Examining the relationship between cognition and driving performance in multiple sclerosis

Abstract

Objective: To identify cognitive predictors of driving performance after multiple sclerosis (MS).

Design: Prospective design examining predictive value of cognitive measures on driving performance.

Setting: All data were collected in an outpatient research setting and an outpatient driver rehabilitation program.

Participants: Participants were community-dwelling persons (N=66) with clinically defined MS (86% relapsing-remitting, 14% progressive) with a mean age of 43.47 years. All were active drivers who met vision requirements established by their respective states, and none required adaptive driving equipment.

Intervention: Not applicable.

Main outcome measures: Participants were administered a comprehensive neuropsychologic assessment and a clinical behind-the-wheel (BTW) driving evaluation. Additional measures of driving performance included history of traffic violations and collisions (since MS onset).

Results: Logistic regression indicated that information processing speed (Symbol Digit Modality Test [SDMT]) was the strongest predictor of BTW performance. A logistic regression revealed that the strongest predictors of collision and violation frequency were visuospatial learning and recall (7/24 Spatial Recall Test [SPART 7/24]).

Conclusions: These findings indicate that information processing and visuospatial skills are predictive of driving performance among persons with MS. These measures (SDMT and SPART 7/24) may serve as screening methods for identifying the potential impact of cognitive impairment on driving. Furthermore, the findings raise questions regarding the appropriateness of the BTW evaluation to evaluate driving difficulties accurately among individuals with MS.