A team of researchers, led by Stony Brook Assistant Professor Roman Kotov, PhD, took a significant step forward in the ongoing effort to develop an empirical system for classifying mental disorders. Their study, titled New Dimensions in the Quantitative Classification of Mental Illness, was published in the October 2011 edition of the Archives of General Psychiatry, the flagship journal of psychiatry.
Psychiatry, unlike other areas of medicine, lacks laboratory tests for objective diagnosis, and the classification of mental disorders itself is decided by expert consensus rather than direct empirical investigation. Over the last decade, researchers have been working to develop an objective classification, using novel statistical techniques such as confirmatory factor analysis. The study by Dr. Kotov and his team is the latest advance in this campaign.
Their research is based on the premise that patterns of co-occurrence among mental disorders may reveal the natural classification of mental illness. Building on work done by co-author Robert F. Krueger, PhD, and others, Dr. Kotov and his team analyzed co-occurrence among 25 disorders in 2,900 patients seeking psychiatric treatment in a general outpatient practice. They found that the disorders can be grouped into five spectra: internalizing (defined by pervasive distress), externalizing (extremely disinhibited behavior), thought disorder (odd thinking and behavior), somatoform (maladaptive response to physical symptoms), and antagonism (callous antisociality).
The study advances research into the natural classification of psychiatric disorders in several ways. It confirms that the three spectra previously found in community samples—internalizing, externalizing, and thought disorder—apply to a patient population; it identifies two new dimensions—somatoform and antagonism—thus broadening the empirical classification system; and it integrates psychiatric and personality disorders into a single framework. The study used state-of-the-art diagnostic and statistical techniques to analyze a broad range of mental disorders in a large clinical sample, making it the most comprehensive study of its type to date.
The 7-spectra model, imbedded in the current Diagnostic and Statistical
Manual of Mental Disorders, explained the data so poorly that it ranked
last among all the models tested. “It is patently clear that the existing diagnostic system fails to meet the needs of clinicians and inhibits psychiatric research,” said Dr. Kotov. “The emerging empirical classification promises to facilitate research on genetic and neurobiological underpinnings of mental disorders and to offer a better guide to treatment.”
Dr. Kotov is faculty member of the Department of Psychiatry and Behavioral Science at Stony Brook University. Additional co-authors are Camilio J Ruggero, PhD; Robert F. Krueger, PhD; David Watson, PhD; Qilong Yuan, PhD; and Mark Zimmerman, MD.