| Autor: |
Lucas G Childers, Danielle R. Hardesty, Nancy Tran, Jenna M. Moore, Michael Persin, Lee D, Michael D. Barnett, Thomas D. Parsons, Cameron Bayer |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Archives of Clinical Neuropsychology. 36:1223-1223 |
| ISSN: |
1873-5843 |
| Popis: |
Objective Virtual reality-based neuropsychological tests offer the ability to capture a variety of data while enabling standardized administration. The purpose of this study was to create an artificial neural network to examine the predictability of the Virtual Environment Grocery Store (VEGS) for neurocognitive impairment among older adults. Method Older adults (N = 71; age 55–90, M = 74.38, SD = 8.32; 13 with a neurocognitive diagnosis and 58 without) completed the VEGS as part of a neuropsychological evaluation. Results The multilayer perceptron found a model which had a 3.4% error rate. The VEGS sum of the learning trials was the most important predictor of this model (i = 0.45). Conclusion Results suggest that the VEGS is sensitive to detecting neurocognitive impairment among older adults, with the sum of the learning trials making a substantial contribution to the model’s accuracy. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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