural heritage and often holistic view of health and well-being, menopause symptoms and management might differ greatly in aboriginals compared to non-aboriginals. Our aim was to investigate the extent and scope of the current literature in describing the menopause experience of aboriginal women. Our systematic literature review included nine health-related databases using the keywords 'menopause' and 'climacteric symptoms' in combination with various keywords describing aboriginal populations. Data were collected from selected articles and descriptive analysis was applied. Twenty-eight relevant articles were included in our analysis. These articles represent data from 12 countries and aboriginal groups from at least eight distinctive geographical regions. Knowledge of menopause and symptom experience vary greatly among study groups. The average age of menopause onset appears earlier in most aboriginal groups, often attributed to malnutrition and a harsher lifestyle. This literature review highlights a need for further research of the menopause transition period among aboriginal women to fully explore understanding and treatment of menopause symptoms and ultimately advance an important dialogue about women's health care.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".