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

2015· article· en· W2236848972 on OpenAlexaff
Kátia Grillo Padilha, Siv K. Stafseth, Diana Solms, Marga Hoogendoom, Francisco Javier Carmona Monge, Om Hashem Gomaa, Konstantinos Giakoumidakis, Μαργαρίτα Γιαννακοπούλου, Maria Cecília Bueno Jayme Gallani, Edyta Cudak, Lilia de Souza Nogueira, Cristiane Moretto Santoro, Regina Márcia Cardoso de Sousa, Ricardo Luís Barbosa, Dinís Dos Reis Miranda

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.275
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations98
Published2015
Admission routes1
Has abstractyes

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Same venueRevista da Escola de Enfermagem da USPSame topicDelphi Technique in ResearchFrench-language works237,207