Objective: The authors developed a computerized adaptive test for anxiety that decreases patient and clinician burden and increases measurement precision.
Method: A total of 1,614 individuals with and without generalized anxiety disorder from a psychiatric clinic and community mental health center were recruited. The focus of the present study was the development of the Computerized Adaptive Testing-Anxiety Inventory (CAT-ANX). The Structured Clinical Interview for DSM-IV was used to obtain diagnostic classifications of generalized anxiety disorder and major depressive disorder.
Results: An average of 12 items per subject was required to achieve a 0.3 standard error in the anxiety severity estimate and maintain a correlation of 0.94 with the total 431-item test score. CAT-ANX scores were strongly related to the probability of a generalized anxiety disorder diagnosis. Using both the Computerized Adaptive Testing-Depression Inventory and the CAT-ANX, comorbid major depressive disorder and generalized anxiety disorder can be accurately predicted.
Conclusions: Traditional measurement fixes the number of items but allows measurement uncertainty to vary. Computerized adaptive testing fixes measurement uncertainty and allows the number and content of items to vary, leading to a dramatic decrease in the number of items required for a fixed level of measurement uncertainty. Potential applications for inexpensive, efficient, and accurate screening of anxiety in primary care settings, clinical trials, psychiatric epidemiology, molecular genetics, children, and other cultures are discussed.