Translation, cultural adaptation and validation of the SCHNOS in French
Bibliographic record
Abstract
BACKGROUND: The Standardized Cosmesis and Health Nasal Outcomes Survey (SCHNOS) is a validated questionnaire that assesses functional and aesthetic outcomes of rhinoplasty patients. There are 274 million French speakers worldwide, and this questionnaire is currently not available in French. The purpose of this study was to translate, adapt, and validate a French version of the SCHNOS questionnaire. METHODS: The SCHNOS questionnaire was translated from English to French according to international guidelines. Ten French-speaking rhinoplasty patients were interviewed in order to evaluate the understandability and acceptability of the translation and produce a final version. The final version was administered prospectively to 25 rhinoplasty patients and 25 controls at two-week intervals. It was then administered to 165 consecutive patients. Psychometric properties were evaluated using the Item Reponse Theory (IRT) and confirmatory factor analysis (CFA). RESULTS: Three items from the original SCHNOS were modified to produce the French-SCHNOS (F-SCHNOS). Discrimination abilities of F-SCHNOS-O and F-SCHNOS-C were perfect, with values of 2.18(p < 0.001, 95% CI 1.74 to 2.62) for SCHNOS-O and 2.62(p < 0.001, 95% CI 2.03 to 3.21). Internal consistency was high, with Cronbach's alpha of 0.93 for F-SCHNOS-O and 0.95 for F-SCHNOS-C. IRT showed good psychometric properties with almost each step up or down across the scale associating with meaningful differences in outcome severity. All four SCHNOS-O items were equally "important" in defining the total score. The F-SCHNOS-C total score was defined by mostly four out of six items. CONCLUSIONS: The SCHNOS was translated, adapted, and psychometrically validated for use in a French-speaking population.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".