Related Experiment Video
Updated: Mar 31, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The Montreal Cognitive Assessment: Creating a Crosswalk with the Mini-Mental State Examination
Jane S Saczynski1,2, Sharon K Inouye2,3,4, Jamey Guess4,5
1Division of Geriatric Medicine, Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts.
Objectives:
To establish Montreal Cognitive Assessment (MoCA) scores that correspond to well-established cut-points on the Mini-Mental State Examination (MMSE).
Design:
Cross-sectional observational study.
Setting:
General medical service of a large teaching hospital.
Participants:
Individuals aged 75 and older (N = 199; mean age 84, 63% female).
Measurements:
The MoCA (range 0-30) and the MMSE (range 0-30) were administered within 2 hours of each other. The Abbreviated MoCA (A-MoCA; range 0-22) was calculated from the full MoCA. Scores from the three tests were analyzed using equipercentile equating, a statistical method for determining comparable scores on different tests of a similar construct by estimating percentile equivalents.
Results:
MoCA scores were lower (mean 19.3 ± 5.8) than MMSE scored (mean 24.1 ± 6.6). Traditional MMSE cut-points of 27 for mild cognitive impairment and 23 for dementia corresponded to MoCA scores of 23 and 17, respectively.
Conclusion:
Scores on the full and abbreviated versions of the MoCA can be linked directly to the MMSE. The MoCA may be more sensitive to changes in cognitive performance at higher levels of functioning.
More Related Videos
06:58Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing
Published on: January 24, 2020
06:23The 4 Mountains Test: A Short Test of Spatial Memory with High Sensitivity for the Diagnosis of Pre-dementia Alzheimer's Disease
Published on: October 13, 2016