Validation of the Attention-Related Driving Errors Scale (ARDES) in an English-Speaking Sample

Barragán, Daniela; Roberts, Daniel M.; Baldwin, Carryl L.

doi:10.1177/0018720816657927

Cited by 9 publications

(4 citation statements)

References 40 publications

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“…On the first day of participation, participants completed eight questionnaires: a demographics and driving history questionnaire, Simulator Sickness Screening (Hoffman et al, 2003 ), Mindful Attention Awareness Scale (MAAS; Brown and Ryan, 2003 ), Cognitive Failures Questionnaire (CFQ; Broadbent et al, 1982 ), Mind Wandering Scale (MWS; Singer and Antrobus, 1970 ; Giambra, 1980 ), Attention-Related Driving Errors Scale (ARDES; Barragán et al, 2016 ), Attention-Related Cognitive Errors Scale (ARCES; Cheyne et al, 2006 ) and Karolinska Sleepiness Scale (KSS; Åkerstedt and Gillberg, 1990 ). The MAAS, CFQ, MWS, ARDES and ARCES have been shown to reliably predict individuals with a greater propensity of experiencing lapses in attention (Broadbent et al, 1982 ; Cheyne et al, 2006 ; Barragán et al, 2016 ) or mind wandering (Giambra, 1980 ; Brown and Ryan, 2003 ; Burdett et al, 2016 ).…”

Section: Methodsmentioning

confidence: 99%

Detecting and Quantifying Mind Wandering during Simulated Driving

Baldwin

Roberts

Barragán

et al. 2017

Front. Hum. Neurosci.

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144

126

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Mind wandering is a pervasive threat to transportation safety, potentially accounting for a substantial number of crashes and fatalities. In the current study, mind wandering was induced through completion of the same task for 5 days, consisting of a 20-min monotonous freeway-driving scenario, a cognitive depletion task, and a repetition of the 20-min driving scenario driven in the reverse direction. Participants were periodically probed with auditory tones to self-report whether they were mind wandering or focused on the driving task. Self-reported mind wandering frequency was high, and did not statistically change over days of participation. For measures of driving performance, participant labeled periods of mind wandering were associated with reduced speed and reduced lane variability, in comparison to periods of on task performance. For measures of electrophysiology, periods of mind wandering were associated with increased power in the alpha band of the electroencephalogram (EEG), as well as a reduction in the magnitude of the P3a component of the event related potential (ERP) in response to the auditory probe. Results support that mind wandering has an impact on driving performance and the associated change in driver’s attentional state is detectable in underlying brain physiology. Further, results suggest that detecting the internal cognitive state of humans is possible in a continuous task such as automobile driving. Identifying periods of likely mind wandering could serve as a useful research tool for assessment of driver attention, and could potentially lead to future in-vehicle safety countermeasures.

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Section: Methodsmentioning

confidence: 99%

Detecting and Quantifying Mind Wandering during Simulated Driving

Baldwin

Roberts

Barragán

et al. 2017

Front. Hum. Neurosci.

Self Cite

144

126

View full text Add to dashboard Cite

show abstract

“…Participants completed a demographic and driving history survey, the attention-related driving errors scale (ARDES) (Barragan et al, 2016), the checkpoint risky driving scale (CRDS) (Simons-Morton et al, 2013), and a driving knowledge test. The CRDS was included to measure drivers' state-level risk-taking whereas, the ARDES was included to assess drivers' trait-level propensity of committing driving errors due to inattention.…”

Section: Surveysmentioning

confidence: 99%

Individual differences predict drivers hazard perception skills

Barragán

Lee

2021

IJHFE

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Detecting dangerous driving scenarios has been shown to be affected by driving experience, risk-taking or risk perception, and visual search. Given that the results are largely mixed, it is important to understand which individual differences affect drivers' hazard perception abilities. Three hundred ninety-eight drivers recruited throughout the USA participated in an online study by completing a hazard perception video task, two visual perception tasks, and surveys. A latent structural equation model was evaluated finding that visual perception skills and knowledge of traffic laws predicted hazard perception skills. Unlike much of the existing literature, driving experience and risk perception did not predict hazard perception skills. Additionally, the results of a latent structural equation mediation model revealed that driving experience did not mediate the relationship between hazard perception skills and knowledge of traffic laws. These results may prove useful in redesigning training programs and targeting the most susceptible individuals to decrease crash risks.

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“…Finally, there are personality features, such as trait mindfulness, distraction, and likelihood of attention-related lapses that are likely related to the ability of a user to keep and maintain SA [12]. Some of these personality characteristics can be quantified using a variety of surveys [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

How Much Practice Is Required to Reduce Performance Variability in a Virtual Reality Mining Simulator?

Nickel

Knight

Langille

et al. 2019

Safety

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Virtual reality allows researchers to explore training scenarios that are not feasible or are potentially risky to recreate in the real world. The aim of this research was to examine whether using a tutorial session prior to using the mining simulator could adequately reduce the performance variability and increase the consistency of participant performance metrics. Eighteen participants were randomly assigned to a tutorial or a non-tutorial group. The tutorial group completed a five-minute tutorial that introduced them to the basics of the machine and virtual reality environment. All participants then completed five sessions in the simulator lasting five minutes each. Personality scores were recorded and participants answered questions to test their situational awareness after each session. Performance metrics such as number of collisions and perception response time were recorded by the simulator. A Wilcoxon signed rank test was used to determine at what point a significant difference in performance metrics was apparent across the five sessions. A mixed effects multilevel regression was done to evaluate the change in variability across time. There were no significant correlations between the personality questionnaire scores and the number of collisions or the perception response time. Both groups demonstrated high standard deviation scores for collisions and perception response time, but the tutorial group had decreasing variability across time. Both groups began to exhibit more consistent scores in the simulator after 10 min of use. Situational awareness questions require some refinement prior to further testing.

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Validation of the Attention-Related Driving Errors Scale (ARDES) in an English-Speaking Sample

Abstract: Potential applications of the ARDES-US include identifying individuals who are at greater risk of attention-related errors while driving and suggesting individually tailored training and safety countermeasures.

Cited by 9 publications

References 40 publications

Detecting and Quantifying Mind Wandering during Simulated Driving

Detecting and Quantifying Mind Wandering during Simulated Driving

Individual differences predict drivers hazard perception skills

How Much Practice Is Required to Reduce Performance Variability in a Virtual Reality Mining Simulator?

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