Educational strategies supporting the development of ethical competence among nursing students: an integrative review
Bibliographic record
Abstract
The academic environment is a good place to develop an ethical competency. The overall goal of the project is to support the development of ethical competence in nursing students and to help them deal with ethical issues and dilemmas. METHOD: An integrative review of scientific studies focused on the strategies used to develop ethical competence and to support resolution of ethical issues and dilemmas among nursing students was conducted in the following databases: CINAHL, PubMed, Embase, Education Source and ERIC 2009-2019). Two reviewers worked independently. The final inclusion was decided after review of all agrees and disagrees with the principal investigator of the project. The Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of studies for this review. The included studies met the following inclusion criteria: (i) derived from a scientific study; (ii) involved nursing students; concerning teachings methods; concerning ethical competence; being published in English or French. Conference papers, proceedings, literature review, non-intervention studies and studies focused in other health specialities were excluded. RESULTS: Electronic searching yielded a total of 2704 citations, 21 publications were selected in the final review. DISCUSSION: The main results showed several gaps in the methodologies used. The first gap is the lack of consensus on the definition of ethical competence resulting in the absence of a specific theoretical framework for teaching it. All the interactive and multimodal teaching methods, with active student engagement were effective and enabled them to develop ethical competencies and related communicative skills, interpersonal skills, collaboration, and critical thinking. Among the pedagogical approaches, the conventional, theoretical approach was rated the least by the students, but not necessarily the least effective. CONCLUSION: Circumscribing the definition of ethical competence and developing a theoretical model adapted to nursing should remain a priority in order to better guide teachers. Multimodal teaching methods seem to be unanimously accepted and meet the learning objectives set by the various studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.021 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".