Philip D Harvey1, William P Horan2, Alexandra S Atkins3, Heather Stevens3, Matthew Welch3, Joshua Yuan3, Thomas L Patterson4, Meera Narasimhan5, Richard S E Keefe6. 1. University of Miami Miller School of Medicine, Research Service Bruce W. Cater VA Medical Center, Miami, FL, United States of America. 2. VeraSci, Durham, NC, United States of America; University of California, Los Angeles, CA, United States of America. 3. VeraSci, Durham, NC, United States of America. 4. University of California, San Diego, CA, United States of America. 5. University of South Carolina, Columbia, SC, United States of America. 6. VeraSci, Durham, NC, United States of America; Duke University, Durham, NC, United States of America. Electronic address: Richard.Keefe@duke.edu.
Abstract
BACKGROUND: Cognition and functional capacity predict functional outcomes in mental illness. Traditional approaches conceptualize cognition as comprised of domains, but many studies support a unifactorial structure. Some functional capacity measures may share a single-factor structure with cognition. In this study, we examined the factor structure of two measures of functional capacity, a conventional assessment and a newer computerized assessment, testing for a shared factor structure with cognition. METHODS: Patients with schizophrenia and healthy controls were examined with the MATRICS Consensus Cognitive Battery (MCCB), the UCSD Performance Based Skills Assessment (UPSA), and the Virtual Reality Functional Capacity Assessment Tool (VRFCAT). Models of the factor structures of the MCCB, UPSA, and VRFCAT were calculated, as were correlations between MCCB scores and individual VRFCAT objectives. RESULTS: The MCCB, VRFCAT, and UPSA all had unifactorial structures. The best fitting model of the correlations between MCCB and UPSA was a shared single factor, while the best fit for the relationship between MCCB and VRFCAT had two factors. Correlations between the MCCB domain and composite scores and the VRFCAT objectives suggested global rather than specific patterns of correlation. DISCUSSION: The relationship between cognitive performance and functional capacity was found to vary across functional capacity assessments. The UPSA and MCCB were not differentiated into separate factors, suggesting that the UPSA may overlap with neurocognitive performance. However, the VRFCAT appears to measure functional abilities that are separable from, yet correlated with, neurocognitive performance. It may provide a more distinctive assessment of the functional capacity construct.
BACKGROUND: Cognition and functional capacity predict functional outcomes in mental illness. Traditional approaches conceptualize cognition as comprised of domains, but many studies support a unifactorial structure. Some functional capacity measures may share a single-factor structure with cognition. In this study, we examined the factor structure of two measures of functional capacity, a conventional assessment and a newer computerized assessment, testing for a shared factor structure with cognition. METHODS:Patients with schizophrenia and healthy controls were examined with the MATRICS Consensus Cognitive Battery (MCCB), the UCSD Performance Based Skills Assessment (UPSA), and the Virtual Reality Functional Capacity Assessment Tool (VRFCAT). Models of the factor structures of the MCCB, UPSA, and VRFCAT were calculated, as were correlations between MCCB scores and individual VRFCAT objectives. RESULTS: The MCCB, VRFCAT, and UPSA all had unifactorial structures. The best fitting model of the correlations between MCCB and UPSA was a shared single factor, while the best fit for the relationship between MCCB and VRFCAThad two factors. Correlations between the MCCB domain and composite scores and the VRFCAT objectives suggested global rather than specific patterns of correlation. DISCUSSION: The relationship between cognitive performance and functional capacity was found to vary across functional capacity assessments. The UPSA and MCCB were not differentiated into separate factors, suggesting that the UPSA may overlap with neurocognitive performance. However, the VRFCAT appears to measure functional abilities that are separable from, yet correlated with, neurocognitive performance. It may provide a more distinctive assessment of the functional capacity construct.
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