Trajectories of MMSE and MoCA scores across the healthy adult lifespan in the Italian population
Bibliographic record
Abstract
BACKGROUND: This study compares the performance at the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) across the healthy adult lifespan in an Italian population sample. METHODS: The MMSE and MoCA were administered to 407 Italian healthy native-speakers (165 males; age range 20-93 years; education range 4-25 years). A generalized Negative Binomial mixed model was run to profile MMSE and MoCA scores across 8 different age classes (≤ 30; 31-40; 41-50; 51-60; 61-70; 71-80; 81-85; ≥ 86) net of education and sex. RESULTS: MMSE and MoCA total scores declined with age (p < 0.001), with the MoCA proving to be "more difficult" than the MMSE (p < 0.001). The Age*Test interaction (p < 0.001) indicates that the MoCA proved to profile a sufficiently linear involutional trend in cognition with advancing age and to be able to detect poorer cognitive performances in individuals aged ≥ 71 years. By contrast, MMSE scores failed in capturing the expected age-related trajectory, reaching a plateau in the aforementioned age classes. DISCUSSION: The MoCA seems to be more sensitive than the MMSE in detecting age-related physiological decline of cognitive functioning across the healthy adult lifespan. The MoCA might be therefore more useful than the MMSE as a test for general cognitive screening aims.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".