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Record W2946313722 · doi:10.1097/cnq.0000000000000266

Nurses' Use of Evidence-Based Practice at Point of Care

2019· review· en· W2946313722 on OpenAlexaff
Ivy McKinney, Rita A. DelloStritto, Steve Branham

Bibliographic record

VenueCritical Care Nursing Quarterly · 2019
Typereview
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsBrantford Energy (Canada)
Fundersnot available
KeywordsMedicineInterrogativeNursingPatient carePoint (geometry)Nursing practiceEvidence-based medicineMEDLINEPoint of careEvidence-based practiceFamily medicineAlternative medicine

Abstract

fetched live from OpenAlex

The article reports results of an interrogative literature review designed to study the acquisition of research-based knowledge among practicing nurses who provide direct patient care for decision making at the point of care. Findings reveal that despite the amount of research done on the use of evidence-based practice among nurses, gaps continue to exist between what is known and what is done in practice. Nurses often cite the lack of time and support and the lack of knowledge as predominant factors that keep them from using evidence-based practice at the point of care. The past research has primarily been completed using a retrospective approach. There is a paucity of research that evaluates specific nursing behaviors that support evidence-based practice in daily patient care.

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)0.031
metaresearch head score (Gemma)0.116
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: Review · Consensus signal: Review
Teacher disagreement score0.031
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.116
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0060.004
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.589
GPT teacher head0.644
Teacher spread0.055 · 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
GenreReview

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

Citations10
Published2019
Admission routes1
Has abstractyes

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