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Record W1578422935 · doi:10.2147/amep.s14100

Evaluating an undergraduate interprofessional simulation-based educational module: communication, teamwork, and confidence performing cardiac resuscitation skills

2010· article· en· W1578422935 on OpenAlexafffund
Marian Luctkar‐Flude, Cynthia Baker, Pulling, McGraw, Dagnone, Medves, Turner-Kelly

Bibliographic record

VenueAdvances in Medical Education and Practice · 2010
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsQueen's University
FundersQueen's UniversityOntario Ministry of Health and Long-Term Care
KeywordsTeamworkMedical educationCommunication skillsResuscitationComputer scienceMedicinePsychologyEmergency medicine

Abstract

fetched live from OpenAlex

PURPOSE: Interprofessional (IP) collaboration during cardiac resuscitation is essential and contributes to patient wellbeing. The purpose of this study is to evaluate an innovative simulation-based IP educational module for undergraduate nursing and medical students on cardiac resuscitation skills. METHODS: Nursing and medical trainees participated in a new cardiac resuscitation curriculum involving a 2-hour IP foundational cardiac resuscitation skills lab, followed by three 2-hour IP simulation sessions. Control group participants attended the existing two 2-hour IP simulation sessions. Study respondents (N = 71) completed a survey regarding their confidence performing cardiac resuscitation skills and their perceptions of IP collaboration. RESULTS: Despite a consistent positive trend, only one out of 17 quantitative survey items were significantly improved for learners in the new curriculum. They were more likely to report feeling confident managing the airway during cardiac resuscitation (P = 0.001). Overall, quantitative results suggest that senior nursing and medical students were comfortable with IP communication and teamwork and confident with cardiac resuscitation skills. There were no significant differences between nursing students' and medical students' results. Through qualitative feedback, participants reported feeling comfortable learning with students from other professions and found value in the IP simulation sessions. CONCLUSION: Results from this study will inform ongoing restructuring of the IP cardiac resuscitation skills simulation module as defined by the action research process. Specific improvements that are suggested by these findings include strengthening the team leader component of the resuscitation skills lab and identifying learners who may benefit from additional practice in the role of team leader and with other skills where they lack confidence.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.508
Teacher spread0.478 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations43
Published2010
Admission routes2
Has abstractyes

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