Objectives: To relate the standardized road test to video recordings of naturalistic driving in older adults with a range of cognitive impairment. Design: Cross‐sectional observational study. Setting: Academic medical center memory disorders clinic. Participants: One hundred three older drivers (44 healthy, 59 with cognitive impairment) who passed a road test. Measurements: Error rate and global ratings of safety (pass with and without recommendations, marginal with restrictions or training, or fail) made by a professional driving instructor. Results: There was fair agreement between global ratings on the road test and naturalistic driving. More errors were detected in the naturalistic environment, but this did not affect global ratings. Error scores between settings were significantly correlated, and the types of errors made were similar. History of crashes corrected for miles driven per week was related to road test error scores but not naturalistic driving error scores. Global cognition ( M ini‐ M ental State E xamination) was correlated with road test and naturalistic driving errors. In healthy older adults, younger age was correlated with fewer errors on the road test and more errors in naturalistic driving. Conclusion: Road test performance is a reasonable proxy for estimating fitness to drive in older individuals' typical driving environments, but differences between performance assessed using these two methods remain poorly understood and deserve further study.

Clock drawing is recommended by medical and transportation authorities as a screening test for unsafe drivers. The objective of the present study was to assess the usefulness of different clock drawing systems as screening measures of driving performance in 122 healthy and cognitively impaired older drivers. Clock drawing was measured using four different scoring systems. Driving outcomes included global ratings of safety and the error rate on a standardized on-road test. Findings revealed that clock drawing was significantly correlated with the driving score on the road test for each of the scoring systems. However, receiver operator curve analyses showed limited clinical utility for clock drawing as a screening instrument for impaired on-road driving performance with the area under the curve ranging from 0.53 to 0.61. Results from this study indicate that clock drawing has limited utility as a solitary screening measure of on-road driving, even when considering a variety of scoring approaches.

Cognitive impairment is a significant risk factor for hazardous driving among older drivers with Alzheimer’s dementia, but little is known about how the driving behavior of mildly symptomatic compares with those in the preclinical, asymptomatic phase of Alzheimer’s disease (AD). This study utilized two in-car technologies to characterize driving behavior in symptomatic and preclinical AD. The goals of this pilot study were to (1) describe unsafe driving behaviors in individuals with symptomatic early AD using G-force triggered video capture and (2) compare the driving habits of these symptomatic AD drivers to two groups of cognitively normal drivers, those with and those without evidence of cerebral amyloidosis (CN/A+ and CN/A−) using a global positioning system (GPS) datalogger. Thirty-three drivers (aged 60+ years) were studied over 3 months. G-force triggered video events captured instances of near-misses/collisions, traffic violations, risky driver conduct, and driving fundamentals. GPS data were sampled every 30 s and all instances of speeding, hard braking, and sudden acceleration were recorded. For the early AD participants, video capture identified driving unbelted, late response, driving too fast for conditions, traffic violations, poor judgment, and not scanning intersections as the most frequently occurring safety errors. When evaluating driving using the GPS datalogger, hard breaking events occurred most frequently on a per trip basis across all three groups. The CN/A+ group had the lowest event rate across all three event types with lower instances of speeding. Slower psychomotor speed (Trail Making Part A) was associated with fewer speeding events, more hard acceleration events, and more overall events. GPS tracked instances of speeding were correlated with total number of video-captured near-collisions/collisions and driving fundamentals. Results demonstrate the utility of electronic monitoring to identify potentially unsafe driving events in symptomatic and preclinical AD. Results suggest that drivers with preclinical AD may compensate for early, subtle cognitive changes by driving more slowly and cautiously than healthy older drivers or those with cognitive impairment. Self-regulatory changes in driving behavior appear to occur in the preclinical phase of AD, but safety concerns may not arise until symptoms of cognitive impairment emerge and the ability to self-monitor declines.

Linear and nonlinear categorization rule learning was examined in patients with Huntington's disease (HD) and a group of controls using the perceptual categorization task. Participants learned to categorize simple line stimuli into 1 of 2 categories over 600 trials. In addition to traditional measures of accuracy, quantitative model-based analyses were applied to each participant's data to characterize better the nature of any observed deficits. In the linear rule condition, HD patients displayed an early-training deficit relative to controls, whereas later in training the HD patients were not statistically different from controls. In the nonlinear rule condition, HD patients displayed both an early- and late-training deficit. The quantitative model-based analyses revealed that the HD patients' deficits in the linear condition were due to an impairment in learning the experimenter-defined rule and not in applying a learned rule inconsistently. In the nonlinear condition, in contrast, the HD patients' deficits were due to an impairment in learning the experimenter-defined rule and in applying a learned rule inconsistently. Overall, these results suggest that HD can result in a deficit in learning both linear and nonlinear categorization rules.

Analyzing naturalistic driving behavior recorded with in-car cameras is an ecologically valid method for measuring driving errors, but it is time intensive and not easily applied on a large scale. This study validated a semi-automated, computerized method using archival naturalistic driving data collected for drivers with mild Alzheimer’s disease (AD; n = 44) and age-matched healthy controls (HC; n = 16). The computerized method flagged driving situations where safety concerns are most likely to occur (i.e., rapid stops, lane deviations, turns, and intersections). These driving epochs were manually reviewed and rated for error type and severity, if present. Ratings were made with a standardized scoring system adapted from DriveCam^®. The top eight error types were applied as features to train a logistic model tree classifier to predict diagnostic group. The sensitivity and specificity were compared among the event-based method, on-road test, and composite ratings of two weeks of recorded driving. The logistic model derived from the event-based method had the best overall accuracy (91.7%) and sensitivity (97.7%) and high specificity (75.0%) compared to the other methods. Review of driving situations where risk is highest appears to be a sensitive data reduction method for detecting cognitive impairment associated driving behaviors and may be a more cost-effective method for analyzing large volumes of naturalistic data.

Background: There is suggestion that self-reported depressive syndromes can independently manifest in the general population as cognitive/affective or somatic/vegetative. The Beck Depression Inventory, 2nd edition (BDI-II), a self-report measure of depressive symptoms, has been shown to support this two-factor structure. However, this finding has not been examined in an older adult sample with cognitive impairment. In order to determine whether older adults with cognitive impairments exhibit similarly independent cognitive/affective and somatic/vegetative depressive syndromes, we explored the factor structure of the BDI-II in this population.Methods: Participants were 228 older adults (mean age = 74, SD = 7.9) diagnosed with mild cognitive impairment (MCI; n = 137) or early Alzheimer's disease (n = 85), who completed the BDI-II as part of an outpatient neuropsychological evaluation. Exploratory principal component factor analysis with direct Oblimin rotation was conducted, and a two-factor solution was specified based on our theoretical conceptualization of the cognitive/affective and somatic/vegetative items from the scale.Results: The first factor represented cognitive/affective symptoms of depression (e.g. self-dislike, pessimism, worthlessness), and accounted for 36% of the variance. Adding the second factor, reflecting somatic/vegetative items (e.g. sleep and appetite changes, loss of energy), accounted for an additional 6.8% of the variance.Conclusion: Results supported the presence of two distinct depressive syndromes, cognitive/affective and somatic/vegetative symptoms. Thus, cognitively impaired older adults report mood symptoms relatively similarly to younger and midlife adults. This supports the validity of self-reported mood in this group, and the results may have implications for psychiatric treatment in this population.