Which drivers are at risk? Factors that determine the profile of the reoffender driver

Trait anger as a predictor of dangerous driving behaviour amongst people who use methamphetamine

INTRODUCTION

Despite increased prevalence of methamphetamine in road trauma, it remains unclear how its use translates to an increased risk of traffic-related harm. Exploration of psychosocial factors may thus help identify relevant predictors of dangerous driving behaviour among people who regularly consume methamphetamine.

METHODS

Licenced individuals who report predominant and sustained methamphetamine use (at least 1-time/month for 6 months at heaviest use) were recruited from the Australian community and via targeted campaign (Eastern Health). Psychosocial, substance use and driving behaviour data (Dula Dangerous Driving Index, DDDI) were collected via a secure anonymous online forced-entry survey platform (Qualtrics).

RESULTS

Seventy-seven individuals (65.5 % male) aged between 20-50 years [mean = 29.7, ± Standard Deviation (SD) 6.1] were included. Most (90 %) respondents met criteria for problematic methamphetamine use [Severity of Dependency Scale (SDS) score ≥ 5], and 75 % were high-risk alcohol consumers [Alcohol Use Disorders Identification Test (AUDIT-C) score ≥ 4 for men and ≥ 3 for women]. On average, age of first methamphetamine use occurred at 23.3 years (±5.2). A best-possible subset's regression selection method with dangerous driving behaviour as the dependent variable determined the model with three predictors (alcohol use, substance dependence severity and trait anger) as most parsimonious. After controlling for substance use, trait anger strongly and positively predicted dangerous driving behaviour as measured by the DDDI ([F(3,74) = 26.06, p < .001, adjusted R2 = 0.50, Cohens f2 = 0.42).

DISCUSSION AND CONCLUSIONS

Trait anger is a strong predictor of risky driving among road users who use methamphetamine. Interactions between stable negative-emotional and situational traffic and driving-related factors may increase risk of harm through greater engagement in risk-taking behaviour.

Drunk driving: a secondary analysis of factors associated with driving under the influence of alcohol in Jamaica

OBJECTIVES

To determine the prevalence of alcohol use patterns, sociodemographic factors and risk of alcohol dependence among vehicle drivers in Jamaica.

DESIGN

A secondary data analysis.

SETTING

This study was conducted using the Jamaica National Drug Prevalence Survey 2016 dataset.

PARTICIPANTS

This included 1060 vehicle drivers derived from the population sample of 4623. The participants from each household were randomly selected as the respondent for the survey.

PRIMARY AND SECONDARY OUTCOME MEASURES

Alcohol use and dependence were measured using the Alcohol Use Disorders Identification Test questionnaire. Driving under the influence of alcohol (DUIA) was assessed by questions regarding its use in the past 12 months. The analysis involved the use of Pearson's χ2 test and logistic regression.

RESULTS

75% of Jamaicans reported lifetime alcohol use. Approximately 65% of drivers indicated that they currently drink alcohol. 18% of drivers who currently drink alcohol admitted to DUIA. Reportedly, 54.5% of these drivers were alcohol binge drinkers, with 41.5% also driving under the influence of cannabis. The bivariate analysis demonstrated that DUIA was higher among Christian participants and those who worked in non-machine operator jobs (p=0.002 and p=0.008, respectively). Vehicle drivers altogether and drivers who drive under the influence of alcohol had significant associations with hazardous drinking (p=0.011 and p<0.001, respectively). Logistic regressions highlighted drivers 34 years and under (p=0.012), male drivers (p=0.002) and the head of the household (p=0.050) were 1.82, 3.30 and 1.86 times more likely, respectively, to report driving under the influence of alcohol in the past year.

CONCLUSIONS

The prevalence of alcohol use among Jamaica's population and vehicle drivers is high. That one in five drivers, who currently consume alcohol, also admits to driving under the influence suggests the urgent need for mitigation strategies and legislative action as part of a preventative effort to reduce drunk driving.

Empathy, impulsiveness, and sensation seeking as mediators between primary psychopathic traits and driving behaviors in French driving offenders

OBJECTIVE

The aim of this study was to examine the links between primary psychopathic traits and driving behavior on the one hand, and driving anger expression on the other hand, through the specific contribution of empathy, impulsiveness, and sensation seeking, in a sample of French driving offenders.

METHODS

One thousand six hundred and eighty-six driving offenders completed a paper-and-pencil questionnaire during 110 drivers' rehabilitation programs.

RESULTS

Primary psychopathic traits were positively associated with violations and aggressive driving anger expression, and negatively associated with prosocial driving behaviors. These associations were partially mediated by empathy, impulsiveness, and sensation seeking. In addition, the negative relation between primary psychopathic traits and adaptive anger expression was fully mediated by these three personal dispositions.

CONCLUSION

Low empathy, high impulsiveness and sensation seeking are important characteristics of driving offenders with high psychopathic traits. Our results provide a better understanding of French driving offenders' risky behaviors and the role of primary psychopathic traits.

Maximum likelihood method of estimating the conflict-crash relationship

The fundamental matters of how traffic conflicts are connected to crashes and how to estimate this connection with traffic conflict data is an active subject of research and refinements. There are still open questions about traffic events that can be analytically extrapolated to related crashes, and how to efficiently estimate the probability of crash associated with such events to enable conversion of observed events to the corresponding expected number of crashes. There are two important uses of a working estimation method: (1) rapid assessment of safety at specific roads locations and evaluation of countermeasures by safety engineers, (2) modeling of safety effects by analysts based on relatively short observations at multiple locations or at limited number of locations but during extended periods. This paper focuses on the application of traffic conflicts by safety engineers where the method practicality is important. The paper first recalls the OLS method of estimating the shape parameter of the underlying Lomax distribution proposed in (Tarko, 2018). Then, the ML method is introduced and the Lomax-based crash estimates obtained with the two methods are compared. Both the methods assume the scale parameter to estimate the shape parameter. The effect of assuming the scale parameter on estimates of the expected number of crashes is evaluated. To bring the scale parameter's effect into a meaningful perspective, it is compared to two other effects: (1) type of driver, and (2) limited number of observations. Finally, re-parametrized Lomax distribution is pointed out as a potential way to address the difficulties with estimating the two distribution parameters simultaneously. The summary of the results closes the paper.

Self-reported changes in aggressive driving within the past five years, and during COVID-19

Aggressive driving is a significant road safety problem and is likely to get worse as the situations that provoke aggression become more prevalent in the road network (e.g. as traffic volumes and density increase and the grey fleet expands). In addition, driver frustration and stress, also recognised as triggers for aggression, are likely to stay high because of the COVID-19 pandemic and associated burdens, leading to increased aggression. However, although drivers report that other drivers are becoming more aggressive, self-report data suggests that the prevalence of aggression has not changed over time. This may be due to the methods used to define and measure aggression. This study sought to clarify whether self-reported aggression has increased over a five-year period and across three different types of aggression: verbal aggression, aggressive use of the vehicle and personal physical aggression. The influence of COVID-19 lockdowns on own and others’ driving styles was also investigated. A total of 774 drivers (males = 66.5%, mean age = 48.7; SD = 13.9) who had been licensed for at least five years (M = 30.6, SD = 14.3), responded to an online survey and provided retrospective frequencies for their current aggression (considered pre-COVID-19 lockdowns) and five years prior. Two open ended questions were included to understand perceived changes in driving styles (own and others) during the COVID-19 pandemic. One third (33%) of drivers believed they were more aggressive now than five years ago but 61% of the sample believed other drivers were more aggressive now than five years ago. Logistic regression analyses on changes in self-reported aggression (same or decreased vs increased) showed the main factor associated with increases in aggressive driving was the perception that other drivers’ aggression had increased. Further, almost half the sample (47%) reported that other drivers had become riskier and more dangerous during, and soon after, the COVID-19 lockdowns. These results show that the driving environment is seen as becoming more aggressive, both gradually and as a direct result of COVID-19 lockdowns. The data indicate that this perceived increase in aggression is likely to provoke higher levels of aggression in some drivers. Campaigns to reduce aggression on the roads need to focus on changing road culture and improving interactions, or perceived interactions, among road users.

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers

Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

Guilt and Shame of What Might Have Been in Optimistic Offender Drivers

Habitual offender drivers are required to recover points lost on their driving license by attending reeducation courses, an experience that may, upon reflection of the incident in question, induce feelings of guilt or shame for the infractions they committed. A simulated driving task studied optimistic offender drivers to analyze the extent to which the controllability of the situational context influenced their use of internal and external factors in counterfactual thoughts and emotions such as guilt and shame. The study involved 160 drivers, of whom 54 were categorized as repeat offender drivers while 106 drivers attended courses for advanced professional driving licenses. The participants drove along a route in a driving simulator, which had been previously adjusted for the difficulty to generate a perception of high or low control. Based on the outcome obtained by the participants in this stage, each driver had to report which resources they required to improve their outcomes. Different factor ANOVAs were used to analyze our findings. The results indicated that optimistic offenders, unlike other groups (i.e., optimistic non-offender and pessimistic non-offender), thought that their results could have been better if external factors had been present (i.e., upward counterfactuals), both under conditions of high and low control. They believed their results would have been worse had it not been for their internal resources (i.e., downward counterfactuals), especially under conditions of low control. Concerning emotions of guilt and shame, offender optimists had the lowest values in both conditions compared with the other groups. We may contend that optimistic offender drivers thought they could have obtained better outcomes if external factors had been involved. In the low control condition, they justified that if it were not for such internal skills, their results could have been worse. When they generated such thoughts, the emotions of guilt and shame were minimal.

Assessing Willingness to Engage in Risky Driving Behaviour Using Naturalistic Driving Footage: The Role of Age and Gender

Young novice drivers are more prone than older drivers to get involved in a risky driving situation. Some young drivers underestimate risk while overestimating their driving abilities, increasing the likelihood of engaging in risky behaviour. Age and inexperience both influence risk estimation, though it is not clear which of these variables is more important. Can drivers’ willingness to engage in risky behaviour be assessed in a similar way to hazard perception skill using video-based risky situations? The aim of the current study was to assess whether a video-based tool could measure the willingness to participate in risky driving situations and whether it can distinguish between different types of risky driving scenarios across gender and driver age groups. We also explored the moderating effect of age and gender on drivers’ experience in relation to the risky manoeuvres and participants’ willingness to engage in risky situations. Participants were presented with naturalistic videos from the perspective of the driver that contained active risky situations (result of driver’s own actions) and were asked to make a decision regarding a potential action (to overtake a bus/bicycle or pass through an amber light) and whether they would accelerate at this point. Participants reported that they were more willing to accelerate and overtake cyclists and buses and less willing to pass a light in amber. Young drivers were more willing to both engage in the risky behaviours and accelerate than older drivers, with young males reporting higher scores than the other groups. Gender differences were observed, with males being more prone to overtake and pass through a light in amber than females; however, this difference was not observed for the intention to accelerate. All the above effects remained when we tested the impact of experience on decision making while controlling for age and gender, although driving experience was no longer significant. These results demonstrate that drivers’ intention to assume risk can indeed be measured in a similar video-based methodology to that used by hazard perception tests. The findings raise the possibility of assessing and training drivers on a wider range of safety-related behaviours.

Measuring Risk Tolerance across Domains: Scale Development and Validation

Risk attitudes are of interest to researchers in many fields as they play a crucial role in our day-to-day decision-making. In this paper we develop a measure of risk attitudes-the Multi-Domain Risk Tolerance (MDRT) scale-that addresses some key shortcomings of popular self-report scales, such as the Domain-Specific Risk-Taking (DOSPERT) scale. We do this by clearly aligning the risk in the items with the particular domain of risk, reducing item ambiguity, and reducing the impact of prior knowledge. We developed the MDRT using an Exploratory Graph Analysis (EGA) and Item Response Theory (IRT) approach with a community sample (N = 921). We examined its construct and convergent validity (N = 493) and construct generalizability (N = 487). We found that the MDRT had excellent internal consistency, dimensionality and latent factor structure. The MDRT also demonstrated significant convergent validity with related scales used in the literature. The MDRT is shown to be a promising alternative measure of risk attitudes.

Risky Decision-Making and Hazard Prediction are Negatively Related and Could Be Assessed Independently Using Driving Footage

Introduction

Traffic collisions are a principal cause of death in Europe, disproportionately affecting young drivers. Driving safety depends not only on our ability to anticipate and respond to dangers on the road but also on the level of risk we are willing to engage within our own driving behaviour.

Methods

Hazard prediction (HPr) and risky decision-making (RDM) tests were given to three groups of young Spaniards (169 participants): 54 non-drivers (M=20), 65 novice (M=21) and, 50 experienced drivers (M=26 years old). Both tests presented participants with video clips of driving recorded from the driver’s perspective. The HPr test contained hazardous situations caused by the actions of another road user (eg, a pedestrian crossing the road). Each HPr clip was occluded as a hazard began to unfold and participants were asked to predict “what happens next?” They selected their answer from four on-screen options. The RDM test used clips where any imminent danger would be provoked by the film-car driver’s risky behaviour (eg, overtaking illegally). Participants were asked to report the probability of following certain types of risky behaviour (eg, “Would you go forward with the lights on amber?” or “Would you overtake the cyclist/lorry/bus at this point?”). In addition, the effect of the locality of the driving scenarios was manipulated: they could take place in the participant’s native country (Spain) or in a different country (UK).

Results

Non-drivers and novice drivers were less able to predict upcoming hazards and more likely to make risky decisions. Driving scenarios from another country (UK) provoked riskier decisions than those from the participants’ home country (Spain).

Conclusion

Improvement in HPr skills among novice or new drivers poses a huge challenge as far as driver training is concerned, though it is only part of the solution. Young inexperienced drivers’ willingness to engage in risky behaviour also needs to be tackled. Our results suggest that such RDM can be assessed in a similar way to HPr skill, using a naturalistic approach, which raises the possibility of assessing and training drivers on a wider range of safety-related behaviours.

Visual attention in realistic driving situations: Attentional capture and hazard prediction

In real life, many objects catch our attention involuntarily or exogenously. Exogenous attention occurs fast and its effects are short-lived. In the laboratory, when attentional orientation is studied, both valid and invalid attentional signals are used: the valid ones direct the attention to a location where something relevant is going to appear. The invalid ones occur in a location where nothing relevant is going to happen. Usually, performance is improved when valid signals rather than invalid ones are presented. This work is novel in that it explores the effects of attentional capture and driving experience in situations of day-to-day driving while participants carry out a Hazard Prediction task. We created new Hazard Prediction (HPr) and Risk Estimation (RE) tests when driving by selecting 48 short videos recorded in a realistic way from the perspective of a car driver. We created valid and invalid trials by selecting videos in which a what?? was presented in the same spatial location as the one where the hazard was beginning to develop or in a different location. Simple situations, with only one developing hazard, were also presented. A total of 92 participants (30 experienced drivers, 32 novices and 30 with no experience) were placed in the position of the driver and answered the questions: 1) What will happen after the video is cut? 2) To what extent do you consider this situation risky? The results from the Hazard Prediction test replicate the attentional capture effect in complex driving situations, with invalid trials obtaining the worst results, followed by valid and simple ones. Participants with experience obtained better scores than novices, and novices were better than drivers without experience. No interaction between attentional orientation and experience was found, suggesting the obligatory and automatic nature of orientation processes, which do not appear to be compensated for by driving experience. No significant differences were found for the Risk Estimation test.

Validity of failure-caused traffic conflicts as surrogates of rear-end collisions in naturalistic driving studies

Although the frequency and severity of crashes are direct measures of road safety, crash data are typically of limited quality and they require long data collection periods to produce conclusive results. Surrogates of crashes that would allow a quick and accurate estimation of safety have been an active topic for years. Among multiple alternatives, traffic conflicts have been established as a promising surrogate measure. This paper is aimed to demonstrate the validity of failure-caused traffic conflicts by applying a recently proposed Lomax-based method to estimate the expected number of crashes from observed traffic conflicts. The data collected in the naturalistic driving program, the Second Strategic Highway Research Program (SHRP2), were used in the validation task. The rear-end crashes recorded during the SHRP2 program and the corresponding rear-end traffic conflicts were analyzed for three categories of drivers: young male, mature male, and mature female. Past research has indicated that these three categories have a distinctively different proneness to involvement in crashes. Out of all rear-end traffic conflicts included in the SHRP2 database, 1.4 % were used to estimate the crash frequencies and rates for each studied type of driver. The Lomax distribution was applied within the counterfactual framework. Then, the conflict-based crash rate estimates were compared to the crash rates of the studied types of drivers calculated from all the rear-end crashes observed in the SHRP2 study period. The conflict-based rate estimates followed well the crash-based rates and the existing knowledge about the safety performance of the studied drivers. The conflict-based results confirmed the over-representation of young male drivers in crashes. It was also confirmed that mature male drivers are involved in rear-end crashes more frequently than mature female drivers. The results demonstrate both the validity of the Lomax-based analysis of failure-caused traffic conflicts and the benefit of traffic conflicts analysis that considerably reduces a period of data collection from years for crashes to days or weeks for traffic conflicts.

A Frontal Neuropsychological Profile in Fitness to Drive

Traffic accidents are a global concern due to the elevated mortality rates of both drivers and pedestrians. The World Health Organization declared 2011-2020 as the Decade of Action for Road Safety, endorsing initiatives to reduce traffic-related deaths. Yet, despite these incentives, fatal accidents still occur. Different studies have linked deficits in executive functions to risky driving attitudes and crashes. The present study focuses on demographic, cognitive and personality factors, related to the prefrontal cortex, that are characteristic of drivers prone to risky behavior behind the wheel. The penalty Points System was used to classify drivers as "safe", with no point loss over a two-year period, or "risky", with full point loss during the same interval. A neuropsychological assessment of prefrontal cognitive functions was carried out on each group to identify variables associated with safe and risky behavior. Neuropsychological indexes were obtained from a continuous performance task without cue (Simple Attention), a continuous performance task with cue (Conditioned Attention), the Tower of Hanoi test and the Neurologically-related Changes in Personality Inventory (NECHAPI). A Discriminant Analysis (DA) found that education level, reaction times in Simple and Conditioned Attention, learning errors in the Tower of Hanoi and vulnerability in the personality test, best predicted whether drivers were likely to be in the safe or risky group. Finally, a cross-validation analysis performed on the same sample correctly classified 87.5% of the drivers. These data suggest that prefrontal dysfunction contributes to risky behavior behind the wheel. The inclusion of cognitive programs to identify and train drivers with this propensity could reduce risky driving, and consequently, save lives on the road.

How You Deal with Your Emotions Is How You Drive. Emotion Regulation Strategies, Traffic Offenses, and the Mediating Role of Driving Styles

Past research indicated the importance of traffic safety and driving behaviors for the sustainability of the traffic system. The aim of this study was to examine the effect of emotion regulation on drivers’ tendency to obey or transgress traffic rules. A sample of 554 Romanian drivers completed a set of measures assessing their driving styles, traffic offenses, and their habitual use of three emotion regulation strategies. The results of the mediation analyses showed that two of these strategies, i.e., reappraisal and experiential avoidance, are associated with less traffic offenses, and that specific driving styles mediate these effects. While the behavioral effects of experiential avoidance were mixed in valence, reappraisal was found to diminish the use of maladaptive driving styles and to foster careful driving. Overall, this pattern of results indicates the potential benefits of future interventions aiming to develop drivers’ abilities to regulate their emotions, especially through reappraisal, for increasing traffic safety.

Adaptation of the multidimensional driving styles inventory for Spanish drivers: Convergent and predictive validity evidence for detecting safe and unsafe driving styles

The Multidimensional Driving Style Inventory (MDSI; Taubman - Ben-Ari et al., 2004) is a well-known and useful instrument that allows us to identify not only "maladaptive" Driving Styles (DS) in order to modify them, but also "adaptive" DS to encourage safe driving. The aim of this study was to adapt the MDSI to the Spanish spoken in Spain and to the rules and driving habits of Spaniards. The Argentinian version of the MDSI was taken as the source version. The sample consisted of 1173 drivers, who completed the Spanish version of the MDSI. The factor structure was analysed by means of an Exploratory Factor Analysis (AFE) and a Confirmatory Factor Analysis (AFC). The 6-factor structure of the Argentinian version of the MDSI was replicated with higher internal consistency values for each of the DS. The original Argentinian and the Spanish versions share 23 items, indicating a relevant overlap in the construct. A cluster analysis grouped the DS into two groups: maladaptive and adaptive. Significant associations were found between DS measures and demographic variables (gender, age, and education level), driving history and theoretically related constructs like the Domain-Specific Risk-Taking Scale (DOSPERT); Lapses, Errors, Violations; Angry Driving; and Sensitivity to Rewards. The Spanish MDSI provides valid measures that could help us understand complex driving behaviours and promote safe driving.

Assessing a domain-specific risk-taking construct: A meta-analysis of reliability of the DOSPERT scale

The DOSPERT scale has been used extensively to understand individual differences in risk attitudes across varying decision domains since 2002. The present study reports a reliability generalization meta-analysis to summarize the internal consistency of both the initial and the revised versions of DOSPERT. It also examined factors that can influence the reliability of the DOSPERT and its subscales. A total of 104 samples (N = 30,109) that reported 465 coefficient alphas were analyzed. Results of meta-regression models showed that the overall coefficient alpha of the DOSPERT total scores was satisfactory, regardless of the scale and study characteristics. Coefficient alphas varied significantly across domain subscales, with values ranging from .68 for the social domain to .80 for the recreational domain. In addition, the alpha coefficients of subscales varied significantly depending on various study characteristics. Finally, we report the meta-analysis of the intercorrelations among DOSPERT subscales and reveal that intercorrelations among the subscales are heterogeneous. We discuss the theoretical implications of the present findings.

Cortisol stress response predicts 9-year risky driving convictions in male first-time driving-while-impaired offenders

BACKGROUND

With driving while impaired by alcohol (DWI) representing a persistent burden on global health, better understanding and prevention of recidivism following a first-time DWI conviction are needed. Progress towards these goals is challenged by the marked heterogeneity in offender characteristics and a traffic safety literature that relies on subjective self-report measures and cross-sectional study designs. The present study tested the hypothesis that an objective neurobiological marker of behavioural maladjustment, the cortisol stress response (CSR), predicts future DWI and other traffic convictions over a 9-year follow-up period.

METHODS

One hundred thirty-two male first-time DWI offenders and 31 non-offender comparators were recruited and assessed at intake for their substance use, psychosocial and psychological characteristics and CSR. Traffic conviction data were obtained from provincial driving records. Survival analysis estimated the association between CSR and risk of a traffic conviction over time.

RESULTS

In support of our hypothesis, blunted CSR predicted traffic convictions during the follow-up duration. This effect generalized to both DWI offenders and non-DWI drivers. While CSR was lower in DWI offenders compared to non-offenders, it did not specifically predict recidivism in DWI offenders. Modelling results indicated that blunted CSR, along with DWI offender group membership, experience seeking and drug use frequency, may demarcate a high-risk driver phenotype.

CONCLUSIONS

CSR is a neurobiological marker of a driver phenotype with elevated generalized driving risk. For drivers with characteristics consistent with this phenotype, expanding the focus of intervention to address multiple forms of risky driving may be necessary to curb their overall threat to traffic safety.

Trait driving anger and driving styles among Colombian professional drivers

This study analyzes the association between trait driving anger and driving styles in a sample of Colombian professional drivers. Additionally, the internal and external validity of the Deffenbacher's Driving Anger Scale (DAS-14) was examined in the study population. The DAS-14 and the Spanish Version of the Multidimensional Driving Style Inventory (S-MDSI) were administered to 492 urban bus and taxi operators. Average trait driving anger scores in the study population were similar to those reported in previous validation studies from Spain, Argentina, China, and Malaysia. After deleting three cross-loaded items, confirmatory factor analyses revealed a three-dimensional latent structure for the DAS-14, similar but not equal to the previous Spanish speaking validations. This factorial structure fits the data reasonably well. Finally, linear regression analyses revealed that the three factors of the DAS-14 (impeded progress by others, illegal driving, and direct hostility) significantly predict adaptive and maladaptive driving styles. Overall, the results of this study suggest that the DAS-14 is a reasonably reliable measure of driving anger traits among professional drivers, and it also provides relevant insights for the prevention of risky driving styles in this occupational group.