Bibliographic record
Abstract
Aims To implement virtual simulation for the PEM training utilizing the Virtual resuscitation room (VRR) during COVID in the paediatric emergency department at The Hospital for Sick Children Methods After need assessment the gaps in the simulation based education for the learners in the paediatric ED were identified. The VRR was identifies as a fit to overcome the barriers. The VRR is a free low cost, interactive, collaborative approach to online simulation based education, adopted from the community ED team. It is a simple platform created using Zoom and google slide interface. The VRR had already been utilized for Medical students and adult EM training with high face validity. Therefore, it was adopted it for PEM. As per the learners needs 12 PEM cases were transformed to the VRR platform including, septic shock, croup, asthma, status epilepticus and DKA. Orientation and training session for using the VRR was organized for simulation fellows, PEM fellows and educators in the department separately. The training sessions were conducted for the Residents, Fellows and EM trainees and Community EM physicians. Debriefing was conducted utilizing the plus delta methodology with a standardized checklist provided to Facilitators. Feedback from both facilitators and learners were taken after each session regarding its Usability and feasibility. Results Total 10 sessions with 120 learners had been provided simulation based Education using the VRR. Total 12 common Paediatric PEM cases were developed to entail the need of the learners. There were 30% junior learners and 70% senior learners. Facilitators described it easy to use tool (83%) and feasibility in developing new cases (77%). They were able to modify or increase complexity as per the level of learners(80%) and interactive (86%). The facilitators felt that it was not useful in teaching resuscitation procedural skills (87%). The Learners feedback was taken on the Likert scale of 1-5 where 1 was least likely and 5 was most likely. Ninety seven percent of learner rated 4.4 out of 5 when said that they learnt something that is applicable to their clinical practise, 82% rated 4.3 out of 5 about the fact that the physiological clues, props, technology, and environment facilitated learning on VRR. The Debriefing was rated as 4.8/5 by 92% of the learners using the virtual platform. 97% of the learners were felt engaged in the virtual simulation and 94% felt that clinical clues provided like respiratory distress, capillary refill time, seizures were felt real. Most of the learners (87%) said that that difficult to learn procedural task. Conclusion VRR was found to be a feasible and useful platform to deliver simulation based education for PEM learners.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.671 | 0.448 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".