Adaptation of the driver behaviour questionnaire and behavioural risk factors for traffic violation arrest and self-reported crash involvement among Nigerian drivers.

CONTEXT: Few studies have been conducted to investigate the driving behaviour of drivers in Africa. AIMS: This study aims to determine the behavioural risk factors for road crashes among Nigerian drivers. SETTINGS AND DESIGN: This is a case-control study. Cases were drivers who were booked for traffic violation or who had been involved in road crashes in the past, while the controls were drivers with no such histories. SUBJECTS AND METHODS: Both the cases and controls were administered the Driver Behaviour Questionnaire (DBQ). Principal component analysis with varimax rotation was run to examine the factor structure of the scale. Cronbach's alpha was used for assessing the internal consistency of the DBQ, and logistic regression was used to determine risk factors for crash involvement. RESULTS: Six hundred active drivers consisting of 300 cases and 300 controls were selected. The mean scores of all DBQ items, except one, were significantly higher among booked drivers compared to those who had never been booked. Consistent with many previous studies, factor analysis identified three factors in the DBQ (aggressive violation, ordinary violation and error). However, the factors were constructed differently with most ordinary violation items in the original DBQ loading as aggressive violation in the present study. Eight variables were predictive of being booked for traffic offences while only five variables were predictive of self-reported crash involvement. CONCLUSIONS: The most important variable associated with previous crash involvement was alcohol use. A major policy implication of this is the need for better attention to anti-drunk driving measures.

Aetiology, prevalence, fracture site and management of maxillofacial trauma.

INTRODUCTION: Maxillofacial fractures are often associated with severe morbidity, functional deficit, disfigurement and significant financial implications. The aim of this review was to investigate whether the aetiology, prevalence and management modalities of facial trauma can identify the common causes of facial trauma with a view to recommending measures to the appropriate governing bodies to change the current practice wherever possible. METHODS: The records of 1,112 patients referred to our oral and maxillofacial unit in Andhra Pradesh, India, between February 2008 and October 2017 were analysed retrospectively. Data including age, sex, aetiology, fracture site and treatment were evaluated. RESULTS: Men aged 20-40 years were the most common victims of facial trauma. Road traffic accidents (RTAs) were responsible in 70% of cases. Mandibular fractures constituted 47% of the overall fractures, and 55% of the total fractures were treated with open reduction and internal fixation. CONCLUSIONS: The main cause of maxillofacial injury among patients reporting to our hospital was RTAs. Mandibular fractures were the most common, accounting for almost half of the cases. Over half (55%) of all maxillofacial fractures were treated with open reduction and internal fixation. Reasons for this high frequency may include the large number of poorly maintained, overloaded vehicles on unsuitable roads, violation of traffic regulations (particularly by inexperienced young drivers), abuse of alcohol or other intoxicating agents and the sociocultural behaviours of some drivers.

Identification of aggressive driving from naturalistic data in car-following situations.

INTRODUCTION: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. METHOD: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. RESULTS: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.

Driving anger and factors related to aggressive driving among Serbian drivers.

Objective: Driving anger has been found to be a motivational determinant of risky and aggressive driving. The study reported in this article focused on research questions concerning the conceptualization of driving anger and relationships between driving anger and aggressive driving.Methods: In a cross-sectional survey study, 1,020 regular Serbian drivers completed a web-based online questionnaire. Exploratory Factor Analysis and Confirmatory Factor Analysis were used to assess the factor structure and psychometric properties of the Driving Anger Scale.Results: The results showed that the adapted DAS was a valid and reliable instrument divided into five subscales such as discourteous behavior, illegal behavior, slow driving, hostile gestures and traffic obstructions. The robustness of the five-factor model obtained from the EFA was confirmed by the CFA. The study provided evidence supporting the predictive validity of the adapted DAS and revealed that the dimensions of driving anger are differently associated with prosocial and aggressive driving behaviors.Conclusions: The study supports the adapted DAS validity and produces evidence that driving anger is associated with driving outcomes.

Links between observed and self-reported driving anger, observed and self-reported aggressive driving, and personality traits.

Driving anger increases risk-taking in traffic and road traffic accident involvement. Herein, we examine the links between self-reported and observed driving anger, self-reported and observed aggressive driving, and personality traits. Specifically, sixty drivers drove in an anger-inducing simulated driving scenario. A video camera recorded their verbal and gestural expression during the simulator drive. Two weeks before the simulator drive, we assessed participants' basic personality traits, driving anger expression, and aberrant driving behaviour via an online survey. State anger was measured immediately before and after the simulator drive. From recorded simulator and video data, we obtained four measures: the number of accidents (simulator), an aggressive driving score (simulator), verbal expression of driving anger (video), and related gestures and headshakes (video). Verbal and gestural expression while driving were related to an increase in state anger in the simulator drive and different self-reported measures: While observed verbal expression was positively related to lapses and negatively related to constructive expression, gestural expression was positively related to both self-reported violations and self-reported aggressive expression. The traits Emotionality and Honesty-Humility were related to an increase in state anger and to verbal expression in the simulator drive, yet, age and gender modified the relation to personality traits. Results can support the development of personalised anger management interventions and anger mitigating in-vehicle devices.

Dimensions of driving-related emotions and behaviors: An exploratory factor analysis of common self-report measures.

OBJECTIVE: A wide variety of driving self-report measures are purported to assess drivers' behaviors and emotions. However, little is known about the underlying factor structure of these measures. This study examined the factor structure of several self-report measures frequently utilized in the assessment of driving-related behaviors and emotions. DESIGN: Cohort survey in a large sample (n = 287) of young adults (mean age = 19.91 years, SD = 1.65). RESULTS: Exploratory factor analysis revealed a four-factor structure that included reckless driving behaviors, negative driving-related emotions, aggressive driving behaviors in response to perceived transgressions from other drivers, and perceived aggressive driving behaviors from other drivers. Aggressive driving behaviors not performed in response to other drivers loaded onto both aggressive driving-related factors. CONCLUSIONS: The factor structure derived in the present study suggests considerable overlap in the content across commonly administered driving self-reports, while also suggesting four distinct dimensions of self-reported driving emotions and behaviors. Whereas some of these dimensions have been explored considerably in the literature (e.g., negative emotions), others deserve further exploration (e.g., perceived aggressive driving behaviors from other drivers). Implications for clinical practice and future investigations are discussed.

The relation between working conditions, aberrant driving behaviour and crash propensity among taxi drivers in China.

Although the taxi industry is playing an important role in Chinese everyday life, little attention has been posed towards occupational health issues concerning the taxi drivers' working conditions, driving behaviour and road safety. A cross-sectional survey was administered to 1021 taxi drivers from 21 companies in four Chinese cities and collected information about (i) sociodemographic characteristics, (ii) working conditions, (iii) frequency of daily aberrant driving behaviour, and (iv) involvement in property-damage-only (PDO) and personal injury (PI) crashes over the past two years. A hybrid bivariate model of crash involvement was specified: (i) the hybrid part concerned a latent variable model capturing unobserved traits of the taxi drivers; (ii) the bivariate part modelled jointly both types of crashes while capturing unobserved correlation between error terms. The survey answers paint a gloomy picture in terms of workload, as taxi drivers reported averages of 9.4 working hours per day and 6.7 working days per week that amount on average to about 63.0 working hours per week. Moreover, the estimates of the hybrid bivariate model reveal that increasing levels of fatigue, reckless behaviour and aggressive behaviour are positively related to a higher propensity of crash involvement. Lastly, the heavy workload is also positively correlated with the higher propensity of crashing, not only directly as a predictor of crash involvement, but also indirectly as a covariate of fatigue and aberrant driving behaviour. The findings from this study provide insights into potential strategies for preventive education and taxi industry management to improve the working conditions and hence reduce fatigue and road risk for the taxi drivers.

Assessing the relationship between self-reported driving behaviors and driver risk using a naturalistic driving study.

The Manchester Driver Behavior Questionnaire (DBQ) identifies risky driving behaviors resulting from psychological mechanisms. Investigating the relationships between these behaviors and drivers' crash risk can provide a better understanding of the personal factors contributing to the incidence of crashes, allowing the more effective development of safety education and road management countermeasures and interventions. The objectives of this study are therefore: 1) to determine the extent to which driver involvement in both crashes and near crashes (CNCs) is related to self-reported driving behaviors, and 2) to assess the relationship between each type of risky behavior and individual driver CNC risk. Driver and crash data were acquired from the Shanghai Naturalistic Driving Study and included 45 males and 12 females, participants with the mean age of 38.7. A K-mean cluster method was adopted to classify participants into three CNC groups of high-, moderate- and low-risk drivers. Drivers completed the DBQ to self-evaluate the frequency during their daily driving of the questionnaire's 24 risky behaviors. Principal component analysis of the 24 items led to a five-component structure including aggressive violations, ordinary violations, lapses, inattention errors, and inexperience errors. Two logistic regression models were developed to investigate the correlation between the five DBQ components and drivers' CNC levels. Conclusions are as follows: 1) high-risk drivers were significantly more likely to have engaged in inattention errors (e.g., missing a "yield" sign) and ordinary violations (e.g., running a red light) than the other drivers, and, 2) aggressive violations (e.g., racing against others) and ordinary violations were positively related to the probability of being a high- or moderate-risk driver.

The association between sensation seeking and driving outcomes: A systematic review and meta-analysis.

The purpose of this study was to evaluate the association between sensation seeking (SS) and driving outcomes (including four aberrant driving behaviors, accident involvement and tickets received) through a systematic review and meta-analysis. Forty-four eligible studies, representing 48 individual trials, were identified from a systematic literature search of four electronic databases, and included in the meta-analysis. Overall, the meta-analysis results showed that SS yielded significant positive correlations with risky driving (pooled r = 0.24, p < 0.001), aggressive driving (pooled r = 0.23, p = 0.019), and errors (pooled r = 0.22, p = 0.016). SS was also positively correlated with accident involvement (pooled r = 0.08, p < 0.001) and tickets received (pooled r = 0.19, p < 0.001), though at weaker levels. The correlations could also be moderated by a number of study and sample characteristics, such as country of origin, publication year, age, gender, driving experience and type of SS measure. The findings help facilitate our understanding of the role of SS in aberrant driving behaviors and accident risk, and provide new insight into the design of evidence-based driving education and accident prevention interventions.

The factors shaping car drivers' attitudes towards cyclist and their impact on behaviour.

Cycling for transportation has multiple benefits to both individuals and societies. However, in many countries, cycling rates are very low. One major deterrent is hostile or aggressive behaviours directed towards cyclists. Past research has established that negative attitudes towards cyclist are a major driver of aggressive behaviour. However, the attitudinal roots that motivate these negative attitudes are currently not well understood. This study investigates to what extent negative attitudes towards cyclists are rooted in a sense of attachment to cars, and environmental attitudes. Furthermore, the study examines whether the distinctiveness of group-membership of cyclists, as signalled by cycling attire, influences the link between attitudes and aggressive behaviours directed at cyclists. An online survey of 308 car drivers measured automobility and environmental attitudes, attitudes towards cyclist, and aggressive behaviour addressed at two groups of cyclists (lycra-clad or casually dressed cyclists). Hierarchical regression analyses showed that automobility attitudes, but not environmental attitudes, were associated with negative car driver attitudes towards cyclists. A significant link between negative attitudes towards cyclists and aggressive behaviour addressed at cyclists was not moderated by the type of cyclist shown. These findings provide a more refined understanding of the basis in which negative attitudes towards cyclists are rooted and how they affect driver behaviour. This research may inform campaigns and initiatives aimed at changing attitudes towards cyclists.

Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers.

Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators) was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety.

Association of posttraumatic stress disorder and traumatic brain injury with aggressive driving in Iraq and Afghanistan combat veterans.

PURPOSE: Aggressive driving contributes to the high rates of postdeployment motor vehicle-related injury and death observed among veterans, and veterans cite problems with anger, aggressive driving, and road rage as being among their most pressing driving-related concerns. Both posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) have been associated with driving-related deficits in treatment-seeking samples of veterans, but the relative contribution of each of these conditions to problems with aggressive driving in the broader population of combat veterans is unclear. METHOD: χ2 and logistic regression analyses were used to examine the relative association of PTSD, TBI, and co-occurring PTSD and TBI to self-reported problems with road rage in a sample of 1,102 veterans living in the mid-Atlantic region of the United States who had served in Afghanistan or Iraq. RESULTS: Results indicate that controlling for relevant demographic variables, PTSD without TBI (odds ratio = 3.44, p < .001), and PTSD with co-occurring TBI (odds ratio = 4.71, p < .001) were associated with an increased risk of road rage, but TBI without PTSD was not. CONCLUSIONS: Our findings suggest that PTSD, with or without comorbid TBI, may be associated with an increased risk of aggressive driving in veterans. Clinical implications for treating problems with road rage are discussed, including use of interventions targeting hostile interpretation bias and training in emotional and physiological arousal regulation skills. (PsycINFO Database Record