Somatization Revisited

The assessment of somatoform disorders is complicated by persistent theoretical and practical questions of classification and assessment. Critical rethinking of professional concepts of somatization suggests the value of complementary assessment of patients' illness explanatory models of somatoform and other common mental disorders. We undertook this prospective study to assess medically unexplained somatic symptoms and their patient-perceived causes of illness and to show how patients' explanatory models relate to professional diagnoses of common mental disorders and how they may predict the short-term course of illness. Tertiary care patients (N=186) with prominent somatoform symptoms were evaluated with the Structured Clinical Interview for DSM-IV, a locally adapted Explanatory Model Interview to elicit patients' illness experience (priority symptoms) and perceived causes, and clinical self-report questionnaires. The self-report questionnaires were administered at baseline and after 6 months. Diagnostic overlap between somatoform, depressive, and anxiety disorders occurred frequently (79.6%). Patients explained pure somatoform disorders mainly with organic causal attributions; they explained pure depressive and/or anxiety disorders mainly with psychosocial perceived causes, and patients in the diagnostic overlap group typically reported mixed causal attributions. In this last group, among patients with similar levels of symptom severity, organic perceived causes were related to a lower physical health sum score on the MOS Short Form, and psychosocial perceived causes were related to less severe depressive symptoms, assessed with the Hospital Anxiety and Depression Scale at 6 months. Among patients meeting criteria for comorbid somatoform with anxiety and/or depressive disorders, complementary assessment of patient-perceived causes, a key element of illness explanatory models, was related to levels of functional impairment and short-term prognosis. For such patients, causal attributions may be particularly useful to clarify clinically significant features of common mental disorders and thereby contribute to clinical assessment.