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Progress in application of Ottawa Model of Research Use in evidence-based nursing practice

2018· article· en· W3028694297 on OpenAlexaboutno aff
Wei Wang, Min Zhang, Yuting Niu, Chaoyu Li, Peiying Zhang, Dong Pang, Ping Yang, Sanli Jin, Qian Lü, Xiaohui Guo

Bibliographic record

VenueZhonghua xiandai huli zazhi · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsNursing practiceNursing researchKey (lock)Clinical PracticeEvidence-based practiceNursingEvidence-based nursingComputer sciencePsychologyMedicineAlternative medicine

Abstract

fetched live from OpenAlex

In order to clarify the characteristics and application status of the Ottawa Model of Research Use, this paper tries to expound its origin, development, core elements, assumptions and implementation steps, and summarize its characteristics. By analyzing the studies of evidence-based nursing practice using this model in recent years, the research aims to help researchers to further understand its implementation steps and provide reference for researchers to apply this model in evidence-based practice. Key words: Review; Evidence-based nursing; Ottawa Model of Research Use; Evidence-based practice model

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)0.012
metaresearch head score (Gemma)0.007
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 score0.411
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
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 head0.442
GPT teacher head0.616
Teacher spread0.174 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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