Validity of the Mini‐Mental State Examination and the Montreal Cognitive Assessment in the Prediction of Driving Test Outcome
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To evaluate the effectiveness of two cognitive screening measures, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), in predicting driving test outcome for individuals with and without cognitive impairment. DESIGN: Retrospective cohort study. SETTING: A clinical driving evaluation program at a teaching hospital in the United States. PARTICIPANTS: Adult drivers who underwent assessment with the MMSE and MoCA as part of a comprehensive driving evaluation between 2010 and 2014 (N=92). MEASUREMENTS: MMSE and MoCA total scores were independent variables. The outcome measure was performance on a standardized road test. RESULTS: A preestablished diagnosis of cognitive impairment enhanced the validity of cognitive screening measures in the identification of at-risk drivers. In individuals with cognitive impairment there was a significant relationship between MoCA score and on-road outcome. Specifically, an individual was 1.36 times as likely to fail the road test with each 1-point decrease in MoCA score. No such relationship was detected in those without a diagnosis of cognitive impairment. CONCLUSION: For individuals who have not been diagnosed with cognitive impairment, neither the MMSE nor the MoCA can be reliably used as an indicator of driving risk, but for individuals with a preestablished diagnosis of cognitive impairment, the MoCA is a useful tool in this regard. A score on the MoCA of 18 or less should raise concerns about driving safety.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it