Evaluation of a Multidisciplinary Pediatric Mock Trauma Code Educational Initiative: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Our aim was to develop and evaluate a multidisciplinary pediatric mock trauma code orientation program for residents on their pediatric hospital rotation. METHODS: A before and after evaluation of trauma team residents from various programs was conducted. The 1-hour educational session consisted of a 15-minute mock trauma code, a debriefing and teaching intervention, and then a new, postintervention mock trauma code. Before and after each session, residents completed a self-assessment questionnaire. All codes were videotaped and later evaluated by two blinded observers using a standardized evaluation tool to assess patient management and team functioning. RESULTS: Thirty-seven prequestionnaire (pre) and postquestionnaire (post) pairs were completed. Residents reported a significant improvement in their (1) comfort in managing pediatric trauma (median pre 3, post 5, p < 0.001); (2) understanding of their role on the trauma team (median pre 4.5, post 6, p < 0.001); (3) familiarity with the resuscitation room (median pre 4, post 5, p = 0.001); (4) comfort with procedural skills (median pre 4, post 5, p = 0.001); (5) awareness of pediatric trauma resuscitation management priorities (median pre 5, post 6, p = 0.007). Postintervention, residents reported lower knowledge scores in locating equipment in the resuscitation room (p < 0.001). There was no significant difference in team performance on the videotaped assessments (premean score = 79.8, postmean score = 79.5). CONCLUSIONS: The pediatric mock trauma code educational initiative improved residents' self-reported confidence, knowledge, and comfort level in managing pediatric trauma. The experience also raised residents' awareness of knowledge gaps. We were unable to measure a significant change in team functioning post intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".