Professional Role Transition in Nursing: Leveraging Transition Theory to Mitigate the Current Human Resource Crises
Bibliographic record
Abstract
New graduate nurse (NGN) turnover is emerging as one of the foremost issues in healthcare systems, primarily due to the implications for patient care and the need to secure the human resource future of the nursing profession. The initial months of transitioning into the professional role are crucial for cultivating and developing clinical practice patterns, professional values and a connection to the profession. However, the initial transition period for new nurses is associated with numerous challenges that can interrupt a healthy introduction into practice, justifying the critical prioritization of these issues. In light of these challenges to NGN entry to practice, this paper aims to conceptualize the contemporary professional role transition experiences of new graduate nurses and highlight the potential leverage that transition theories offer in managing this experience. Eleven transition theories relevant to this discourse were identified to enhance the understanding and comprehension of the new graduate nurses to inform future initiatives, directives, interventions and policies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".