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.
Bartone, P.T., Eid, J., Johnsen, B.H., Laberg, J.C. and Snook, S.A. (2009) Big Five Personality Factors, Hardiness, and Social Judgment as Predictors of Leader Performance. Leadership and Organization Development Journal, 30, 498- 521. http://dx.doi.org/10.1108/01437730910981908
Ladstätter, F., Garrosa, E., Badea, C. and Moreno, B. (2010) Application of Artificial Neural Networks to a Study of Nursing Burnout. Ergonomics, 53, 1085-1096. http://dx.doi.org/10.1080/00140139.2010.502251