Differences between Saudi Arabian and Australian radiographers' knowledge and attitudes about paediatric CT doses
Bibliographic record
Abstract
Abstract Purpose : Computed tomography (CT) is used extensively in diagnostic radiology for examination of human soft tissues and is widely used in the paediatric population. Researchers and government regulators have expressed concerns about the cancer risk of CT radiation on children. The authors surveyed Saudi Arabian and Australian radiographers to enable comparison of their attitudes and knowledge towards paediatric CT radiation dose. Methods : Radiographers from all exclusively paediatric public hospitals in Australia and Saudi Arabia were sent a structured, purpose‐designed questionnaire. Data were analysed using univariate statistics. Results : 56 of 71 eligible Saudi Arabian radiographers (79%) and 50 of 83 Australian radiographers (60%) participated. Australian participants were more highly educated and had longer work experience than their Saudi counterparts, and undertook most forms of ongoing training and education significantly more frequently. Australians' mean ratings of radiation risk for head and chest CT scans were similar to those given by Saudi respondents, but Australians' mean ratings for abdomen/pelvis CT scans were significantly lower. More Australians reported intervening to reduce paediatric dose (95.7% vs 72.7%, P < 0.005), and 88.0% believed that over 60% of CT scans are justified compared with 8.9% of Saudi participants. Conclusion : Australian and Saudi Arabian radiographers working in paediatric hospitals differ in their knowledge bases. Knowledge can be improved through enhancement of hospital protocols and continuing education and training, and will lead to reduced radiation exposure among paediatric patients.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".