Abiodun Emmanuel Akinwuntan

Effect of simulator training on driving after stroke : A randomized controlled trial

Background: Neurologically impaired persons seem to benefit from driving-training programs, but there is no convincing evidence to support this notion. The authors therefore investigated the effect of simulator-based training on driving after stroke. Methods: Eighty-three first-ever subacute stroke patients entered a 5-week 15-hour training program in which they were randomly allocated to either an experimental (simulator-based training) or control (driving-related cognitive tasks) group. Performance in off-road evaluations and an on-road test were used to assess the driving ability of subjects pre- and post-training. Outcome of an official predriving assessment administered 6 to 9 months poststroke was also considered. Results: Both groups significantly improved in a visual and many neuropsychological evaluations and in the on-road test after training. There were no significant differences between both groups in improvements from pre- to post-training except in the “road sign recognition test” in which the experimental subjects improved more. Significant improvements in the three-class decision (“fit to drive,” “temporarily unfit to drive,” and “unfit to drive”) were found in favor of the experimental group post-training. Academic qualification and overall disability together determined subjects that benefited most from the simulator-based driving training. Significantly more experimental subjects (73%) than control subjects (42%) passed the follow-up official predriving assessment and were legally allowed to resume driving. Conclusions: Simulator-based driving training improved driving ability, especially for well educated and less disabled stroke patients. However, the findings of the study may have been modified as a result of the large number of dropouts and the possibility of some neurologic recovery unrelated to training.

Screening for fitness to drive after stroke: A systematic review and meta-analysis

Objective: To identify the best determinants of fitness to drive after stroke, following a systematic review and meta-analysis. Methods: Twenty databases were searched, from inception until May 1, 2010. Potentially relevant studies were reviewed by 2 authors for eligibility. Methodologic quality was assessed by Newcastle-Ottawa scores. The fitness-to-drive outcome was a pass–fail decision following an on-road evaluation. Differences in off-road performance between the pass and fail groups were calculated using weighted mean effect sizes (dw). Statistical heterogeneity was determined with the I2 statistic. Random-effects models were performed when the assumption of homogeneity was not met. Cutoff scores of accurate determinants were estimated via receiver operating characteristic analyses. Results: Thirty studies were included in the systematic review and 27 in the meta-analysis. Out of 1,728 participants, 938 (54%) passed the on-road evaluation. The best determinants were Road Sign Recognition (dw 1.22; 95% confidence interval [CI] 1.01–1.44; I2, 58%), Compass (dw 1.06; 95% CI 0.74–1.39; I2, 36%), and Trail Making Test B (TMT B; dw 0.81; 95% CI 0.48–1.15; I2, 49%). Cutoff values of 8.5 points for Road Sign Recognition, 25 points for Compass, and 90 seconds for TMT B were identified to classify unsafe drivers with accuracies of 84%, 85%, and 80%, respectively. Three out of 4 studies found no increased risk of accident involvement in persons cleared to resume driving after stroke. Conclusions: The Road Sign Recognition, Compass, and TMT B are clinically administrable office-based tests that can be used to identify persons with stroke at risk of failing an on-road assessment.

Prediction of Driving After Stroke: A Prospective Study

The process of determining whether patients with stroke should drive again often involves off-road evaluations and road tests that usually take about 2 to 3 h to complete. Objectives. This prospective study sought to identify the combination of tests that best predicts fitness to drive after stroke. The main aim was to develop a short and predictive predriving assessment battery. Methods. Sixty-eight consecutive stroke patients were studied who performed a mandatory predriving assessment at the Belgian Road Safety Institute, Brussels, within 18 months. Performance in a predriving assessment included medical examination (when needed), visual and neuropsychological evaluations, and an on-road test. Based on these assessments, a physician, psychologist, and the driving safety expert who administered the tests decided if a subject was either “fit to drive,”“temporarily unfit to drive,” or “unfit to drive.” Results. Logistic regression analysis revealed a combination of visual neglect, figure of Rey, and on-road tests as the model that best predicted (R 2 = 0.73) fitness to drive after stroke. Using a discriminant function that included the 3 tests of the logistic model, the fitness to drive judgments of 59 (86.8%) subjects were correctly predicted. The sensitivity and specificity of the predictions were 79.4% and 94.1%, respectively. Conclusion. Fitness to drive after stroke can be predicted from performance on a few road-related tests with a high degree of accuracy. However, some individuals require extended assessments and further tests.

Comparison of the Effect of Two Driving Retraining Programs on On-Road Performance After Stroke:

Background. Several driving retraining programs have been developed to improve driving skills after stroke. Those programs rely on different rehabilitation concepts. Objectives. The current study sought to examine the specific carryover effect of driving skills of a comprehensive training program in a driving simulator when compared with a cognitive training program. Methods. Further analysis from a previous randomized controlled trial that investigated the effect of simulator training on driving after stroke. Forty-two participants received simulator-based driving training, whereas 41 participants received cognitive training for 15 hours. Overall performance in the on-road test and each of its 13 items were compared between groups immediately posttraining and at 6 months poststroke. Results. Generalized estimating equation analysis showed that the total score on the on-road test and each item score improved significantly over time for both groups. Those who received driving simulator training achieved better results when compared with the cognitive training group in the overall on-road score and the items of anticipation and perception of signs, visual behavior and communication, quality of traffic participation, and turning left. Most of the differences in improvement between the 2 interventions were observed at 6 months poststroke. Conclusions . Contextual training in a driving simulator appeared to be superior to cognitive training to treat impaired on-road driving skills after stroke. The effects were primarily seen in visuointegrative driving skills. Our results favor the implementation of driving simulator therapy in the conventional rehabilitation program of subacute stroke patients with mild deficits.

Driving Simulation for Evaluation and Rehabilitation of Driving After Stroke

Driving is an important activity of daily living. Loss of driving privileges can lead to depression, decreased access to medical care, and increased healthcare costs. The ability to drive is often affected after stroke. In approximately 30% of stroke survivors, it is clear from the onset that driving will no longer be possible. Approximately 33% of survivors will be able to return to driving with little or no retraining, and 35% will require driving-related rehabilitation before they can resume safe driving again. The ability to drive is not routinely evaluated after stroke, and there is no established rehabilitation program for poststroke driving. When driving evaluation does occur, it is not always clear which tests are the most salient for accurately assessing poststroke driving ability. Investigators have examined the efficacy of various methodologies to predict driving performance after stroke and have found mixed results, with each method having unique weaknesses, including poor predictive ability, poor face validity, poor sensitivity or specificity, and limited reliability. Here we review common models of driving to gain insight into why single-construct visual or cognitive off-road measures are inadequate for evaluating driving, a complex and dynamic activity that involves timely interaction of multiple motor, visual, cognitive, and perceptual skills. We also examine the potential for driving simulators to overcome the problems currently faced in the evaluation and rehabilitation of driving after stroke. Finally, we offer suggestions for the future direction of simulator-based poststroke driving evaluation and training.

Driving and off‐road impairments underlying failure on road testing in Parkinson's disease

Parkinsons disease (PD) affects driving ability. We aimed to determine the most critical impairments in specific road skills and in clinical characteristics leading to failure on a road test in PD. In this cross‐sectional study, certified driving assessment experts evaluated specific driving skills in 104 active, licensed drivers with PD using a standardized, on‐road checklist and issued a global decision of pass/fail. Participants also completed an off‐road evaluation assessing demographic features, disease characteristics, motor function, vision, and cognition. The most important driving skills and off‐road predictors of the pass/fail outcome were identified using multivariate stepwise regression analyses. Eighty‐six (65%) passed and 36 (35%) failed the on‐road driving evaluation. Persons who failed performed worse on all on‐road items. When adjusted for age and gender, poor performances on lateral positioning at low speed, speed adaptations at high speed, and left turning maneuvers yielded the best model that determined the pass/fail decision (R2 = 0.56). The fail group performed poorer on all motor, visual, and cognitive tests. Measures of visual scanning, motor severity, PD subtype, visual acuity, executive functions, and divided attention were independent predictors of pass/fail decisions in the multivariate model (R2 = 0.60). Our study demonstrated that failure on a road test in PD is determined by impairments in specific driving skills and associated with deficits in motor, visual, executive, and visuospatial functions. These findings point to specific driving and off‐road impairments that can be targeted in multimodal rehabilitation programs for drivers with PD.

Effect of Simulator Training on Fitness-to-Drive after Stroke: a 5-Year Follow-up of a Randomized Controlled Trial

Background. No long-term studies have been reported on the effect of training programs on driving after stroke. Objectives. The authors’ primary aim was to determine the effect of simulator versus cognitive rehabilitation therapy on fitness-to-drive at 5 years poststroke. A second aim was to investigate differences in clinical characteristics between stroke survivors who resumed and stopped driving. Methods. In a previously reported randomized controlled trial, 83 stroke survivors received 15 hours of simulator training (n = 42) or cognitive therapy (n = 41). In this 5-year follow-up study, 61 participants were reassessed. Fitness-to-drive decisions were obtained from medical, visual, neuropsychological, and on-road tests; 44 participants (simulator group, n = 21; cognitive group, n = 23) completed all assessments. The primary outcome measures were fitness-to-drive decision and current driving status. Results. The authors found that 5 years after stroke, 18 of 30 participants (60%) in the simulator group were considered fit to drive, compared with 15 of 31 (48%) in the cognitive group (P = .36); 34 of 61 (56%) participants were driving. Current drivers were younger (P = .04), had higher Barthel scores (P = .008), had less comorbidity (P = .01), and were less severely depressed (P = .02) than those who gave up driving. Conclusions. The advantage of simulator-based driving training over cognitive rehabilitation therapy, evident at 6 months poststroke, had faded 5 years later. Poststroke drivers were younger and less severely affected and depressed than nondrivers.

Retraining moderately impaired stroke survivors in driving-related visual attention skills.

Abstract Background: Visual inattention is a major cause of road accidents and is a problem commonly experienced after stroke. Purpose: This study investigated the effects of 2 training programs on performance in the Useful Field of View (UFOV), a validated test of driving-related visual attention skills. Method: Data from 69 first-ever, moderately impaired stroke survivors who participated in a randomized controlled trial (RCT) to determine the effects of simulator training on driving after stroke were analyzed. In addition to regular interventions at a rehabilitation center, participants received 15 hours of either simulator-based driving-related training or non–computer-based cognitive training over 5 weeks. Results: Total percentage reduction in UFOV and performance in divided and selective attention and speed of processing subtests were documented at 6 to 9 weeks (pretraining), 11 to 15 weeks (posttraining), and 6 months post stroke (follow-up). Generalized estimating equation (GEE) model revealed neither group effects nor significant interaction effects of group with time in the UFOV total score and the 3 subtests. However, there were significant within-group improvements from pre- through posttraining to follow-up for all the UFOV parameters. Post-hoc GEE analysis revealed that most improvement in both groups occurred from pre- to posttraining. Conclusion: Both training programs significantly improved visual attention skills of moderately impaired stroke survivors after 15 hours of training and retention of benefit lasted up to 6 months after stroke. Neither of the training programs was better than the other.

Predictors of driving in individuals with relapsing-remitting multiple sclerosis.

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.

Establishing an evidence-base framework for driving rehabilitation in Parkinson's disease: a systematic review of on-road driving studies

BACKGROUND Individuals with Parkinsons disease (PD) experience problems with on-road driving that can be targeted in driving rehabilitation programs. OBJECTIVE To provide a framework for driving rehabilitation in PD by identifying the critical on-road driving impairments and their associated visual, cognitive, and motor deficits. METHODS We conducted a systematic review of the literature on on-road driving and naturalistic driving practices in PD. Relevant databases including Pubmed, Medline, PsychINFO, ISI Web of Science, Cochrane library, and ClinicalTrials.gov, were reviewed using the key words Parkinsons disease, on-road driving, naturalistic driving, and their related entry words. On-road driving skills were mapped onto an existing theoretic model of operational, tactical, and strategic levels. The on-road and off-road cognitive, motor, and visual predictors of global on-road driving were summarized. RESULTS Twenty-seven studies were included. All but one study were prospective and Class II studies according to the American Academy of Neurology Classification Criteria. Participants were on average 68 years old and in the mild to moderate stages of PD. Drivers with PD were more likely to fail a driving assessment compared to age- and gender-matched controls. Compared with controls, drivers with PD experienced difficulties on all levels of driving skill. However, the compensation strategies on the strategic level showed that drivers with PD were aware of their diminished driving skills on the operational and strategic levels. Operational and tactical on-road driving skills best predicted global on-road driving. A combination of visual, cognitive, and motor deficits underlie impaired on-road driving performance in PD. CONCLUSION Driving rehabilitation strategies for individuals with PD should include training of operational and tactical driving skills or indirect comprehensive training program of visual, cognitive, and motor skills.