Translation, Cross-Cultural Adaptation, and Validation of the Chronic Rhinosinusitis Patient-Reported Outcome (CRS-PRO) into Hebrew
Bibliographic record
Abstract
Backgrounds: Designed to measure symptoms and quality-of-life impacts, the chronic rhinosinusitis patient-reported outcome (CRS-PRO) questionnaire is a novel instrument tailored to CRS patients. This study aimed to translate the CRS-PRO into Hebrew, adapt it cross-culturally, and assess its reliability and validity. Methods: A prospective study was conducted with 127 participants across three groups: CRS, functional endoscopic sinus surgery (FESS), and control groups (healthy individuals). Participants completed the Hebrew CRS-PRO at baseline and one month later. The Hebrew version was developed according to the International Society for Pharmacoeconomics and Outcomes Research guidelines for translation and cross-cultural adaptation. Results: Of the 127 participants (mean age 47.3 ± 17.7 years, range 18–93), 77 were males (60.6%), and 50 were females (39.4%). The Hebrew CRS-PRO demonstrated high internal consistency (Cronbach’s alpha 0.936) and strong discriminant validity among the three groups. Baseline mean scores were 7.2 for the control group, 25.2 for the FESS group, and 27.1 for the CRS group, which subsequently decreased to 6.5, 12.9, and 20.4, respectively, after one month (ANOVA, p < 0.001). Test–retest reliability, supported by Pearson’s correlation (p < 0.01) and intraclass correlation (p < 0.0001), demonstrated the questionnaire’s effectiveness in identifying CRS-related symptoms and monitoring improvement after FESS. Conclusions: The adaptation and validation of the CRS-PRO into Hebrew resulted in a reliable instrument in patients with CRS. It exhibited robust reliability, internal consistency, and strong discriminant validity, effectively differentiating between healthy individuals and CRS patients and those who are pre- and post-FESS. Additionally, the Hebrew CRS-PRO questionnaire may be effective for evaluating patients before and after FESS surgery.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".