Postural/Gait and cognitive function as predictors of driving performance in Parkinson's disease.

BACKGROUND: The primary influence of motor symptoms on driving performance remains unclear due to the inconsistent use of various motor rating scales used in prior studies. OBJECTIVE: This study aimed to determine which of three measures utilized in PD, the Unified Parkinson's Disease Rating Scale (UPDRS) motor section; the Modified Hoehn and Yahr; and the Rapid Paced Walk Test would best predict pass/fail outcomes on a road test in a sample of PD drivers. METHODS: All participants (N = 55; 79% men) completed a road test. Receiver Operating Characteristics were then contrasted for all subjects based on assessments from all three disease severity indices. MMSE scores were then modelled with significant disease severity measures (if any) to determine if the predictive accuracy could be improved. RESULTS: The Rapid Paced Walk Test and the Modified Hoehn & Yahr both predicted pass/fail outcomes on the road test (Area under the curve of 0.73 and 0.82, respectively). UPDRS motor scores, however, did not predict safe driving. When optimal cut-off points on the Modified Hoehn & Yahr (≥ 2.5) and Rapid Paced Walk Test (>6.22 seconds) were modelled with MMSE scores indicative of mild cognitive impairment (<27), the model accurately classified 92% and 100% as failing the road test, respectively. CONCLUSION: Although the Rapid Paced Walk Test had a slight advantage in differentiating between pass/fail outcomes compared to the Modified Hoehn & Yahr, both tests alone cannot be used in isolation to predict driving safety. Predictive accuracy can be improved using both select cut-off points on the Modified Hoehn & Yahr and Rapid Paced Walk test with MMSE scores in PD drivers. Though these findings are useful, an on-road test is still the gold standard, and screening should always be followed by formal testing.

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.

Driving performance and behaviors: a comparison of gender differences in Parkinson's disease.

OBJECTIVE: The primary objective of this study was to determine gender differences by comparing self-reported driving behaviors, clinical tests, and on-road driving performance in a cohort of men and women drivers with Parkinson's disease (PD). METHODS: In this prospective observational study, we analyzed data of a convenience sample of 63 men (mean age = 70.9 ± 6.6 years) and 21 women (mean age 67.1 ± 7.3 years) with diagnosed PD. All participants underwent a comprehensive driving evaluation by a certified driving rehabilitation specialist. RESULTS: On average, both men and women were active drivers (driving ∼4.6 times/week). A substantial proportion of both groups avoided driving at night (40% of men versus 46% of women), during rush hour, and in heavy traffic (36% of men versus 57% of women), although the differences were not significant. Both groups reported some avoidance behaviors: making left-hand turns (9.7% men versus 9.5% women), driving in the rain (12.9% men versus 19.0% women), or on the interstate/highway (14.3% men versus 7.7% women). With respect to driving performance, both groups were equally likely to fail the on-road test (42.6% men versus 42.9% women). Although men committed slightly more total driving errors compared to women, the differences were not statistically significant. Specific driving errors also did not differ by gender. Controlling for gender and disease severity, age was an independent predictor of total driving errors in men but not in women. Additionally, a cut-point of ≥2.5 on the modified Hoehn and Yahr was predictive of pass-fail outcomes in men when controlling for age. CONCLUSIONS: Our study shows preliminary evidence that few gender differences exist with respect to driving errors and overall driving performance. Future studies should better balance gender distribution by age in PD driving studies to determine whether there are indeed differences in driving performance between men and women.

Gender differences among older drivers in a comprehensive driving evaluation.

Research studies typically consider older drivers as a homogenous group and do not report on the influence of gender on driving performance. Prior studies report that females are over-represented in crashes compared to males, caused by errors of yielding, gap acceptance, and speed regulation, all of which are assessed in a comprehensive driving evaluation (CDE). In a sample of 294 community dwelling older drivers, we examined and compared specific and total driving errors of both genders, and determined predictors of gender-specific driving errors and pass/fail outcomes who completed a CDE assessed by a certified driving rehabilitation specialist. No differences in specific or total number of driving errors on the CDE were found between older males (Mean age 73.4±6.0) and older females (Mean age 73.8±5.7). Education, days of driving, Useful Field of View™ (UFOV), Rapid Paced Walk Test (RPW) and the Mini-Mental State Exam (MMSE) were all independent predictors of failing a road test for both genders (p<0.05). However, older females were 22% less likely than older males to fail an on-road test. Within group comparisons showed that older males and females >75 years were 3.2 and 3.5 times more likely to fail the on-road test compared to younger males and females (aged between 63 and 75), respectively. Our findings suggest that focusing on older old (75+) and old-old (85+) age groups may be more efficient for future investigations of driving performance.

Concurrent criterion validity of the safe driving behavior measure: a predictor of on-road driving outcomes.

We determined the concurrent criterion validity of the Safe Driving Behavior Measure (SDBM) for on-road outcomes (passing or failing the on-road test as determined by a certified driving rehabilitation specialist) among older drivers and their family members-caregivers. On the basis of ratings from 168 older drivers and 168 family members-caregivers, we calculated receiver operating characteristic curves. The drivers' area under the curve (AUC) was .620 (95% confidence interval [CI] = .514-.725, p = .043). The family members-caregivers' AUC was .726 (95% CI = .622-.829, p ≤ .01). Older drivers' ratings showed statistically significant yet poor concurrent criterion validity, but family members-caregivers' ratings showed good concurrent criterion validity for the criterion on-road driving test. Continuing research with a more representative sample is being pursued to confirm the SDBM's concurrent criterion validity. This screening tool may be useful for generalist practitioners to use in making decisions regarding driving.

Exploratory pilot study of driving perceptions among OIF/OEF Veterans with mTBI and PTSD.

Veterans of Iraq and Afghanistan may experience driving-related challenges postdeployment, including more at-fault crashes. Causes may include defensive driving tactics learned for combat zones and consequences of traumatic brain injuries (TBIs) and posttraumatic stress disorder (PTSD). Tailoring driver interventions to meet Veterans' needs requires an understanding of their driving perceptions. We explored the driving perceptions of five combat Veterans (4 men, 1 woman) with mild TBI and PTSD using grounded theory methods. Veterans participated in single, semistructured interviews during a comprehensive driving evaluation. Interviews were digitally recorded, transcribed verbatim, verified, and imported into NVivo 8 software for coding and analysis. Veterans were insightful about driving and identified specific environmental triggers for anxious driving, speeding, and road rage. Veterans used strategies to moderate driving behaviors, but continued to drive aggressively. Themes were used to develop a conceptual framework of driving postdeployment, laying the foundation for intervention studies.

MMSE as a predictor of on-road driving performance in community dwelling older drivers.

Screening tools such as the MMSE have been used extensively in driving research studies to determine mild cognitive impairment or dementia. While some studies have shown the MMSE to correlate with driving performance, few studies have shown the predictive validity of the MMSE in determining on-road performance. In a sample of 168 community dwelling older adults, including 20 with Parkinson's disease (PD), the primary objective was to determine the validity of the MMSE to predict pass/fail outcomes of an on-road driving test using receiver operating characteristics curves. The area under the curve (AUC), an index of discriminability, for the total sample was .654, 95% CI=0.536-0.772, p=.009. Meanwhile, the AUC for the PD group was 0.791, 95% CI=0.587-0.996, p=.036. The total sample showed statistically significant yet poor predictive validity. However, the PD group showed statistically significant and good predictive validity of the MMSE to predict pass/fail outcomes on the road test, but caution is warranted as the confidence intervals are wide (due to small sample) and the positive and negative predictive values are less than desirable due to the associated error. The findings show that using the current cut-off point of ≤24 on the MMSE is not adequately sensitive to predict on-road performance in both community dwelling older drivers and in drivers with PD. This study offers strong evidence to support the current best practice of not using the MMSE in isolation to predict on-road performance.

Rater reliability and rater effects of the Safe Driving Behavior Measure.

We used Safe Driving Behavior Measure (SDBM) to determine rater reliability and rater effects (erratic responses, severity, leniency) in three rater groups: 80 older drivers (mean age = 73.26, standard deviation = 5.30), 80 family members or caregivers (age range = 20-85 yr), and two driving evaluators. Rater agreement was significant only between the evaluators and the family members or caregivers. Participants rated driving ability without erratic effects. We observed an overall rater effect only between the evaluator and family members or caregivers, with the evaluators being the more severe rater group. Training family members or caregivers to rate driving behaviors more consistently with the evaluator's ratings may enhance the SDBM's usability and provide a role for occupational therapists to interpret proxy reports as an entry point for logical and efficient driving safety interventions.

Psychometrics of the self-report safe driving behavior measure for older adults.

We investigated the psychometric properties of the 68-item Safe Driving Behavior Measure (SDBM) with 80 older drivers, 80 caregivers, and 2 evaluators from two sites. Using Rasch analysis, we examined unidimensionality and local dependence; rating scale; item- and person-level psychometrics; and item hierarchy of older drivers, caregivers, and driving evaluators who had completed the SDBM. The evidence suggested the SDBM is unidimensional, but pairs of items showed local dependency. Across the three rater groups, the data showed good person (≥3.4) and item (≥3.6) separation as well as good person (≥.93) and item reliability (≥.92). Cronbach's α was ≥.96, and few items were misfitting. Some of the items did not follow the hypothesized order of item difficulty. The SDBM classified the older drivers into six ability levels, but to fully calibrate the instrument it must be refined in terms of its items (e.g., item exclusion) and then tested among participants of lesser ability.

Simulated driving performance of combat veterans with mild tramatic brain injury and posttraumatic stress disorder: a pilot study.

OBJECTIVE: We determined differences in driving errors between combat veterans with mild traumatic brain injury and posttraumatic stress disorder and healthy control participants. METHOD: We compared 18 postdeployed combat veterans with 20 control participants on drivingerrors in a driving simulator. RESULTS: Combat veterans were more likely to be male; were younger; and had more racial diversity, less formal education, and lower cognitive scores than control participants. Control participants made more signaling errors (t [19] = -2.138, p = .046, SE = 0.395), but combat veterans made more overspeeding (t [17.3] = 4.095, p = .001, SE = 0.708) and adjustment-to-stimuli (t [17] = 2.380, p = .029, SE = 0.140) errors. Young age was related to overspeeding. CONCLUSION: Combat veterans made more critical driving errors than did control participants. Such errors made on the road may lead to crashes or injuries. Although limited in generalizability, these findings provide early support for developing safe driving interventions for combat veterans.

Focus group findings for the self-report safe driving behaviour measure.

BACKGROUND: Older adults, family members, and professionals may benefit from a safe driving behaviour self-/proxy-report. PURPOSE: During development of the Safe Driving Behavior Measure (SDBM), we conducted focus groups to (1) generate items based on respondents' driving experiences, and (2) obtain SDBM item-refinement feedback. METHODS: Twenty-three older drivers (mean age 70.5, SD = 4.5) and eight family members (mean age 50, SD = 20) from Ontario and Florida described safe driving behaviour (Focus Groups 1 and 2) and critiqued the SDBM (Focus Group 3). We coded responses using content and thematic analyses. FINDINGS: Findings from Focus Groups 1 and 2 generated 23 themes (e.g., others' erratic driving) leading to 16 new items (e.g., avoiding collisions). Focus Group 3 findings generated 13 item revisions (e.g., indicating number of highway lanes). Implications. Using focus group findings, we created a version of the SDBM for future testing of construct validity with older drivers.

Traffic violations versus driving errors of older adults: informing clinical practice.

Certain driving errors are predictive of crashes, but whether the type of errors evaluated during on-road assessment is similar to traffic violations that are associated with crashes is unknown. Using the crash data of 5,345 older drivers and expert reviewers, we constructed a violation-to-error classification based on rater agreement. We examined the effects of predictor variables on crash-related injuries by risk probability using logistic regression. Drivers' mean age was 76.08 (standard deviation = 7.10); 45.7% were women. Of drivers, 44.6% sustained crash-related injuries, and female drivers had a higher injury probability (44%) than male drivers (29%). Lane maintenance, yielding, and gap acceptance errors predicted crash-related injuries with almost 50% probability; speed regulation (34%), vehicle positioning (25%), and adjustment-to-stimuli (21%) errors predicted crash-related injuries to a lesser degree. We suggest injury prevention strategies for clinicians and researchers to consider for older drivers, especially older women.

Validity and critical driving errors of on-road assessment for older drivers.

OBJECTIVES: We examined the validity of our on-road driving assessment to quantify its outcomes. METHOD: Older drivers (N = 127) completed a driving assessment on a standardized road course. Measurements included demographics, driving errors, and driving test outcomes; a categorical global rating score (pass-fail); and the sum of maneuvers (SMS) score (0-273). RESULTS: There were significant differences in the SMS (F = 29.9, df = 1, p < or = .001) between drivers who passed the driving test and those who failed. The SMS cutoff value of 230 points was established as the criterion because it yielded the most optimal combination of sensitivity (0.91) and specificity (0.87). The strongest predictors of failure were adjustment to stimuli and lane maintenance errors. CONCLUSION: The SMS differentiated between passing and failing drivers and can be used to inform clinical decision making.

Item development and validity testing for a self- and proxy report: the safe driving behavior measure.

OBJECTIVE: We report on item development and validity testing of a self-report older adult safe driving behaviors measure (SDBM). METHOD: On the basis of theoretical frameworks (Precede-Proceed Model of Health Promotion, Haddon's matrix, and Michon's model), existing driving measures, and previous research and guided by measurement theory, we developed items capturing safe driving behavior. Item development was further informed by focus groups. We established face validity using peer reviewers and content validity using expert raters. RESULTS: Peer review indicated acceptable face validity. Initial expert rater review yielded a scale content validity index (CVI) rating of 0.78, with 44 of 60 items rated > or = 0.75. Sixteen unacceptable items (< or = 0.5) required major revision or deletion. The next CVI scale average was 0.84, indicating acceptable content validity. CONCLUSION: The SDBM has relevance as a self-report to rate older drivers. Future pilot testing of the SDBM comparing results with on-road testing will define criterion validity.

Traumatic brain injury and driving assessment: an evidence-based literature review.

OBJECTIVE: We conducted a literature review of assessment tools predicting driving performance for people with traumatic brain injury (TBI). METHOD: Data sources were Web of Science, EBSCOhost, PubMed, and recently published literature from experts and team members not yet catalogued in the databases. We used the American Academy of Neurology's classification criteria to extract data from 13 studies, and we assigned a class (I-IV, with I being the highest level of evidence) to each study. We grouped primary studies into categories of driving assessment (neuropsychological; simulator; off-road; self-report, other report, and postinjury disability status; and comprehensive driving evaluation) and synthesized the predictability of these tools as it relates to driving performance for people with TBI. CONCLUSIONS: To assist clinicians and researchers in making decisions regarding testing the driving performance of people with TBI, we provide recommendations for neuropsychological tests; off-road tests; self-report, other report, and postinjury disability status; and comprehensive driving evaluation.

Predictability of clinical assessments for driving performance.

PROBLEM: As the number of older drivers grows, it is increasingly important to accurately identify at-risk drivers. This study tested clinical assessments predictive of real-time driving performance. METHOD: Selected assessment tools considered important in the identification of at-risk older drivers represented the domains of vision, cognition, motor performance, and driving knowledge. Participants were administered the battery of assessments followed by an on-road test. A univariate analysis was conducted to identify significant factors (<.05) to be included in a multivariate regression model. RESULTS: Assessments identified as independently associated with driving performance in the regression model included: FACTTM Contrast sensitivity slide-B, Rapid Pace Walk, UFOV rating, and MMSE total score. DISCUSSION: The domains of vision, cognitive, and motor performance were represented in the predictive model. SUMMARY: Due to the dynamic nature of the driving task, it is not likely that a single assessment tool will identify at risk drivers. IMPACT ON INDUSTRY: By standardizing the selection of clinical assessments used in driving evaluations, practitioners should be able to provide services more efficiently, more objectively, and more accurately to identify at-risk drivers.