ASSESSMENT OF HEALTH AND QUALITY OF LIFE: VARIATIONS BETWEEN NATURAL AND INDUCED MENOPAUSAL WOMEN
Bibliographic record
Abstract
Menopausal health impacts among women vary. The research aimed to examine the problems of women with natural menopause and induced menopause in the year 2022-23.The evaluation of the study was on the basis of a self-prepared questionnaire and Menopause-Specific Quality of Life developed by Department of Family and Community Medicine, Sunnybrook Health Science Centre, University of Toronto, Canada in 1996 (MENQOL),the tool to evaluate the quality of life. About fifty sample each in natural menopause and induced menopause were chosen from various places in Kerala.The study opined that either the induced and natural menopause women had no significant relation with BMI. But the waist hip ratio pointed out that 20 per cent induced menopause women were at higher risk category than natural menopausal women (4%). Also, the physiological problems like diabetes (70%), dizziness (62%) and gastritis (60%), psychological problems like mood swings (100%), anxiety (66%), trouble sleeping (64%), sexual and genital problems like decreased libido (84%), itching (72%), vaginal dryness (60%) were high among induced menopausal women than natural menopause women. Menopause specific quality of life questionnaire showed that the quality of life at physical (flatulence-90%, aching in muscles and joints- 96%) and sexual domains (change in sexual desire-90%) affected mostly among induced menopause women.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".