A scoping review of the integration of ethics education in undergraduate nursing high‐fidelity human simulation‐based learning
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To systematically assemble, examine and map the extant literature pertaining to the integration of ethics education in high-fidelity simulation-based learning experiences in nursing undergraduate programmes. BACKGROUND: The value of ethics education for undergraduate nursing students is well established in the literature. Whether high-fidelity human simulation (HFHS) supports the development of ethical reasoning or positively impacts the acquisition of ethical knowledge and reasoning skills in undergraduate nursing students is inconsistently addressed. DESIGN: A scoping review was conducted using the Arksey and O'Malley framework. METHOD: CINAHL, ProQuest Nursing & Allied Health Source, ProQuest Dissertations & Theses A&I, MEDLINE, Web of Science, ERIC, Scopus, PsycINFO, and the Joanna Briggs Institute EBP databases were searched for English-language manuscripts published between 2012 and 2020. The PRISMA-ScR was used. RESULTS: Eight papers that met the inclusion criteria were extracted for this review. Three broad categories were identified: the 'what' in ethics education, the 'how' of ethics education and the 'when' of ethics education in high-fidelity human simulation. CONCLUSION: The integration of ethics education into simulation-based learning has the potential to positively promote nursing students' ability to develop knowledge of and skills in ethical practice. However, the inclusion of ethics education scenarios in HFHS is a relative new teaching innovation in undergraduate nursing education. As such, there continues to be no consensus on the 'what', 'how' or 'when' of ethics education for best practice in ethics education for undergraduate nursing programmes. RELEVANCE TO CLINICAL PRACTICE: Quality improvement processes and research studies are needed to determine: the types of ethical dilemmas and debriefing sessions and optimal timing of HFHS ethics simulation in undergraduate nursing education, student support needed for running HFHS, and the learning needs of nurse educators seeking to incorporate ethics within HFHS.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".