Growth and Adaptation of Newly Graduated Nurses Based on Duchscher’s Stages of Transition Theory and Transition Shock Model: A Longitudinal Quantitative Study
Bibliographic record
Abstract
Background: The transition from student to registered nurse is a vulnerable period characterised by emotional strain, role ambiguity, and transition shock. Although Graduate Nurse Transition Programs (GNTPs) aim to strengthen early practice readiness, few evaluations use longitudinal, theory-informed approaches or validated tools. Aim: To examine the professional role development of new graduate nurses (NGNs) across three transition stages within a major Australian health service. Design and Methods: A longitudinal quantitative study guided by Duchscher’s Stages of Transition Theory and the Transition Shock Model. A customised 75-item questionnaire—adapted from the Professional Role Transition Risk Assessment Instrument and the Professional and Graduate Capability Framework—was administered at three transition points (March 2020–March 2021). Four domains were assessed: Responsibilities, Role Orientation, Relationships, and Knowledge and Confidence. Descriptive statistics, Principal Component Analysis (PCA), chi-square tests, and multinomial logistic regression identified developmental patterns and predictors of transition stage. Results: PCA supported a four-factor structure consistent with the theoretical domains, explaining 62% of variance. Significant stage-based improvements were found in clinical decision-making (RS6, p = 0.005), managing pressure (RS11, p = 0.003), leadership perception (RO5, p = 0.001), and emotional regulation (RL20, p < 0.001). Regression analysis identified role confusion (RS7, χ2 = 18.112, p = 0.001), leadership potential (RL1, χ2 = 25.590, p < 0.001), workplace support (RL16, χ2 = 12.760, p = 0.013), and critical thinking confidence (KN13, χ2 = 10.858, p = 0.028) as strong predictors of transition stage. By Stage 3, most NGNs demonstrated increased autonomy, confidence, and professional integration. A coordinator-to-graduate ratio of 1:12 facilitated personalised mentorship. Conclusions: Findings provide robust evidence for theoretically grounded GNTPs. Tailored interventions—such as early mentorship, mid-stage stress support, and late-stage leadership development—can enhance role clarity, confidence, and workforce sustainability.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".