Neural Network Analysis of Nonlinear Effects of Hardiness on Burnout in Chinese Nurses

Felix Ladstätter, Eva Garrosa, Junming Dai

1Department of Psychology, IE University, Segovia, Spain 2Faculty of Psychology, UAM, Madrid, Spain 3School of Public Health, Fudan University, Shanghai, China.

DOI: 10.4236/jss.2014.25019                

Abstract

Substantial research attention is evident in the hardiness and related literature concerning the topic of moderational effects of hardiness on work-related stressors and strains. In this research mostly linear methods have been used to analyze these moderational effects. However, it is not very likely that these effects are purely linear. The present study uses a neural network, a method which can model nonlinear relationships, to analyze the effects of hardiness. A cluster analysis of 268 Chinese nurses based on their self-ratings in the hardiness dimensions of commitment, challenge, and control was performed. Two groups of individuals were identified, consisting of (1) those who scored above average and (2), those who scored below average on all hardiness dimensions. On the basis of these clusters, a multi-layer neural network was used to analyze the data.

Keywords

Hardiness, Cluster Analysis, Artificial Neural Network, Burnout, Nursing

Conflicts of Interest

The authors declare no conflicts of interest.

References

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