Sherrilene Classen

Practice Parameter update: Evaluation and management of driving risk in dementia Report of the Quality Standards Subcommittee of the American Academy of Neurology

Objective: To review the evidence regarding the usefulness of patient demographic characteristics, driving history, and cognitive testing in predicting driving capability among patients with dementia and to determine the efficacy of driving risk reduction strategies. Methods: Systematic review of the literature using the American Academy of Neurologys evidence-based methods. Recommendations: For patients with dementia, consider the following characteristics useful for identifying patients at increased risk for unsafe driving: the Clinical Dementia Rating scale (Level A), a caregivers rating of a patients driving ability as marginal or unsafe (Level B), a history of crashes or traffic citations (Level C), reduced driving mileage or self-reported situational avoidance (Level C), Mini-Mental State Examination scores of 24 or less (Level C), and aggressive or impulsive personality characteristics (Level C). Consider the following characteristics not useful for identifying patients at increased risk for unsafe driving: a patients self-rating of safe driving ability (Level A) and lack of situational avoidance (Level C). There is insufficient evidence to support or refute the benefit of neuropsychological testing, after controlling for the presence and severity of dementia, or interventional strategies for drivers with dementia (Level U).

Comparison of Driving Errors Between On-the-Road and Simulated Driving Assessment: A Validation Study

Objective: Driving simulation provides a convenient and safe method for assessing driving behaviors. Many authors, however, agree that validation is a key component of any study that utilizes simulators to assess driving performance. The purpose of this study was to test driver response validity by discerning whether behavioral responses of drivers, as expressed by type and number of errors, are similar on the road and in the simulator. Methods: We replicated real-world intersections in our driving simulator (STISIM M500W; Systems Technology Inc.) and assessed the number and type of driving errors committed by the same 39 participants while negotiating a right and a left turn both on the road and in the simulator. Results: We found no significant interactions between the type of vehicle (road vs. simulator) and the type of turn (right versus left) for any of the driving errors, indicating that the same trends exist between driving errors made on the road and in the simulator and thus suggesting relative validity of the simulator. We also found no significant differences between the road and the simulator for lane maintenance, adjustment to stimuli, and visual scanning errors, indicating absolute validity for these types of errors. Conclusions: The findings suggest early support for external validity for our driving simulator, indicating that the results of assessing driving errors when negotiating turns in the simulator can be generalized or transferred to the road under the same testing conditions. A follow-up study with larger sample size is needed to establish whether driving performance in the simulator is predictive of driving performance on the road.

Parkinson disease and driving An evidence-based review

ABSTRACT The growing literature on driving in Parkinson disease (PD) has shown that driving is impaired in PD compared to healthy comparison drivers. PD is a complex neurodegenerative disorder leading to motor, cognitive, and visual impairments, all of which can affect fitness to drive. In this review, we examined studies of driving performance (on-road tests and simulators) in PD for outcome measures and their predictors. We searched through various databases and found 25 (of 99) primary studies, all published in English. Using the American Academy of Neurology criteria, a study class of evidence was assigned (I–IV, I indicating the highest level of evidence) and recommendations were made (Level A: predictive or not; B: probably predictive or not; C: possibly predictive or not; U: no recommendations). From available Class II and III studies, we identified various cognitive, visual, and motor measures that met different levels of evidence (usually Level B or C) with respect to predicting on-road and simulated driving performance. Class I studies reporting Level A recommendations for definitive predictors of driving performance in drivers with PD are needed by policy makers and clinicians to develop evidence-based guidelines.

Useful Field of View as a Reliable Screening Measure of Driving Performance in People With Parkinson's Disease: Results of a Pilot Study

Purpose: To determine the correlations of the Useful Field of View (UFOV), compared to other clinical tests of Parkinsons disease (PD); vision; and cognition with measures of on-road driving assessments and to quantify the UFOVs ability to indicate passing/failing an on-road test in people with PD. Methods: Nineteen randomly selected people with idiopathic PD, mean age = 74.8 (6.1), 14 (73.7%) men, 18 (94.7%) Caucasians, were age-matched to 104 controls without PD. The controls had a mean age of 75.4 (6.4), 59 (56.7%) men, 96 (92.3%) Caucasians. Both groups were referred for a driving evaluation after institutional review board approval. Results: Compared to neuropsychological and clinical tests of vision and cognition, the UFOV showed the strongest correlations (r > .75, p < 0.05) with measures of failing a standardized road test and number of driving errors. Among PD patients, the UFOV Risk Index score of 3 (range 1–5) was established as the optimal cutoff value for passing the on-road test, with sensitivity 87 percent and specificity 82 percent, AUC = 92 percent (SE 0.61, p = .002). Similarly, the UFOV 2 (divided attention) optimum cutoff value is 223 ms (range 16–500 ms), sensitivity 87.5 percent, specificity 81.8 percent, AUC = 91 percent (SE 0.73, p = .003). The UFOV 3 (selected attention) optimal cutoff value is 273 ms (range 16–500 ms), sensitivity 75 percent, specificity 72.7 percent, AUC = 87 percent (SE 0.81, p = .007). Conclusion: In this pilot study among PD patients, the UFOV may be a superior screening measure (compared to other measures of disease, cognition, and vision) for predicting on-road driving performance but its rigor must be verified in a larger sample of people with PD.

Clinical Predictors of Older Driver Performance on a Standardized Road Test

Objectives. To determine the relationship between clinical variables (demographics, cognitive testing, comorbidities, and medications) and failing a standardized road test in older adults. Methods. Analysis of on-the road studies performed in optimal weather conditions, between January 1, 2005, and May 1, 2007. The standardized testing was held at the National Older Driver Research and Training Center (NODRTC), Florida, and included 127 adults aged 65 and older with current driver licenses, recruited by advertisement from the Gainesville, Florida, community. Measurements consist of demographics, self-reported medications and medical conditions, cognitive testing including Trail Making Part B, global rating score (pass/fail), and driver maneuver score (0–273, with 273 indicating perfect driving or zero errors). Results. A total of 127 older adults completed the protocol. Mean age was 74.8 years (SD = 6.3); 46.5% females. Mean time for Trail Making Part B was 114.3 seconds (SD of 83). Among the 127 drivers, the mean Sum of Maneuvers Score was 238.9 (SD of 25.0) and 24 (19%) failed the driver test. Odds ratio estimates for failing the test included advanced age (6.7, 95% CI 2.2 to 19.8), presence of a neurological disease (2.8, 95% CI 1.2 to 6.5), and prolonged time to complete the Trail Making Part B cognitive test (2.5, 95% CI 1.0 to 5.9). Conversely, odds ratio estimates lowering the risk of failure included taking a non-diabetic hormonal medications (e.g., thyroid and estrogen drugs; 0.3, 95% CI .09 to 0.7) and having a musculoskeletal diagnosis (0.3, 95% CI .1 to 0.7). Conclusions. To our knowledge, this is the first study to examine the medical predictors of failing a standardized road test. Advanced age and prolonged time on Trail Making Part B were the two major predictors of test failure and a lower Sum of Maneuvers Score. Our study also found that having a neurological diagnosis (primarily cerebrovascular and Parkinsons disease) predicted test failure. Medications from neurological class also predicted a lower Sum of Maneuvers Score. Further study needs to be done to explain the apparent protective effect of musculoskeletal conditions and hormonal medications.

The Impact of Roadway Intersection Design on Driving Performance of Young and Senior Adults

Objective. To test the effectiveness of the FHWA guidelines for intersection design. Methods. In an experimental design we used kinematics measures from an instrumented vehicle and behavioral (error) data collected during on-road evaluations to quantify the effects of improved versus unimproved intersections (turn phase) and to determine if these intersections were safer (vehicular stability and driver confidence) for both older (65–85 years) and younger (25 –45) drivers. We analyzed kinematics data with a 2 × 2 repeated measures ANOVA and behavioral data (driving errors yes, no) with Wilcoxon sign rank test (within subject variable: intersection improved vs. unimproved) and Wilcoxon rank sum test (between subject variable: age, younger vs. older driver). Results. Kinematics measures (turn phase), showed three maneuvers had statistically significantly lesser side forces (measured by lateral acceleration and combined acceleration) for the improved conditions, and four maneuvers had statistically significantly greater, yet appropriate, speeds for the improved conditions. Lesser side forces indicated improved lateral stability and increased speed indicated greater confidence. Drivers made fewer errors on two of the improved intersections; but across all maneuvers, older drivers appeared to make fewer errors on the improved intersections. Conclusions. This study brings empirical intersection design and safety information for engineers and city planners to consider as they plan and develop intersections. Future researchers may want to use the conceptual and analytical framework of this study to determine the effectiveness of other FHWA guidelines. Given that these intersection design guidelines benefit younger and older drivers alike, plausible policy-making opportunities are opened in the design of safe roadway systems, to benefit the broad spectrum of adult drivers.

Evidence-Based Review on Interventions and Determinants of Driving Performance in Teens with Attention Deficit Hyperactivity Disorder or Autism Spectrum Disorder

Objective: We conducted an evidence-based review of intervention studies and predictor studies related to driving outcomes in teens with attention deficit–hyperactivity disorder (ADHD) or autism spectrum disorder (ASD). Methods: Ten primary studies were classified using the American Academy of Neurologys criteria (class I–IV, I = highest level of evidence). We provided recommendations including Level A: intervention/factors are effective/predictive or not; Level B: probably effective/predictive or not; Level C: possibly effective/predictive or not; Level U: no recommendations. Results: For the intervention studies we identified 1 Class II and 1 Class III study; for predictor studies, we identified 7 ADHD studies consisting of 1 Class II and 6 Class III studies. Only 1 Class III ASD study was found. In synopsizing the evidence, the following recommendations are made for the intervention studies pertaining to on-road performance in teens with ADHD: a multimodal intervention is possibly effective in improving driving performance (Level C); stimulants possibly do not affect driving negatively (Level C); no recommendations can be made for hazard perception training in ADHD or ASD (Level U). Consider the following recommendations useful for simulated driving performance: Stimulants possibly improve driving performance (Level C); ADHD diagnosis and being unmedicated possibly worsen driving performance (Level C); no recommendations for driving in low-stimulus conditions (Level U). From self-/proxy report, no recommendations can be made related to gender or ADHD subtype affecting adverse driving outcomes (Level U). Conclusion: Class I studies with Level A recommendations, currently lacking in the literature, are urgently needed to make clear the mechanism underlying driving performance outcomes in ADHD and ASD. Supplementary materials are available for this article. Go to the publishers online edition of Traffic Injury Prevention for the following supplemental resource: Table: Evidence-based Synopsis of ADHD, ASD and Driving Performance: Variables, Sample, Findings & Rationale

Evidence-based review on epilepsy and driving.

OBJECTIVE The aim of this study was to synopsize the evidence on predictors of crashes and driving status in people with epilepsy (PWE). METHODS Evidence-based review of the published English literature was the method used. We searched various databases and extracted data from 16 (of 77) primary studies. On the basis of American Academy of Neurology criteria, we assigned each study a class of evidence (I-IV, where I indicates the highest level of evidence) and made recommendations (Level A: predictive or not; Level B: probably predictive or not; Level C: possibly predictive or not; Level U: no recommendations). RESULTS For PWE, the following characteristics are considered useful: For identifying crash risk, epilepsy (level B) and short seizure-free intervals (≥3 months) (Level C) are not predictive of motor vehicle crash (MVC). For self/proxy-reported crash risk, epilepsy surgery (Level B), seizure-free intervals (6-12 months) (Level B), few prior non-seizure-related crashes (Level B), and regular antiepileptic drug adjustments (Level B) are protective against crashes; seizures contribute to MVCs (Level C); mandatory reporting does not contribute to reduced crashes (Level C). No recommendations for reliable auras, age, and gender (Level U), as data are inadequate to make determinations. For self-reported driving or licensure status, employment and epilepsy surgery are predictive of driving (Level C); there are no recommendations for antiepileptic drug use, self-reported driving, gender, age, receiving employment benefits, or having reduced seizure frequency (Level U). CONCLUSION Limitations, that is, heterogeneity among studies, examining the English literature from 1994 to 2010, must be considered. Yet, this is the first evidence-based review to synopsize the current PWE and driving literature and to provide recommendation(s) to clinicians and policy makers. Class I studies, matched for age and gender, yielding Level A recommendations are urgently needed to define the risks, benefits, and causal factors underlying driving performance issues in PWE.

The Impact of Intersection Design on Simulated Driving Performance of Young and Senior Adults

Purpose. The Federal Highway Administration (FHWA) proposed guidelines for highway design to increase the safe driving ability of older drivers; however, little empirical evidence exists to support the effectiveness of these guidelines. The purpose of this study was to investigate the effects of implementing these guidelines (in 4 pairs of intersections) on safe driving performance of older and younger drivers using a high-fidelity driving simulator. Design and Methods. We replicated four intersection pairs (improved versus unimproved) in a high-fidelity, virtual reality driving simulator. Simulator scenarios were created from actual road locations, replicating road geometrics and traffic control devices. The simulators controls were integrated with an actual vehicle to make the driving experience as realistic as possible. Kinematic measures were obtained from the simulator in conjunction with driving errors recorded by trained driving evaluators sitting in the cab of the car. Thirty-nine subjects, 19 younger and 20 older adults, participated in the study. Results. For the kinematic data we found greater lateral control, as indicated by significantly smaller maximum yaw during the turn phase, at all of the improved intersections when compared to the unimproved intersections. We found some significant age differences, but mostly in only one of the intersection-pairs. For the behavioral data, there were significant differences in driving errors between improved and unimproved intersections in two intersection-pairs; however, there were no significant differences in driving errors between the older and younger drivers. Implications. The findings suggest that both young and older drivers may benefit from roadways with safety features recommended by the FHWA guidelines as indicated by the increased lateral control of the vehicle when negotiating these intersections. These findings generate critical information for those involved in the design of roadway systems.

Predicting older driver on-road performance by means of the useful field of view and trail making test part B

The Useful Field of View(®) (UFOV) and Trail Making Test Part B (Trails B) are measures of divided attention. We determined which measure was more accurate in predicting on-road outcomes among drivers (N = 198, mean age = 73.86, standard deviation = 6.05). Receiver operating characteristic curves for the UFOV (Risk Index [RI] and Subtests 1-3) and Trails B significantly predicted on-road outcomes. Contrasting Trails B with the UFOV RI and subtests, the only difference was found between the UFOV RI and Trails B, indicating the UFOV RI was the best predictor of on-road outcomes. Misclassifications of drivers totaled 28 for the UFOV RI, 62 for Trails B, and 58 for UFOV Subtest 2. The UFOV RI is a superior test in predicting on-road outcomes, but the Trails B has acceptable accuracy and is comparable to the other UFOV subtests.