Factors that indicate performance on the MoCA 7.3 in healthy adults over 50 years old
Bibliographic record
Abstract
Human aging is a physiological, progressive, heterogeneous global process that causes a decline of all body systems, functions, and organs. Throughout this process, cognitive function suffers an incremental decline with broad interindividual variability.The first objective of this study was to examine the differences in the performance on the MoCA test (v. 7.3) per gender and the relationship between the performance and the variables age, years of schooling, and depressive symptoms .The second objective was to identify factors that may influence the global performance on the MoCA test (v. 7.3) and of the domains orientation, language, memory, attention/calculation, visuospatial and executive function, abstraction, and identification.A cross-sectional study was carried out in which five hundred seventy-three (573) cognitively healthy adults ≥ 50 years old were included in the study. A sociodemographic questionnaire, the GDS-15 questionnaire to assess depression symptoms and the Spanish version of the MoCA Test (v 7.3) were administered. The evaluations were carried out between the months of January and June 2022. Differences in the MoCA test performance per gender was assessed with Student's t-test for independent samples. The bivariate Pearson correlation was applied to examine the relationship between total scoring of the MoCA test performance and the variables age, years of schooling, and depressive symptoms. Different linear multiple regression analyses were performed to determine variables that could influence the MoCA test performance.We found gender-related MoCA Test performance differences. An association between age, years of schooling, and severity of depressive symptoms was observed. Age, years of schooling, and severity of depressive symptoms influence the MoCA Test performance, while gender does not.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".