The Patient and Observer Scar Assessment Scale: Translation for portuguese language, cultural adaptation, and validation
Bibliographic record
Abstract
Evaluating scars is fundamental to analyse the outcome of treatments that include surgical intervention. Scales facilitate this type of assessment, but most of these measuring instruments are in different languages. The Patient and Observer Scar Assessment Scale (POSAS) is one of the most robust instruments available in the literature for the evaluation of scars, although there is no validated version in Brazilian Portuguese. The aims of this study were to culturally translate and validate POSAS for the Portuguese language of Brazil and to test its reproducibility, face validity, content, and construct. Following the methodology proposed by Beaton DE, Bombardier C, Guillemin F, Ferraz, MB, Spine 2000, 25, 3186, the questionnaire was translated and adapted to the Brazilian culture. The reproducibility, face, content, and construct validity were then analysed. In all, the scale was applied to 35 patients with postoperative scars (patient version) and 35 hand surgery specialists (version for the observer). The internal consistency was tested by Cronbach's alpha, and construct validation was performed by correlating the translated instrument with the Brazilian Portuguese translation of the Vancouver Scar Scale (VSS). The cultural adaptation of POSAS Escola Paulista de Medicina/Universidade Federal de São Paulo (EPM/UNIFESP) was confirmed. Both subscales showed strong internal consistency (Cronbach's α = 0.77-0.93), demonstrating reliability. The reproducibility was excellent, and the adapted scale demonstrated significant intra- and inter-observer reproducibility (r > 0.9) (P < 0.05). The validity of the construct was significant and showed good sensitivity between POSAS EMP/UNIFESP and the VSS. This study confirmed that POSAS EPM/UNIFESP can be used to evaluate patients with surgical scars in the Brazilian population. It has proven to be useful for clinical and research purposes, lending itself to capturing medical opinions and those of the patients themselves.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".