Nurses' perceptions of leadership, teamwork, and safety climate in a community hospital in western Canada: A cross-sectional survey design
Bibliographic record
Abstract
ABSTRACT Patient safety and safety outcomes in hospitals are a major concern. A hospital’s safety climate indicates the degree to which the organization prioritizes patient safety and achieves intended care outcomes. Relationships between nurse managers and frontline nurses and relationships between health care team members are pivotal in promoting a positive safety climate which in turn reduces adverse patient outcomes. Therefore, the purpose of this study was to examine frontline nurses’ perceived relationships with nurse managers and health team members to identify factors associated with safety climate (SC) in a community hospital located in a western Canadian city. The study was guided by Leader-Member Exchange (LMX) theory. Leader-Member Exchange theory postulates that dyadic relationships and work roles develop over time through a series of exchanges between nurse managers and frontline nurses. The study further incorporated Team-member exchange (TMX), a theoretical extension of LMX. Team-Member Exchange was used to guide the study of reciprocal exchanges among nurses and other members of the health care team. A non-experimental, cross-sectional survey design was used to explore the relationship between acute care nurses’ perceived LMX, TMX, and SC. A convenience sampling technique was employed. Licensed practical nurses (LPNs) and registered nurses (RNs) were invited to complete a survey package comprised of four scales. A response rate of 31.1% was achieved with N=105. The majority of respondents were female (89.5%), over 45 years of age, and employed part-time. About half of the respondents were diploma-prepared nurses, whereas the other half had a baccalaureate degree in nursing. Based upon data’s non-normal distribution and various levels of variables, Kruskall Wallis H statistics were used to assess and compare groups in terms of the nurses’ education, gender, length of experience in their current position, specialty experience, organization experience, age, and LMX, TMX, and SC scores. Age was the sole demographic factor that had a statistically significant positive association with LMX and SC. This finding supported the notion that mature nurses enhance the SC. The relationship between TMX, LMX, and SC was explored through Spearman’s rho correlation statistics. LMX and TMX were found to have statistically significant relationships with SC. Multivariable regression analysis was used to identify factors with an association with SC. Nurses’ relationships with team members had a slightly stronger association with SC in comparison with LMX. Over 66% of SC variance was accountable by LMX, TMX, and nurses’ age. This study’s results support the nurse manager who partners with nurses to promote team work to deliver safe patient care and accomplish organizational goals. The presence of strong leadership that incorporates LMX and TMX theories into practice with the reliance upon mature nurses may facilitate the attainment of a positive SC and positive patient outcomes. Further longitudinal studies are recommended to add to the knowledge of the relationships between LMX, TMX, SC and patient outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".