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A Dimensional Approach to Depression and Anxiety

            The Diagnostic and Statistical Manual of Mental Disorders (DSM) 4 system is based on the non-Kraepelinian model where disorders are seen as independent from one another. Categories of mental disorders are based on observable, phenotypic features rather than etiologies and neurobiological factors (Brown & Barlow, 2009; Watson, 2005). The DSMs categorical approach to disorders brings up questions about the validity of these categories. In the DSM 4, psychopathology is organized into general diagnostic classes of specific disorders and diagnostic subtypes. This type of classification of disorders has been used in numerous editions of the DSM. Researchers have recognized the limitations in using the categorical approach. Researchers started focussing on incorporating a dimensional system for assessing psychopathology in 2005. (McGlinchey & Zimmerman, 2007).There is not enough data that supports the non-Kraepelinian, categorical approach of mood and anxiety disorders. However, we have enough data to argue that a dimensional model is more theory driven and based on advanced knowledge of psychopathology. .
             There has been a big dispute of the conceptualization of mood and anxiety disorders. Watson's quantitative dimensional model should apply to anxiety and depression. While the DSM of mood and anxiety disorders hold great reliability (Brown & Barlow, 2009), the current categorical grouping lacks empirical evidence based on validity. Another issue is the excessive comorbidity (Watson, 2005) between mood and anxiety disorders which leads to an improper diagnosis of the patients. The use of the exclusion rule in diagnosing patients also causes a distortion in diagnosis where one disorder is overdiagnosed and the other disorder is underdiagnosed. Not otherwise specified diagnoses for depression and anxiety is another issue that the categorical approach brings up but cannot explain. In the DSM, mood and anxiety disorders are split into subcategories.

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