Montreal Cognitive Assessment (MoCA): Validation Study for Vascular Dementia
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is a brief instrument developed for the screening of milder forms of cognitive impairment, having surpassed the well-known limitations of the MMSE. The aim of the present study was to validate the MoCA as well as its short version, which was proposed by the NINDS-CSN VCI Harmonization Standards for screening Vascular Dementia (VaD) patients. The results, based on a homogeneous sample of 34 VaD patients, indicate that the MoCA is a psychometrically valid and reliable instrument for cognitive screening in VaD patients, showing excellent discriminant validity. Both the full and short versions of the MoCA had excellent diagnostic accuracy in discriminating VaD patients, exhibiting an area under curve (AUC) higher than the MMSE [AUC(MoCA full version) = .950; 95% IC = .868-.988; AUC(MoCA short version) = .936; 95% IC = .849-.981; AUC(MMSE) = .860; 95% IC = .754-.932]. With a cutoff below 17 on the MoCA full version and 8 on the short version, the results for sensitivity, specificity, positive and negative predictive values, and classification accuracy were superior compared to the MMSE. In conclusion, both versions of the MoCA are valid, reliable, sensitive and accurate screening instruments for VaD patients.
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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 | 0.005 | 0.013 |
| 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 | 0.001 |
| 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".