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Record W2156366164 · doi:10.12927/cjnl.2000.16289

RN and RPN Decision Making Across Settings

2000· article· en· W2156366164 on OpenAlexaffvenue
J Royle, Alba DiCenso, Andrea Baumann, B Boblin-Cummings, J Blythe, Claire Mallette

Bibliographic record

VenueNursing leadership · 2000
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychologyHealth carePlan (archaeology)NursingMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

Nursing decision making was a focus of the Province-Wide Nursing Project (PWNP), a 3-year project to promote best nursing practice. In much of the growing literature on nursing decision making, it is assumed that there are differences in the way RNs and RPNs make decisions. However, there is little scientific evidence to support this assumption. The RN and RPN decision making across settings questionnaire was completed by nurses employed in the 23 agencies of the 4 Participating Complexes taking part in the project. The survey questions were subjected to factor analysis and reduced to five factors. Results revealed measurable differences between the way that RNs and RPNs made decisions. Both RNs and RPNs reported making decisions frequently and experiencing little difficulty in making them. However, there were statistically significant differences in the frequency with which RNs and RPNs perceived they made decisions and the difficulty they found in making them. To plan effective health care, it is important to take account of the strengths of different health care workers. There is a need for further research to investigate the reasons behind the differences revealed in these findings.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.188
GPT teacher head0.439
Teacher spread0.251 · 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.

Study designOther design
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

Citations9
Published2000
Admission routes2
Has abstractyes

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