EDUCATIONAL FACTORS INFLUENCING THE SELF-EFFICACY OF NEW GRADUATE NURSES FOR PROFESSIONAL COMPETENCIES DURING THE TRANSITION TO REGISTERED NURSE
Bibliographic record
Abstract
Problem: New graduate nurses (NGNs) are often considered the solution to the global\nnursing shortage. However, researchers are reporting an alarming new trend; NGNs are leaving the profession (Duchscher & Cowin, 2004; Sochalski, 2002). They are unprepared to work in the ‘real world’, even after successfully graduating from a nursing program.\nAim: This study examined the relationship between each of four educational factors (biological science courses, clinical practicum in undergraduate education; orientation/training provided by the employing hospital; post-registration preceptorship) and NGNs’ self-efficacy (confidence) for professional competencies as they transition to the role o f registered nurse.\nMethods: Based on Bandura’s theory of self-efficacy, a researcher-designed self-report questionnaire was mailed to 339 NGNs working in acute care hospitals across the province of Ontario. Results: Post-registration preceptorship most positively influenced NGNs’ confidence with their professional competencies. Specifically, preceptorship lasting at least 4 weeks, and the consistency of one preceptor, contributed to greater confidence for NGNs
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".