Laptop-Administered NIH Toolbox and Cogstate Brief Battery in Community-Dwelling Black Adults: Unexpected Pattern of Cognitive Performance between MCI and Healthy Controls

Abstract

Objective: Black adults are approximately twice as likely to develop Alzheimer’s disease (AD) than non-Hispanic Whites and access diagnostic services later in their illness. This dictates the need to develop assessments that are cost-effective, easily administered, and sensitive to preclinical stages of AD, such as mild cognitive impairment (MCI). Two computerized cognitive batteries, NIH Toolbox-Cognition and Cogstate Brief Battery, have been developed. However, utility of these measures for clinical characterization remains only partially determined. We sought to determine the convergent validity of these computerized measures in relation to consensus diagnosis in a sample of MCI and healthy controls (HC). Method: Participants were community-dwelling Black adults who completed the neuropsychological battery and other Uniform Data Set (UDS) forms from the AD centers program for consensus diagnosis (HC = 61; MCI = 43) and the NIH Toolbox-Cognition and Cogstate batteries. Discriminant function analysis was used to determine which cognitive tests best differentiated the groups. Results: NIH Toolbox crystallized measures, Oral Reading and Picture Vocabulary, were the most sensitive in identifying MCI apart from HC. Secondarily, deficits in memory and executive subtests were also predictive. UDS neuropsychological test analyses showed the expected pattern of memory and executive functioning tests differentiating MCI from HC. Conclusions: Contrary to expectation, NIH Toolbox crystallized abilities appeared preferentially sensitive to diagnostic group differences. This study highlights the importance of further research into the validity and clinical utility of computerized neuropsychological tests within ethnic minority populations.

Mild Cognitive Impairment Subtype Performance in Comparison to Healthy Older Controls on the NIH Toolbox and Cogstate

“…Interestingly, the NIHTB-CB picture vocabulary test differentiated MCI from HCs, and oral reading also unexpectedly approached statistical significance. This is similar to findings by Kairys et al 25 on a sample of African American older adults. Given documented differences in reading level by race, 40 it is possible that this finding is an artifact of the shared variance among MCI, education level, and race.…”

“…However, there were no differences between HC and MCI on race or educational attainment, thus arguing against this point when it comes to Picture vocabulary findings. Another consideration is that differences in picture vocabulary and oral reading may be related to language deficits in the MCI group, 25 which is especially notable in patients with AD and may reflect those patients with MCI who are early cases for this type of etiology.…”

“…Moreover, Hackett et al 24 used factor scores derived from a principal component analysis to predict diagnostic classification in the discriminant function analysis instead of modeling subtest scores directly, which may obscure individual differences in the predictive ability of each of the individual NIHTB-CB subtests. Similarly, a separate study on African American older adults found that the NIHTB-CB was able to identify MCI from healthy control (HC) participants, especially when considering Oral Reading and Picture Vocabulary performance 25 . However, specific information on the predictive qualities of each subtest, as well as the differential diagnosis of MCI subtypes, have yet to be examined.…”

“…Similarly, a separate study on African American older adults found that the NIHTB-CB was able to identify MCI from healthy control (HC) participants, especially when considering Oral Reading and Picture Vocabulary performance. 25 However, specific information on the predictive qualities of each subtest, as well as the differential diagnosis of MCI subtypes, have yet to be examined.…”

A Paradox in Digital Memory Assessment: Increased Sensitivity With Reduced Difficulty

“…Such tests also make use of computer software to analyze in real time, performance data in order to adjust instructional and training procedures so individuals understand and adhere to the rules and requirements of the tests (7,8). Such refinement has allowed one of these digital tools, the Cogstate Brief Battery (CBB), to extend aspects of neuropsychological decision-making from one-on-one clinical interviews (9,10), to supervised settings in large groups (11), high frequency repeated testing (12,13) and pre-interview triage (14), as well as wide-scale unsupervised internet-based cognitive assessment (15)(16)(17). Despite this success, it remains important to continue the refinement and optimization of digital tools, especially where use cases identify the need for such improvement.…”