Cognitive function in generally healthy adults age 70 years and older in the 5-country DO-HEALTH study: MMSE and MoCA scores by sex, education and country
Bibliographic record
Abstract
BACKGROUND: Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are validated and frequently used screening tools for cognitive function. AIMS: To present MMSE and MoCA scores by sex, age and education among community-dwelling older adults. METHODS: This is a post-hoc observational analysis using data from the DO-HEALTH trial, which included generally healthy adults (≥ 70 years) from Switzerland, Germany, Austria, France, and Portugal who scored at least 24 points on the MMSE at baseline. We present MMSE and MoCA scores overall and by country, sex, age (70-74 years, ≥ 75 years), education (≤ and > median education years). RESULTS: 2151 DO-HEALTH participants (mean age 74.9 years, 57% aged 70-74 years, 62% women) were included. The median (IQR) years of education was 12 (10-15), median MMSE score was 29 (28-30) and median MoCA score was 26 (23-28) points. In subgroups by sex, age, and education, the median MMSE score remained 29 for all subgroups, except for participants with shorter education (≤ 12 years) and higher age (≥ 75), who scored 28 points. For MoCA, the median score in subgroups ranged from 24 to 27 points. Participants with shorter education (≤ 12 years) and higher age (≥ 75) had lowest scores (men 24, women 25 points). CONCLUSIONS: We provide MMSE and MoCA scores for generally healthy, community-dwelling older adults from Switzerland, Germany, Austria, France and Portugal. The median MMSE and MoCA scores differed with age and education, and - less consistently - with sex. TRIAL REGISTRATION: International Trials Registry (clinicaltrials.gov; registration ID: NCT01745263), registered December 2012.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".