Evaluation of a Telephone Version for the Montreal Cognitive Assessment: Establishing a Cutoff for Normative Data From a Cross-Sectional Study
Bibliographic record
Abstract
OBJECTIVE: Compare a telephone version and full version of the Montreal Cognitive Assessment (MoCA). METHODS: Cross-sectional analysis of a prospective study. A 20-point telephone version of MoCA (Tele-MoCA) was compared to the Full-MoCA and Mini Mental State Examination. RESULTS: Total of 140 participants enrolled. Mean scores for language were significantly lower with Tele-MoCA than with Full-MoCA (P = .003). Mean Tele-MoCA scores were significantly higher for participants with over 12 years of education (P < .001). Cutoff score of 17 for the Tele-MoCA yielded good specificity (82.2%) and negative predictive value (84.4%), while sensitivity was low (18.2%). CONCLUSIONS: Remote screening of cognition with a 20-point Tele-MoCA is as specific for defining normal cognition as the Full-MoCA. This study shows that telephone evaluation is adequate for virtual cognitive screening. Our sample did not allow accurate assessment of sensitivity for Tele-MoCA in detecting MCI or dementia. Further studies with representative populations are needed to establish sensitivity.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".