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Determining dimensions of job satisfaction in healthcare using factor analysis
Dimitris Karaferis1, Vassilis Aletras2, Dimitris Niakas3
1Department of Health Economics, Medical School, National and Kapodistrian University of Athens, 75, M. Assias Street, 11527, Athens, Greece. karafedis@yahoo.gr.
Background:
Job satisfaction in health care has a great impact as it affects quality, productivity, effectiveness, and healthcare costs. In fact, it is an indicator of the well-being and quality of life of the organization's employees, as it has been variously linked with increased performance and negatively to absenteeism and turnover. Better knowledge of healthcare employees' job satisfaction and performance can directly contribute to the quality of the services provided to patients and is critical for the success of organizations.
Methods:
The Cronbach's alpha coefficient, split-half reliability, exploratory factor and confirmatory factor analysis were employed to assess the reliability and validity of JSS.
Results:
Six underlying dimensions were extracted (benefits and salary, management's attitude, supervision, communication, nature of work, and colleagues' support). Internal consistency reliability was satisfactory since Cronbach's alpha for the overall scale was 0.81 and for the various dimensions ranged from 0.61 to 0.81, respectively. Exploratory factor analysis showed a KMO value of 0.912. The confirmatory factor analysis indicated good fit: SRMR = 0.050, RMSEA = 0.055, IFI = 0.906 and CFI = 0.906.
Conclusion:
Job satisfaction is a multidimensional construct that encompasses different facets of satisfaction. There is a lack of consensus as to which factors are more important and a researcher may find satisfaction with some factors while at the same time dissatisfaction with others. Our findings are significant for improving our understanding of the nature and assessment of job satisfaction in the Greek healthcare context, providing a more stable ground in a rapidly changing environment. A short JSS developed that could be much more widely used in the future.
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