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Factors predicting job performance of nurses: A descriptive predictive study
Wai Wai Aung Po1,2, Orn-Anong Wichaikhum2, Kulwadee Abhicharttibutra2
1Department of Fundamental Nursing, University of Nursing, Mandalay, Myanmar.
Aim:
This study investigated the job performance and predictability of job demands, job resources, personal resources, work engagement, job crafting, and the transformational leadership of nurse managers on this among nurses in Myanmar.
Background:
The ongoing crisis of nursing shortages along with heavy workloads combines to form a major challenge in Myanmar and these affected the job performance of nurses during the COVID-19 pandemic.
Methods:
Utilizing a stratified random sample of 474 nurses from tertiary-level general hospitals in the Republic of the Union of Myanmar, a descriptive predictive analysis was carried out. The Demographic Data Sheet, Job Performance Scale, Work Engagement Scale, Job Demands Scale, Job Resources Scale, Personal Resources Scale, Job Crafting Scale, and Global Transformational Leadership Scale were utilized to collect data.
Results:
The overall level of job performance was perceived to be high, considering various factors such as job demands, personal resources, work engagement, and job crafting were found as significant predictors of nurses' job performance, explaining 63.30% of the total variance.
Discussion:
These findings make a valuable contribution toward enhancing nurses' job performance by addressing job demands, fostering work engagement, and nurturing their job-crafting capabilities. Self-reporting data collection may not have accurately represented the actual level of study variable.
Conclusion:
This study highlighted factors that significantly affect nurses' job performance in general hospitals in Myanmar.
Implications For Nursing And Health Policy:
The findings provide important evidence for nursing administrators and policymakers wishing to develop strategies to enhance the working environment and remain active in helping the performance of nurses.
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