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Nursing Activities Score: an updated guideline for its application in the Intensive Care Unit

2015· article· en· W2236848972 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

VenueRevista da Escola de Enfermagem da USP · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGuidelineWorkloadStandardizationIntensive care unitMedicineDelphi methodNursingIntensive careDelphiIntensive care medicinePolitical scienceStatistics

Abstract

fetched live from OpenAlex

Objective To describe nursing workload in Intensive Care Units (ICU) in different countries according to the scores obtained with Nursing Activities Score (NAS) and to verify the agreement among countries on the NAS guideline interpretation. Method This cross-sectional study considered 1-day measure of NAS (November 2012) obtained from 758 patients in 19 ICUs of seven countries (Norway, the Netherlands, Spain, Poland, Egypt, Greece and Brazil). The Delphi technique was used in expertise meetings and consensus. Results The NAS score was 72.8% in average, ranging from 44.5% (Spain) to 101.8% (Norway). The mean NAS score from Poland, Greece and Egypt was 83.0%, 64.6% and 57.1%, respectively. The NAS score was similar in Brazil (54.0%) and in the Netherlands (51.0%). There were doubts in the understanding of five out 23 items of the NAS (21.7%) which were discussed until researchers' consensus. Conclusion NAS score were different in the seven countries. Future studies must verify if the fine standardization of the guideline can have a impact on differences in the NAS results.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.275
GPT teacher head0.509
Teacher spread0.233 · 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