Authentic Nursing Leadership and Safety Climate Across Hospital Settings During the <scp>COVID</scp> ‐19 Pandemic: A Cross‐Sectional Study
Bibliographic record
Abstract
AIM: To analyse the relationship between authentic nursing leadership and safety climates across hospital settings during the COVID-19 pandemic. BACKGROUND: Authentic nursing leadership shapes the safety climate by fostering positive perceptions of workplace policies, processes, procedures and practices that influence how safety is prioritised and addressed within an organisation. DESIGN: A cross-sectional study. METHODS: Our study was conducted from December 2021 to December 2022 in six Brazilian hospitals. Participants were nursing staff working in General Medicine Units, Intensive Care Units (ICU) and Emergency Departments (ED) who provided care to patients with COVID-19. The Authentic Leadership Questionnaire and the Safety Attitudes Questionnaire were used to measure nursing staff perceptions of authentic leadership and safety climates. Data were analysed using descriptive and inferential statistics. RESULTS: 391 nursing staff across six hospitals participated. Self-awareness significantly enhanced perceptions of the safety climates. Additionally, being a Registered Nurse and working in the ICU were positively associated with achieving safe climates in the working environment. In contrast, working in EDs was significantly negatively related to safety climates. CONCLUSIONS: The COVID-19 pandemic underscored a lack of authentic nursing leadership and unsafe climates. Therefore, it is critical to implement educational strategies that foster authentic leadership, particularly focusing on self-awareness, to promote more positive safety climates. Ensuring that leadership and safety climates are relationship-focused is critical to enhancing patient outcomes. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Nursing staff's perceptions of authentic leadership and safety climates are important in making more informed decisions about patient management. IMPACT: Since self-awareness increases positive perceptions of safety climates, nursing staff should exercise it to guide their actions in facing future health crises. REPORTING METHOD: STROBE guidelines. PATIENT OR PUBLIC CONTRIBUTION: Higher self-awareness in relationships with others is a predictor of safety climates and can lead to enhanced patient outcomes.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".