Exploring clinical leadership in long‐term care: An integrative literature review
Bibliographic record
Abstract
AIM: The aim of this study is to understand the concept of clinical leadership and clinical leadership development for nurses working with older adults in long-term care health care facilities. BACKGROUND: In Canada, clinical care within long-term care is undertaken by registered nurses and licenced practical nurses working with health care aides. Effective clinical leadership is essential for providing quality nursing care. EVALUATION: An integrative literature review using the framework of Whittemore and Knafl (2005). All selected articles were quality appraised using the Critical Appraisal Skills Program and the accuracy, authority, coverage, objectivity, date and significance checklist. KEY ISSUES: The analysis resulted in four themes: ambiguous definitions, practice-based and value-driven care, the impact of clinical leadership and clinical leadership development for Canadian nurses. CONCLUSION: The findings suggest that ambiguity surrounds the concept of clinical leadership, with the term denoting both 'management' as a formal administrative role and 'leadership' in general. More recently, the clinical leadership focus has been on informal leadership by nurses at the bedside, where personal and professional values align with clinical action. IMPLICATIONS FOR NURSING MANAGEMENT: Effective clinical leadership can have a positive impact on quality care and employee job satisfaction.
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 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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".