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Record W4241079944 · doi:10.1097/hcm.0000000000000297

Night Shift Work and Its Health Effects on Nurses

2020· article· en· W4241079944 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

VenueThe Health Care Manager · 2020
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsShift workSleep deprivationMoodStressorMedicineConfidentialityData collectionQualitative researchPsychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

The purpose of this research was to study night shift work and its health effects on nurses. This was a quantitative study using descriptive design; it also incorporated three qualitative open-ended questions to complement the study. The data were collected using Survey Monkey, with an Internet based confidential data collection tool. The population of relevance to this study was nurses employed in hospital settings in the United States. E-mail addresses and Facebook were used to recruit participants. Results indicated that there is an increased risk of sleep deprivation, family stressors, and mood changes because of working the night shift. Rotating shifts were mentioned as a major concern for night shift nurses. Respondents agreed that complaints about fatigue and fatigue related illnesses in night shift workers were ignored. There was also a general perception among nurses working the night shift that sleep deprivation leads to negative health consequences including obesity; however, they were not as high a concern as rotating shifts or fatigue.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score1.000

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)0.0000.001

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 head0.022
GPT teacher head0.324
Teacher spread0.302 · 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