Identifying, describing, and assessing interventions that support new graduate nurse transition into critical care nursing practice: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Given a persistent nursing shortage in Canada and a decline in new nurses entering the profession, new graduate nurses (NGNs) are being hired into positions historically reserved for more experienced staff. Critical care settings, which are areas of specialty nursing practice, are now routinely hiring NGNs in many hospitals. While evidence on NGN transition into critical care is emerging, best practices around training and support for these nurses are limited internationally, and non-existent within the Canadian context. Therefore, the aim of this systematic review is to identify, describe, and assess the effectiveness of interventions that support NGN transition into critical care clinical practice settings. METHODS: This is a systematic review of interventions using the Joanna Briggs Institute Methodology. Data sources will include MEDLINE, CINAHL, PsychINFO, Education Source, and Nursing and Allied Health electronic databases. Two independent reviewers will screen titles and abstracts using predetermined inclusion criteria. A consensus meeting will be held with a third reviewer to resolve conflicts when necessary. Full texts will also be screened by two independent reviewers and with conflicts resolved by consensus. Data will be extracted using a standardized extraction form. We will assess the quality of all included studies using Joanna Briggs Institute quality assessment tools. Data describing interventions will be reported narratively and a meta-analysis will be conducted to determine effectiveness, if appropriate. DISCUSSION: This systematic review will identify interventions that support NGN transition into critical care nursing practice. The findings of this study will provide a foundation for developing strategies to support NGN transition into these areas of specialty nursing practice. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020147962.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".