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Record W2109651568 · doi:10.12927/cjnl.2006.18603

Leadership Strategies to Influence the Use of Clinical Practice Guidelines

2006· article· en· W2109651568 on OpenAlexaffvenueabout
Wendy Gifford, Barbara Davies, Nancy Edwards, Ian D. Graham

Bibliographic record

VenueNursing leadership · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBest practiceGuidelineGrounded theoryPsychologyClinical PracticeQualitative researchLeadership studiesNursingLeadership styleMedical educationMedicinePolitical scienceSociologySocial psychology

Abstract

fetched live from OpenAlex

Support from nursing managers and administrators, together with the role of a dedicated project Lead, are consistently identified as important strategies for nurses to be able to use research evidence in their practice. However, little is known about the key behaviours and activities required to successfully implement and sustain research-based innovations in practice. This study describes the leadership behaviours and activities that influenced nurses' use of clinical practice guidelines. A secondary analysis of qualitative data was conducted to investigate factors that contributed to sustaining (or not) the use of clinical guidelines two and three years after implementation as part of the Registered Nurses Association of Ontario Best Practice Guidelines project. Grounded theory techniques were used to develop a theoretical model of Leadership. Findings indicated a different pattern of leadership in organizations that sustained guidelines, when compared to those that did not. Three broad leadership strategies emerged as central to successfully implementing and sustaining guidelines: (1) facilitating staff to use the guidelines, (2) creating a positive milieu of best practices and (3) influencing organizational structures and processes. Leadership for guideline implementation was found to include such behaviours as support, role-modelling commitment and reinforcing organizational policies and goals consistent with evidence-based 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 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)0.006
metaresearch head score (Gemma)0.027
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: none
Teacher disagreement score0.626
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.915
GPT teacher head0.651
Teacher spread0.263 · 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.

Study designNot applicable
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

Citations7
Published2006
Admission routes3
Has abstractyes

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