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Record W2067309769 · doi:10.1108/09526860410557561

Nursing work environment and quality of care: differences between units at the same hospital

2004· article· en· W2067309769 on OpenAlexaffabout
Jane McCusker, Nandini Dendukuri, Linda Cardinal, Johanne Laplante, Linda Bambonye

Bibliographic record

VenueInternational Journal of Health Care Quality Assurance · 2004
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsMcGill UniversitySt Mary's Hospital Centre
Fundersnot available
KeywordsNursingScale (ratio)Work (physics)Confirmatory factor analysisMultilevel modelQuality (philosophy)Work environmentMedicineComputer scienceStructural equation modeling

Abstract

fetched live from OpenAlex

The literature suggests that improvements in nurses' work environments may improve the quality of patient care. Furthermore, monitoring the work environment through staff surveys may be a feasible method of identifying opportunities for quality improvement. This study aimed to confirm five proposed sub-scales from the Nursing Work Index - Revised (NWI-R) to assess the nursing work environment and the performance of these sub-scales across different units in a hospital. Data were derived from a cross-sectional survey of 243 nurses from 13 units of a 300-bed university-affiliated hospital in Quebec, Canada, during 2001. Using confirmatory factor analysis, the five subscales were confirmed; three of the sub-scales had greater ability to discriminate between units. Using hierarchical regression models, "resource adequacy" was the sub-scale most strongly associated with the perceived quality of care at the last shift. The NWI-R sub-scales are potentially useful for comparison of work environments of different nursing units at the same hospital.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.434
Teacher spread0.357 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations68
Published2004
Admission routes2
Has abstractyes

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