Arabic Translation and Validation of the Adult Oral Health Standard Set Questionnaire
Bibliographic record
Abstract
INTRODUCTION: The Adult Oral Health Standard Set (AOHSS) questionnaire was developed by the International Dental Federation (FDI) and the Oral Adult Health Working Group (OHWG) for oral health assessment in clinical settings, research and population health surveillance. The AOHSS comprises clinical-reported outcome measures (CROMs) and patient-reported outcome measures (PROMs), including demographics, oral health and oral function, record of pain, oral hygiene practices and treatment cost. This survey was developed in the English language; it has been tested in European populations and translated to other languages such as French. However, an Arabic translation would be needed to apply it for clinical and population-based research on oral health in the Arab world. This study aimed to translate and validate the PROMs section of the AOHSS questionnaire into Arabic. METHODS: The AOHSS questionnaire was translated into Arabic according to the guidelines of the International Society for Pharmacoeconomics and Outcome Research (ISPOR), through a process that included forward translation, backward translation, expert committee consensus and cognitive debriefing. The questionnaire's test-retest reliability was assessed using the intra-class correlation coefficient (ICC) at a 2-week interval on a convenience sample of 30 subjects. Internal consistency was assessed using Cronbach alpha. Construct validity of the final Arabic version was examined against the validated Arabic Oral Health Assessment WHO questionnaire on 100 participants from different Arab nationalities. The participants completed both questionnaires, and the results were compared using Spearman's rho correlation coefficient. RESULTS: The test-retest reliability assessment for the Arabic version of the AOHSS presented an average ICC of 0.83 (95% CI of 0.68-0.92), indicating excellent agreement. Cronbach's alpha coefficient was 0.75, indicating satisfactory internal consistency. For construct validity, Spearman's rho correlation coefficient ranged from 0.14 to 0.90, indicating a statistically significant correlation with the WHO questionnaire. CONCLUSIONS: The Arabic version of the AOHSS is good for reliability, internal consistency and validity.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".