Criterion and Convergent Validity of the Montreal Cognitive Assessment with Screening and Standardized Neuropsychological Testing
Bibliographic record
Abstract
OBJECTIVES: To compare the validity of the Montreal Cognitive Assessment (MoCA) with the criterion standard of standardized neuropsychological testing and to compare the convergent validity of the MoCA with that of existing screening tools and global measures of cognition. DESIGN: Cross-sectional observational study. SETTING: Tertiary care hospital-based cognitive neurology subspecialty clinic. PARTICIPANTS: A convenience sample of 107 individuals with mild Alzheimer's disease (AD, n=75) or mild cognitive impairment (MCI, n=32) from the Sunnybrook Dementia Study. MEASUREMENTS: In addition to the MoCA, all participants completed the Mini-Mental State Examination (MMSE), the Mattis Dementia Rating Scale (DRS), and detailed neuropsychological testing. RESULTS: Convergent validity was supported, with MoCA scores correlating well with the MMSE (correlation coefficient (r)=0.66, P<.001) and the DRS (r=0.77, P<.001) and the MoCA better associated with the DRS than did the MMSE. Criterion validity was supported, with MoCA subscores according to cognitive domain correlating well with analogous neuropsychological tests and, in the case of memory (area under the receiver operating characteristic curve (AUC)=0.86), executive (AUC=0.79), and visuospatial function (AUC=0.79), being reasonably sensitive to impairment in those domains. CONCLUSION: The MoCA is a valid assessment of cognition that shows good agreement with existing screening tools and global measures (convergent validity) and was superior to the MMSE in this regard. The MoCA domain-specific subscores align with performance on more-detailed neuropsychological tests, suggesting not only good criterion validity for the MoCA, but also that it may be useful in guiding further neuropsychological testing.
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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 | 0.020 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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 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".