Nurse Residency Programs in Canada: A National Needs Assessment
Bibliographic record
Abstract
Purpose: Newly graduated registered nurses (NGRNs) often face significant challenges when transitioning into professional practice, including the need to bridge the gap between academic preparation and clinical expectations, manage high workloads, and further develop their practice. Organizational support is crucial for their growth, and nurse residency programs have shown promise in addressing these challenges. This project aimed to conduct a comprehensive needs assessment of hospitals across Canada to examine current practices supporting NGRN transitions and to assess employer interest in adopting a national standardized new graduate nurse residency program. Additionally, the assessment sought to identify barriers that may hinder the successful implementation of such a program. Method: This study used a mixed-methods needs assessment design to investigate the transition to practice and the use of nurse residency programs. We developed a survey, consisting of 11 questions adapted from previous research, to collect insights on current transition practices, challenges, barriers, and motivations for participating in a national residency program. The survey was initially distributed through HealthCareCAN, with additional outreach efforts aimed at nursing leaders responsible for NGRNs’ education and practice to ensure broader participation. Results: The survey received responses from 33 participants, representing hospitals in Atlantic and Northern Canada. The findings highlighted significant gaps in the current orientation and support systems for NGRNs. Respondents expressed a clear need for improvements in existing transition-to-practice programs and demonstrated a strong willingness to adopt changes, particularly through a national standardized nurse residency program. Most participants recognized the potential benefits of such a program, noting that it could address current challenges. Conclusion: The study identified significant gaps in current orientation support for NGRNs, highlighting the need for an enhanced approach to easing their transition into practice. Most participants showed strong interest in the development of a national standardized new graduate nurse residency program, recognizing its potential to improve their professional integration. Key challenges included a shortage of experienced nurses to serve as preceptors and mentors, inconsistent onboarding practices across health care settings, and limited resources for comprehensive education. To effectively address these issues, it is recommended to develop inclusive and supportive programs that meet the needs of both NGRNs and nurse leaders. Additionally, conducting further comprehensive and diverse needs assessments using mixed-methods research approaches would provide valuable insights for improving these initiatives.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".