State of pathophysiology in undergraduate nursing education: A systematic review
Bibliographic record
Abstract
Background: Nurses who understand pathophysiology can provide higher quality patient care. Various pedagogical strategies make it unclear which practice meets the challenges of teaching pathophysiology. The aim of this systematic review was to synthesize research in the last ten years to report the current state of pedagogical strategies related to teaching pathophysiology concepts in undergraduate nursing.Methods: A systematic review of mixed, quantitative, and qualitative literature guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted from 2010 to 2020 through electronic databases.Results: Seven studies met the inclusion criteria. A gap exists among comparable research designs, pedagogy strategies, and outcomes specific to undergraduate nursing pathophysiology courses. Conclusions: Findings suggest that more rigorous research designs with validated measurement instruments are needed to compare student satisfaction and outcomes after different pedagogical strategies are applied to undergraduate pathophysiology courses. Also, there is a need to elicit findings related to the retention and effectiveness of pathophysiology concepts in clinical 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 | 0.021 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".