Evaluation of the Satisfaction with Appearance Scale and Its Short Form in Systemic Sclerosis: Analysis from the UCLA Scleroderma Quality of Life Study
Bibliographic record
Abstract
OBJECTIVE: Changes in appearance are common in patients with systemic sclerosis (SSc) and can significantly affect well-being. The Satisfaction with Appearance Scale (SWAP) measures body image dissatisfaction in persons with visible disfigurement; the Brief-Satisfaction with Appearance Scale (Brief-SWAP) is its short form. The present study evaluated the reliability and validity of SWAP and Brief-SWAP scores in SSc. METHODS: A sample of 207 patients with SSc participating in the University of California, Los Angeles Scleroderma Quality of Life Study completed the SWAP. Brief-SWAP scores were derived from the SWAP. The structural validity of both measures was investigated using confirmatory factor analysis. Internal consistency reliability of total and subscale scores was assessed with Cronbach's alpha coefficients. Convergent and divergent validity was evaluated using the Center for Epidemiological Studies Depression Scale, the Health Assessment Questionnaire-Disability Index, and the Medical Outcomes Study Short Form-36 questionnaire. RESULTS: SWAP and Brief-SWAP total scores were highly correlated (r = 0.97). The 4-factor structure of the SWAP fit well descriptively; the 2-factor structure of the Brief-SWAP fit well descriptively and statistically. Internal consistencies for total and subscale scores were good, and results supported convergent and divergent validity. CONCLUSION: Both versions are suitable for use in patients with SSc. The Brief-SWAP is most efficient; the full SWAP yields additional subscales that may be informative in understanding body image issues in patients with SSc.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".