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Abstract
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This article describes a system for diagnosing mood disorders that is empirically derived and designed for its clinical utility in everyday practice. A ran-dom national sample of psychiatrists and clinical psychologists described a randomly selected current patient with a measure designed for clinically ex-perienced informants, the Mood Disorder Diagnostic Questionnaire (MDDQ), and completed additional research forms. We applied factor analysis to the MDDQ to identify naturally occurring diagnostic groupings within the patient sample. The analysis yielded three clinically distinct mood disorder dimen-sions or spectra, consistent with the major mood disturbances included in the DSM and ICD over successive editions (major depression, dysthymia, and mania), along with a suicide risk index. Diagnostic criteria were determined strictly empirically. Initial data using diagnostic efficiency statistics sup-ported the accuracy of the dimensions in discriminating DSM-IV diagnoses; regression analyses supported the discriminant validity of the MDDQ scales; and correlational analysis demonstrated coherent patterns of association with family history of mood disorders and functional outcomes, supporting va-lidity. Perhaps most importantly, the MDDQ diagnostic scales demonstrated incremental validity in predicting adaptive functioning and psychiatric his-tory over and above DSM-IV diagnosis. The empirically derived syndromes can be used to diagnose mood syndromes dimensionally without complex di-agnostic algorithms or can be combined into diagnostic prototypes that eliminate the need for ever-expanding categories of mood disorders that are clini-cally unwieldy.
Two questions are at the heart of psychiatric diagnosis: how to classify psychopathology, and how to apply that taxonomy to diagnose patients, particularly in practice. Initial efforts to address the first question with respect to mood disorders involved a clinical expert approach, in which the premiere psychopathologists of the early 20th century attempted to find order in the clinical cases they were seeing 1. This remained the predominant approach until the 1970s, when criteria designed for research purposes proved useful in standardizing diagnosis across sites. Versions of these criteria became the official taxonomy of affective disorders in the DSM-III 2. Since that time, researchers have gradually honed the criteria for the various disorders for both the DSM and ICD, but this has dramatically increased the number of disorders, reflecting in part the recognition that mood disorders are spectrum disorders, with patients displaying a range of symptom presentations 3,4,5,6.
With the emergence of research-based criteria, a new approach came not only to classification (the first question central to psychiatric diagnosis) but also to assigning diagnoses in practice using that taxonomy (the second question). The DSM-III and subsequent editions of the DSM and ICD provided highly specific criteria and algorithms for combining those criteria into a categorical diagnosis. Advantages included substantially higher interrater reliability, at least for research purposes 7,8. Over time, however, a number of disadvantages became apparent, including tradeoffs between validity and reliability, with cutoffs for diagnosis, severity, and duration of illness often arbitrary; and an increasing number of disorders and not-otherwise-specified (NOS) diagnoses (see 9). Further, a consensus has emerged across a range of disorders, including mood disorders, that categorical (present/absent) diagnosis does not reflect the nature of clinical reality as well as dimensional diagnosis (the extent to which a syndrome is present) 10,11,12. For decades, dimensional diagnosis has actually been the “unofficial” norm in research, with instruments such as the Hamilton Rating Scale for Depression 13 and the Beck Depression Inventory 14 used to measure both severity of depression and treatment response, given that a patient in a clinical trial can fall just below threshold but remain highly symptomatic. Another emerging problem was artifactual comorbidity 15,16, which reflects a number of causes, including overlapping criterion sets and the nature of spectrum pathology, in which clear demarcations among disorders may be lacking. A related problem is clinical utility. The mood disorder section of DSM-IV comprises nearly 100 pages of text and includes so many disorders, each with its own criteria, subcriteria, and cut-points, that clinicians find them minimally useful and hence often do not use the manual as designed, instead relying on mental prototypes they have built up over the course of training and experience ...
Language: en |