| Summary: | <p>Abstract</p> <p>Background</p> <p>Efficient, accurate instruments for measuring depression are increasingly important in clinical practice. We developed a computerized adaptive version of the Beck Depression Inventory (BDI). We examined its efficiency and its usefulness in identifying Major Depressive Episodes (MDE) and in measuring depression severity.</p> <p>Methods</p> <p>Subjects were 744 participants in research studies in which each subject completed both the BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale.</p> <p>Results</p> <p>The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%, equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21 items). The adaptive latent depression score correlated <it>r </it>= .92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (<it>r </it>= .74) than the BDI total score did (<it>r </it>= .70).</p> <p>Conclusions</p> <p>Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity.</p>
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