The aim of this investigation is to develop and evaluate computerized adaptive testing programs and algorithms for the assessment of depression. In the original study we demonstrated the feasibility of item response theory (IRT), and computerized adaptive testing (CAT) in the development and administration of a large (626 item) mental health rating scale. Using an item bank of 626 mood and anxiety disorder symptom items, we found that (a) the majority of the items in the item bank (90%) were discriminating of high and low levels of mood disorders, (b) the bi-factor IRT model did an excellent job of accounting for the clustering of items within symptom domains, (c) on average, CAT administration of the test resulted in a 95% reduction in the number of items administered to an individual subject (24 out of 626 items using simulated CAT and 31 items for live CAT testing), and (d) the correlation between the CAT based impairment rating and the score based on all 626 items was r=0.93. Based on these very encouraging preliminary results, this competitive renewal proposes to use IRT and CAT to develop a CAT Depression Inventory (CAT-DI). The specific objectives of the renewal are (1) create a depression item bank by collecting items from a review of approximately 100 existing depression scales and depression items previously identified as a part of the PROMIS network, (2) calibrate the depression item bank using a variety of IRT models (unidimensional, bi-factor, multidimensional) using a balanced incomplete blocks (BIB) design administered to 800 depressed patients and 200 non-depressed controls, (3) obtain a new sample of 300 subjects (200 depressed, 100 non-depressed) that take all of the items in the bank, perform a simulated CAT, and optimize the tuning parameters of the CAT, (4) obtain a new sample 300 subjects (200 depressed, 100 non- depressed) for live CAT testing, (5) apply the final CAT-DI to a community sample of 700 patients (approximately 200 meeting criteria for major depressive disorder - MOD) to test validity (comparison of impairment estimates in patients with and without MOD), predicting MOD, and establishing normative ranges for patient screening, and (6) conduct 20 cognitive interviews of patients from a behavioral health clinic who have taken the CAT-DI as a qualitative research approach to beta-testing of the instrument.
Depression costs the United States $40 billion annually (Rice &Miller, 1998). In 2002, the U.S. Preventive Services Task Force endorsed depression screening in general medical practice but did not recommend a specific screening tool (Pignone, Gaynes, Rushton et al., 2002). The proposed research responds to this important recommendation by developing a new paradigm for the rapid diagnosis of major depressive disorder (MDD) based on a novel application of computer adaptive testing (CAT) and item response theory. The resulting CAT-based MDD diagnostic system provides a screening tool that can be used in both psychiatric and primary care settings, and is based on patient reported outcomes.
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