Arabic Translation and Validation of Olfactory-Specific Quality of Life Assessment Questionnaire
Bibliographic record
Abstract
BACKGROUND: Olfaction plays a critical role in our health, emotions, social life and safety, which is why olfactory dysfunction has a great impact on a person's life. This has been highlighted with the recent coronavirus disease 2019 (COVID-19) pandemic. Despite Arabic being the fifth most commonly spoken language and one of the six official languages of the United Nations, there is no Arabic version for an olfactory-specific quality of life assessment tool. METHOD: The Questionnaire of Olfactory Disorders-Negative Statements (QOD-NS) is a validated questionnaire that assesses many aspects of a patient's daily life. We translated this questionnaire to the Arabic language following European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group Translation Procedure guidelines. A pilot-testing of the Arabic version was done among 20 participants, 10 of whom were confirmed to have normosmia based on scoring at least 11/12 on the Sniffin' Sticks (SS) olfactory testing (Group 1) and another 10 participants who reported anosmia and scored less than 7/12 on the SS test. Patients could agree, partially agree, partially disagree, or disagree with each questionnaire statement. RESULTS: The pilot study revealed that participants with confirmed anosmia had higher questionnaire scores compared to participants with normosomia (median 22 compared to 1, p value < 0.001). For each statement on the Arabic questionnaire, all questions scored at least 80% of intra-rater reliability, and the overall intra-rater reliability was 90%. CONCLUSION: The Arabic translation of QOD-NS is a validated questionnaire that can be used both in academic and clinical practice.
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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".