Latent structure of depression in a community sample: a taxometric analysis

Abstract

The latent structure of depression was examined using taxometric analysis, a family of statistical procedures designed specifically to test whether a given construct is best conceptualized as a distinct category or a continuous dimension. Data were derived from the Australian National Survey of Mental Health and Well-Being, a large epidemiological survey that measured the prevalence of the major DSM-IV and ICD-10 mental disorders. Two taxometric procedures, maximum covariance (MAXCOV) and mean above minus below a cut (MAMBAC), were carried out on a sample of 1933 community volunteers. Simulated categorical and dimensional datasets aided in the interpretation of the research data. The results of the taxometric analyses in the subsample who endorsed at least one symptom of depression were consistent with a dimensional latent structure of depression. The findings of the current study suggest that depression, as measured in this subsample, is best conceptualized, measured and classified as a continuously distributed syndrome rather than as a discrete diagnostic entity. Incorporation of dimensional measurement into psychiatric classification systems remains a challenge for the future.