Identify which NIH Toolbox Cognition Battery (NIHTB-CB) subtest(s) best differentiate healthy controls (HC) from those with amnestic mild cognitive impairment (aMCI) and compare the discriminant accuracy between a model using a priori “Norm Adjusted” scores versus “Unadjusted” standard scores with age, sex, race/ethnicity, and education controlled for within the model. Racial differences were also examined.

Participants were Black/African American (B/AA) and White consensus-confirmed (HC = 96; aMCI = 62) adults 60–85 years old that completed the NIHTB-CB for tablet. Discriminant function analysis (DFA) was used in the Total Sample and separately for B/AA (n = 80) and White participants (n = 78).

Picture Sequence Memory (an episodic memory task) was the highest loading coefficient across all DFA models. When stratified by race, differences were noted in the pattern of the highest loading coefficients within the DFAs. However, the overall discriminant accuracy of the DFA models in identifying HCs and those with aMCI did not differ significantly by race (B/AA, White) or model/score type (Norm Adjusted versus Unadjusted).

Racial differences were noted despite the use of normalized scores or demographic covariates—highlighting the importance of including underrepresented groups in research. While the models were fairly accurate at identifying consensus-confirmed HCs, the models proved less accurate at identifying White participants with an aMCI diagnosis. In clinical settings, further work is needed to optimize computerized batteries and the use of NIHTB-CB norm adjusted scores is recommended. In research settings, demographically corrected scores or within model correction is suggested.

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).

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.

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.

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.