TY - JOUR T1 - Computerized adaptive measurement of depression: A simulation study JF - BMC Psychiatry Y1 - 2004 A1 - Gardner, W. A1 - Shear, K. A1 - Kelleher, K. J. A1 - Pajer, K. A. A1 - Mammen, O. A1 - Buysse, D. A1 - Frank, E. KW - *Computer Simulation KW - Adult KW - Algorithms KW - Area Under Curve KW - Comparative Study KW - Depressive Disorder/*diagnosis/epidemiology/psychology KW - Diagnosis, Computer-Assisted/*methods/statistics & numerical data KW - Factor Analysis, Statistical KW - Female KW - Humans KW - Internet KW - Male KW - Mass Screening/methods KW - Patient Selection KW - Personality Inventory/*statistics & numerical data KW - Pilot Projects KW - Prevalence KW - Psychiatric Status Rating Scales/*statistics & numerical data KW - Psychometrics KW - Research Support, Non-U.S. Gov't KW - Research Support, U.S. Gov't, P.H.S. KW - Severity of Illness Index KW - Software AB - Background: Efficient, accurate instruments for measuring depression are increasingly importantin clinical practice. We developed a computerized adaptive version of the Beck DepressionInventory (BDI). We examined its efficiency and its usefulness in identifying Major DepressiveEpisodes (MDE) and in measuring depression severity.Methods: Subjects were 744 participants in research studies in which each subject completed boththe 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 21items). The adaptive latent depression score correlated r = .92 with the BDI total score and thelatent depression score correlated more highly with the Hamilton (r = .74) than the BDI total scoredid (r = .70).Conclusions: Adaptive testing for depression may provide greatly increased efficiency withoutloss of accuracy in identifying MDE or in measuring depression severity. VL - 4 ER -