Latent structure of self-reported depression in undergraduates: Using taxometric procedures and information-theoretic latent variable modeling

Many depression studies dichotomize the participants as depressed or nondepressed on the basis of a self-reported depression scale score. However, there is little statistical rationale for such a procedure. The purpose of this study was to clarify whether depression assessed by the Zung Self-rating Depression Scale (SDS) is categorical or dimensional by using taxometric procedures and information-theoretic latent variable modeling. The present sample comprises 2187 Japanese undergraduates. The latent structure of depression was evaluated by mean above minus below a cut (MAMBAC) and maximum eigenvalue (MAXEIG). In addition, in order to test convergent validity, we performed information-theoretic latent variable modeling. Both taxometric procedures (MAMBAC and MAXEIG) and information-theoretic latent variable modeling, using indicators drawn from the SDS, were consistent with the dimensional latent structure of depression. The latent structure of depression assessed by the SDS is dimensional in undergraduates. For the assessment of depression, researchers should not stratify the participants on the basis of a conventional cutoff score. In addition, it is recommended that researchers use correlational designs, which include individuals with a wider range of severity with regard to depressive symptoms, rather than group comparative research designs.