Assessment of knowledge of celiac disease among health care professionals
Bibliographic record
Abstract
OBJECTIVES: To assess knowledge of celiac disease among medical professionals (physicians). METHODS: We conducted a cross-sectional survey of hospital-based medical staff in primary, secondary, and tertiary care public, and private hospitals in Riyadh, Saudi Arabia (KSA). We carried out the study between January 2013 and January 2104 at King Khalid University Hospital, King Saud University, Riyadh, KSA. A pretested questionnaire was distributed to the potential participants. A scoring system was used to classify the level of knowledge of participants into 3 categories: poor, fair, and good. RESULTS: A total of 109 physicians completed the survey and of these participants, 86.3% were from public hospitals, and 13.7% from private hospitals; 58.7% were males. Of the physicians, 19.2% had poor knowledge. Interns and residents had fair to good knowledge, but registrars, specialists, and even the consultants were less knowledgeable of celiac disease. CONCLUSION: Knowledge of celiac disease is poor among a significant number of physicians including consultants, which can potentially lead to delays in diagnosis. Educational programs need to be developed to improve awareness of celiac disease in the health care profession.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 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".