Classification statistics of the Montreal Cognitive Assessment (MoCA): Are we interpreting the MoCA correctly?

The Montreal Cognitive Assessment (MoCA) is a common cognitive screener for detecting mild cognitive impairment (MCI). However, previously suggested cutoff scores of 26/30 and above is often criticized and lacks racial diversity. The purpose of this study is to investigate the potential influence of race on MoCA classification cutoff score accuracy.

Data were obtained from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set and yielded 4,758 total participants. Participants were predominately White (82.8%) and female (61.7%) with a mean age of 69.3 years (SD = 10.3) and education level of 16.3 years (SD = 2.6). Based on NACC's classification, participants were either cognitively normal (n = 3,650) or MCI (n = 1,108).

Sensitivity and specificity analyses revealed that when using the cutoff score of ≤26/30, the MoCA correctly classified 73.2% of White cognitively normal participants and 83.1% of White MCI participants. In contrast, this criterion correctly classified 40.5% of Black cognitively normal participants and 90.8% of Black MCI participants. Our sample was highly educated; therefore, we did not observe significant differences in scores when accounting for education across race. Classification statistics are presented.

Black participants were misclassified at a higher rate than White participants when applying the ≤26/30 cutoff score. We suggest cutoff scores of ≤25/30 be applied to White persons and ≤22/30 for Black persons. These findings highlight the need for racially stratified population-based norms given the high misclassification of Black participants without such adjustment.