Exploring the Influence of Toxic Leadership Behavior in Nursing Organizations within Hospital Settings: An Integrative Review
Bibliographic record
Abstract
Toxic leadership in nursing organizations has emerged as a significant concern due to its negative impact on nurses’ well-being, job satisfaction, patient safety, and overall quality of care. While many scholars highlight its harmful consequences, some argue that the term “toxic leadership” may oversimplify complex organizational and interpersonal dynamics, potentially overlooking contextual factors that influence leadership behaviors. This integrative review aims to examine the influence of toxic leadership behavior in nursing organizations and synthesize current evidence regarding its impact on nurses, organizational culture, and patient outcomes. An integrative review approach was employed using literature from PubMed, Scopus, Google Scholar, and ResearchGate. Studies focusing on toxic leadership among nurse leaders and its organizational consequences were screened and analyzed thematically. Research conducted in various countries including the United States, Canada, Australia, the United Kingdom, China, Korea, and the Philippines consistently shows that toxic leadership contributes to decreased job satisfaction, heightened burnout, increased turnover intention, compromised patient safety, and a deteriorating organizational climate. These effects extend beyond individual nurses and can negatively influence team performance and care quality. Toxic leadership behavior in nursing organizations poses substantial risks to both staff and patient outcomes. Addressing this issue requires organizational strategies that promote healthy leadership styles, psychological safety, and supportive work environments. Future studies should focus on designing and evaluating interventions that reduce toxic leadership behaviors and strengthen positive, evidence-based leadership practices in nursing.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".