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Record W2409529552

New Zealand nurses' reports on hospital care: an international comparison.

2007· article· en· W2409529552 on OpenAlexaboutno aff
Mary Finlayson, Linda H. Aiken, Ivana Nakarada‐Kordic

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingNursingCompetence (human resources)Health careEconomic shortageWork (physics)PerceptionNursing shortageJob satisfactionMedicinePsychologyFamily medicineNurse educationPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Despite the differences in health care systems, nursing shortages and their contributing factors and consequences no longer seem to be solely country-specific. The present study replicated a cross-national study of nurses' perceptions of staffing, work organisation and outcomes conducted in more than 700 hospitals in the United States, Canada, England, Scotland, and Germany. This paper compares the 2001 New Zealand findings with the findings of the five-country study. New Zealand nurses report similar shortcomings in their work environment as do the nurses in countries with distinctly different health care systems. While they report similar high levels of competence and good relations between doctors and nurses as the respondents in the other five countries, higher numbers of New Zealand nurses 30 years of age or younger report their intention to leave their current jobs. New Zealand nurses also report the highest levels of job related stress, high levels of job dissatisfaction, and more than half report receiving inadequate organisational support. The implications of these findings are discussed in light of recent changes in the hospital environment.

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)0.001
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 score0.297
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.038
GPT teacher head0.417
Teacher spread0.380 · 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

Citations15
Published2007
Admission routes1
Has abstractyes

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