Development of a New Patient-reported Outcome Instrument to Evaluate Treatments for Scars: The SCAR-Q
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Every year millions of individuals acquire scars. A literature review of patient-reported outcome (PRO) instruments identified content limitations in existing scar-specific measures. The aim of this study was to develop a new PRO instrument called SCAR-Q for children and adults with surgical, traumatic, and burn scars. METHODS: We performed a secondary analysis of the qualitative datasets used in the development of PRO instruments for plastic and reconstructive surgery, that is, BREAST-Q, FACE-Q, BODY-Q, and CLEFT-Q. The keyword "scar*" was used to extract scar-specific text. Data were analyzed to identify concepts of interest and to form a comprehensive item pool. Scales were developed and refined through multiple rounds of cognitive interviews with patients and with input from international clinical experts between July 2015 and December 2016. RESULTS: A total of 52 children and 192 adults from the qualitative datasets provided between 1 and 34 scar-specific codes (n = 1,227). The analysis led to the identification of 3 key domains for which scales were developed: scar appearance (eg, size, color, contour), scar symptoms (eg, painful, tight, itchy), and psychosocial impact (eg, feeling self-conscious, bothered by scar). Cognitive interviews with 25 adults and 20 pediatric participants with scars, plus feedback from 27 clinical experts, led to rewording and removal of items, and new items added. These steps ensured content validity for SCAR-Q in a broad range of scars. CONCLUSIONS: The SCAR-Q is now being field-tested. Once completed, we anticipate SCAR-Q will be used in clinical practice and in clinical trials to test different scar therapies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it