Detection of Mild Cognitive Impairment in an At-Risk Group of Older Adults: Can a Novel Self-Administered Serious Game-Based Screening Test Improve Diagnostic Accuracy? - Zygouris, Stelios; Iliadou, Paraskevi; Lazarou, Eftychia; Giakoumis, Dimitrios; Votis, Konstantinos; Alexiadis, Anastasios; Triantafyllidis, Andreas; Segkouli, Sofia; Tzovaras, Dimitrios; Tsiatsos, Thrasyvoulos; Papagianopoulos, Sotirios; Tsolaki, Magda (J Alzheimers Dis, 2020)
BACKGROUND: Literature supports the use of serious games and virtual environments to assess cognitive functions and detect cognitive decline. This promising assessment method, however, has not yet been translated into self-administered screening instruments for pre-clinical dementia. OBJECTIVE: The aim of this study is to assess the performance of a novel self-administered serious game-based test, namely the Virtual Supermarket Test (VST), in detecting mild cognitive impairment (MCI) in a sample of older adults with subjective memory complaints (SMC), in comparison with two well-established screening instruments, the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). METHODS: Two groups, one of healthy older adults with SMC (N = 48) and one of MCI patients (N = 47) were recruited from day centers for cognitive disorders and administered the VST, the MoCA, the MMSE, and an extended pencil and paper neuropsychological test battery. RESULTS: The VST displayed a correct classification rate (CCR) of 81.91% when differentiating between MCI patients and older adults with SMC, while the MoCA displayed of CCR of 72.04% and the MMSE displayed a CCR of 64.89%. CONCLUSION: The three instruments assessed in this study displayed significantly different performances in differentiating between healthy older adults with SMC and MCI patients. The VST displayed a good CCR, while the MoCA displayed an average CCR and the MMSE displayed a poor CCR. The VST appears to be a robust tool for detecting MCI in a population of older adults with SMC.

A Preliminary Study on the Feasibility of Using a Virtual Reality Cognitive Training Application for Remote Detection of Mild Cognitive Impairment. - Zygouris, Stelios; Ntovas, Konstantinos; Giakoumis, Dimitrios; Votis, Konstantinos; Doumpoulakis, Stefanos; Segkouli, Sofia; Karagiannidis, Charalampos; Tzovaras, Dimitrios; Tsolaki, Magda (J Alzheimers Dis, 2017)
BACKGROUND: It has been demonstrated that virtual reality (VR) applications can be used for the detection of mild cognitive impairment (MCI). OBJECTIVE: The aim of this study is to provide a preliminary investigation on whether a VR cognitive training application can be used to detect MCI in persons using the application at home without the help of an examiner. METHODS: Two groups, one of healthy older adults (n = 6) and one of MCI patients (n = 6) were recruited from Thessaloniki day centers for cognitive disorders and provided with a tablet PC with custom software enabling the self-administration of the Virtual Super Market (VSM) cognitive training exercise. The average performance (from 20 administrations of the exercise) of the two groups was compared and was also correlated with performance in established neuropsychological tests. RESULTS: Average performance in terms of duration to complete the given exercise differed significantly between healthy(μ  = 247.41 s/ sd = 89.006) and MCI (μ= 454.52 s/ sd = 177.604) groups, yielding a correct classification rate of 91.8% with a sensitivity and specificity of 94% and 89% respectively for MCI detection. Average performance also correlated significantly with performance in Functional Cognitive Assessment Scale (FUCAS), Test of Everyday Attention (TEA), and Rey Osterrieth Complex Figure test (ROCFT). DISCUSSION: The VR application exhibited very high accuracy in detecting MCI while all participants were able to operate the tablet and application on their own. Diagnostic accuracy was improved compared to a previous study using data from only one administration of the exercise. The results of the present study suggest that remote MCI detection through VR applications can be feasible.