9 resultados para Older drivers

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Background/Study Context: Older drivers are at increased risk of becoming involved in car crashes. Contrary to well-studied illness-related factors contributing to crash risk, the non-illness-related factors that can influence safety of older drivers are underresearched. METHODS: Here, the authors review the literature on non-illness-related factors influencing driving in people over age 60. We identified six safety-relevant factors: road infrastructure, vehicle characteristics, traffic-related knowledge, accuracy of self-awareness, personality traits, and self-restricted driving. RESULTS: The literature suggests that vehicle preference, the quality of traffic-related knowledge, the location and time of traffic exposure, and personality traits should all be taken into account when assessing fitness-to-drive in older drivers. Studies indicate that self-rating of driving skills does not reliably predict fitness-to-drive. CONCLUSIONS: Most factors discussed are adaptable or accessible to training and collectively may have the potential to increase traffic safety for older drivers and other road users.

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In Switzerland, approximately 350,000 people aged 70 years or older own a valid driving license. By law, these drivers are medically assessed every other year, most commonly by their general practitioner, to exclude that a medical condition is interfering with their driving skills. A prerequisite for driving is the integration of high-level cognitive functions with perception and motor function. Ageing, per se, does not necessarily impair driving or increase the crash risk. However, medical conditions, such as cognitive impairment and dementia, become more prevalent with advancing age and may contribute to poor driving and an increased crash risk. The extent to which driving skills are impaired depends on the cause of dementia, disease severity, other co-morbidities and individual compensation strategies. Dementia often remains undiagnosed and therefore general practitioners (GPs) can find themselves in the difficult situation to disclose a suspicion about cognitive impairment and queries about medical fitness to drive, at the same time. In addition, the literature suggests that cognitive screening tests, most commonly used by GPs, have a limited role in judging whether an older person remains fit to drive. Further specialist assessment, for example in a memory clinic or on the road testing (ORT), may be helpful when the diagnosis or its implication for driving remain unclear. Here, we review the literature about cognition and driving, for GPs who advise older drivers who wish to continue driving.

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Intact cognitive abilities are fundamental for driving. Driving-relevant cognition may be affected in older drivers due to aging or cognitive impairment. The aim of this study was to investigate the effects of cognitive impairment on driving-relevant cognition in older persons. Performance in selective and divided attention, eye-hand-coordination, executive functions and the ability to regulate distance and speed of 18 older persons with CI-Group (cognitive impairment group) was compared to performance of older control group (18 age and gender-matched cognitively normal subjects) and young control group (18 gender-matched young subjects). The CI-Group showed poorer performance than the other two control groups in all cognitive tasks (significance level (p) < 0.001, effect size (partial η2) = 0.63). Differences between cognitively impaired and cognitively normal subjects were still significant after controlling for age (effect sizes from 0.14 to 0.28). Dual tasking affected performance of cognitively impaired subjects more than performance of the other two groups (p = 0.016, partial η2 = 0.14). Results show that cognitive impairment has age-independent detrimental effects on selective and divided attention, eye-hand-coordination, executive functions and the ability to regulate distance and speed. Largest effect sizes are found for reaction times in attention tasks.

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BACKGROUND Driving a car is a complex instrumental activity of daily living and driving performance is very sensitive to cognitive impairment. The assessment of driving-relevant cognition in older drivers is challenging and requires reliable and valid tests with good sensitivity and specificity to predict safe driving. Driving simulators can be used to test fitness to drive. Several studies have found strong correlation between driving simulator performance and on-the-road driving. However, access to driving simulators is restricted to specialists and simulators are too expensive, large, and complex to allow easy access to older drivers or physicians advising them. An easily accessible, Web-based, cognitive screening test could offer a solution to this problem. The World Wide Web allows easy dissemination of the test software and implementation of the scoring algorithm on a central server, allowing generation of a dynamically growing database with normative values and ensures that all users have access to the same up-to-date normative values. OBJECTIVE In this pilot study, we present the novel Web-based Bern Cognitive Screening Test (wBCST) and investigate whether it can predict poor simulated driving performance in healthy and cognitive-impaired participants. METHODS The wBCST performance and simulated driving performance have been analyzed in 26 healthy younger and 44 healthy older participants as well as in 10 older participants with cognitive impairment. Correlations between the two tests were calculated. Also, simulated driving performance was used to group the participants into good performers (n=70) and poor performers (n=10). A receiver-operating characteristic analysis was calculated to determine sensitivity and specificity of the wBCST in predicting simulated driving performance. RESULTS The mean wBCST score of the participants with poor simulated driving performance was reduced by 52%, compared to participants with good simulated driving performance (P<.001). The area under the receiver-operating characteristic curve was 0.80 with a 95% confidence interval 0.68-0.92. CONCLUSIONS When selecting a 75% test score as the cutoff, the novel test has 83% sensitivity, 70% specificity, and 81% efficiency, which are good values for a screening test. Overall, in this pilot study, the novel Web-based computer test appears to be a promising tool for supporting clinicians in fitness-to-drive assessments of older drivers. The Web-based distribution and scoring on a central computer will facilitate further evaluation of the novel test setup. We expect that in the near future, Web-based computer tests will become a valid and reliable tool for clinicians, for example, when assessing fitness to drive in older drivers.

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BACKGROUND: The assessment of driving-relevant cognitive functions in older drivers is a difficult challenge as there is no clear-cut dividing line between normal cognition and impaired cognition and not all cognitive functions are equally important for driving. METHODS: To support decision makers, the Bern Cognitive Screening Test (BCST) for older drivers was designed. It is a computer-assisted test battery assessing visuo-spatial attention, executive functions, eye-hand coordination, distance judgment, and speed regulation. Here we compare the performance in BCST with the performance in paper and pencil cognitive screening tests and the performance in the driving simulator testing of 41 safe drivers (without crash history) and 14 unsafe drivers (with crash history). RESULTS: Safe drivers performed better than unsafe drivers in BCST (Mann-Whitney U test: U = 125.5; p = 0.001) and in the driving simulator (Student's t-test: t(44) = -2.64, p = 0.006). No clear group differences were found in paper and pencil screening tests (p > 0.05; ns). BCST was best at identifying older unsafe drivers (sensitivity 86%; specificity 61%) and was also better tolerated than the driving simulator test with fewer dropouts. CONCLUSIONS: BCST is more accurate than paper and pencil screening tests, and better tolerated than driving simulator testing when assessing driving-relevant cognition in older drivers.

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ABSTRACT Background: Driving a car requires adapting one's behavior to current task demands taking into account one's capacities. With increasing age, driving-relevant cognitive performance may decrease, creating a need for risk-reducing behavioral adaptations. Three different kinds of behavioral adaptations are known: selection, optimization, and compensation. These can occur on the tactical and the strategic level. Risk-reducing behavioral adaptations should be considered when evaluating older drivers' traffic-related risks. Methods: A questionnaire to assess driving-related behavioral adaptations in older drivers was created. The questionnaire was administered to 61 years older (age 65-87 years; mean age = 70.2 years; SD = 5.5 years; 30 female, 31 male) and 31 younger participants (age 22-55 years; mean age = 30.5 years; SD = 6.3 years; 16 female and 15 male) to explore age and gender differences in behavioral adaptations. Results: Two factors were extracted from the questionnaire, a risk-increasing factor and a risk-reducing factor. Group comparisons revealed significantly more risk-reducing behaviors in older participants (t(84.5) = 2.21, p = 0.013) and females (t(90) = 2.52, p = 0.014) compared, respectively, to younger participants and males. No differences for the risk-increasing factor were found (p > 0.05). Conclusions: The questionnaire seems to be a useful tool to assess driving-related behavioral adaptations aimed at decreasing the risk while driving. The possibility to assess driving-related behavioral adaptations in a systematic way enables a more resource-oriented approach in the evaluation of fitness to drive in older drivers.

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BACKGROUND: Central and peripheral vision is needed for object detection. Previous research has shown that visual target detection is affected by age. In addition, light conditions also influence visual exploration. The aim of the study was to investigate the effects of age and different light conditions on visual exploration behavior and on driving performance during simulated driving. METHODS: A fixed-base simulator with 180 degree field of view was used to simulate a motorway route under daylight and night conditions to test 29 young subjects (25-40 years) and 27 older subjects (65-78 years). Drivers' eye fixations were analyzed and assigned to regions of interests (ROI) such as street, road signs, car ahead, environment, rear view mirror, side mirror left, side mirror right, incoming car, parked car, road repair. In addition, lane-keeping and driving speed were analyzed as a measure of driving performance. RESULTS: Older drivers had longer fixations on the task relevant ROI, but had a lower frequency of checking mirrors when compared to younger drivers. In both age groups, night driving led to a less fixations on the mirror. At the performance level, older drivers showed more variation in driving speed and lane-keeping behavior, which was especially prominent at night. In younger drivers, night driving had no impact on driving speed or lane-keeping behavior. CONCLUSIONS: Older drivers' visual exploration behavior are more fixed on the task relevant ROI, especially at night, when driving performance becomes more heterogeneous than in younger drivers.

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OBJECTIVE: In this article, we review the impact of vision on older people's night driving abilities. Driving is the preferred and primary mode of transport for older people. It is a complex activity where intact vision is seminal for road safety. Night driving requires mesopic rather than scotopic vision, because there is always some light available when driving at night. Scotopic refers to night vision, photopic refers to vision under well-lit conditions, and mesopic vision is a combination of photopic and scotopic vision in low but not quite dark lighting situations. With increasing age, mesopic vision decreases and glare sensitivity increases, even in the absence of ocular diseases. Because of the increasing number of elderly drivers, more drivers are affected by night vision difficulties. Vision tests, which accurately predict night driving ability, are therefore of great interest. METHODS: We reviewed existing literature on age-related influences on vision and vision tests that correlate or predict night driving ability. RESULTS: We identified several studies that investigated the relationship between vision tests and night driving. These studies found correlations between impaired mesopic vision or increased glare sensitivity and impaired night driving, but no correlation was found among other tests; for example, useful field of view or visual field. The correlation between photopic visual acuity, the most commonly used test when assessing elderly drivers, and night driving ability has not yet been fully clarified. CONCLUSIONS: Photopic visual acuity alone is not a good predictor of night driving ability. Mesopic visual acuity and glare sensitivity seem relevant for night driving. Due to the small number of studies evaluating predictors for night driving ability, further research is needed.