|Title||Computerized adaptive measurement of depression: A simulation study|
|Publication Type||Journal Article|
|Year of Publication||2004|
|Authors||Gardner, W, Shear, K, Kelleher, KJ, Pajer, KA, Mammen, O, Buysse, D, Frank, E|
|Keywords||*Computer Simulation, Adult, Algorithms, Area Under Curve, Comparative Study, Depressive Disorder/*diagnosis/epidemiology/psychology, Diagnosis, Computer-Assisted/*methods/statistics & numerical data, Factor Analysis, Statistical, Female, Humans, Internet, Male, Mass Screening/methods, Patient Selection, Personality Inventory/*statistics & numerical data, Pilot Projects, Prevalence, Psychiatric Status Rating Scales/*statistics & numerical data, Psychometrics, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, P.H.S., Severity of Illness Index, Software|
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.