How Formal and Informal Nurse Leaders Enact Shared Implementation Leadership in a Hospital Setting
Bibliographic record
Abstract
AIM: To describe how implementation leadership manifests among formal and informal point of care nurse leaders during a successful evidence-based practice implementation. DESIGN: A collective case study. METHODS: A conceptual framework on shared implementation leadership guided the study. Two units known for strong implementation were selected as instrumental cases from a healthcare network. Data were collected from multiple sources (2022-2023), including document review, site visits, focus group and individual interviews with formal managerial and non-managerial nurse leaders, staff nurses, interdisciplinary clinical staff and departmental leaders. The Framework Method was used to thematically analyse within-case findings, followed by cross-case comparison. RESULTS: Nurse leaders in formal and informal roles engaged in collaborative processes to collectively enact leadership behaviours throughout the implementation phases. Change-, relation- and task-oriented behaviours aimed to foster staff readiness, ensure supportive presence, structure implementation activities and reinforce the use of evidence-based practices on the units. Collaborative processes fostered leaders' engagement and kept one another informed to align and synchronise their collective actions. CONCLUSION: This study extends our understanding of implementation leadership in nursing by highlighting a shared and relational approach among diverse point of care leaders. Strengthening team-level processes is essential to enhance leadership capacity for implementation in nursing. IMPLICATIONS FOR THE PROFESSION: Given the global push for innovative, high-quality healthcare, strong leadership is needed to create conditions for implementation and practice change. This study makes visible how multiple and diverse leaders collectively support implementation. IMPACT: With much focus on nurse manager roles, there is a gap in the research showing how multiple point of care leaders facilitate implementation, which this study addresses. This study can serve as a template to assist nurse leaders in their implementation efforts and to advocate for developing diverse nurse leadership roles. REPORTING METHOD: The report adheres to the COnsolidated criteria for REporting Quality research (COREQ) guidelines. PATIENT OR PUBLIC CONTRIBUTION: This study did not include patient or public involvement in the design, conduct or reporting. TRIAL REGISTRATION: International Registered Report Identifier (IRRID): DERRI-10.2196/54681.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".