Latent Class Analysis of Lifetime Depressive Symptoms in the National Comorbidity Survey

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Abstract
Objective:Although clinical trials have documented the importance of identifying individuals with major depression with atypical features, there are fewer epidemiological data. In a prior report, the authors used latent class analysis (LCA) to identify a distinctive atypical depressive subtype; they sought to replicate that finding in the current study.Method:Using the National Comorbidity Survey data, the authors applied LCA to 14 DSM-III-R major depressive symptoms in the participants’ lifetime worst episodes (N=2,836). Validators of class membership included depressive disorder characteristics, syndrome consequences, demography, comorbidity, personality/attitudes, and parental psychiatric history.Results:The best-fitting LCA solution had six classes. Four were combinations of atypicality and severity: severe atypical, mild atypical, severe typical, and mild typical. Syndrome severity (severe atypical and typical versus mild atypical and typical classes) was associated with a pronounced pattern of more ...

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