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Record W2088347401 · doi:10.3928/01484834-20100730-06

Nursing Student Perceptions of Intraprofessional Team Education Using High-Fidelity Simulation

2010· article· en· W2088347401 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Nursing Education · 2010
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDebriefingNursingCompetence (human resources)Nurse educationPerceptionInstructional simulationMedical educationPsychologyContext (archaeology)MedicinePedagogy

Abstract

fetched live from OpenAlex

High-fidelity simulation in health professional programs helps educators and students meet the challenges of increasingly complex clinical practice settings. Simulation has been used primarily to train nursing students either in interprofessional teams or within their respective nursing training levels. However, students' experiences of learning alongside others in different levels or years of the nursing program have not been explored. BSN students (N = 48) were placed in intraprofessional teams (i.e., one student from each nursing level) to manage acute pediatric and adult simulation scenarios. Students were instructed to manage the clinical scenario based on their level of clinical competence and education. Following debriefing, students responded to a satisfaction survey regarding their simulation experiences and their perceptions of learning within an intraprofessional nursing team. Project results suggest that intraprofessional educational experiences provide rich learning opportunities for both third-year and fourth-year nursing students. In addition, simulation provides a context within which to support intraprofessional nursing student education.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.512
Teacher spread0.455 · 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