Final Year Dental Students’ Perception of Knowledge, Training and Competence in Medical Emergency Management
Bibliographic record
Abstract
OBJECTIVE: The potential for a medical emergency to occur during dental treatment must be met by dental practitioners who are competent to manage such situations. However the literature shows that not all dentists have received training in this area, and of those who have, many are deficient in knowledge, skills and confidence. The objective of this study was to examine the perceptions of final year Jordanian dental students regarding their education and preparedness to manage medical emergencies.METHODS: This study was a cross-sectional, descriptive study which gathered questionnaire data from an undergraduate student cohort at two Jordanian universities. Descriptive analysis of the data was undertaken, and a Chi-squared test was used to explore the relationships between participants’ responses and the variables of gender and previous attendance at any ME workshop. Statistical significance was deemed at p<.05.RESULTS: Three hundred and seventy dental students responded to the questionnaire with response rates of 76.2% and 81.8% from the two sites. The results indicate that not all of the students had received training in medical emergency management, and their self-reported proficiency and experience was sub-optimal. However, participating in a workshop on managing medical emergencies was associated with changes in some skills and experiences.CONCLUSION: The low levels of medical emergency management knowledge and skills in the final year dental students reflects the situation reported in existing literature. This study indicates the importance of effective medical emergency management training within the dental undergraduate program, and may be used to inform future curricula planning.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".