52 SCAR-Q, A Patient-Reported Outcome Measure for Scars, Field-Test of Individuals with Burn Scars
Bibliographic record
Abstract
As mortality rates of burn survivors continues to decrease, burn surgeons are facing more complex reconstructive challenges and need a systematic way to elicit patient input about their scars. Burn scars are especially difficult to treat as the vast majority will develop hypertrophic scars, which are more symptomatic and lead to increased functional and cosmetic disabilities. A comprehensive scar-specific PROM for the burn, surgical, and traumatic scar populations was field-tested worldwide. Our aim is to describe the field-test findings specific for the burn population and the overall Rasch Measurement Theory (RMT) analysis. A preliminary PROM, the SCAR-Q, was developed from a secondary analysis of 244 qualitative interviews, 45 cognitive interviews, and feedback from 27 clinical experts worldwide to encompass three scales: Appearance, Symptoms, and Psychosocial Impact. SCAR-Q was field-tested in 4 burn-specific clinics worldwide. RMT was used to analyze its psychometric properties and to further refine it of the overall sample. Of the 731 participants who filled out the SCAR-Q booklet, a total of 184 burn survivors completed the SCAR-Q study booklet. The majority were adults(87,47%), individuals with flame burns(97,53%), immature scars(92,50%), normal scar type(96,52%), spanning multiple anatomic locations(average 3.1+/12.9). The RMT findings are on the overall sample. RMT analysis decreased the number of items from 48 to 29 due to poor item fit, disordered thresholds, and/or redundancy. No DIF was found based on scar etiology suggesting items worked the same across all scar etiologies. Person separation indexes were above 0.80 (with extremes) and 0.79 (without extremes). Cronbach’s alpha values were 0.91 and higher, and the intraclass correlation coefficients were 0.88 and above. Lower mean scores were associated with burn scars on all three SCAR-Q scales. With surgical evaluations becoming more person-centered, a PROM specific to scars is essential to adequately capture patient concerns and the impact of interventions on their lives. The SCAR-Q can be used in the burn scar population. We anticipate that SCAR-Q will be used to determine the crucial timing for scar modulation, evaluate outcomes in scar therapies, aid in clinical trials, and be part of quality improvement initiatives.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".