The comparison of latent variable models of non-psychotic psychiatric morbidity in four culturally diverse populations

Abstract

Background: Factor analysis has been employed to identify latent variables that are unifying constructs and that parsimoniously describe correlations among a related group of variables. Confirmatory factor analysis is used to test hypothesized factor structures for a set of variables; it can also, as in this paper be used to model data from two or more groups simultaneously to determine whether they have the same factor structure.

Method: Non-psychotic psychiatric morbidity, elicited by the Revised Clinical Interview Schedule (CIS-R), from four culturally diverse populations was compared. Confirmatory factor analysis was employed to compare the factor structures of CIS-R data sets from Santiago, Harare, Rotherhithe and Ealing. These structures were compared with hypothetical one and two factor (depression-anxiety) models.

Results: The models fitted well with the different data sets. The depression-anxiety model was marginally superior to the one factor model as judged by various statistical measures of fit. The two factors in depression-anxiety model were, however, highly correlated.

Conclusions: The findings suggest that symptoms of emotional distress seem to have the same factor structure across cultures.