RESUMO
BACKGROUND: Nursing managers have the potential to significantly impact the outcomes of nurses, patients, and organizations. Their competencies for effective performance are crucial. The global nursing workforce is facing a severe shortage of nurses. Dissatisfaction with management is one of the most important reasons for nurses' inclination to leave their jobs. Therefore, this study examines the relationship between nursing managers' competencies, job satisfaction and intention to leave among clinical nurses. METHODS: An analytical cross-sectional study was conducted on 354 nurses in five hospitals affiliated with Ardabil University of Medical Sciences from May to August 2023. This research used web-based software to design demographic information forms, nurse manager competency scale, turnover intention, and single-item job satisfaction questionnaires. The significance level for the study was set at p < 0.05. RESULTS: This study revealed that participants had an average score of 3.06 out of 5 in perceived nurse manager competence. Only one-fourth of the participants (25.7%) were satisfied with their current job, and less than half (46.9%) intended to leave. Employee support and development, change and resource management, supervision and quality monitoring, and personal mastery positively influenced nurses' job satisfaction. These competencies hurt employees' intention to leave their jobs. CONCLUSIONS: The research findings indicate that nursing managers in Iran have lower competency than in previous studies. Developing and strengthening these competencies is very important, as it significantly improves job satisfaction and reduces nurses' tendency to leave their jobs. Additionally, the results show that nursing managers who excel in supporting and developing staff, resource management, quality supervision, and personal mastery positively impact nurses' job satisfaction. However, these competencies can also help reduce employees' intention to leave their jobs. Retaining and maintaining nurses in the healthcare field is of utmost importance.
RESUMO
BACKGROUND: Innovation in nursing involves applying new knowledge to create novel ideas, methods, or technologies, resulting in higher-quality care and improved patient outcomes. Adequate support for innovation is crucial for progress in nursing. This study aimed to translate the Innovation Support Inventory (ISI-12) into Persian and assess its psychometric properties specifically among clinical nurses. METHODS: A methodological cross-sectional study was conducted from September 2022 to July 2023 to evaluate the face, content, and construct validity of the ISI-12. Construct validity was assessed through confirmatory factor analysis (CFA) and convergent and discriminant validity evaluation using data obtained from 321 clinical nurses. The test-retest stability and internal consistency of the ISI-12 were also evaluated to assess its reliability. RESULTS: The Persian version of the ISI-12 validation through confirmatory factor analysis has confirmed its fit with the proposed three-factor model. The ISI-12 demonstrated high reliability, as evidenced by a Cronbach's alpha coefficient (α = 0.969), McDonald's omega coefficient (ω = 0.922), coefficient H (H = 0.979), and mean inter-item correlation (ρ = 0.418). Additionally, the stability of the ISI-12 during two weeks among 40 clinical nurses was found to be excellent, with an ICC of 0.951. CONCLUSION: The Persian version of the ISI-12 is a valid inventory for evaluating the innovation Support of clinical nurses.