Predictors of driving in individuals with relapsing-remitting multiple sclerosis

Mult Scler. 2013 Mar;19(3):344-50. doi: 10.1177/1352458512451944. Epub 2012 Jul 3.

Abstract

Background: We previously reported that performance on the Stroke Driver Screening Assessment (SDSA), a battery of four cognitive tests that takes less than 30 min to administer, predicted the driving performance of participants with multiple sclerosis (MS) on a road test with 86% accuracy, 80% sensitivity, and 88% specificity.

Objectives: In this study, we further investigated if the addition of driving-related physical and visual tests and other previously identified cognitive predictors, including performance on the Useful Field of View test, will result in a better accuracy of predicting participants' on-road driving performance.

Methods: Forty-four individuals with relapsing-remitting MS (age = 46 ± 11 years, 37 females) and Expanded Disability Status Scale values between 1 and 7 were administered selected physical, visual and cognitive tests including the SDSA. The model that explained the highest variance of participants' performance on a standardized road test was identified using multiple regression analysis. A discriminant equation containing the tests included in the best model was used to predict pass or fail performance on the test.

Results: Performance on 12 cognitive and three visual tests were significantly associated with performance on the road test. Five of the tests together explained 59% of the variance and predicted the pass or fail outcome of the road test with 91% accuracy, 70% sensitivity, and 97% specificity.

Conclusion: Participants' on-road performance was more accurately predicted by the model identified in this study than using only performance on the SDSA test battery. The five psychometric/off-road tests should be used as a screening battery, after which a follow-up road test should be conducted to finally decide the fitness to drive of individuals with relapsing-remitting MS. Future studies are needed to confirm and validate the findings in this study.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Automobile Driver Examination* / statistics & numerical data
  • Automobile Driving / psychology*
  • Automobile Driving / statistics & numerical data
  • Female
  • Humans
  • Male
  • Middle Aged
  • Multiple Sclerosis, Relapsing-Remitting / physiopathology*
  • Neuropsychological Tests / standards*
  • Predictive Value of Tests
  • Psychometrics / instrumentation
  • Regression Analysis
  • Sensitivity and Specificity