Development of a pediatric orientation resource for new nurses in the operating room
Bibliographic record
Abstract
Background: Education on diverse patient populations is crucial for many unit orientations within nursing. Few units in acute care hospitals care for multiple populations; however, the operating room (OR) is a common one. Many ORs care for patients across their lifespans and should receive education on pediatric and adult populations. This is not the case at one acute care hospital. To address this issue, I developed a pediatric orientation for new nurses to the OR to increase their knowledge and competency when caring for pediatric patients. Methods: I completed a literature review, consultations with unit stakeholders, and an environmental scan to identify the impact of education on nursing practice, critical pediatric knowledge for OR nurses, and impactful delivery modalities for a pediatric orientation for new nursing hires to the OR. Utilizing the data from the literature review, consultations, and environmental scan, I created an OR pediatric orientation for new nursing hires. Results: Using the information from the literature review, consultations, and environmental scan, I created a one-day pediatric orientation. The foundational perioperative pediatric content covered in the orientation includes pediatric vital signs, airway and skin anatomy, thermoregulation, perioperative anxiety, parental presence for induction, developmental stages, and pediatric anesthesia and surgical considerations. This foundational content will be delivered by lecture using a PowerPoint presentation that will include text, videos, pictures, and gamification through knowledge checkpoints, rewards, and a crossword. Following the lecture, simulation and demonstration will be utilized to provide hands-on experience with parental presence for induction, mask induction, nasal and oral induction, and surgical instruments.
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".