Since publication of the article by Regier et al on the prevalence mental health problems within primary care, much attention has been focused on their epidemiology, recognition, and treatment in the primary care setting. Studies have used various tools to detect mental health disorders, including the Hamilton Rating Scale for Depression, the Center for Epidemiologic Studies-Depression Scale, the Structured Clinical Interview, and the PRIME-MD. The rates at which primary care physicians have detected mental health disorders in their offices, as well as the impact of recognition and treatment, have been studied. The issue of comorbid anxiety and mood disorders has also been examined. Together these primary care studies indicate that mental health problems are common, the rate of detection of disorders is low, undetected disorders tend to be less severe, and treatment of undetected disorders might have little effect on outcomes.
The use of instruments based on DSM criteria to screen primary care patients for mood and anxiety disorders implies two assumptions. First, it assumes that mood and anxiety disorders occur in primary care with the same constellation of symptoms as they do in specialty offices. Second, it assumes that all patients who meet DSM criteria for a particular disorder will experience similar levels of morbidity and, therefore, be equally recognizable and have similar treatment outcomes. If these assumptions are not valid, much of the non detection of disorders in primary care could be explained, and a primary-care-specific approach to the classification of mood and anxiety disorders would be required. Schwenk has discussed the issues of screening for depression in primary care.
This study began with an interest in investigating the patterns or clusters of mood and anxiety symptoms in primary care patients. The study progressed in two phases: development of clusters of patients with common patterns of mood and anxiety symptoms, and validation of these clusters and their ability to predict health-related quality of life. To derive common groupings of mood and anxiety symptoms, we applied cluster analysis to a set of measures already collected. Cluster analysis has been used previously to distinguish groups of patients with psychiatric symptoms and to validate DSM classification criteria, but it has not been used in primary care for this purpose. Our initial hypothesis was that primary care patients would exhibit groups of symptoms that are consistent with DSM disorders. After establishing groups or clusters of patients, we proceeded to describe and validate these clusters. Finally, we compared our derived clusters with groups based on DSM criteria.
The above information thankfully comes from the medscape.com at the following link.
