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Record W2322504088 · doi:10.3928/00220124-20120904-33

Building Partnerships Using Student Role Models for Neonatal Resuscitation Simulation

2012· article· en· W2322504088 on OpenAlexaboutno aff
Desirée Hensel, Julie Kathman, Ronda Hendricks, Sonita Ball

Bibliographic record

VenueThe Journal of Continuing Education in Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsNeonatal resuscitationResuscitationNursingSimulation trainingMedical educationQuarter (Canadian coin)PsychologyMedicineNeonatal nursingNeonatal intensive care unitEmergency medicineSimulationPediatricsComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Although the use of simulation in schools of nursing is becoming common, its use in clinical practice is still emerging. This project explored how students could contribute to the clinical unit by supporting learning among experienced registered nurses who are new to simulation. METHODS: This quasi-experimental pilot study used a convenience sample of all perinatal nurses who participated in a neonatal resuscitation program renewal course in the fall quarter at a Midwestern U.S. hospital (N = 88). Satisfaction and confidence in learning were compared between groups of nurses who watched a simulation DVD with either instructors or students as team members before participating in a neonatal resuscitation scenario. RESULTS: The participants viewed the simulation as a positive experience. There was no significant difference in satisfaction or confidence with the simulation between the two groups. CONCLUSION: There may be opportunities for student nurses to make positive contributions to staff education on clinical units through simulation.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.458
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

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