The MATRICS Consensus Cognitive Battery, part 2: co-norming and standardization

Robert S Kern, Keith H Nuechterlein, Michael F Green, Lyle E Baade, Wayne S Fenton, James M Gold, Richard S E Keefe, Raquelle Mesholam-Gately, Jim Mintz, Larry J Seidman, Ellen Stover, Stephen R Marder
American Journal of Psychiatry 2008, 165 (2): 214-20

OBJECTIVE: The consensus cognitive battery developed by the National Institute of Mental Health's (NIMH's) Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative includes 10 independently developed tests that are recommended as the standard battery for clinical trials of cognition-enhancing interventions for schizophrenia. To facilitate interpretation of results from the MATRICS Consensus Cognitive Battery using a common scaling across tests, normative data were obtained from a single representative U.S. community sample with the battery administered as a unit.

METHOD: The MATRICS Consensus Cognitive Battery was administered to 300 individuals from the general community at five sites in differing geographic regions. For each site, recruitment was stratified by age, gender, and education. A scientific survey sampling method was used to help avoid sampling bias. The battery was administered in a standard order to each participant in a single session lasting approximately 60 minutes. Descriptive data were generated, and age, gender, and education effects on performance were examined.

RESULTS: Prominent age and education effects were observed across tests. The results for gender differed by measure, suggesting the need for age and gender corrections in clinical trials. The MATRICS Consensus Cognitive Battery components were co-normed, with allowance for demographic corrections.

CONCLUSIONS: Co-norming a battery such as the MATRICS Consensus Cognitive Battery, comprising tests from independent test developers each with their own set of norms, facilitates valid interpretation of test scores and communication of findings across studies. These normative data will aid in estimating the magnitude of change during clinical trials of cognition-enhancing agents and make it possible to derive more directly interpretable composite scores.

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