The Computerized Adaptive Diagnostic Test for Major Depressive Disorder (CAD-MDD): A Screening Tool for Depression

Objective: To develop a computerized adaptive diagnostic screening tool for depression that decreases patient and clinician burden and increases sensitivity and specificity for clinician-based DSM-IV diagnosis of major depressive disorder (MDD).

Method: 656 individuals with and without minor and major depression were recruited from a psychiatric clinic and a community mental health center and through public announcements (controls without depression). The focus of the study was the development of the Computerized Adaptive Diagnostic Test for Major Depressive Disorder (CAD-MDD) diagnostic screening tool based on a decision-theoretical approach (random forests and decision trees). The item bank consisted of 88 depression scale items drawn from 73 depression measures. Sensitivity and specificity for predicting clinician-based Structured Clinical Interview for DSM-IV Axis I Disorders diagnoses of MDD were the primary outcomes. Diagnostic screening accuracy was then compared to that of the Patient Health Questionnaire-9 (PHQ-9).

Results: An average of 4 items per participant was required (maximum of 6 items). Overall sensitivity and specificity were 0.95 and 0.87, respectively. For the PHQ-9, sensitivity was 0.70 and specificity was 0.91.

Conclusions: High sensitivity and reasonable specificity for a clinician-based DSM-IV diagnosis of depression can be obtained using an average of 4 adaptively administered self-report items in less than 1 minute. Relative to the currently used PHQ-9, the CAD-MDD dramatically increased sensitivity while maintaining similar specificity. As such, the CAD-MDD will identify more true positives (lower false-negative rate) than the PHQ-9 using half the number of items. Inexpensive (relative to clinical assessment), efficient, and accurate screening of depression in the settings of primary care, psychiatric epidemiology, molecular genetics, and global health are all direct applications of the current system.

J Clin Psychiatry 2013;74(7):669-674

© Copyright 2013 Physicians Postgraduate Press, Inc.

Submitted: December 20, 2012; accepted April 5, 2013 (doi:10.4088/JCP.12m08338).

Corresponding author: Robert D. Gibbons, PhD, Center for Health Statistics, Departments of Medicine and Health Studies, University of Chicago, 5841 S Maryland Ave, MC 2007 Office W260, Chicago, IL 60637 (rdg@uchicago.edu).