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Clinical Nurse Specialists' Use of Evidence in Practice: A Pilot Study

2007· article· en· W2025530992 on OpenAlexaffabout
Joanne Profetto‐McGrath, Karen Bulmer Smith, Kylie Hugo, Michael Taylor, Hannan El‐Hajj

Bibliographic record

VenueWorldviews on Evidence-Based Nursing · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExploratory researchEvidence-based practiceNursingVariety (cybernetics)Qualitative researchEvidence-based nursingPsychologyHealth careEvidence-based medicineMedicineMedical educationAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The interest in finding ways to bridge the gap between nursing research and implementation of findings into practice has been increasing. Clinical nurse specialists (CNSs) may be a bridge between frontline nurses and current developments in practice. While several researchers have studied the use of evidence by nurses in general, no known studies have been focused specifically on the use of evidence by CNSs. PURPOSE: The purpose of this pilot study was to develop an understanding of the sources, nature, and application of evidence used by CNSs in practice and to investigate the feasibility of conducting a qualitative study focused on the CNS role in relation to evidence use in practice. METHODS: This pilot study is a descriptive exploratory design in the qualitative paradigm. Seven CNSs from a large Western Canadian health region were interviewed. Interview transcripts were reviewed for recurrent themes about sources of evidence, evidence use, and barriers and facilitators to evidence use. FINDINGS: CNSs access and use evidence from a variety of sources. All CNSs indicated that research literature was a primary source of evidence and research was used in decision-making. Peers and experience were also important sources of evidence. CNSs used the Internet extensively to consult research databases, online sources of evidence, and to contact peers about current practice. CNSs also gathered evidence from frontline nurses, healthcare team members, and families before decision-making. The choice of evidence often depended upon the type of question they were attempting to answer. Barriers cited by CNSs support previous research and included lack of time, resources, and receptivity at clinical and organizational levels. Facilitators included peers, organizational support, and advanced education. DISCUSSION: CNSs in Canada have advanced education and clinical expertise and many are employed in roles that permeate organizational management and clinical nursing care. It is suggested that qualitative research in naturalized settings that investigates the role of CNSs in relation to the dissemination of evidence in nursing practice needs attention.

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)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.969
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.004
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.758
GPT teacher head0.661
Teacher spread0.097 · 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.

Study designObservational
DomainMethods
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

Citations54
Published2007
Admission routes2
Has abstractyes

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