Background: 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.
Method: 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.
Results: 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.
Conclusions: 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.