Psychometric evaluation of the Beck Depression Inventory-II with primary care medical patients.

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Abstract

This study evaluated the psychometric characteristics of the Beck Depression Inventory-II (BDI-II; A. T. Beck, R. A. Steer, & G. K. Brown, 1996) in a primary care medical setting. A principal-components analysis with Promax rotation indicated the presence of 2 correlated factors, Somatic-Affective and Cognitive, which explained 53.5% of the variance. A hierarchical, second-order analysis indicated that all items tap into a second-order construct of depression. Evidence for convergent validity was provided by predicted relationships with subscales from the Short-Form General Health Survey (SF-20; A. L. Stewart, R. D. Hayes, & J. E. Ware, 1988). A receiver operating characteristic analysis demonstrated criterion-related validity: BDI-II scores predicted a diagnosis of major depressive disorder (MDD), as determined by the Primary Care Evaluation of Mental Disorders (PRIME-MD) Patient Health Questionnaire (PHQ). This study demonstrated that the BDI-II yields reliable, internally consistent, and valid scores in a primary care medical setting, suggesting that use of the BDI-II in this setting may improve detection and treatment of depression in these medical patients.

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The meaning and use of the area under a receiver operating characteristic (ROC) curve.

J A Hanley, B J McNeil, Marnix van Holsbeeck (1982)

A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.

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The functioning and well-being of depressed patients. Results from the Medical Outcomes Study.

K Wells, A. Stewart, R Hays … (1989)

We describe the functioning and well-being of patients with depression, relative to patients with chronic medical conditions or no chronic conditions. Data are from 11,242 outpatients in three health care provision systems in three US sites. Patients with either current depressive disorder or depressive symptoms in the absence of disorder tended to have worse physical, social, and role functioning, worse perceived current health, and greater bodily pain than did patients with no chronic conditions. The poor functioning uniquely associated with depressive symptoms, with or without depressive disorder, was comparable with or worse than that uniquely associated with eight major chronic medical conditions. For example, the unique association of days in bed with depressive symptoms was significantly greater than the comparable association with hypertension, diabetes, and arthritis. Depression and chronic medical conditions had unique and additive effects on patient functioning.