Varying perceptions of the role of “nurse as teacher” for medical trainees: A qualitative study
Bibliographic record
Abstract
INTRODUCTION: The informal curriculum-an essential complement to the formal curriculum-is delivered to medical trainees through learning outside the classroom. We sought to explore nurse-mediated aspects of trainee education in the informal curriculum in obstetrics and gynecology (OBGYN), as well as nursing perceptions of their role in medical trainee education. METHODS: Naturalistic, non-participant observations (40 h) were performed on a tertiary care birthing unit (BU) to document teaching and learning interactions. Insights gleaned from observations informed subsequent semi-structured interviews with BU nurses (n = 10) and focus group discussions with third-year medical students who had completed an OBGYN rotation (n = 10). Thematic analysis was conducted across data sets. RESULTS: Conceptions of nurse-mediated education differed considerably between nurses and trainees. Nurses were widely acknowledged as gatekeepers and patient advocates by both groups, although this role was sometimes perceived by trainees as impacting on learning. Interest and engagement were noted as mediators of teaching, with enhanced access to educational opportunities reported by trainees who modelled openness and enthusiasm for learning. Nurse-driven education was frequently tailored to the learner's level, with nurses feeling well positioned to share procedural knowledge or hard skills, soft skills (i.e. bedside manners), and clinical insights gained from bedside practice. DISCUSSION: Nurses are instrumental in the education of medical trainees; however, divergence was noted in how this role is enacted in practice. Given the valuable teaching resource BU nurses present, more emphasis should be placed on interprofessional co-learning and the actualization of this role within the informal curriculum.
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 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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".