The BODY-Q Chest Module: Further Validation in a Canadian Chest Masculinization Surgery Sample
Bibliographic record
Abstract
BACKGROUND: The BODY-Q Chest module is a patient-reported outcome (PRO) instrument that measures satisfaction with how the chest (10 items) and nipples (5 items) look. This PRO instrument was previously field tested in an international sample of people seeking treatment for gynecomastia (n = 174), weight loss (n = 224), and chest masculinization (n = 341). OBJECTIVES: The aim of this study was to examine the psychometric performance of the BODY-Q Chest module in a new chest masculinization surgery sample. METHODS: Data were collected from patients attending a private plastic surgery outpatient clinic in Canada between January 2018 and June 2019. Rasch measurement theory analysis was used to examine how the scales performed psychometrically. RESULTS: The sample provided 266 assessments (115 preoperative, 151 postoperative). All items had ordered thresholds, providing evidence that the 4 response options for each scale worked as expected. Item fit was within ±2.5 for all items, with all Bonferroni adjusted chi-square values nonsignificant. The data for the chest (χ2(20) = 18.72, P = 0.54) and nipples (χ 2(10) = 12.28, P = 0.27) scales fit the requirements of the Rasch model. Reliability was high with person separation index and Cronbach's α values of ≥0.95 for the chest and ≥0.87 for the nipple scales, respectively. More depressive symptoms on the Patient Health Questionnaire-9 and lower health-related quality of life scales were weakly correlated with worse scores on the chest and nipple scales (P < 0.001). CONCLUSIONS: The BODY-Q Chest module was shown to be scientifically sound in an independent sample of patients seeking chest masculinization surgery.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".