Methodology and measurement properties of health-related quality of life instruments: A prospective study of patients undergoing breast reduction surgery
Bibliographic record
Abstract
BACKGROUND: Breast hypertrophy is associated with clinically important morbidity. A prospective study was conducted to assess the change in health-related quality of life (HRQL) following breast reduction mammoplasty. This paper describes the measurement properties of each of the HRQL questionnaires used. METHODS: The reliability, responsiveness, and the construct validity of each HRQL instrument (the Health Utilities Index Mark 2 (HUI2) and Mark 3 (HUI3) and the Breast Reduction Assessment Value and Outcomes (BRAVO) instruments) were assessed. The BRAVO instruments are a set of separate instruments including the Short Form-36 (SF-36), the Multidimensional Body Self Relations Questionnaire Appearance Assessment (MBSRQ-AS), and the Breast Related Symptoms Questionnaire (BRSQ). RESULTS: The HUI2, the HUI3, the MBSRQ-AS, and the breast severity symptom (BSS) score from the BRSQ all demonstrated good test-retest reliability. The SF-36 physical component summary, the MBSRQ-AS, and the BSS score demonstrated high responsiveness. The SF-36 mental component summary and the HUI3 had a moderate effect size and the HUI2 had a small effect size. All of the changes in scales are correlated in the same direction except for the SF-36 physical component summary and the SF-36 mental component summary. CONCLUSION: All four instruments were found to be reliable and responsive. These instruments can be used in similar clinical settings to evaluate the change in patients' HRQL.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".