The confirmatory factor analysis of the job diagnostic survey: the oncology nursing setting
Article first published online: 28 APR 2012
© 2012 Blackwell Publishing Ltd
Journal of Nursing Management
Special Issue: This issue: Patient safety management in the health services Issue editor: Elisabeth Severinsson
Volume 21, Issue 2, pages 273–282, March 2013
How to Cite
CHARALAMBOUS, A., RAFTOPOULOS, V. and TALIAS, M. A. (2013), The confirmatory factor analysis of the job diagnostic survey: the oncology nursing setting. Journal of Nursing Management, 21: 273–282. doi: 10.1111/j.1365-2834.2012.01386.x
- Issue published online: 11 MAR 2013
- Article first published online: 28 APR 2012
- Accepted for publication: 19 December 2011
- factor analysis;
- job diagnostic survey;
- job satisfaction;
- oncology nurses
Aim To explore the factorial validity of the five-factor measurement model of the job diagnostic survey (JDS) in oncology settings.
Background The research comes as a response to the lack of studies examining the factorial dimensions of the instrument in specific nursing populations.
Methods This was a cross-sectional, census survey design including all the oncology departments in Cyprus. The final sample included 398 oncology nurses.
Results A confirmatory factor analytic model, based on previous research, was tested. A unidimensional model including all five job characteristics items was found to be the best explanation of the data. This model produced fair-to-good internal consistency estimates.
Conclusion The findings supported a shorter version of the JDS as a reliable and factorially valid instrument for use with the oncology nursing population. These promising results should pave the way for further research and the search for more conclusive evidence on the construct validity of the shorter version of the JDS.
Implications for Nursing Management Nurse managers should use scales such as the JDS in order to evaluate the oncology nurses’ job satisfaction, work attitudes and motivation and redesign the job accordingly.