University of Miami Miller School of Medicine, Research Service Bruce W. Cater VA Medical Center, Miami, FL, United States of America.
VeraSci, Durham, NC, United States of America; University of California, Los Angeles, CA, United States of America.
Schizophr Res. 2020 Sep;223:297-304. doi: 10.1016/j.schres.2020.08.010. Epub 2020 Sep 11.
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.
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.
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.
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.
认知和功能能力可预测精神疾病的功能结局。传统方法将认知概念化为由多个领域组成,但许多研究支持单因素结构。一些功能能力测量可能与认知具有单一因素结构。在这项研究中,我们检查了两种功能能力测量的因素结构,一种是传统评估,另一种是较新的计算机化评估,以测试与认知的共同因素结构。
精神分裂症患者和健康对照者接受了 MATRICS 共识认知电池 (MCCB)、圣地亚哥表现能力评估 (UPSA) 和虚拟现实功能能力评估工具 (VRFCAT) 的检查。计算了 MCCB、UPSA 和 VRFCAT 的因素结构模型,以及 MCCB 分数与个别 VRFCAT 目标之间的相关性。
MCCB、VRFCAT 和 UPSA 均具有单因素结构。MCCB 和 UPSA 之间相关性的最佳拟合模型是共享的单一因素,而 MCCB 和 VRFCAT 之间关系的最佳拟合模型有两个因素。MCCB 领域和综合分数与 VRFCAT 目标之间的相关性表明,相关性是整体的,而不是特定的。
认知表现与功能能力之间的关系在不同的功能能力评估中有所不同。UPSA 和 MCCB 没有分为单独的因素,这表明 UPSA 可能与神经认知表现重叠。然而,VRFCAT 似乎测量了与神经认知表现分离但相关的功能能力。它可能提供了对功能能力结构的更独特评估。