Using Low Dose, High Frequency Simulation to Improve Skill Retention Among Pediatric Intensive Care Registered Nurses
Bibliographic record
Abstract
Background: The registered nurse (RN) and the respiratory therapist (RT) are integral parts of the care team in the PICU. The RTs are trained to become proficient in using a flow-inflating bag to provide bag-endotracheal tube (ETT) ventilation. The RN does not receive specialized training to adequately utilize the equipment. Methods: A low dose, high frequency (LDHF) randomized study was conducted with 39 RNs with less than 2 years of PICU experience. The RNs were informed of what the study involved and signed consent to participate. The study was IRB approved. RNs were randomized into three groups: control group A, intervention group B, and intervention group C. All participants were provided an educational handout with steps to manually ventilate a patient with an ETT. Group B participated in 2 LDHF simulation sessions utilizing a manikin within the first and third month following the initial skills assessment. Group C participated in 5 LDHF simulation sessions utilizing a manikin on a monthly basis. Each RN was rated on their ability to properly use the flow-inflating bag for ETT ventilation. The skill assessment was based on 9 components with a score of 1-5, 5 being proficient. The assessor was blind to the assigned groups and interventions. Primary components included rapid patient assessment, safety and infection prevention, adjusting flow and PEEP, monitoring end-tidal CO2 and oxygen saturations. Results: Group A had an initial score of 63% and a follow up score of 66%. Group B had a pre-intervention score of 60% and a post score of 76%. Group C had a pre-intervention score of 63% and a post score of 80%. A one-way ANOVA determined the results to be statistically significant (P < .05). Pre-study comfort level was evaluated, 68% of the 39 RNs reported they were uncomfortable using the flow inflating bag. Following the intervention 11% of the RNs remained uncomfortable. Approximately 30% reported neutrality before and after the study, and overall comfort level rose from 4% to 53%. Conclusions: Utilizing the LDHF simulation improved skill retention and comfort level. Continuing a culture of patient safety and interprofessional collaboration closed the gap for RNs between comfort and skill level. Education will be ongoing through skills lab with hands-on practice, interprofessional simulations with high-fidelity manikins, and accountability practices for continued patient safety.
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 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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".