Computerized adaptive measurement of depression: A simulation study

Background: 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. Methods: 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. Results: 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 r = .92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (r = .74) than the BDI total score did (r = .70). Conclusions: Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity.

Keywords

Mood Disorders, Unipolar, Computers, Diagnosis and Classification, Test/Interviews, Psychometrics

Citation

William Gardner et al, "Computerized adaptive measurement of depression: A simulation study," BMC Psychiatry 4 (2004), doi:10.1186/1471-244X-4-13, http://www.biomedcentral.com/1471-244X/4/13

URI

http://hdl.handle.net/1811/47410

Collections

Ohio State University Research and Scholarship

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