Montreal Cognitive Assessment: Influence of Sociodemographic and Health Variables
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is a brief cognitive instrument for screening milder forms of cognitive impairment. The present study aimed to analyze the influence of sociodemographic (age, gender, educational level, marital and employment status, geographic region, geographic localization, and residence area) and health variables (subjective memory complaints of the participant and evaluated by the informant, depressive symptoms, and family history of dementia) on the participants' performance on the MoCA. The investigation was carried out in a Portuguese community-based sample of 650 cognitively healthy adults, who were representative of the distribution observed in the Portuguese population. Educational level and age significantly contributed to the prediction of the MoCA scores, explaining 49% of the variance. Regarding health variables, only the subjective memory complaints of the participant showed a small contribution (9%) to the variance on the MoCA scores. This study contributes a useful approach to understanding MoCA performance, stressing the great impact of education and age on scores.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".