Validación preliminar del Montreal Cognitive Assessment Basic (Moca-B) en población adulta mayor colombiana con bajo o nulo nivel escolar.
Bibliographic record
Abstract
Dementia is a global disease that impacts the world economy. Currently, there are few instruments that assess the cognitive status of the population with little or no education that are useful, sensitive and specific for the detection of cognitive impairment, which is why we need to review whether Moca-B meets the criteria to evaluate MCI in our context, especially taking into account that there are no studies of this test carried out in our country. Objective: To review the psychometric parameters of the cognitive screening "Montreal Cognitive Assessment Basic (Moca-B)" in the Colombian context in a population with little or no schooling. Method: Empirical-analytical paradigm, with a cross-sectional descriptive scope. Results: A satisfactory performance of the MoCa B was found for the population with Mild Cognitive Impairment and the control group, however, an inconsistent result is observed in the subtests with respect to the total scores. The cut-off points were found based on the youden index, being consistent with each population group. Conclusions: The Montreal Cognitive Assessment Basic (Moca-B) test showed a high scientific potential to detect MCI and discriminate healthy population, it is recommended to carry out more research about this evaluation in our country with a more significant sample in order to obtain generalizable data.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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 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".