Dissemination, Utilization, and Satisfaction With Emergency Medicine Resident Simulation Curriculum for Pediatrics (EM ReSCu Peds) by North American Residency Programs
Bibliographic record
Abstract
OBJECTIVES: Our research team's primary objective was to investigate how a custom standard simulation curriculum for teaching emergency medicine residents about pediatrics was being used by programs across North America. We also wanted to know if program directors were satisfied with the curriculum and whether they had challenges with implementing it. Our long-term goal is to promote the Emergency Medicine Resident Simulation Curriculum for Pediatrics for use by all programs in the United States. METHODS: We distributed an electronic questionnaire to individuals who have downloaded the Emergency Medicine Resident Simulation Curriculum for Pediatrics in the form of an e-book from the Academic Life in Emergency Medicine Web site. The curriculum was marketed through national emergency medicine (EM) and pediatric emergency medicine (PEM) groups, PEM listserv, and through the International Network for Simulation-Based Pediatric Innovation, Research, and Education. We asked survey recipients how they used the curriculum, plans for future maintenance, satisfaction with curriculum use, and whether they had any challenges with implementation. Finally, we asked demographic questions. RESULTS: Most survey respondents were EM or PEM health care physicians in the United States or Canada. Respondents' primary goal of using the curriculum was resident education. Through assessment with the Net Promoter Score, satisfaction with the curriculum was net positive with users largely scoring as curriculum promoters. We found COVID-19 and overall time limitations to be implementation barriers, whereas learner interest in topics was the largest cited facilitator. Most responders plan to continue to implement either selected cases or the entire curriculum in the future. CONCLUSIONS: Of those who responded, our target audience of EM physicians used our curriculum the most. Further investigation on implementation needs, specifically for lower resource emergency programs, is needed.
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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 | 0.005 | 0.021 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".