Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 1, 2021
Date Accepted: Oct 5, 2021
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VStore: A Novel Virtual Reality Assessment of Functional Cognition
ABSTRACT
Background:
Cognitive deficits are present in a number of neuropsychiatric disorders including, Alzheimer’s disease, schizophrenia and depression. Assessments used to measure cognition in these disorders are time-consuming, burdensome, and have low ecological validity. To address these limitations, we developed a novel virtual reality shopping task – VStore.
Objective:
This study aims to establish the concurrent and construct validity of VStore in relation to the established computerized cognitive battery, Cogstate; and tests its sensitivity to age related cognitive decline.
Methods:
Hundred and four healthy volunteers aged 20-79 completed both assessments. Main VStore outcomes included: 1) verbal recall of 12 grocery items, 2) time to collect items, 3) time to select items on a self-checkout machine, 4) time to make the payment, 5) time to order coffee, and 6) total completion time. To establish concurrent validity, bivariate correlations were performed between VStore outcomes and Cogstate tasks measuring attention, processing speed, verbal and visual learning, working memory, executive function, and paired associate learning. Construct validity analysis was also performed to examine which cognitive domains best predicted VStore performance. Finally, two ridge regression models were built using VStore outcomes in the first, and Cogstate outcomes in the second model as predictors of biological age to compare their sensitivity to age-related cognitive decline.
Results:
We found moderate correlations between VStore and Cogstate outcomes. VStore Total Time was best explained by tasks measuring working memory and paired associate learning, in addition to age and technological familiarity, accounting for 46% of the variance. Finally, with λ = 5.16, the model fitting selected five parameters for VStore when predicting biological age (MSE = 185.8, SE= 19.34). With λ = 9.49 for Cogstate, the model fitting selected all eight tasks (MSE = 226.8, SE = 23.48).
Conclusions:
Our findings suggest that VStore is a promising assessment that engages standard cognitive domains and is sensitive to age-related cognitive decline. Clinical Trial: NA
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