An empowerment framework for nursing leadership development: supporting evidence
Bibliographic record
Abstract
AIM: This article is a report on a descriptive study of nurse leaders' perspectives of the outcomes of a formal leadership programme. BACKGROUND: Effective nurse leaders are necessary to address complex issues associated with healthcare systems reforms. Little is known about the types of leadership development programmes that most effectively prepare nurse leaders for healthcare challenges. When nurse leaders use structural and psychological empowerment strategies, the results are safer work environments and better nurse outcomes. The leadership development programme associated with this study is based on a unifying theoretical empowerment framework to empower nurse leaders and enable them to empower others. METHODS: Twenty seven front-line and mid-level nurse leaders with variable years of experience were interviewed for 1 year after participating in a formal leadership development programme. Data were gathered in 2008-2009 from four programme cohorts. Four researchers independently developed code categories and themes using qualitative content analysis. RESULTS: Evidence of leadership development programme empowerment included nurse leader reports of increased self-confidence with respect to carrying out their roles and responsibilities; positive changes in their leadership styles; and perceptions of staff recognition of positive stylistic changes. Regardless of years of experience, mid-level leaders had a broader appreciation of practice environment issues than front-line leaders. Time for reflection was valuable to all participants, and front-line leaders, in particular, appreciated the time to discuss nurse-specific issues with their colleagues. CONCLUSION: This study provides evidence that a theoretical empowerment framework and strategies can empower nurse leaders, potentially resulting in staff empowerment.
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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 | 0.036 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".