Validation of Montreal Cognitive Assessment and Discriminant Power of Montreal Cognitive Assessment Subtests in Patients With Mild Cognitive Impairment and Alzheimer Dementia in Turkish Population
Bibliographic record
Abstract
Montreal Cognitive Assessment (MoCA) is a new cognitive tool developed for screening mild cognitive impairment (MCI). The authors examined validity of MoCA and discriminating power of subtests in a Turkish population comprising of 474 participants (246 healthy controls, 114 subjects with MCI and 114 subjects with dementia). The ANCOVAs showed that age and education had a main effect on MoCA scores. Cut scores were computed according to different education levels. The overall cut-off values for MCI and dementia were found to be lower compared to western studies. MoCA was found to have good internal consistency. The subtests most useful in discriminating MCI from healthy controls were recall, visuospatial and language, while in discriminating dementia from MCI were visuospatial, orientation and attention subtests. The results demonstrated that MoCA is a valid and reliable instrument in screening MCI, and compared with the MMSE, MoCA was proved to have superior sensitivity and specificity in detecting MCI.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".