Disturbances of nursing students in internship during emerging disease COVID‐19 pandemic: A qualitative study
Bibliographic record
Abstract
AIM: The aim of the study was to examine the experiences of nursing students in internship during the COVID-19 pandemic. DESIGN: A qualitative study. METHODS: Purposeful sampling was conducted among undergraduate nursing students at Tabriz School of Nursing in November 2021. Students participated in 14 in-depth open-ended interviews and stated their experiences and opinions on internships during the COVID epidemic until full data saturation. Data analysis was performed using the conventional content analysis method. This study followed the Standards for Reporting Qualitative Research (SRQR) checklist. RESULTS: Findings were extracted and classified into five main categories, including a lack of facilities and equipment, psychological disturbances, physical risk, disturbances in education and learning activities and movement to continue clinical learning in the situation. CONCLUSION: Nursing students in clinical training during the COVID epidemic have experienced physical and mental health issues, as well as educational challenges. During an infectious disease epidemic period, education administrators should adopt appropriate strategies to protect students' health and facilitate their educational and learning activities.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".