Computerized Adaptive Testing of Neurocognitive Deficits in Psychosis

Abstract

Computerized adaptive testing (CAT) is a technology that has been used to improve the precision and efficiency of individual difference estimates for cognitive, achievement, personality, and clinical symptom assessments. Motivated by the psychometric limitations of experimental cognitive tasks, we determined whether experimental cognitive tasks, such as those being developed for the National Institute of Mental Health’s Research Domain Criteria (RDoC) initiative and similar projects, could also benefit from CAT. Participants were 64 patients diagnosed with psychosis spectrum disorders and 50 healthy controls who completed at least one of six experimental cognitive tasks: a probabilistic learning task (PLT), a continuous performance task (CPT), a Flanker task, a Sternberg task, a self-ordered pointing task (SOPT), and an N-back task. Results indicated strong correlations between ability estimates for fixed and CAT versions of most tasks, except the PLT. CAT significantly reduced standard error for the CPT, Sternberg, and SOPT, but not for the N-back, Flanker, or PLT. The tasks benefiting most from CAT were those with more fine-grained levels of difficulty. These findings suggest that adaptive testing can improve the psychometric properties of experimental cognitive tasks relevant to the RDoC framework. This improvement depends on the granularity of conditions and difficulty levels, however, highlighting an important consideration for integrating CAT into cognitive psychopathology research.