Enacting Nurses' Leadership Through A Critical Action Research Initiative
Bibliographic record
Abstract
Background: In Alberta, Canada, groups of family physicians engage with the provincial health authority to form Primary Care Networks. A major objective of PCNs is transformation of family practice clinics to the Patient’s Medical Home model. This model is built on a premise of strong leadership within the clinic typically provided by the family physician. Evidence of physician leadership is not consistently forthcoming. Towards this end I have explored how registered nurses enact leadership in the Patient’s Medical Home without occupying a specified leadership position. Aim of my Research: The aim of my research was to understand how nurses enact leadership in their respective Patient’s Medical Home. Further, in my research, I endeavoured to understand how leadership could be enhanced within each nurses’ unique context. Specifically, I explored (a) the impact of role identity on nursing leadership in the PMH; (b) the impact of physician-nurse power differentials on nursing leadership in the PMH; (c) the impact of unrecognized leadership potential on nursing leadership in the PMH; and (d) the impact of lack of agreement, among nurses, regarding the nursing leadership role in the PMH. Design/Methodology/Approach: I used a critical action research approach to explore this unfolding situation. I chose a constructivist approach as it respects the practice-based, emergent understanding, and knowledge, of the nurses as they collectively and collaboratively explored leadership within their respective PMHs. Findings: Nurses enact non-positional nursing leadership (NPNL) within their respective PMHs through the interaction of identity, power, social influence, competence, and dialogue. Each incidence of leadership is unique to the actors and the context in which the actors find themselves. I have conceptualized my findings regarding NPNL via a flower metaphor whereby identity, power, social influence, and competence form petals around the pistal (center) of dialogue. The flower of NPNL is nourished via lifelong learning which fosters critical reflection and reflexivity. As the flower of NPNL grows and becomes more robust petals of leaderful practice (collaborative, collective, concurrent, and compassionate) will emerge. Implications: The complexity of leadership in the PMH requires us to look beyond current leadership models and training opportunities. The visual metaphor of the NPNL flower enables nurses, team members, employers, and policy makers to not only recognize the as yet untapped potential of NPNL, but also provides a mechanism to accelerate enactment of NPNL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".