Exploring the contribution of executive functions to on-road driving performance during aging: A latent variable analysis

Adrian, Julien; Moessinger, Michèle; André, Charles; Postal, Virginie

doi:10.1016/j.aap.2019.02.010

Cited by 27 publications

(19 citation statements)

References 104 publications

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“…Meanwhile, the processing load on these memory systems can also be manipulated by controlling the size of N, allowing the investigation of the processing mechanisms of working memory under different memory loads [ 58 , 59 ]. The Go/NoGo task is the most classic research paradigm for evaluating inhibitory interference in working memory [ 60 , 61 ]. Therefore, the n-back task was mainly used to measure the visual working memory of the subjects, while the Go/NoGo task was used to measure the auditory working memory of the subjects.…”

Section: Discussionmentioning

confidence: 99%

Effects of Audiovisual Interactions on Working Memory Task Performance—Interference or Facilitation

Guo

Wang

et al. 2022

Brain Sciences

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(1) Background: The combined n-back + Go/NoGo paradigm was used to investigate whether audiovisual interactions interfere with or facilitate WM. (2) Methods: College students were randomly assigned to perform the working memory task based on either a single (visual or auditory) or dual (audiovisual) stimulus. Reaction times, accuracy, and WM performance were compared across the two groups to investigate effects of audiovisual interactions. (3) Results: With low cognitive load (2-back), auditory stimuli had no effect on visual working memory, whereas visual stimuli had a small effect on auditory working memory. With high cognitive load (3-back), auditory stimuli interfered (large effect size) with visual WM, and visual stimuli interfered (medium effect size) with auditory WM. (4) Conclusions: Audiovisual effects on WM follow the resource competition theory, and the cognitive load of a visual stimulus is dominated by competition; vision always interferes with audition, and audition conditionally interferes with vision. With increased visual cognitive load, competitive effects of audiovisual interactions were more obvious than those with auditory stimuli. Compared with visual stimuli, audiovisual stimuli showed significant interference only when visual cognitive load was high. With low visual cognitive load, the two stimulus components neither facilitated nor interfered with the other in accordance with a speed–accuracy trade-off.

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Section: Discussionmentioning

confidence: 99%

Effects of Audiovisual Interactions on Working Memory Task Performance—Interference or Facilitation

Guo

Wang

et al. 2022

Brain Sciences

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“…Driving is a complex instrumental activity of daily living (iADL). There is extensive literature on the cognitive domains that are associated with driving risk; these include visual attention [ 7 ], visuospatial ability [ 8 ], speed of processing [ 9 ] and executive function [ 10 , 11 , 12 ]. Work examining executive functioning suggests that it is important in novel and demanding situations requiring rapid adaptation as compared to usual dominant responses [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Decline in Other Instrumental Activities of Daily Living as Indicators of Driving Risk in Older Adults at an Academic Memory Clinic

2023

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Background: Decisions around driving retirement are difficult for older persons living with cognitive decline and their caregivers. In many jurisdictions, physicians are responsible for notifying authorities of driving risks. However, there are no standardized guidelines for this assessment. Having access to a driving risk assessment tool could help older adults and their caregivers prepare for discussions around driving retirement. This study compares the clinical profiles of older adult drivers assessed in an academic memory clinic who were referred to the driving authority to older drivers who were not with a focus on instrumental activities of daily living (iADLs). Methods: Data on referred (R) and not-referred (NR) drivers were extracted from medical records. Elements from the medical history, cognitive history, functional abilities, Modified Mini-Mental State (3MS) examination, Trails A/B, and clock drawing were included in the analysis. Four risk factors of interest were examined in separate logistic regression analyses, adjusted for demographic variables. Results: 50 participants were identified in each group. The R group was older on average than the NR. As expected, R were more likely to have Trails B scores over 3 min and have significantly abnormal clock drawing tests. R also showed lower 3MS scores and a higher average number of functional impairments (including managing appointments, medications, bills, or the television). Conclusion: Beyond standard cognitive tests, impairment in iADLs may help general practitioners identify at-risk drivers in the absence of standardized guidelines and tools. This finding can also inform the design of a risk assessment tool for driving and could help with approaches for drivers with otherwise borderline test results.

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“…Significant age differences in simulated driving performance were demonstrated [11][12][13][14]. Furthermore, driving tasks and scenarios were also analyzed to identify the age-related driving performance [15][16][17]. Bunce revealed that older drivers exhibited significantly greater performance inconsistency, particularly marked in the faster motorway condition [18].…”

Section: Introductionmentioning

confidence: 99%

Impact of Age on Takeover Behavior in Automated Driving in Complex Traffic Situations: A Case Study of Beijing, China

et al. 2022

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Research on the influence of age on various automated driving conditions will contribute to an understanding of driving behavior characteristics and the development of specific automated driving systems. This study aims to analyze the relationship between age and takeover behavior in automated driving, where 16 test conditions were taken into consideration, including two driving tasks, two warning times and four driving scenarios. Forty-two drivers in Beijing, China in 2020 were recruited to participate in a static driving simulator with Level 3 (L3) conditional automation to obtain detailed test information of the recorded takeover time, mean speed and mean lateral offset. An ANOVA test was proposed to examine the significance among different age groups and conditions. The results confirmed that reaction time increased significantly with age and the driving stability of the older group was worse than the young and middle groups. It was also indicated that the older group could not adapt to complex tasks well when driving due to their limited cognitive driving ability. Additionally, the higher urgency of a scenario explained the variance in the takeover quality. According to the obtained influencing mechanisms, policy implications for the development of vehicle automation, considering the various driving behaviors of drivers, were put forward, so as to correctly identify the high-risk driving conditions in different age groups. For further research, on-road validation will be necessary in order to check for driving simulation-related effects.

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Exploring the contribution of executive functions to on-road driving performance during aging: A latent variable analysis

Cited by 27 publications

References 104 publications

Effects of Audiovisual Interactions on Working Memory Task Performance—Interference or Facilitation

Effects of Audiovisual Interactions on Working Memory Task Performance—Interference or Facilitation

Decline in Other Instrumental Activities of Daily Living as Indicators of Driving Risk in Older Adults at an Academic Memory Clinic

Impact of Age on Takeover Behavior in Automated Driving in Complex Traffic Situations: A Case Study of Beijing, China

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