The Future of Mental Health Measurement

• Activity Number: 265
• Type: Invited
• Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Mental Health Statistics Section
• Author(s): Robert Gibbons*+
• Companies: University of Chicago
• Keywords: Item Response Theory ; Computerized Adaptive Testing ; Mental Health Statistics

Abstract

Mental health measurement has been based primarily on subjective judgment and classical test theory. Typically, impairment level is determined by a total score, requiring that all respondents be administered the same items. An alternative to full scale administration is computerized adaptive testing (CAT) in which different individuals may receive different scale items that are targeted to their specific impairment level. We have developed a CAT depression inventory (CAT-DI), based on multidimensional IRT, well suited to mental health constructs, that can be administered adaptively such that each individual responds only to those items that are most informative for assessing his/her level of depression. The shift in paradigm is from small fixed length tests with questionable psychometric properties to large item banks from which an optimal small subset of items is adaptively drawn for each individual, targeted to their level of impairment. Results to date reveal that depressive severity can be measured using an average of only 12 items (2 minutes) from a bank of 400 items, yet maintains a correlation of r=0.95 with the 400 item scores. We review numerous potential applications.