Nursing students’ experiences of a post-licensure practical nurse bridging program: a qualitative systematic review protocol
Bibliographic record
Abstract
OBJECTIVE: This systematic review will synthesize the qualitative literature on students' experiences of a post-licensure practical nurse to registered nurse bridging program. INTRODUCTION: The worldwide shortage of registered nurses has prompted governments and educational institutions to develop alternative pathways to nursing licensure. One strategy used to increase the supply of registered nurses is bridging programs. These grant practical nurses academic credit for previous educational and practical experience, which allows them to complete a Bachelor of Nursing degree in a shorter period of time. However, attrition in bridging programs is a concern. Understanding the experiences of students enrolled in bridging programs will help identify their specific needs and the educational support needed for them to successfully transition into the registered nursing role. INCLUSION CRITERIA: This review will include published and unpublished studies that examine the experiences of practical nurses enrolled in bridging programs. Studies published in English will be considered, with no date limitations. METHODS: Databases to be searched include CINAHL, MEDLINE, Embase, and ERIC. Gray literature will be searched for in ProQuest Dissertations and Theses and GreyNet International. Reference lists of included studies will also be reviewed to identify additional studies. The critical appraisal of selected studies and the extraction of data will be independently undertaken by two reviewers using JBI methodology. The findings will be pooled using meta-aggregation to produce comprehensive synthesized findings. A ConQual Summary of Findings will also be presented. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42021278408.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.120 | 0.081 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.043 | 0.005 |
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".