MétaCan
Menu
Back to cohort
Record W4407253854 · doi:10.12968/bjon.2023.0099

Global perspectives: learning from the experiences of nursing students during the pandemic to enhance education

2025· article· en· W4407253854 on OpenAlexaffabout
Barry Hill, Catherine Liao, Ian Peate, Helen Underdown

Bibliographic record

VenueBritish Journal of Nursing · 2025
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsFraser Health
Fundersnot available
KeywordsPandemicNursingNurse educationCoronavirus disease 2019 (COVID-19)NarrativeMedicinePsychologyMedical education

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.475
Teacher spread0.441 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueBritish Journal of NursingSame topicCOVID-19 and Mental HealthFrench-language works237,207