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Exploring COVID-19’s Impact On Undergraduate Nursing Students

2024· article· en· W4400405183 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePapers on postsecondary learning and teaching. · 2024
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicStressorNurse educationMental healthNursing2019-20 coronavirus outbreakPsychologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Medical educationMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

The researchers aimed to assess the effects of the COVID-19 pandemic on nursing education through semi-structured interviews with undergraduate nursing students. The researchers explored themes related to online education, clinical placements, and mental health. Findings revealed that the sudden shift to online learning caused increased stress, and decreased confidence. Clinical placements were affected, leading to missed time and altered learning experiences. Mental health suffered as students faced stressors and challenges brought on by the pandemic. These interviews elucidate the challenges faced by nursing students during the COVID-19 pandemic and provide valuable information for future planning in nursing education during 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.455
Teacher spread0.361 · 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