Improving the Impact of BODY-Q Scores Through Minimal Important Differences in Body Contouring Surgery: An International Prospective Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The BODY-Q is a widely used patient-reported outcome measure for comprehensive assessment of treatment outcomes specific to patients undergoing body contouring surgery (BCS). However, for the BODY-Q to be meaningfully interpreted and used in clinical practice, minimal important difference (MID) scores are needed. A MID is defined as the smallest change in outcome measure score that patients perceive as important. OBJECTIVES: The aim of this study was to determine BODY-Q MID estimates for patients undergoing BCS to enhance the interpretability of the BODY-Q. METHODS: Data from an international, prospective cohort from Denmark, Finland, Germany, Italy, the Netherlands, and Poland were included. Two distribution-based methods were used to estimate MID: 0.2 standard deviations of mean baseline scores and the mean standardized response change of BODY-Q scores from baseline to 3 years postoperatively. RESULTS: A total of 12,554 assessments from 3237 participants (mean age 42.5 ± 9.3 years; BMI 28.9 ± 4.9 kg/m2) were included. Baseline MID scores ranged from 1 to 5 on the health-related quality of life (HRQL) scales and 3 to 6 on the appearance scales. The estimated MID scores from baseline to 3-year follow-up ranged from 4 to 5 for HRQL and from 4 to 8 on the appearance scales. CONCLUSIONS: The BODY-Q MID estimates from before BCS to 3 years postoperatively ranged from 4 to 8 and are recommended for interpretation of patients' BODY-Q scores, evaluation of treatment effects of different BCS procedures, and calculation of sample size for future studies.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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