A Validation Study of the Inbrain CST: a Tablet Computer-based Cognitive Screening Test for Elderly People with Cognitive Impairment

Abstract

Background: Computerized versions of cognitive screening test could have advantages over pencil-and-paper versions by eliminating rater-dependent factors and saving the time required to score the tests and report the results. We developed a computerized cognitive screening test (Inbrain Cognitive Screening Test [Inbrain CST]) that takes about 30 minutes to administer on a touchscreen computer and is composed of neuropsychological tests already shown to be sensitive in detecting early cognitive decline in Alzheimer's disease (AD). The aims of this study were to 1) introduce normative data for Inbrain CST, 2) verify its reliability and validity, 3) assess clinical usefulness, and 4) identify neuroanatomical correlates of Inbrain CST. Methods: The Inbrain CST runs on the Microsoft Windows 10 operating system and comprises 7 subtests that encompass 5 cognitive domains: attention, language, visuospatial, memory, and executive functions. First, we recruited 480 cognitively normal elderly people (age 50-90) from communities nationwide to establish normative data for Inbrain CST. Second, we enrolled 97 patients from our dementia clinic (26 with subjective cognitive decline [SCD], 42 with amnestic mild cognitive impairment [aMCI], and 29 with dementia due to AD) and investigated sensitivity and specificity of Inbrain CST for discriminating cognitively impaired patients from those with SCD using receiver operating characteristic (ROC) curve analyses. Third, we compared the Inbrain CST scores with those from another neuropsychological test battery to obtain concurrent validity and assessed test-retest reliability. Finally, magnetic resonance imaging (MRI)-based cortical thickness analyses were performed to provide anatomical substrates for performances on the Inbrain CST. Results: First, in the normative sample, the total score on the Inbrain CST was significantly affected by age, years of education, and gender. Second, Inbrain CST scores among the three patient groups decreased in the order of SCD, aMCI, and AD dementia, and the ROC curve analysis revealed that Inbrain CST had good discriminative power for differentiating cognitively impaired patients from those with SCD. Third, the Inbrain CST subtests had high concurrent validity and test-retest reliability. Finally, in the cortical thickness analysis, each cognitive domain score and the total score of Inbrain CST showed distinct patterns of anatomical correlates that fit into the previously known brain-behavior relationship. Conclusion: Inbrain CST had good validity, reliability, and clinical usefulness in detecting cognitive impairment in the elderly. Furthermore, it showed neuroanatomical validity

Digital Cognitive Biomarker for Mild Cognitive Impairments and Dementia: A Systematic Review

“…While most of the cognitive outcomes measured in computerized test batteries showed moderate to large group differences, the visuospatial subset of Tablet-based Cognitive Assessments ( g = 0.3) only showed small group difference [ 54 ]. Again, large group differences were reported in test batteries including CANTAB [ 41 ], NeuroTrax Mindstreams [ 55 ], Inbrain CST [ 15 ], and BHA [ 44 ], and the largest group differences were observed in memory subsets, followed by executive function subsets. Other single/multiple cognitive tests showed a large group means difference ranging from 0.9 to 3.1, suggesting that various cognitive domains including processing speed, attention, emotion recognition, and visual-motor skills can well-differentiate MCI from normal controls.…”

“…Two types of tasks for yielding digital biomarkers were identified: one is active tasks that require active engagement in the evaluation, such as computerized versions of traditional cognitive tests (e.g., [ 15 , 16 ]) or online games (e.g., [ 17 , 18 , 19 ]) for assessing a broad domain of cognitive functions, voluntary speech production for assessing language ability [ 20 ], or virtual reality techniques (e.g., [ 21 , 22 ]). Another type is passive tasks in which people were monitored without active input, such sleep quality, walking speed, phone usage, and daily activities [ 13 , 23 ].…”

An Effective Test (EOmciSS) for Screening Older Adults With Mild Cognitive Impairment in a Community Setting: Development and Validation Study

“…The Hosmer-Lemeshow goodness-of-fit test also indicated good data for model fitting ( χ 2 8 =11.54, P =.17). Weighted scores of the 9 item factors were derived based on the β coefficients [ 25 ] obtained from the logistic regression model. The inclusion of factors CD-Acc1 ( P =.07), CD-Acc2 ( P =.06), TM-Acc4 ( P =.07), RS ( P =.06), and DR-RT2 ( P =.05), despite their marginal significance in the regression model, was to strengthen content representativeness of EOmciSS ( Table 4 ).…”

“…The latter has been found to be a common comorbidity of MCI [23]. Depressive symptoms (eg, lack of motivation, slowness to respond) would contribute to the false-positive rate of test results [24][25][26]. However, the test of a depressive mood is not a feature in the aforementioned computerized screening tests.…”

The Seoul Neuropsychological Screening Battery (SNSB) for Comprehensive Neuropsychological Assessment

“… 30 Another tablet-based neuropsychological test battery, Inbrain Cognitive Screening Test, was analyzed for reliability and validity compared to the SNSB. 31 Additionally, the SNSB domain scores serve a standard role for validating scores provided by other tests, such as the MoCA Index score. 32 …”