Translation, validation, and cultural adaptation of the Rhinosinusitis Disability Index and the Chronic Sinusitis Survey into Arabic
Bibliographic record
Abstract
BACKGROUND: Disease-specific quality of life instruments assess the impact of chronic rhinosinusitis on patients' quality of life (QoL). To the extent of our knowledge, there are no Arabic versions of two instruments-the Rhinosinusitis Disability Index (RSDI) and the Chronic Sinusitis Survey (CSS). OBJECTIVE: Develop an Arabic-validated version of both instruments, thus allowing its use among the Arabic population. DESIGN: Prospective cross-sectional study for instrument validation. SETTING: Tertiary university hospital. SUBJECTS AND METHODS: This study was conducted between September 2015 and October 2016. We followed the international comprehensive guidelines for translation and cross-cultural adaptation of QoL instruments. MAIN OUTCOME MEASURES: Test-retest reliability, discriminant validity, and responsiveness ability of both the RSDI and CSS Arabic versions. SAMPLE SIZE: 124. RESULTS: The sample comprised 75 patients diagnosed with chronic rhinosinusitis and 49 healthy control subjects. The Arabic version of both instruments showed high internal consistency (Cronbach's alpha: RSDI=0.97, CSS=.88) and the ability to differentiate between diseased and healthy volunteers (P less than .0001). The translated versions also detected significant change in response to an intervention (P less than .0001). CONCLUSION: These Arabic validated versions of the RSDI and CSS can be used for both clinical and research purposes. LIMITATIONS: This study was performed in only one tertiary hospital. CONFLICT OF INTEREST: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".