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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH066302-07
Application #
7688508
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Breiling, James P
Project Start
2002-09-20
Project End
2011-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
7
Fiscal Year
2009
Total Cost
$555,007
Indirect Cost
Name
University of Illinois at Chicago
Department
Psychiatry
Type
Schools of Medicine
DUNS #
098987217
City
Chicago
State
IL
Country
United States
Zip Code
60612
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Gibbons, Robert D; Hooker, Giles; Finkelman, Matthew D et al. (2013) The computerized adaptive diagnostic test for major depressive disorder (CAD-MDD): a screening tool for depression. J Clin Psychiatry 74:669-74
Brown, C Hendricks; Mohr, David C; Gallo, Carlos G et al. (2013) A computational future for preventing HIV in minority communities: how advanced technology can improve implementation of effective programs. J Acquir Immune Defic Syndr 63 Suppl 1:S72-84

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