A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Supervised digital neuropsychological tests for cognitive decline in older adults: Usability and clinical validity study
Background: Dementia is a major and growing health problem, and early diagnosis is key to its management. Objective: With the ultimate goal of providing a monitoring tool that could be used to support the screening for cognitive decline, this study aims to develop a supervised, digitized version of 2 neuropsychological tests: Trail Making Test and Bells Test. The system consists of a web app that implements a tablet-based version of the tests and consists of an innovative vocal assistant that acts as the virtual supervisor for the execution of the test. A replay functionality is added to allow inspection of the user's performance after test completion. Methods: To deploy the system in a nonsupervised environment, extensive functional testing of the platform was conducted, together with a validation of the tablet-based tests. Such validation had the two-fold aim of evaluating system usability and acceptance and investigating the concurrent validity of computerized assessment compared with the corresponding paper-and-pencil counterparts. Results: The results obtained from 83 older adults showed high system acceptance, despite the patients' low familiarity with technology. The system software was successfully validated. A concurrent validation of the system reported good ability of the digitized tests to retain the same predictive power of the corresponding paper-based tests. Conclusions: Altogether, the positive results pave the way for the deployment of the system to a nonsupervised environment, thus representing a potential efficacious and ecological solution to support clinicians in the identification of early signs of cognitive decline.
Supervised digital neuropsychological tests for cognitive decline in older adults: Usability and clinical validity study
Background: Dementia is a major and growing health problem, and early diagnosis is key to its management. Objective: With the ultimate goal of providing a monitoring tool that could be used to support the screening for cognitive decline, this study aims to develop a supervised, digitized version of 2 neuropsychological tests: Trail Making Test and Bells Test. The system consists of a web app that implements a tablet-based version of the tests and consists of an innovative vocal assistant that acts as the virtual supervisor for the execution of the test. A replay functionality is added to allow inspection of the user's performance after test completion. Methods: To deploy the system in a nonsupervised environment, extensive functional testing of the platform was conducted, together with a validation of the tablet-based tests. Such validation had the two-fold aim of evaluating system usability and acceptance and investigating the concurrent validity of computerized assessment compared with the corresponding paper-and-pencil counterparts. Results: The results obtained from 83 older adults showed high system acceptance, despite the patients' low familiarity with technology. The system software was successfully validated. A concurrent validation of the system reported good ability of the digitized tests to retain the same predictive power of the corresponding paper-based tests. Conclusions: Altogether, the positive results pave the way for the deployment of the system to a nonsupervised environment, thus representing a potential efficacious and ecological solution to support clinicians in the identification of early signs of cognitive decline.
Supervised digital neuropsychological tests for cognitive decline in older adults: Usability and clinical validity study
Lunardini F. (author) / Luperto M. (author) / Romeo M. (author) / Basilico N. (author) / Daniele K. (author) / Azzolino D. (author) / Damanti S. (author) / Abbate C. (author) / Mari D. (author) / Cesari M. (author)
2020-01-01
Article (Journal)
Electronic Resource
English
DDC:
690
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