Objective: The Montreal Cognitive Assessment (MoCA) is among the most frequently administered cognitive screening tests, yet demographically diverse normative data are needed for repeated administrations.
Method: Data were obtained from 18,410 participants using the National Alzheimer's Coordinating Center Uniform Data Set. We developed regression-based norms using Tobit regression to account for ceiling effects, explored test-retest reliability of total scores and by domain stratified by age and diagnosis with Cronbach's alpha, and reported the cumulative change frequencies for individuals with serial MoCA administrations to gage expected change.
Results: Strong ceiling effects and negative skew were observed at the total score, domain, and item levels for the cognitively normal group, and performances became more normally distributed as the degree of cognitive impairment increased. In regression models, years of education was associated with higher MoCA scores, whereas older age, male sex, Black and American Indian or Alaska Native race, and Hispanic ethnicity were associated with lower predicted scores. Temporal stability was adequate and good at the total score level for the cognitively normal and cognitive disorders groups, respectively, but fell short of reliability standards at the domain level.
Conclusions: MoCA total scores are adequately reproducible among those with cognitive diagnoses, but domain scores are unstable. Robust regression-based norms should be used to adjust for demographic performance differences, and the limited reliability, along with the ceiling effects and negative skew, should be considered when interpreting MoCA scores.
Keywords: Blind; MoCA; Normative data; Regression; Reliability; Reliable change.
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