Cognitive Performance on the Mini-Mental State Examination and the Montreal Cognitive Assessment Across the Healthy Adult Lifespan
Bibliographic record
Abstract
OBJECTIVE: We sought to compare age-related performance on the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) across the adult lifespan in an asymptomatic, presumably normal, sample. BACKGROUND: The MMSE is the most commonly used brief cognitive screening test; however, the MoCA may be better at detecting early cognitive dysfunction. METHODS: We gave the MMSE and MoCA to 254 community-dwelling participants ranging in age from 20 to 89, stratified by decade, and we compared their scores using the Wilcoxon signed rank test. RESULTS: For the total sample, the MMSE and MoCA differed significantly in total scores as well as in visuospatial, language, and memory domains (for all of these scores, P<0.001). Mean MMSE scores declined only modestly across the decades; mean MoCA scores declined more dramatically. There were no consistent domain differences between the MMSE and MoCA during the third and fourth decades; however, significant differences in memory (P<0.05) and language (P<0.001) emerged in the fifth through ninth decades. CONCLUSIONS: We conclude that the MoCA may be a better detector of age-related decrements in cognitive performance than the MMSE, as shown in this community-dwelling adult population.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".