Evaluating the criterion validity of the Cybernetic Coping Scale: Cross-lagged predictions of psychological strain, job and family satisfaction

Abstract

The assessment of self-report coping continues to pose difficulties for stress and coping research. The inclusion of multiple coping constructs, as well as the distinction between state and trait-based coping continues to be largely overlooked. Edwards’ (1988) Cybernetic Stress Theory recognizes coping as a cyclic ongoing comparison of an individual's desired state with their current state. The Cybernetic Coping Scale (CSS), devised from this theory, acknowledges the function of coping as both an independent variable and an outcome. However, the inclusion of the CCS in stress and coping research is sparse, despite its ease of administration and measurement of meaningful multiple coping behaviours. A recently revised 14-item version of the CCS showed robust psychometric qualities across its five constructs (including Changing the situation, and Avoidance). The 14-item CCS was tested in a cross-lagged structural model to predict three criterion variables (psychological strain, and job and family satisfaction). The respondents consisted of 691 (T1) and 415 (T2) employees from 24 organizations. The five CCS constructs demonstrated stability over time and significantly predicted psychological strain. Avoidance also predicted job satisfaction over time. Strain predicted four of the five coping behaviours. These results support previous reports that changing the stressful situation is associated with positive outcomes, while coping behaviours aimed at avoiding the implications of the stressful incident are associated with maladaptive outcomes. This research illustrates that the inclusion of psychometrically robust measures, especially within multivariate longitudinal designs (as is continually recommended) should also be applied to the measurement of coping.

Keywords:

• Coping
• Cybernetic Coping Scale
• avoidance coping
• strain
• satisfaction
• health
• structural model
• longitudinal

This research was funded by the New Zealand Foundation for Research, Science and Technology, whose support is gratefully acknowledged.