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Record W2808069815 · doi:10.1111/jocn.14547

Response to Commentary on Cheng, Broome, Feng, and Hu (2017) Leadership behaviours play a significant role in implementing evidence‐based practice. Journal of Clinical Nursing, 2018;27:e1684–e1685

2018· article· en· W2808069815 on OpenAlexaboutno aff
Lei Cheng, Sheng Feng, Yan Hu, Marion E. Broome

Bibliographic record

VenueJournal of Clinical Nursing · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)AcknowledgementLeadership developmentEvidence-based practicePsychologyLeadership styleEditor in chiefTransformational leadershipPublic relationsMedical educationManagementPolitical scienceMedicineSocial psychologyAlternative medicineComputer science

Abstract

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Thank you for the opportunity to respond to Hu and Gifford's comments (Hu & Gifford, 2018). We appreciated their acknowledgement of our findings about the factors influencing the successful implementation of evidence-based practice (EBP). The authors described leadership behaviours as having a significant role in implementing evidence-based practice. Although we did not specifically discuss leadership in the previous paper (Cheng, Broome, Feng, & Hu, 2017a), we agree and acknowledge the importance of leadership during evidence implementation. It was interesting to read about Hu and Gifford's work in progress related to the study of leadership behaviours in EBP. In subsequent papers, we have further explicated the role of leaders in EBP and therefore wish to offer further insights in this commentary. Hu and Gifford (2018) described two measures (i.e., O-MILe and ILS) that have been developed and validated to assess leadership in the EBP context based on the literature. These measures will be very important to scholars of EBP implementation. In our work, three questions arose related to leadership in this context and go beyond just the behaviours evidenced by leaders: (a) Who are the leaders for evidence implementation; (b) what is essential preparation for the leaders; and (c) how do the leaders manifest their roles during the implementation. By reviewing the 24 implementation projects, we found many formal leaders, for example, nurse managers, staff nurses and faculty members. Their leadership is exemplified and differentiated by the implementation approaches they take, for example, top-down, bottom-up and outsider-in (Cheng, Broome, Feng, & Hu, 2017b). Meanwhile, informal leader that might complement the formal project leaders’ role during evidence implementation was also evident. For instance, staff nurse champions emerged in some projects to assist the leaders in educating colleagues, auditing actual performance and solving problems. Some staff nurses who were informal leaders also expressed their wiliness to become a formal leader to fill a new “gap” which became evident during implementation. This pattern of formal and informal leadership intertwined together to make the evidence “take root” in nursing practice. Thus, there is a need to prepare evidence implementation leadership at all levels of the health system. Although there had not been any formal requirements, we did find some common characteristics among those “successful/effective” formal and informal leaders. First, the leaders had a passion about looking for the latest evidence to solve patient care problems in nursing practice. They were aware of the needs of clinical settings and knew exactly what the gaps were. Second, they shared and exchanged their views with stakeholders across disciplines, for example, administrators, medicine, nursing, pharmacy, physiotherapy, logistics and information systems. Sometimes, they took on the informal role of “knowledge broker” as part of the leadership role, by identifying key attributes of the evidence that might be used and analysed the context and achieve the census among the stakeholders on implementation plans. Third, during the implementation, the leaders wisely allocated resources and struck a common ground where each stakeholder would be able to understand and achieve their own goal. In order to move the projects forward, they had to keep alert constantly to align the overlapping goals between person and system. Finally, leaders were able to foresee the proximal and long-term outcomes, as well as tangible and intangible impacts from evidence implementation. This vision lay behind their every act (even sacrificing personal time) and kept them persisting on this evidence implementation leadership journey. We realise that some of these behaviours are measured in Ottawa Model of Implementation Leadership (Gifford, Graham, Ehrhart, Davies, & Aarons, 2017). However, the qualitative approach that we took enabled us to paint a better picture of the “process of leadership” versus just the isolated behaviours evidenced by leaders as measured by quantitative scales. We found that leaders were often formally appointed by the hospitals, while other times they naturally took the lead. However, in either situation, they engaged in a variety of behaviours designed to keep “the projects moving.” For example, they responded to a particular clinical context, worked in a collective manner, engaged in strategic planning and functional management, exhibiting multifaceted behaviours at multiple levels. Support from higher administration was critical for the leaders fully play out their roles, especially for the bottom-up and outsider leaders. In a more recently published paper in the Journal of Nursing Management (Cheng, Feng, Hu, & Broome, 2018), we further analysed data from the previous study and provided exemplars for a better understanding of the nurse managers’ leadership role during evidence implementation. We found it important to consider “hierarchy and obedience” as important concepts in the mainstream culture of the Chinese existing health care system, and suggest enhancing managerial support with recognition of their efforts and preparation of the leaders as facilitators to integration of the best available evidence into nurses’ workflow. As Hu and Gifford pointed out in their commentary, leadership is much more than a role, position or status. Their work, as well as ours and others, has begun to build a more comprehensive picture of leadership and provide a deeper and broader understanding of how evidence-based practice can be achieved. However, the leadership for evidence implementation needs further exploration from the perspectives of staff nurse leaders, outsider leaders as well as the informal nursing leaders in various levels that assisted in compensating the formal leadership of nursing managers. None. None to declare.

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)0.011
metaresearch head score (Gemma)0.131
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.040
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.131
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0060.005
Scholarly communication0.0040.007
Open science0.0070.005
Research integrity0.0400.057
Insufficient payload (model declined to judge)0.0170.013

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 head0.495
GPT teacher head0.649
Teacher spread0.154 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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