156: Improving Pediatric Health Care Response in a Disaster Through Inter Professional Training
Bibliographic record
Abstract
Disasters can have a significant impact on the population. Children are particularly vulnerable due to their anatomical, physiological, developmental and psychological characteristics. Disaster preparedness must include consideration for the needs of pediatric populations. Training for the practical aspects of disaster medicine is a difficult task, simulation being the traditional method for these rare, high impact events. To assess the effect of an experiential learning experience, on inter professional pediatric health care providers' disaster preparedness skills and confidence. In 2012, the regional health agency launched a project in collaboration with public health, first responders, municipal police and public transit system, the Canadian Armed Forces and our level 1 pediatric trauma center as the first receiver site for pediatric victims. This large-scale unannounced in-situ, real-time, mixed-modality, pediatric disaster simulation included 43 simulated patients (high/medium/low fidelity simulators and standardized patients). The hospital care teams included a variety of inter professional participants. Since this group of learners had never been exposed to such an in- situ experiential learning experience, we assessed its educational value and effects. Ninety-three participants (from most medical and paramedical services) completed a self-assessment survey immediately following the simulation (with a retrospective pre-component to assess perceived change in skills and abilities) to determine perceived acquisition of knowledge and confidence. Participants' ratings of skills, abilities and confidence significantly increased following participation in this simulation for both medical items (n=53; F(1, 642)=44.1; P<0.0001), and non-medical items (n=83; F(1, 228)=29.7; P<0.0001), consistently across participant groups. Some target items were (standard deviations in parentheses): “Differentiate conventional triage from disaster triage” (pre = 3.91/6 (1.7), post = 4.8 (1.3), “Prioritize resources- maximize survival versus individual outcome” (pre = 3.64/6 (1.7), post = 4.40/6 (1.5), “Feel confident in own ability to respond to disaster” (pre = 3.58/6 (1.5) post = 4.94/6 (1.1), “Feel confident in hospital's ability to respond to disaster” (pre = 4.29/6 (1.3), post = 5.02 (0.9). Participants felt the pediatric disaster simulation day was valuable to their learning (5.68/6). The inter professional members of the pediatric disaster first receiver teams, believed that this simulation experience improved their ability to manage patients and increased their confidence in disaster situations, suggesting that inter professional training is beneficial in preparation for situations that require high level of inter professional communication and coordination, such as disasters.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".