Driver prototypes and behavioral willingness: Young driver risk perception and reported engagement in risky driving

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Author(s)
Harbeck, Emma L
Glendon, A Ian
Griffith University Author(s)
Year published
2018
Metadata
Show full item recordAbstract
Introduction:
This study aimed to explore perceived risk and reported willingness to engage in risky driving in a sample of young Australian drivers. The study also considered the influence of gender, driving experience, and risky driver prototypes on willingness to engage in risky driving. Within this context, a prototype is a social image of the type of person who engages in specific risk behaviors. In the prototype willingness model (PWM), willingness accounts for motivations that do not directly rely on planning or goal formation.
Methods:
The PWM was applied to a sample of 554 drivers (aged 17-25 years) to explore how ...
View more >Introduction: This study aimed to explore perceived risk and reported willingness to engage in risky driving in a sample of young Australian drivers. The study also considered the influence of gender, driving experience, and risky driver prototypes on willingness to engage in risky driving. Within this context, a prototype is a social image of the type of person who engages in specific risk behaviors. In the prototype willingness model (PWM), willingness accounts for motivations that do not directly rely on planning or goal formation. Methods: The PWM was applied to a sample of 554 drivers (aged 17-25 years) to explore how risky driver prototypes: similarity (extent of identification with the prototype), favorability (how positive is the image), and behavioral willingness, may influence their perceived risk and reported engagement in risky driving behaviors. Drivers holding an Australian driver’s license (Provisional 1, Provisional 2, or Open) anonymously completed an online survey measuring: 1) driver prototypes and behavioral willingness to engage in risky driving behaviors, 2) perceived risk of driving-related behaviors, and 3) the Behavior of Young Novice Drivers Scale transient and fixed violations subscales. Results: Path analysis explored relationships between prototypes and willingness variables, perceived risk, and reported driving engagement. Goodness-of-fit statistics supported the conceptual model. Behavioral willingness showed the strongest relationship with perceived risk (negative) and reported driving violation engagement (positive). Conclusions: Risky driver prototypes and behavioral willingness, as well as driver’s sex and driving experience, may help to explain individual differences in perceived risk, and young driver reported risky driving engagement. Practical applications Identifying relevant factors that could be amenable to change, such as driver prototype and willingness variables, may contribute to improved road safety initiatives, and provide information and support to counter factors that might otherwise facilitate young drivers’ risk perceptions and risky driving engagement.
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View more >Introduction: This study aimed to explore perceived risk and reported willingness to engage in risky driving in a sample of young Australian drivers. The study also considered the influence of gender, driving experience, and risky driver prototypes on willingness to engage in risky driving. Within this context, a prototype is a social image of the type of person who engages in specific risk behaviors. In the prototype willingness model (PWM), willingness accounts for motivations that do not directly rely on planning or goal formation. Methods: The PWM was applied to a sample of 554 drivers (aged 17-25 years) to explore how risky driver prototypes: similarity (extent of identification with the prototype), favorability (how positive is the image), and behavioral willingness, may influence their perceived risk and reported engagement in risky driving behaviors. Drivers holding an Australian driver’s license (Provisional 1, Provisional 2, or Open) anonymously completed an online survey measuring: 1) driver prototypes and behavioral willingness to engage in risky driving behaviors, 2) perceived risk of driving-related behaviors, and 3) the Behavior of Young Novice Drivers Scale transient and fixed violations subscales. Results: Path analysis explored relationships between prototypes and willingness variables, perceived risk, and reported driving engagement. Goodness-of-fit statistics supported the conceptual model. Behavioral willingness showed the strongest relationship with perceived risk (negative) and reported driving violation engagement (positive). Conclusions: Risky driver prototypes and behavioral willingness, as well as driver’s sex and driving experience, may help to explain individual differences in perceived risk, and young driver reported risky driving engagement. Practical applications Identifying relevant factors that could be amenable to change, such as driver prototype and willingness variables, may contribute to improved road safety initiatives, and provide information and support to counter factors that might otherwise facilitate young drivers’ risk perceptions and risky driving engagement.
View less >
Journal Title
Journal of Safety Research
Volume
66
Copyright Statement
© 2018 National Safety Council and Elsevier Ltd. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Subject
Applied and developmental psychology
Cognitive and computational psychology
Health services and systems
Public health
Psychology
Transportation, logistics and supply chains