Z-scores of the teachers and job consultants were negative, indicating a flat distribution, meaning that large variance was found; z-score of driving instructors was positive, indicating a pointy distribution, meaning that small variance was found (Table 1).
The driving and peripheral vision sub-scales displayed the largest declines even among patients in the early stages of POAG, with the median score for driving ability equal to 0 in the 3rd and 4th quartiles.
Results indicated that MMSE scores did not significantly differ between individuals based upon driving ability, but that CDT scores were predictive of driving impairment based upon level of impairment and whether participants were instructed to simply copy an existing clock, or construct their own according to specific directions.
An additional 150 were held in connection with traffic violations, including a score of people accused of driving without a license.
MMSE scores, driving status, and reports of driving problems were also coded for subsequent analyses.
These have included age, sex, marital status, miles driven (as reported by the driver) — and even credit scores, which can penalize those guilty of driving while poor.
Hashtags are also key indicators that drive success, with #pretty, #boy, #daily, #girl and #hair scoring higher than most in terms of driving likes.
As in previous studies that discriminated high-risk subjects and predicted future driving collisions (7, 8, 14, 17– 21), 32 we generated and analyzed a composite impaired driving score (IDS) to compare the various aspects of driving poorly.
Additionally, scores on the MMSE, CDT, and caregiver ratings of driving ability were analyzed.
Non parametric correlations (Rho Spearman) were computed between fatigue and sleepiness scores and driving performance (Inappropriate Line Crossing) in the last hour of driving for each driving sessions.
To address these concerns, this study explored the relations of patient scores on the CDT and MMSE to patient or family reports of driving problems.
