VALIDATION OF THE BRAZILIAN ALTERNATIVE VERSION OF THE MONTREAL ASSESSMENT (MOCA): PILOT STUDY
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is a screening tool designed to detect mild cognitive impairment (MCI). The current version used in Brazil, MoCA-BR, did not have a reliable cross-cultural adaptation to Brazilian Portuguese and has structural aws that might lead to a higher rate of false-positives. In previous stages of this study, the Alternative Version of the MoCA-BR was developed, with changes in the sections: Memory and Delayed Recall, Language and Naming. to verify the inuence of cross-cultural Objectives: adaptation on the performance of cognitive tools, and the applicability and internal accuracy of the Alternative Version of the MoCA-BR. a pilot, prospective, monocentric, longitudinal, Methods: and analytical study. Both versions of the test were applied in a randomized and cognitively healthy population, between 18 and 60 years, within a medium interval of 54,56 days (median = 32 days) between the questionnaires. out of 104 part Results: icipants, 70 were included (64.3% female, 40.2 years). The alternative version was superior in the naming domain (p < 0.001), and in the adapted sentence within the language domain (p = 0.003). There were no signicant differences within the delayed recall domain. The alternative version showed good internal consistency, with a Cronbach's alpha coefcient of 0.75. The cut-off point suggested by the study is 27 points, with sensitivity and specicity of 91.3% and 79.2%, respectively. Cultural factors affect the accuracy of cognitive tests, and Conclusions: adaptation is essential for their use in different countries.
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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 | 0.016 | 0.033 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".