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Comparative Analysis of MoCA and DigiMoCA Test Results: A Pilot Study

Authors :
Noelia Lago-Priego
Iván Otero-González
Moisés Pacheco-Lorenzo
Manuel J. Fernández-Iglesias
Carlos Dosil-Díaz
César Bugallo-Carrera
Manuel Gandoy-Crego
Luis Anido-Rifón
Source :
Applied Sciences, Vol 14, Iss 12, p 5073 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

This study examined the cognitive performance of older adults aged 60 and above using the Montreal Cognitive Assessment (MoCA) test and DigiMoCA, a digital tool for cognitive screening administered by means of a smart speaker, to investigate whether the additional variables utilised by DigiMoCA allow for the identification of significant differences between individuals with depressive symptoms and those with mild cognitive impairment, which are not detected using the original MoCA test. A total of 73 senior adults located in Northwestern Spain, 22 male and 51 female, participated in this study. Subjects were divided into four groups based on the presence of depressive symptoms and mild cognitive impairment, with the aim of analysing the results of each dimension of the MoCA and DigiMoCA tests and assessing the additional insights provided by the digital administration tool. The results indicate significant differences among groups. Individuals with depressive symptoms exhibited poorer performance in forward number span, attention, and clock drawing compared to healthy controls. Furthermore, individuals with depressive symptoms and mild cognitive impairment exhibited significantly worse memory and orientation compared to those with cognitive impairment alone. Correlations revealed that a greater severity of depressive symptoms was associated with poorer performance across cognitive domains, including visuospatial skills, attention, language, memory, and phonemic verbal fluency. This study also illustrated how the exploitation of additional variables systematically captured by digital instruments, such as completion times or response delays to individual interactions, may facilitate the early identification of cognitive and depressive conditions, providing initial evidence about the importance of integrating advanced digital tools in cognitive assessment to inspire the development of more effective, personalised interventions.

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.26ec2abd05c5482cad7145fb504f887e
Document Type :
article
Full Text :
https://doi.org/10.3390/app14125073