Teaching professionalism to Saudi nursing students using guided reflection on clinical vignettes
Bibliographic record
Abstract
Background and objective: Professionalism has to be explicitly taught in clinical rotations, yet little is reported about approaches for teaching professionalism in undergraduate nursing education. This study aims to educate undergraduate nursing students on professionalism using guided reflection on clinical vignettes.Methods: Real-life vignettes were designed to describe common professionalism dilemmas in Obstetrics and Gynecological Nursing curriculum. Teachers used a set of seven questions to trigger discussions and guide reflection on each vignette. During the session, observation notes were taken by peers on teachers’ performance, students interaction and group dynamics during the sessions. After the session, students fill in a survey to report their feedback on the sessions.Results: A total of 91 third-year nursing students participated in the study felt as if they are professional nurses who manage real cases, with feedback from teachers. Students – in groups – were able to indicate stakeholders in each dilemma and advocate their decision. They enjoyed the sessions the highest mean (4.48 ± 0.93) and felt more prepared to encounter similar situations in their future clinical practice.Conclusions: Interactive sessions of guided reflections on professionalism dilemmas enabled students to reflect as individuals and in groups, to respect the scope of practice and acknowledge perspectives of different stakeholders. Apart from students’ feedback, teachers acknowledged essential competencies that have to be addressed while dealing with professionalism dilemmas. A couple of strategies were recommended for teaching professionalism in nursing education using guided reflection. Nursing students need to learn about: emotional intelligence, risk estimation, and strategies for interference in cases of conflict with colleagues, patients and their relatives, doctors in charge, and the fetus, if applicable, in Obstetrics. Guided reflection sessions on clinical dilemmas were found effective to teach professionalism in nursing students in Obstetrics and Gynecological nursing clinical experience.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".