The Relationship between Negative Leadership Behaviours and Silence among Nurses
Bibliographic record
Abstract
Background : Negative leadership behaviour is very common and pervasive in nursing and healthcare, often leading to adverse effects such as nurses’ silence, decreased job performance, and turnover. However, there is a lack of systematic reviews that summarize negative leadership types and nurses silencing behaviours. Aim : This systematic review examined the relationship between negative leadership behaviour and nurses’ silence. Evaluation : We searched PubMed, Embase, the Cochrane Library, Web of Science, CNKI, VIP, and Wanfang databases from their inception until 30 April 2024 for articles examining the relationship between negative leadership and silent behaviour among nurses. The studies were reviewed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. The risk of bias in the included studies was assessed using the Newcastle–Ottawa Scale. Key Issues : After full‐text analysis, six papers were included in this systematic review. Four of the studies were conducted with nurses, and the remaining two were conducted with all medical staff including nurses. While most studies have shown that negative leadership causes nurses to become increasingly silent, others have shown that appropriate negative leadership behaviour instead reduces nurses’ silence. Conclusions : Negative leadership behaviour can affect the silent behaviour of nurses. Implications for Nursing Management : Hospitals need to take the initiative to build a harmonious and safe working environment, correctly recognize and identify negative management behaviour, take appropriate and effective measures to enhance the positive leadership of nurse managers, and make an effort to prevent nursing staff’s exposure to the negative management of direct leadership and mental health threats, which is a key point that hospital administrators and health policymakers tend to overlook. This is also effective for enhancing the leadership of hospital administrators.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".