The impact of a supplemental drivers’ education program on teenage risk perception and driving behaviors

Lanning, Beth A.; Melton, Karen K.; Abel, Naomi

doi:10.1016/j.trf.2018.06.019

Cited by 16 publications

(4 citation statements)

References 33 publications

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“…We also did not include drivers under 18 years old in the study, following Thailand’s licensing law. The inclusion of younger drivers and other road users may have reveal differing perspectives, attitudes toward safety, and knowledge of road safety [ 71 ]. Thus, collecting such information will more comprehensively represent the population.…”

Section: Conclusion Implications and Research Limitationsmentioning

confidence: 99%

Influence of Psychological Perspectives and Demographics on Drivers’ Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model

Wisutwattanasak

Jomnonkwao

et al. 2022

Behavioral Sciences

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Property damage and loss from road traffic accidents are a major concern in developing countries; thus, studies on accident damage in such countries may include more latent factors. This study aims to examine the effect of psychological perspectives and sociodemographic status on drivers’ willingness-to-pay (WTP) for road accident risk reduction, using confirmatory factor analysis (CFA) and the random parameters multinomial logit model with heterogeneity in means and variances (RPMNLHMV). The CFA results from interviews with 1650 car drivers in Thailand demonstrate that concepts of the theory of planned behavior and health access process approach are key factors for describing drivers’ behavioral intention and WTP. The RPMNLHMV results indicate that drivers’ demographics affected drivers’ WTP to reduce road accidents, and psychological perspectives were also found to have an influence on WTP. The results also reveal unobserved characteristics that could affect drivers’ WTP. The study concludes that ignoring unobserved heterogeneity in studies on WTP to reduce road accidents can lead to biased results and neglect important influential factors. The methodological approaches applied herein offer another layer of insight into unobserved characteristics in road accident valuation. These findings could be used to provide relevant authorities practical insights for policy development on road accident mitigation and road safety education programs in accordance with drivers’ characteristics.

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Section: Conclusion Implications and Research Limitationsmentioning

confidence: 99%

Influence of Psychological Perspectives and Demographics on Drivers’ Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model

Wisutwattanasak

Jomnonkwao

et al. 2022

Behavioral Sciences

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show abstract

“…Risk perceptions (RP) refer to cognitive interpretations regarding the probability of road traffic crashes and the potential severity of their consequences, which has a significant relation effect on drivers' risky behavioral intentions [25,34,35]. The higher the risk perception level of someone who produces the behaviors, the lower behavioral intentions, and the less likely it is to have the actions [32,33,36].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

et al. 2021

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With the rapid emergence of connected vehicle (CV) technologies, there is a shortage of research to understand CV technology's effect on drivers' risk-taking behavioral intentions. This paper aims to analyze driver responses to the real-time information by comparing their reactions to driving intentions between the CV and non-CV environments. A multi-group structural equation model (SEM) is employed to explore the heterogeneity in the relationships between behavioral intentions, attitudes, subjective norms, perceived behavioral control, and risk perceptions under the two different environments. This study reveals two key findings: 1) regarding driver responses to the theory of planned behavior (TPB) model, there are significant differences in attitudes and risk perceptions between the CV and non-CV environments; 2) irrespective of driving environments, risk-taking behavioral intentions are directly related to perceived behavioral control and risk perceptions. While intentions are directly related to attitudes but not associated with subjective norms under the non-CV environment. In contrast, intentions are directly related to subjective norms but not associated with attitude under the CV environment. The findings provide a theoretical basis for using TPB to evaluate CV technology's effects and understanding the differences between the CV and non-CV environments. INDEX TERMS Connected vehicles, Risky driving intentions, Structural equation model, Theory of planned behavior, Unsignalized intersections.

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“…Further studies have linked the age of drivers to perceived risks (Dionne et al, 2007) and when younger drivers participated in a program that included an emergency room visit in order to see the results of accidents for themselves, they rated the risks while driving to be higher following the program. In particular, the risk of driving at high speed was perceived to be higher (Lanning et al, 2018). Additional studies have found a relationship between the magnitude of perceived risk and the risk of a driver being involved in an accident (Wetton et al, 2010).…”

Section: Introductionmentioning

confidence: 97%

The Relationships between the Perception of Physical and Economic Risks Measured within the Road Environment and within the Digital Environment and the Relationships between Risk Perceptions Measured in Separate Environments

Perlman

2023

Preprint

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Risk perception may be measured in different, separate environments. For example, drivers and pedestrians assess the risks in the road environment and workers assess the risks in the workplace environment.The purpose of this study is to examine the relationships between the risks perceived in several different environments in order to examine whether separate environments – such as the workplace environment and the road environment – are perceived as distinct environments, and whether the knowledge gained by learning to assess risks in one environment can be transferred to a new one.This study found a relationship between measures of risk perception while driving and a while crossing a road. Another finding is that a relationship was observed between the perception of risks related to vaccines and those related to medication, and a relationship was also observed between measures of risk perception while browsing the Internet and while using social media.The relationships between the measures of risk perception while crossing a road and the measures of risk perception while hiking in nature or in the workplace are small, as are the relationships between health-related risks and stock market-related risks.These findings suggest that separate environments, such as the workplace environment and the natural environment, are perceived as distinct environments from the road environment, and that knowledge learned in one environment cannot be transferred and used when in the other environment. The findings are discussed in the context of digital classroom learning.

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The impact of a supplemental drivers’ education program on teenage risk perception and driving behaviors

Cited by 16 publications

References 33 publications

Influence of Psychological Perspectives and Demographics on Drivers’ Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model

Influence of Psychological Perspectives and Demographics on Drivers’ Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model

Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

The Relationships between the Perception of Physical and Economic Risks Measured within the Road Environment and within the Digital Environment and the Relationships between Risk Perceptions Measured in Separate Environments

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