The BODY-Q Belly Button Scale: A Development and Validation Study
Bibliographic record
Abstract
BACKGROUND: One of the critical steps in abdominoplasty or in reconstructive procedures involving abdominal tissue involves repositioning the belly button. However, there is limited knowledge about patient satisfaction regarding the appearance of the belly button after such procedures. Currently, there is no standardized patient-reported outcome measure designed to assess this outcome. OBJECTIVES: This study aimed to develop and validate a BODY-Q scale that measures patient satisfaction with the appearance of the belly button. METHODS: In Phase 1 (qualitative), patient interview data were used to develop and refine the new BODY-Q scale. In Phase 2 (quantitative), the scale was field-tested through a crowdsourcing platform. Rasch measurement theory analysis was used for item reduction and to examine reliability and validity. Predefined hypotheses were tested by applying a 75% acceptance threshold, which was considered indicative of sufficient evidence for construct validity. RESULTS: The BODY-Q Belly Button scale was refined through qualitative input from 5 patients. Psychometric validation was performed in a sample of 372 participants. Out of the 15 items assessed, 6 were retained in the final scale. This scale showed ordered thresholds, and the data fit the Rasch model (χ2 = 22.72, df = 24, P-value = .54). The scale evidenced reliability, with Person Separation Index and Cronbach α values ≥.81. For construct validity, acceptance of hypotheses was 89%. CONCLUSIONS: The BODY-Q Belly Button scale can be used in clinical practice and in research to assess satisfaction with the belly button from the patient's perspective. LEVEL OF EVIDENCE: 4 (RISK): For image description, please refer to the figure legend and surrounding text.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".