Re-examining content validity of the BREAST-Q more than a decade later to determine relevance and comprehensiveness
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The BREAST-Q is the most used patient-reported outcome measure (PROM) in breast cancer surgery. The purposes of this study were to re-examine the content validity of BREAST-Q cancer modules (mastectomy, lumpectomy and reconstruction) and to determine the need for new scales. METHODS: Interviews were conducted with women with breast cancer (Stage 0-4, any treatment), and were audio-recorded and transcribed verbatim. Deductive (based on original BREAST-Q conceptual framework) and inductive (new codes from the data) content analysis approaches were used to analyze the data. The number of codes that mapped to BREAST-Q were recorded. RESULTS: Dataset included 3948 codes from 58 participants. Most of the breast (n = 659, 96%) and all psychosocial (n = 127, 100%), sexual (n = 179, 100%) and radiation-related (n = 79, 100%) codes mapped to BREAST-Q Satisfaction with Breast, Psychosocial Wellbeing, Sexual Wellbeing and Adverse Effects of Radiation scales, respectively. For the physical wellbeing codes (n = 939) for breast/chest and arm, 34% (n = 321) mapped to the Physical Wellbeing-Chest scale. Most of the abdomen codes (n = 311) mapped to Satisfaction with Abdomen (n = 90, 76%) and Physical Wellbeing-Abdomen (n = 171, 89%) scales. Codes that did not map (n = 697, 30%) covered breast sensation and lymphedema. Concerns related to fatigue, cancer worry, and work impact were most reported and did not map to BREAST-Q. CONCLUSION: The BREAST-Q, which was developed using extensive patient input more than a decade ago, is still relevant. To ensure the BREAST-Q remains comprehensive, new scales for upper extremity lymphedema, breast sensation, fatigue, cancer worry, and work impact were developed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it