Construction of a computerized adaptive test (CAT-CCNB) for efficient neurocognitive and clinical psychopathology
Tyler M Moore1, Akira Di Sandro2, J Cobb Scott3
1Department of Psychiatry, Brain Behavior Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI), Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA.
Background:
Traditional paper-and-pencil neurocognitive evaluations and semi-structured mental health interviews can take hours to administer and score. Computerized assessment has decreased that burden substantially, and contemporary psychometric tools such as item response theory and computerized adaptive testing (CAT) allow even further abbreviation.
New Method:
The goal of this paper was to describe the application of CAT and related methods to the Penn Computerized Neurocognitive Battery (CNB) and a well-validated clinical assessment in order to increase efficiency in assessment and relevant domain coverage. To calibrate item banks for CAT, N = 5053 participants (63% female; mean age 45 years, range 18-80) were collected from across the United States via crowdsourcing, providing item parameters that were then linked to larger item banks and used in individual test construction. Tests not amenable to CAT were abbreviated using complementary short-form methods.
Results:
The final "CAT-CCNB" battery comprised 21 cognitive tests (compared to 14 in the original) and five adaptive clinical scales (compared to 16 in the original).
Comparison With Existing Methods:
This new battery, derived with contemporary psychometric approaches, provides further improvements over existing assessments that use collections of fixed-length tests developed for stand-alone administration. The CAT-CCNB provides an improved version of the CNB that shows promise as a maximally efficient tool for neuropsychiatric assessment.
Conclusions:
We anticipate CAT-CCNB will help satisfy the clear need for broad yet efficient measurement of cognitive and clinical domains, facilitating implementation of large-scale, "big science" approaches to data collection, and potential widespread clinical implementation.
