Nurses’ Perception of Readiness for Mass Casualty Events Involving Children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: During mass casualty events, hospitals must be ready to receive and provide patient care for both children and adults. However, many studies have shown that due to a lack of funding, resources, training, and time, nurses consistently report feeling unprepared to care for children during mass casualty events. Methods: To improve understanding of how prepared pediatric-trained nurses are to respond to mass casualty events involving children, Registered Nurses (RN) completed a survey with questions that included four domains: professional demographics and employment history, experience working as an RN in a mass casualty event, knowledge questions related to current organizational mass casualty procedures, and perceptions on professional preparedness.Results: Seventy-four percent of participants agree that a mass casualty event primarily involving children, requiring what is known as a Code Orange activation, will occur at some point during their career. Nurse participants do not currently receive regular training related to a Code Orange activation, and are overall dissatisfied with the little training provided. Nurses believe emergency preparedness is important to their professional development.Discussion: Increasing nurses’ preparedness to respond to a mass casualty event involving children is important and may require additional training across nurses’ career trajectory.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it