The Value of Exploratory Structural Equation Modeling in Identifying Factor Overlap in the Mental Health Continuum-Short Form (MHC-SF): A Study with a New Zealand Sample

Abstract

This study is the first to investigate the factor structure of the Mental Health Continuum-Short Form (MHC-SF) in New Zealand. Towards this end, traditional Confirmatory Factor Analysis (CFA) and the new method of Exploratory Structural Equation Modeling (ESEM) were used. Both ESEM and CFA supported the tripartite model of mental well-being in comparison to the one- and two-factor models; however, ESEM provided better fit with the data. Moreover, interfactor correlations were considerably lower in ESEM than they were in CFA, indicating greater factor distinctiveness in ESEM. ESEM also revealed a number of important cross-loadings for items in the measurement model of the MHC-SF. The results supported full metric and full scalar invariance of the MHC-SF across gender. The attenuated correlations among well-being factors obtained by ESEM here provide an important insight about the ongoing controversy regarding the failure of empirical research to identify distinct eudaimonic and hedonic factors in well-being measures. An overreliance on CFA methods may have led the field to rely on inflated estimates of shared variance between eudaimonia and hedonia.