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Record W1830258719 · doi:10.1186/1477-7525-2-45

The Menopause Rating Scale (MRS) scale: A methodological review

2004· review· en· W1830258719 on OpenAlexaff
Klaas Heinemann, Alexander Ruebig, Peter Potthoff, Hermann PG Schneider, Frank Strelow, Lothar Heinemann, Do Minh Thai

Bibliographic record

VenueHealth and Quality of Life Outcomes · 2004
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsAS Composite (Canada)
Fundersnot available
KeywordsRating scaleScale (ratio)Reliability (semiconductor)Clinical psychologyPsychologyPsychometricsMedicineDevelopmental psychologyGeographyCartography

Abstract

fetched live from OpenAlex

BACKGROUND: This paper compiles data from different sources to get a first comprehensive picture of psychometric and other methodological characteristics of the Menopause Rating Scale (MRS) scale. The scale was designed and standardized as a self-administered scale to (a) to assess symptoms/complaints of aging women under different conditions, (b) to evaluate the severity of symptoms over time, and (c) to measure changes pre- and postmenopause replacement therapy. The scale became widespread used (available in 10 languages). METHOD: A large multinational survey (9 countries in 4 continents) from 2001/ 2002 is the basis for in depth analyses on reliability and validity of the MRS. Additional small convenience samples were used to get first impressions about test-retest reliability. The data were centrally analyzed. Data from a postmarketing HRT study were used to estimate discriminative validity. RESULTS: Reliability measures (consistency and test-retest stability) were found to be good across countries, although the sample size for test-retest reliability was small. VALIDITY: The internal structure of the MRS across countries was astonishingly similar to conclude that the scale really measures the same phenomenon in symptomatic women. The sub-scores and total score correlations were high (0.7-0.9) but lower among the sub-scales (0.5-0.7). This however suggests that the subscales are not fully independent. Norm values from different populations were presented showing that a direct comparison between Europe and North America is possible, but caution recommended with comparisons of data from Latin America and Indonesia. But this will not affect intra-individual comparisons within clinical trials. The comparison with the Kupperman Index showed sufficiently good correlations, illustrating an adept criterion-oriented validity. The same is true for the comparison with the generic quality-of-life scale SF-36 where also a sufficiently close association has been shown. CONCLUSION: The currently available methodological evidence points towards a high quality of the MRS scale to measure and to compare HRQoL of aging women in different regions and over time, it suggests a high reliability and high validity as far as the process of construct validation could be completed yet.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.087
metaresearch head score (Gemma)0.170
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.170
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0190.019
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0040.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.482
GPT teacher head0.563
Teacher spread0.081 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
Domainnot available
GenreReview

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".

Quick stats

Citations586
Published2004
Admission routes1
Has abstractyes

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