Global perspectives: learning from the experiences of nursing students during the pandemic to enhance education
Bibliographic record
Abstract
This research explored the lived experiences of 40 undergraduate nursing students from the UK, Canada, Australia and Gibraltar during the COVID-19 pandemic. A retrospective survey of nursing students was aimed at understanding the impact of the pandemic on nursing education, placements and student wellbeing, as well as the challenges and emotional impact students endured associated with caring for COVID-19 patients. The narratives were collected through an online questionnaire disseminated via a Twitter (X) platform on social media. The findings revealed five key themes: the impact of the pandemic on nursing education and support; the impact of the pandemic on placements and student wellbeing; the challenges and realities of caring for COVID-19 patients as a nursing student; the impact of the pandemic on the students' education and placements; and the emotional impact of the pandemic on them. Based on these findings, evidence-based recommendations are provided for supporting nursing students worldwide during pandemics and other public health crises.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".