Personality, Executive Control, and Neurobiological Characteristics Associated with Different Forms of Risky Driving

Brown, Thomas G.; Ouimet, Marie Claude; Eldeb, Manal; Tremblay, Jacques; Vingilis, Evelyn; Nadeau, Louise; Pruessner, Jens C.; Bechara, Antoine

doi:10.1371/journal.pone.0150227

Cited by 70 publications

(60 citation statements)

References 90 publications

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“…These results suggest that other psychological characteristics of pre-drivers should be assessed together with attitudes towards risky driving in order to have more completed picture of future traffic rules violators. For example, other research confirmed that difficulties in emotion regulation, lack of executive functions are important correlates of novice drivers risky driving (Brown et al, 2016;Nabi et al, 2005).…”

Section: Resultsmentioning

confidence: 98%

“…In most countries including Lithuania male role is related to risk taking, showing off and disobeying the rules (Motiejūnaitė-Timinskienė, Bulotaitė, 2012;Gulliver, Begg, 2007;Özkan, Lajunen, 2006;Akaateba, Amoh-Gyimah, 2013;Yilmaz, Çelik, 2004). Similarly, disregard of the rules, importance of peer pressure and limitations in emotion regulation which are related to the young age (Brown et al, 2016;Cerniglia et al, 2015;Chan, Sinhal, 2013;Rhodes, Pivik, Sutton, 2015) might also be important for the positive attitudes towards risky driving.…”

Section: Resultsmentioning

confidence: 99%

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Predicting Future Traffic Offenders By Pre-Drivers’ Attitudes Towards Risky Driving

Slavinskienė¹,

Žardeckaitė-Matulaitienė²,

Endriulaitienė³

et al. 2017

European Proceedings of Social and Behavioural Sciences

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Worldwide statistics indicate that novice drivers are still one of the riskiest drivers' groups as they highly contribute to road accidents and traffic rules violations. Thus, the psychological variables that allow predicting whether novice drivers will violate traffic rules are important in risky driving research. The aim of this study is to find out if pre-drivers' attitudes towards risky driving measured before obtaining driving license could predict future traffic offences during the first year of independent driving. The research method was a longitudinal study, based on self-reported web-based questionnaire and later records by police. The Scale of Risk-Taking Attitudes to Driving (Ulleberg, Rundmo, 2002) was used to measure six different attitudes towards risky driving. Demographic data and information about committed traffic rules violations during the first year of independent driving were obtained from police records. 598 pre-drivers (262 males, 336 females), averagely aged at 23.63, participated in the study. Results showed that all types of pre-drivers' attitudes towards risky driving were distributed differently, with the attitude towards showing off driving skills as the highest scores and attitudes towards drunk driving and traffic rules violations as the lowest scores. It was found that male and younger pre-drivers possess some riskier attitudes towards driving than female and older pre-drivers. None of six different attitudes towards risky driving measured before obtaining driving license were significant in predicting traffic offences during the first independent driving year.

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Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Predicting Future Traffic Offenders By Pre-Drivers’ Attitudes Towards Risky Driving

Slavinskienė¹,

Žardeckaitė-Matulaitienė²,

Endriulaitienė³

et al. 2017

European Proceedings of Social and Behavioural Sciences

View full text Add to dashboard Cite

show abstract

“…Based on these and similar studies on recidivism among previously convicted DUI offenders it has been established that these drivers indeed are at higher risk of repeated DUI violations [4,5]. As these drivers pose a serious threat of injury and death not only to themselves but also to other road users, research have been directed towards strategies for preventing both potential new cases and recidivists to commit DUI offences [6,7].…”

Section: Introductionmentioning

confidence: 98%

“…Because DUI offenders seem to be less susceptible to e.g. threats of sanctioning in terms of imprisonment, suspension of driver's license, fines and/or educational programs than other drivers, it has been suggested that more tailored interventions based on a clearer understanding of underlying mechanisms, such as personality traits, that governs their behavior would be beneficial [7].…”

Section: Introductionmentioning

confidence: 99%

Associations between psychoactive substance use and sensation seeking behavior among drivers in Norway

et al. 2020

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Background/aim: Drug use and risky driving is associated with sensation seeking. The aim of this study was to investigate the association between use of psychoactive substances and levels of the sensation seeking personality trait as measured with the Brief Sensation Seeking Scale 4 among drivers in Norway. Method: A cross-sectional design was applied to estimate the association between psychoactive substance use and sensation seeking behavior. Drivers in normal traffic were included in two roadside surveys: one in the north (September 2014-October 2015) and the other in the southeast of Norway (April 2016-April 2017). Oral fluid was analyzed for alcohol and psychoactive drugs, and data on sex, age and time of participation were recorded. Participants filled in the Brief Sensation Seeking Scale 4 questionnaire. Results: A total of 8053 drivers were included, of which 32% were women and 62% were under 40 years. The prevalence of alcohol was 0.3%, stimulants 0.6%, tetrahydrocannabinol 1.4%, benzodiazepines and/or z-hypnotics 2.0% and polydrug use 0.6%. Associations were found between the use of tetrahydrocannabinol or benzodiazepines and/or z-hypnotics and a low score on the "thrill and adventure seeking" domain of the Brief Sensation Seeking Scale 4 (OR = 1.723, 95% C.I. = 1.001-2.966). Associations were also found between the use of stimulants and the highest scores on the "experience seeking" (OR = 2.085, 95% C.I. = 1.084-4.009) and "disinhibition" (OR = 4.791, 95% C.I. =1.748-13.135) domains of the Brief Sensation Seeking Scale 4. No associations were found between sensation seeking behavior and alcohol or polydrug use. Conclusion: A high degree of sensation seeking was found among drivers who had used stimulating drugs, in contrast to drives who had used tetrahydrocannabinol and benzodiazepines and/or z-hypnotics who showed a low degree of sensation seeking. The combination of sensation seeking behavior and the use of stimulants might lead to increased risky behavior and thus traffic crashes.

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“…In [8], results revealed that anger leads to stress, which is reflecting in the form of aggressive and negative cognitive driving behavior. On the other hand, research argued that risky drivers generally exhibited more antisocial and substance misuse, reward sensitive personality features and sensation seeking [9]. In addition, traffic penalties reported by public transport drivers are preceded by individual factors, personality and work-related when combined with driving anger.…”

mentioning

confidence: 99%

A Generic Design of Driver Drowsiness and Stress Recognition Using MOGA Optimized Deep MKL-SVM

Chui

Lytras

Liu

2020

Sensors

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Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to existing works, this paper proposes a generic model using multiple-objective genetic algorithm optimized deep multiple kernel learning support vector machine that is capable to recognize both driver drowsiness and stress. This algorithm simplifies the research formulations and model complexity that one model fits two applications. Results reveal that the proposed algorithm achieves an average sensitivity of 99%, specificity of 98.3% and area under the receiver operating characteristic curve (AUC) of 97.1% for driver drowsiness recognition. For driver stress recognition, the best performance is yielded with average sensitivity of 98.7%, specificity of 98.4% and AUC of 96.9%. Analysis also indicates that the proposed algorithm using multiple-objective genetic algorithm has better performance compared to the grid search method. Multiple kernel learning enhances the performance significantly compared to single typical kernel. Compared with existing works, the proposed algorithm not only achieves higher accuracy but also addressing the typical issues of dataset in simulated environment, no cross-validation and unreliable measurement stability of input signals. Driver drowsiness is about the sleepiness of drivers that is an undesired condition in real-world driving. Surveys revealed that more than half of adult drivers felt sleepy while driving and even more severe that about 30% of them fell asleep [3]. This high prevalence can further estimate that drivers could experience accidents (affect or being influenced attributable to drowsy driving). It is worth mentioning that driver drowsiness is differed from driver fatigue [4]. Drivers drive unconsciously in the former condition but are with a conscious status in latter condition. In reality, people are usually fatigued in today's fast paced world.Stress is body's way to react any kind of threat, challenge and demand. Research has revealed that stress has played a crucial role in adapting to driving and making decision [5]. The primary sources for driver stress are congestion and adverse driving condition as well as time pressure [6]. The stress can lead to poor and dangerous driving behaviors, for instance, flashing high beams, eliciting anger in drivers, road rage and aggressive driving, which are major causes of road traffic accidents [7]. Various recent studies have been carried out on the investigation between psychological factors and driving behaviors. In [8], results revealed that anger leads to stress, which is reflecting in the form of aggressive and negative cognitive driving behavior. On the other hand, research argued that risky drivers generally exhibited more antisocial and substance misuse, reward sensitive personality features and sensation seeking [9]. In addition, traffic penalties reported by public transp...

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Personality, Executive Control, and Neurobiological Characteristics Associated with Different Forms of Risky Driving

Cited by 70 publications

References 90 publications

Predicting Future Traffic Offenders By Pre-Drivers’ Attitudes Towards Risky Driving

Predicting Future Traffic Offenders By Pre-Drivers’ Attitudes Towards Risky Driving

Associations between psychoactive substance use and sensation seeking behavior among drivers in Norway

A Generic Design of Driver Drowsiness and Stress Recognition Using MOGA Optimized Deep MKL-SVM

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