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Record W4301956181

Barriers and Facilitators to Evidence-Based Nursing in Colombia: Perspectives of Nurse Educators, Nurse Researchers and Graduate Students

2014· article· en· W4301956181 on OpenAlexaff
Rebecca R. DeBruyn, Sandra Catalina Ochoa Marín, Sonia Semenic

Bibliographic record

VenueVitae (Universidad de Antioquia) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsNursingNurse educatorNurse educationPsychologyMedicineMedical education
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT: To identify and describe the perceptions of nursing researchers, educators, and graduate students regarding the barriers to, and facilitators for, EBN in Medellín, Colombia.Methodology. Using a qualitative descriptive design, in-depth-semi-structured interviews were conducted with 12 participants associated with a large university faculty of nursing in Medellín,and one member of the National Association of Nurses. Qualitative content analysis was used to analyze the interview transcripts.Results. Several barriers to EBN were reported, including: lack off recognition of nursing as an autonomous profession; a lack off incentives for nurses to pursue advanced education or engage in research; limited availability and utility of nursing evidence;and a lack of communication between academic and clinical practice environments. Perceived facilitators included an increase in nurses pursuing advanced education opportunities; the current healthcare accreditation process; access to international research and research collaborations; and clinical and research partnerships between universities and clinical institutions.Conclusion. Effective implementation of evidence-based nursing practices is a necessity to translate the vast amount of health related research, knowledge, and experience into positive changes in healthcare quality.Key words: evidence-based nursing; education, nursing; research,nursing; information dissemination.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.132
GPT teacher head0.505
Teacher spread0.373 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations23
Published2014
Admission routes1
Has abstractyes

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