Use of the Menopause-Specific Quality of Life (MENQOL) questionnaire in research and clinical practice: a comprehensive scoping review
Bibliographic record
Abstract
OBJECTIVE: The Menopause-Specific Quality of Life (MENQOL) questionnaire was developed as a validated research tool to measure condition-specific QOL in early postmenopausal women. We conducted a comprehensive scoping review to explore the extent of MENQOL's use in research and clinical practice to assess its value in providing effective, adequate, and comparable participant assessment information. METHODS: Thirteen biomedical and clinical databases were systematically searched with "menqol" as a search term to find articles using MENQOL or its validated derivative MENQOL-Intervention as investigative or clinical tools from 1996 to November 2014 inclusive. Review articles, conference abstracts, proceedings, dissertations, and incomplete trials were excluded. Additional articles were collected from references within key articles. Three independent reviewers extracted data reflecting study design, intervention, sample characteristics, MENQOL questionnaire version, modifications and language, recall period, and analysis detail. Data analyses included categorization and descriptive statistics. RESULTS: The review included 220 eligible papers of various study designs, covering 39 countries worldwide and using MENQOL translated into more than 25 languages. A variety of modifications to the original questionnaire were identified, including omission or addition of items and alterations to the validated methodological analysis. No papers were found that described MENQOL's use in clinical practice. CONCLUSIONS: Our study found an extensive and steadily increasing use of MENQOL in clinical and epidemiological research over 18 years postpublication. Our results stress the importance of proper reporting and validation of translations and variations to ensure outcome comparison and transparency of MENQOL's use. The value of MENQOL in clinical practice remains unknown.
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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 | 0.043 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.033 | 0.028 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".