A systematic review to appraise the evidence relating to the impact and effects of formal continuing professional education on professional practice
Bibliographic record
Abstract
The literature relating to post-registration education showed that registered nurses demand higher education in order to keep up with pre-registrants. The systematic review of the literature also suggested that registered nurses undertake higher education for personal reward but that it may have no direct benefit to patient care. This review was undertaken as part of an MSc in Health and Social Care Education. The review included 21 papers on registered nurses who had completed individual modules and full educational pathways, but did not consider mandatory study sessions or pre-registration programmes. Each article was critically appraised, data was extracted, tabulated, and synthesised using a narrative synthesis approach. The findings showed that diploma level students (those obtaining a qualification at an academic level equivalent to the 2nd year of a degree programme, but already professionally registered) acquired more knowledge during their studies. They were able to transpose them into practical skills and enhance the skills required for registration; but the literature also shows that these changes could not be maintained, due to other influences. Students of Bachelors and Masters Education developed academically and professionally, and whilst these effects advance more gradually, they are apparent long-term. All registered nurses, regardless of the level of academic study, met a number of barriers to implementing newfound knowledge and skills; and managerial constraints were found to be the most prominent. Overall findings indicate that post-registration higher education undertaken by nurses does positively influence professional practice.
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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 | 0.029 | 0.143 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".