How graduate nurses adapt to individual ward culture: A grounded theory study
Bibliographic record
Abstract
AIM: To increase understanding of strategies graduate nurses use on a day-to-day basis to integrate themselves into pre-existing social frameworks. BACKGROUND: Being a graduate nurse and transitioning from a novice to beginner in the first year of clinical practice is stressful, challenging and overwhelming due to steep learning curves and adjusting to working in professional environments. How graduate nurses socially adapt and fit into ward cultures is a hurdle to successful transition and can be difficult. DESIGN: A qualitative constructivist grounded theory methodology was used. METHODS: Seven adult, Registered Nurses were recruited using a purposive sampling technique. Participants were undertaking a graduate nurse transition programme, in one of two acute care, adult public hospitals in South Australia. Data collection conducted in 2016 used individual interviews consisting of open-ended questions in an unstructured format. Transcripts were transcribed verbatim. Data analysis processes included initial and focused coding, theory building, memo-writing and theoretical sampling. RESULTS: Three main categories: self-embodiment and self-consciousness, navigating the social constructs and raising consciousness, supported by subcategories describe the main strategies graduate nurses use to facilitate adaptation into complex clinical environments and ward cultures. Subsequent concept and theory development explains how graduate nurses find the social and professional balance to fit in. CONCLUSIONS: Understanding the graduates' adaptation strategies can inform improvements in graduate nurse transition programmes. Facilitating and enhancing graduate nurse adaptation is the precursor in creating more resilient nurses ready to face the challenges that exist in today's work environments.
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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 | 0.001 |
| 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".