The BODY-Q Cellulite Scale: A Development and Validation Study
Bibliographic record
Abstract
BACKGROUND: Cellulite is a localized metabolic disorder of the subcutaneous tissue. To measure the impact of cellulite and its treatment(s) on patients' health-related quality of life, a psychometrically sound patient-reported outcome measure is needed. OBJECTIVES: The authors sought to develop and field test a new BODY-Q cellulite scale to measure the appearance of cellulite. METHODS: Appearance-related codes from the original BODY-Q qualitative interviews were reexamined, and a set of cellulite-specific items was developed and refined through cognitive patient interviews (n = 10) and expert input (n = 17). This scale was field-tested in adults with cellulite through 2 crowdworking platforms. Rasch Measurement Theory analysis was employed to refine the scale and examine its psychometric properties. RESULTS: The field-test sample included 2129 participants. The 15-item scale was reduced in length to 11 items. Data from the sample fit the Rasch model (X2 [99] = 21.32, P = 0.06). All items had ordered thresholds and mapped out a targeted clinical hierarchy. The reliability statistics for the person separation index was 0.94 and for Cronbach's alpha was 0.97. In terms of validity, worse scores on the cellulite scale were associated with being more bothered by how the cellulite looked overall, having more severe cellulite on the Patient-Reported Photo-numeric Cellulite Severity Scale, and having more self-reported cellulite and more areas of the body with cellulite. CONCLUSIONS: The BODY-Q cellulite scale can be utilized to measure appearance of cellulite and provides a solid basis for future studies evaluating the impact of cellulite and its treatment.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.002 | 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".