Knowledge and Attitude towards Menopause and Hormone Replacement Therapy in Chinese Women
Bibliographic record
Abstract
OBJECTIVE: To explore the knowledge and prevalence of menopausal symptoms as well as the use and attitude toward hormone replacement therapy (HRT) in Chinese women. METHODS: A cross-sectional study was conducted between May 2011 and April 2012 in Shanghai, China. The structured questionnaire addressing sociodemographic characteristics, knowledge and prevalence of menopausal symptoms, and knowledge and attitude towards HRT and its use were investigated. RESULTS: 3,619 women aged 40-65 years were included in the analysis. The majority of the women had knowledge of menopause. Symptoms were prevalent in 16.1% of premenopausal women and in 49.3% of peri-, post- and surgical-menopausal women. Back and joint pain, sleeplessness, fatigue and sweating/hot flushes were frequently reported. HRT awareness among women was 3.5% and was related to menopausal, working and marital status; 75 (2.1%) women had used or were using HRT, of which 57.3% used HRT with a doctor's prescription and 29.3% experienced side effects from the use of HRT. CONCLUSION: Most Chinese women had knowledge of menopause and thought menopausal symptoms should not be treated. The awareness of HRT was poor and influenced by menopausal, working and marital status. Chinese health care providers have to assume responsibility for educating women about menopause and HRT use.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".