Impact of Nurse Residency Programs on Retention and Job Satisfaction: An Integrative Review
Bibliographic record
Abstract
Objects: Retention of new nurses is vital within the context of the nursing shortage Canada is currently facing. Nurse residency programs (NRP) need to be explored to better understand their role in combating the nursing shortage. The aim of this study is to explore current nurse residency programs and their impacts on retention and job satisfaction with the aim to inform development of similar programs in Canada. Methods: The study utilized Whittemore and Knafl’s integrative review methodology to review current literature on nurse residency programs in The United States of America with focuses on retention rates, job satisfaction and intent to leave. Overall, this article drew on seven distinct research studies. Findings: The literature review found that Nurse Residency Programs (NRP) can improve retention rates however, this may be due to contracts signed upon beginning of NRP. Job satisfaction for newly licensed registered nurses (NLRNs) participating in NRP also showed improvements but their impact on reducing turnover intention is unclear and needs further study. Conclusion: The impact of nurse residency programs on retention and job satisfaction has some positive effects, but the strength of this relationship remains unclear and would benefit from further research.
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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 | 0.003 | 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 | 0.000 |
| 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".