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Critical Care Nurses' Perceptions of DNR Status

2000· article· en· W1966710262 on OpenAlexaffabout
Jocelyne Thibault‐Prevost, Louise Jensen, Marilyn J. Hodgins

Bibliographic record

VenueJournal of Nursing Scholarship · 2000
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of New BrunswickUniversity of Alberta
Fundersnot available
KeywordsDo not resuscitateNursingDocumentationMedicineCritical care nursingPerceptionFamily medicinePsychologyHealth care

Abstract

fetched live from OpenAlex

PURPOSE: To describe the perceptions of nurses regarding do-not-resuscitate (DNR) decisions in critical care settings. DESIGN: A survey assessing knowledge, attitudes, and practices concerning DNR status was distributed to all critical care nurses who were registered with the provincial licensing body in Alberta, Canada, and held positions of staff nurse, educator, or manager. METHODS: Four hundred and five surveys were completed and returned. Descriptive analyses were conducted. FINDINGS: The term "DNR" was found to be ambiguous. The rationale for DNR orders were also not well articulated in practice. Although nurses believed that patients, families, and nurses should participate in DNR decisions, physicians were most often cited as being responsible for the decision. CONCLUSIONS: Documentation of a comprehensive patient treatment plan and awareness of the rationale for DNR designation are strategies suggested to help achieve desire patient care goals in critical care settings.

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)0.005
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.157
GPT teacher head0.504
Teacher spread0.347 · 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 designQualitative
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

Citations49
Published2000
Admission routes2
Has abstractyes

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