Age and gender differences in risky driving: The roles of positive affect and risk perception

Rhodes, Nancy; Pivik, Kelly

doi:10.1016/j.aap.2010.11.015

Cited by 410 publications

(257 citation statements)

References 57 publications

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“…Before or during driving, drivers are susceptible to experiencing mood changes due to changed subjective and objective factors, which exerts significant influences upon driving safety (Rhodes and Pivik, 2011;Pecher et al, 2009;Slovic et al, 2004;Yeung and Wong, 2015). Positive emotions are conducive to safe driving whereas negative moods might inhibit safe driving by influencing drivers' attention and reaction (White, 2011).…”

Section: Methodsmentioning

confidence: 99%

BP neural network-based smog environment and the risk model of mood driving

You¹

2017

Appl Ecol Env Res

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Abstract. In order to evaluate and study the influence of smog environment on driving safety, this paper utilizes the measurability of mood states, adopts back propagation (BP) artificial neural network instrument to establish a smog-risky mood network model. Six pictures in different smog levels were used as emotional stimuli to verify the BPM neural network-based smog-risky mood relation model. The result shows that the smog is a main factor affecting the driver's mood. The method of estimating moods based on the smog environment of BP network is able to predict 70% of the danger. It was proved to be an effective means for the safety management and self-detection of drivers, especially professional drivers.

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Section: Methodsmentioning

confidence: 99%

BP neural network-based smog environment and the risk model of mood driving

You¹

2017

Appl Ecol Env Res

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“…However, there is still no clear evidence that increased risk perception or risk awareness reduces risky driving behaviour and ultimately the rate of road traffic accidents. 10,12 For many individuals, driving is characterised by positive emotions associated with the pleasures of driving. 13 Liking or enjoyment of (or positive feelings towards) specific driving behaviours, including risky behaviours, may be especially strong for young drivers.…”

mentioning

confidence: 99%

“…[4][5][6][7] Risky driving behaviour is also attributed to a number of cognitive processes in young drivers, including underestimating the seriousness of the risk, overestimating driving skills and overconfidence in the ability to recognise hazards. [8][9][10][11] Commonly applied theoretical models generally assume that risky behaviour decision-making occurs through rational processes, such as risk perception and risk assessment of a specific behaviour. However, there is still no clear evidence that increased risk perception or risk awareness reduces risky driving behaviour and ultimately the rate of road traffic accidents.…”

mentioning

confidence: 99%

Risky Driving Behaviours among Medical Students in Erbil, Iraq

Shabila

Ismail

Saleh

et al. 2015

Sultan Qaboos Univ Med J

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abstract:Objectives: This study aimed to assess risky driving behaviours among medical students in Erbil, Iraq, and to explore the relationship between risky driving behaviours and perceptions of risky driving. Methods: This self-administered questionnaire-based survey was conducted from January to May 2014 among a random sample of 400 medical students at Hawler Medical University in Erbil. The questionnaire was designed to assess the frequency of engagement in 21 risky driving behaviours, the perceived risk of each behaviour and the preference for each behaviour as ranked on a 5-point scale. Results: A total of 386 students responded to the survey (response rate: 96.5%). Of these, 211 reported that they currently drove a vehicle (54.7%). Drivers most frequently engaged in the following behaviours: playing loud music (35.9%), speeding (30.4%), allowing front seat passengers to not wear seat belts (27.9%) and using mobile phones (27.7%). Least frequent driving behaviours included not stopping at a red light (3.9%), driving while sleepy (4.4%), driving after a mild to moderate intake of alcohol (4.5%) and drunk driving (6.4%). Mean risky driving behaviour scores were significantly higher among males (P <0.001) and those who owned a car (P = 0.002). The mean risk perception score was higher among >20-year-olds (P = 0.028). There was a significant positive relationship between the preference for risky behaviours and risky driving behaviours (beta = 0.44; P <0.001). Conclusion: Medical students in Erbil reported high frequencies of several serious risky driving behaviours. The preference for risky behaviours was found to be an important predictor of risky driving behaviours among medical students in Erbil.

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“…A large body of research has provided support for this argument. For example, Rhodes and Pivik (2011) found that young, male drivers overestimate their driving skills and their ability to recognise hazardous situations and underestimate the consequences of a crash. Similarly, older studies by Finn and Bragg (1986) as well as Matthews and Moran (1986) found that young male drivers perceived their own chances of an accident to be significantly lower than those of both their peers and older males and that young drivers rated their peers as having poorer driver abilities than themselves.…”

Section: Optimism Bias and Overconfidencementioning

confidence: 99%

“…Such behaviours have been linked to poor perceptions of risks (Rhodes & Pivik 2011) , frustration (Chliaoutakis et al 2002) , and sensation seeking (Dahlen et al 2005) , among other factors. These links are useful to explain relationships between safety risks and personality factors, enabling improvements in driver education and targeted awareness campaigns.…”

Section: Routine Repetition and Automationmentioning

confidence: 99%

Risky Gadgets to the Rescue - Reframing In-Car Technology Use as Task Engagement

Steinberger¹

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Age and gender differences in risky driving: The roles of positive affect and risk perception

Cited by 410 publications

References 57 publications

BP neural network-based smog environment and the risk model of mood driving

BP neural network-based smog environment and the risk model of mood driving

Risky Driving Behaviours among Medical Students in Erbil, Iraq

Risky Gadgets to the Rescue - Reframing In-Car Technology Use as Task Engagement

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