Knowledge, Perceptions and Information about Hormone Therapy (HT) among Menopausal Women: A Systematic Review and Meta-Synthesis
Bibliographic record
Abstract
BACKGROUND: The use of hormone therapy (HT) by menopausal women has declined since the Women's Health Initiative randomized trial (WHI) in 2002 demonstrated important harms associated with long-term use. However, how this information has influenced women's knowledge and attitudes is uncertain. We aimed to evaluate the attitudes and perceptions towards HT use, as well as specific concerns and information sources on HT since the WHI trial. METHOD/RESULTS: We did a systematic review to assess the attitudes and knowledge towards HT in women, and estimate the magnitude of the issue by pooling across the studies. Using meta-synthesis methods, we reviewed qualitative studies and surveys and performed content analysis on the study reports. We pooled quantitative studies using a random-effects meta-analysis. We analyzed 11 qualitative studies (n = 566) and 27 quantitative studies (n = 39251). Positive views on HT included climacteric symptom control, prevention of osteoporosis and a perceived improvement in quality of life. Negative factors reported included concerns about potential harmful effects, particularly cancer risks. Sources of information included health providers, media, and social contact. By applying a meta-synthesis approach we demonstrate that these findings are broadly applicable across large groups of patients. CONCLUSIONS: Although there are clear hazards associated with long-term HT use, many women view HT favorably for climacteric symptom relief. Media, as a source of information, is often valued as equivalent to health providers.
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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 | 0.034 | 0.107 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.021 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".