A-306 MoCA-22: Criterion Validity and Classification Accuracy of the MoCA’s Auditory Items
Bibliographic record
Abstract
Abstract Objective: Our research aims to evaluate criterion validity of the auditory Montreal Cognitive Assessment (MoCA-22; also disseminated as telephone-MoCA and MoCA-blind) when compared to individuals with and without vision impairment and of different dementia syndromal stages. Additionally, we explore the classification accuracy of MoCA-22 in distinguishing mild cognitive impairment (MCI) from unimpaired cognition and mild-to-moderate dementia from MCI. Methods: The National Alzheimer’s Coordinated Center database included 11,284 participants who completed a portion of the MoCA during their first visit to an Alzheimer’s Disease Research Center. Participants were mostly women (57.64%), self-identified as White (77.98%), were older adults (M age=69.22), and college educated (M education years=15.89). Dementia stages included: unimpaired (43.73%), MCI (40.99%), and mild-to-moderate dementia (14.87%) with 71.7% having some visual impairment and 2.8% not benefitting from lenses. ANOVAs and t-tests were used to evaluate criterion validity. Area under the receiver operating characteristic (ROC) curves were investigated for diagnostic accuracy. Results: The visually mediated MoCA items had larger differences among those with and without visual impairment compared to the MoCA-22. There were also strong differences across the dementia syndromal stages which carried over to strong classification accuracy in distinguishing MCI from normal cognition (AUC = .79), and mild-to-moderate dementia from MCI (AUC = .85). Conclusions: These findings add to the evidence of the MoCA-22’s utility for visual impaired individuals who otherwise cannot complete the full version of the MoCA. The MoCA-22 serves as a useful cognitive screening tool in differentiating between cognitive severities.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 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 | 0.000 |
| 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".