The comparison of latent variable models of nonpsychotic psychiatric morbidity in four culturally diverse populations

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.