Nurse practitioner affecting systems change in the context of a LEADS leadership framework: Experience from the field
Bibliographic record
Abstract
AIM: This paper highlights a new role of Advanced Practice Nurse/Nurse Practitioner as the clinical planning lead in the development of a unique model of care and service delivery for children living with health complexity, in the context of a LEADS leadership framework and related capabilities. BACKGROUND: The LEADS in a Caring Environment Framework is an effective tool for leadership development and systems change. An experienced Advanced Practice Nurse/Nurse Practitioner hired into a leadership role contributes to system change for a complex population across a large geographic area. SOURCES OF EVIDENCE: World Health Organization, Canadian Nurses Association and other websites, academic databases (PubMed and CINAHL) and relevant books were explored, and the expertise and knowledge of the authors and the redevelopment project team were utilized. DISCUSSION: The Advanced Practice Nurse/Nurse Practitioner (first author) shares and reflects on her own lived experience as a leader in the planning for programmes and services at the new centre utilizing the five LEADS domains and related capabilities. CONCLUSION: The utilization of the LEADS in a Caring Environment Capabilities Framework showcases the strengths and skills of an Advanced Practice Nurse/Nurse Practitioner shifting from direct clinical care to successfully leading system-level change. By incorporating the LEADS framework into practice, in any setting or role, Advanced Practice Nurse/Nurse Practitioners can both evaluate and develop their leadership skills while positively effecting system transformation. IMPLICATIONS FOR NURSING PRACTICE: The LEADS framework fosters ongoing professional development and can be used to measure the added value of Advanced Practice Nurses within an organization. IMPLICATIONS FOR NURSING POLICY: Advanced Practice Nurses improve outcomes within the health care system. Leaders must consider this evidence in health workforce planning, ensuring that Advanced Practice Nursing roles become fully integrated and are supported in the context of national and regional health systems.
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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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".