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Development of nurses' evidence-based practice skills: contributions of clinical supervision

2021· article· en· W3191192788 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRev Rene · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsWilcoxon signed-rank testTriangulationNursingClinical PracticeDescriptive statisticsTest (biology)Evidence-based practicePatient carePsychologyMedicineMedical educationAlternative medicine

Abstract

fetched live from OpenAlex

Objective: to evaluate the impact of the implementation of the SafeCare Model on the evidence-based practice competencies of nurses. Methods: mixed method characterized by concomitant triangulation. Quantitative data were collected before and after the implementation of the Model, by means of the Clinical Effectiveness and Evidence-Based Practice Questionnaire, with descriptive statistical analysis. Evidence values were obtained using the Wilcoxon test. Thirteen nurses participated. Qualitative data were obtained from interviews with 11 nurses from a public hospital and analyzed using the Content Analysis technique. Results: there were no statistically significant differences with the implementation of the model. However, nurses identified increased competencies in evidence-based practice with the recognition of advantages in their professional development, organization, and patient care. Conclusion: the implementation of the model has been shown to have contributed to the development of competencies in evidence-based practice.

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.

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)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.226
GPT teacher head0.570
Teacher spread0.344 · 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