Medical Students’ Knowledge and Adherence to Paediatric Choking Rescue Manoeuvre Guidelines: A Multicentre Study of Medical Education Curricula
Bibliographic record
Abstract
Background/Objectives: Bystander first aid in paediatric choking is crucial. It ought to be universally comprehensible and backed up by evidence-based guidelines. However, there still are inconsistencies in guidelines worldwide. The objective of this research was to assess the knowledge of medical students on paediatric choking rescue manoeuvres and their educational backgrounds in order to evaluate the impact of differences in educational curricula. Methods: Medical students from a total of 12 universities across Canada, Libya, and Poland were surveyed online. The questionnaire assessed the respondents’ experience, training, and knowledge in first aid regarding foreign body airway obstruction in infants and children. Results: Out of 324 responses, 290 were evaluated. Although the students studied in only 3 countries, they represented 37 countries of origin. A total of 7 new reference groups were created based on guideline identification. A comparison of 4 clinical scenario questions revealed that certain training providers communicate recommendations more effectively to medical students, as their guidelines seem to have better knowledge retention. Conclusions: There are important differences in medical student knowledge, possibly due to discrepancies in training programs and guidelines. Variability was found in body position, anti-choking suction devices, blind finger sweeps, and medical follow-ups. More research is needed to standardize training and improve worldwide choking management outcomes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".