Comparison of an Electronic and Paper-based Montreal Cognitive Assessment Tool
Bibliographic record
Abstract
This pilot study compared a novel electronic Montreal Cognitive Assessment (eMoCA) tool to the original paper-based MoCA. Potential participants were approached at primary care practices, a geriatric day hospital, and a university campus. Each of the 401 participants were randomly assigned to either the eMoCA (N=182) or MoCA (N=219). Scores were adjusted by self-reported demographic and health information using regression analysis. The difference in average scores (26.21±3.11 for the MoCA group and 24.84±4.21 for the eMoCA group) was found to be statistically significant. Controlling for the effect of potential covariate factors with regression analyses, the adjusted difference is -0.90 (95% confidence interval, -1.45 to -0.35). This difference may be due to factors related to use of the electronic device or software usability. However, the standardized, self-administered eMoCA may offer an opportunity for health systems to screen for early changes in cognitive function in primary care settings and offer greater access to assessment for rural or remote communities. Population-level research may be required to identify whether the score difference between test versions requires a downward adjustment to the eMoCA score taken as indicative of cognitive impairment.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".