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Record W2426511212

Napping during breaks on night shift: critical care nurse managers' perceptions.

2013· article· en· W2426511212 on OpenAlexaboutno aff
Marie Edwards, Diana E. McMillan, Wendy M. Fallis

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionNursingPatient safetyHealth carePsychologyUnit (ring theory)Variety (cybernetics)Shift workWork (physics)Medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Fatigue associated with shiftwork can threaten the safety and health of nurses and the patients in their care. Napping during night shift breaks has been shown to be an effective strategy to decrease fatigue and enhance performance in a variety of work environments, but appears to have mixed support within health care. PURPOSE: The purpose of this study was to explore critical care unit managers'perceptions of and experiences with their nursing staff's napping practices on night shift, including their perceptions of the benefits and barriers to napping/not napping in terms of patient safety and nurses'personal health and safety. METHODS: A survey design was used. Forty-seven Canadian critical care unit managers who were members of the Canadian Association of Critical Care Nurses responded to the web-based survey. Data analysis involved calculation of frequencies and percentages for demographic data, use of the Friedman rank test for comparison of managers' perceptions, and content analysis for responses to open-ended questions. RESULTS: The findings of this study offer valuable insights into the complexities and conflicts perceived by managers with respect to napping on night shift breaks by nursing staff Staff and patient health and safety issues, work and break expectations and experiences, and strengths and deficits related to organizational napping resources and policy are considerations that will be instrumental in the development of effective napping strategies and guidelines.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.997

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)0.0030.004

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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations20
Published2013
Admission routes1
Has abstractyes

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