AN EXPLORATION OF CRITICAL CARE NURSESâ EXPERIENCE OF NIGHT SHIFT FATIGUE AND WORKPLACE NAPPING: BRINGING IT OUT FROM UNDER THE COVERS
Bibliographic record
Abstract
Recently, there has been increasing recognition of the threat of fatigue on safety. Nursing has been slow to recognize this threat. Workplace napping is a fatigue management strategy that is used in some nursing workplaces, although often hidden. \n\nThis feminist interpretive phenomenological study explored the lived experience of night shift fatigue and the use of workplace napping among critical care nurses. An understanding of the meaning of night shift fatigue, the concern for safety as embodied by fear, was illuminated by exploring the phenomenological commonalities within the nurses’ historical, social and cultural world. Five main themes were identified within this overarching understanding. \n\nThere is a need to recognize oppressive constraints, and share the responsibility for managing fatigue among individuals, professions and organizations. In education, practice and research, nurses must be supported through validated evidence-informed strategies to manage what is a normal consequence of shift work, thus leading to enhanced safety for both the patient and nurse.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".