Introduction: Anxiety and depressive symptoms are seen in patients with anxiety and mood disorders but are also common in those with organic disorders. However, since physical symptoms are predominant complaints from patients who visit nonpsychiatric outpatient clinics, anxiety and depressive symptoms are often unrecognized. It is important for physicians to be aware of these issues concurrent with the physical symptoms. We therefore examined whether a self-administered medical questionnaire could identify anxiety and depressive symptoms.

Patients And Methods: A total of 453 patients on their first visit to the Department of General Medicine, Chiba University Hospital, Chiba, Japan, participated in this study. They were asked to complete a medical questionnaire and the Hospital Anxiety and Depression Scale questionnaire before examination. Data on age, sex, number of complaints, symptom duration, and number of previous physicians were extracted from the medical questionnaire. These data were used as independent variables in logistic regression analysis to develop a predictive model for the presence of anxiety and depressive symptoms.

Results: Data from 358 (79.0%) patients were included in the analyses. Logistic regression analysis identified the following predictors: "three or more complaints" (odds ratio [OR] 2.39; 95% confidence interval [CI] 1.48-3.88) and "four or more previous physicians" (OR 1.72; 95% CI 1.10-2.69). In the predictive model for the presence of symptoms of anxiety and depression, the likelihood ratio was 2.40 (95% CI 1.33-4.34) in patients reporting both conditions and 1.35 (95% CI 1.04-1.77) in those reporting either condition.

Conclusion: The presence of anxiety and depressive symptoms can be predicted from the items of a medical questionnaire in outpatients visiting a general medicine department of a university hospital. When patients report three or more complaints or four or more previous physicians on a medical questionnaire, physicians should consider the presence of anxiety or depression or both in differential diagnosis.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4910684PMC
http://dx.doi.org/10.2147/IJGM.S101556DOI Listing

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