The Montreal Cognitive Assessment: Creating a Crosswalk with the Mini‐Mental State Examination
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".