Crash risk and aberrant driving behaviors among bus drivers: the role of personality and attitudes towards traffic safety

Validity and Reliability of the Attitudes toward Traffic Safety Scale in Argentina

The main objective of this research was to investigate the psychometric properties of a Spanish-language version of the Attitudes toward Traffic Safety Scale (ATTS) for the assessment of risky driving attitudes among Spanish-speaking populations. Five hundred and fifty-eight drivers from Argentina participated in the study. Confirmatory factor analysis supported the ATTS three-factor structure: Attitude towards violations and speeding, attitude towards the careless driving of others and attitude towards drinking and driving, χ2(87) = 205.91, p < .001; χ2/df = 2.36; GFI = .94; CFI = .93; TLI = .91; RMSEA = .05; 90% CI [.04, .06]. A model with one higher-order factor (overall attitude toward risky driving) also fits the data. Reliability estimates were acceptable for the total scale (α = .81) and for all subscales (with α values ranging from .74 to .84), and concurrent validity was supported by theoretically expected correlations with self-reported risky driving behavior (r ranging from .27 to .45, ps < .01). Subsequent comparison between zero-order correlation and partial correlation (controlling for Driver Impression Management) between ATTS subscales and self-reported risky driving behavior revealed minor or no effects of social desirability bias. Implications for road safety intervention are discussed.

Structural equations modeling of real-time crash risk variation in car-following incorporating visual perceptual, vehicular, and roadway factors

In this study, we attempted to explain drivers' crash risk variation in car-following for crash avoidance considering the effects of drivers' visual perception, vehicle type, and horizontal curves, with a structural equations model. The model was built by incorporating drivers' speed risk perception and distance risk perception as latent variables. A series of on-road experiments was conducted on the curved segments of a freeway in China to collect naturalistic driving data to approximate the model. The results indicate that (1) the amount of variance in speed risk perception accounted for by the temporal and spatial frequency and the following vehicle type was 21%; (2) the amount of variance in distance risk perception accounted for by the temporal and spatial frequency, leading vehicle type, stopping sight distance (SSD), horizontal sightline offset (HSO), and radius was 29%; and (3) speed risk perception and distance risk perception explained 27% of the total variance in crash risk variation, which is significantly higher than previous similar results that were commonly limited to 10%. The results were explained from the perspective of the effect of line markings, vehicle type (size), and curves on driving behaviors, respectively. In addition, the difference between the effect of speed risk perception and distance perception on crash risk variation was discussed considering the direct and indirect origins of risk in driving. The findings suggests that the incorporation of visual perceptual, vehicular, and roadway factors and its relevant speed risk perception and distance risk perception can better explain the crash risk in car-following. This study also emphasized the possibility and the need of applying the line markings as a visual intervention to prevent the drivers from rear-end crashes on curves, which may provide new insights and be a new solution for roadway 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.

Correlation Among Behavior, Personality, and Electroencephalography Revealed by a Simulated Driving Experiment

Drivers play the most important role in the human-vehicle-environment system and driving behaviors are significantly influenced by the cognitive state of the driver and his/her personality. In this paper, we aimed to explore the correlation among driving behaviors, personality and electroencephalography (EEG) using a simulated driving experiment. A total of 36 healthy subjects participated in the study. The 64-channel EEG data and the driving data, including the real-time position of the vehicle, the rotation angle of the steering wheel and the speed were acquired simultaneously during driving. The Cattell 16 Personality Factor Questionnaire (16PF) was utilized to evaluate the personalities of subjects. Through hierarchical clustering of the 16PF personality traits, the subjects were divided into four groups, i.e., the Inapprehension group, Insensitivity group, Apprehension group and the Unreasoning group, named after their representative personality trait. Their driving performance and turning behaviors were compared and EEG preprocessing, source reconstruction and the comparisons among the four groups were performed using Statistical Parameter Mapping (SPM). The turning process of the subjects can be formulated into two steps, rotating the steering wheel toward the turning direction and entering the turn, and then rotating the steering wheel back and leaving the turn. The bilateral frontal gyrus was found to be activated when turning left and right, which might be associated with its function in attention, decision-making and executive control functions in visual-spatial and visual-motor processes. The Unreasoning group had the worst driving performance with highest rates of car collision and the most intensive driving action, which was related to a higher load of visual spatial attention and decision making, when the occipital and superior frontal areas played a very important role. Apprehension (O) and Tension (Q4) had a positive correlation, and Reasoning (B) had a negative correlation with dangerous driving behaviors. Our results demonstrated the close correlation among driving behaviors, personality and EEG and may be taken as a reference for the prediction and precaution of dangerous driving behaviors in people with specific personality traits.

Impulsive and Self-Regulatory Processes in Risky Driving Among Young People: A Dual Process Model

The present study empirically examined a novel dual process model of self-reported aberrant driving behavior in young and novice drivers that incorporates both impulsive and self-regulatory processes. Four hundred and nine participants aged 18-25 years (M age = 21.18 years, SD = 2.12; 65.5% females) completed online questionnaires on impulsivity, normlessness, sensation seeking, emotion and self-regulation, and attitudes toward driving safety. Path analysis showed that motor impulsivity was associated with self-reported driving violations, errors, and lapses, whereas sensation seeking was uniquely directly associated with self-reported errors. Non-planning impulsivity, normlessness and sensation seeking had significant indirect effects on self-reported errors, via self-regulation. Finally, motor impulsivity and normlessness had a significant indirect effect on self-reported violations, errors and lapses, via attitudes to driving safety. Based on our findings we suggest that a dual-process approach is relevant to the study of aberrant driving behavior in young and novice drivers, and the results of the present study have important implications for initiatives to promote driving safety in this population.

Evaluation of Driver Behavior Criteria for Evolution of Sustainable Traffic Safety

Driver behavior has been considered as the most influential factor in reducing fatal road accidents and the resulting injuries. Thus, it is important to focus on the significance of driver behavior criteria to solve road safety issues for a sustainable traffic system. The recent study aims to enumerate the most significant driver behavior factors which have a critical impact on road safety. The well-proven Analytic Hierarchy Process (AHP) has been applied for 20 examined driver behavior factors in a three-level hierarchical structure. Linguistic judgment data have been collected from three nominated evaluator groups in order to detect the difference of responses on perceived road safety issues. The comparison scales had been averaged prior to computing the weights of driver behavior factors. The AHP ranking results have revealed that most of the drivers are most concerned about the “Errors”, followed by the “Lapses” for the first level. The highest influential sub-criteria for the second level is the “Aggressive violations” and for the third level, the “Drive with alcohol use”. Kendall’s rank correlation has also been applied to detect the agreement degree among the evaluator groups for each level in the hierarchical structure. The estimated results indicate that road management authorities should focus on high-rank significant driver behavior criteria to solve road safety issues for sustainable traffic safety.

Reliability and validity of the Multidimensional Driving Style Inventory in Chinese drivers

OBJECTIVE

The Multidimensional Driving Style Inventory (MDSI) has been widely used in assessing the associations between driving styles and traffic violations and accidents in different cultural contexts. Due to the lack of a valid instrument to assess driving style, studies concerning driving style and its influence factors are limited in China. Thus, this study aimed to adapt and validate a Chinese version of the MDSI.

METHODS

Seven hundred and sixty drivers aged from 19 to 60 years old were asked to complete the MDSI and a personality scale (trait anger, sensation seeking, altruism, and normlessness). Exploratory factory analysis (EFA) and confirmatory factor analysis (CFA) were used to obtain the factorial structure of the MDSI. The external validity of the MDSI was then evaluated by examining the associations between driving styles and personality traits, demographic variables, and traffic violations and crashes.

RESULTS

EFA revealed a 6-factor structure of the MDSI (i.e., risky, anxious, angry, distress reduction, careful, and dissociative driving styles). CFA confirmed that the model fit of the MDSI was acceptable. The MDSI factors were moderately or weakly correlated with trait anger, sensation seeking, altruism, and normlessness. Significant gender and age differences in driving styles were found. Moreover, drivers who had traffic violations or crashes in the past year scored higher on risky and angry driving styles and lower on careful driving style than those who had not have traffic violations or crashes.

CONCLUSIONS

The Chinese version of the MDSI proved to be a reliable, valid, and highly useful instrument. It could be used to assess Chinese drivers who are at risk due to their maladaptive driving styles.

Personality Traits and Attitudes Toward Traffic Safety Predict Risky Behavior Across Young, Adult, and Older Drivers

In the last few decades, several studies have investigated the role of personality traits and attitudes toward traffic safety in predicting driving behaviors in diverse types of drivers across several countries. However, to the best of our knowledge, no studies so far have investigated the possible moderating role played by age in relation to predictors of accident risk. Answering this open question would provide information about the generalizability of the model across different subpopulations and would make possible the tailoring of the interventions to specific target groups. The study involved 1,286 drivers from three different age groups (young: n = 435; adult: n = 412; old: n = 439) which completed a questionnaire measuring drivers’ personality traits (i.e., anxiety, hostility, excitement seeking, altruism, normlessness), positive attitudes toward traffic safety, risky driving behaviors (i.e., errors, lapses, and traffic violations), accident involvement and number of traffic fines issued in the last 12 months. Multi-group Variance Based Structural Equation Modeling (VB-SEM) across the three age groups showed that the hypothesized model had a good fit with the data in all the three age groups. However, some pattern of relationships between the variables varied across the three groups, for example, if considering the direct effects of personality traits on risky driving behaviors, anxiety, altruism, and normlessness predicted violations only in young and adult drivers, whereas excitement seeking was associated with lapses only in young drivers; anxiety was a positive predictor of drivers’ errors, both in adult and older drivers, whereas excitement seeking predicted errors in adult and young drivers. On the other hand, attitudes significantly and negatively predicted violations and errors in all the three age groups, whereas they significantly and negatively predicted lapses only in young and older drivers. The results of the present study provided empirical basis to develop evidence-based road safety interventions differently tailored to the specific life’s stage of the drivers.

Validating Driver Behavior and Attitude Measure for Older Italian Drivers and Investigating Their Link to Rare Collision Events

The present study aimed to: (a) validate the factor structures of three scales assessing driving behavior, attitudes toward traffic safety (ATTS) and self-regulation in driving, in a sample of Italian older adults, through confirmatory factor analyses and (b) to determine the effectiveness of these measures in predicting the likelihood and the frequency of collision involvements in the following year. A 28-item driver behavior questionnaire (DBQ), a 16-item ATTS, a 21-item extended driving mobility questionnaire (DMQ-A) were administered to 369 active Italian drivers, aged between 60 and 91 years. Results showed a four-factor structure for the DBQ, a five-factor structure for the ATTS and a two-factor structure for the Extended DMQ-A, as the best fitting models. Hurdle model analysis of count data with extra-zeros showed that all factors of DBQ predicted the likelihood of road collisions. Risky behavior, except for aggressive violations, self-regulation and attitudes toward traffic rules were associated with the frequency of collision involvement. The aforementioned three scales seemed to be a useful and concise suite of instruments assessing risky as well as protective factors of driving behavior in elderly.

Riding the Adolescence: Personality Subtypes in Young Moped Riders and Their Association With Risky Driving Attitudes and Behaviors

The aim of the present study was to identify sub-types of moped riders based on a cluster analysis of specific personality characteristics (i.e., driving anger, anxiety, angry hostility, excitement-seeking, altruism, normlessness, and driving locus of control) within a large sample of Italian adolescents. The study had also the aim to compare the emerged sub-types of moped riders on measures of attitudes toward safe driving, risky driving behaviors (e.g., rule's violations and speeding, not using helmet, drinking and driving, etc.), and self-reported tickets and accident involvement. One thousand two hundred seventy-three Italian high school students aged from 13 to 19 years (mean_age = 15.43, SD = 0.98) with a valid driving license for moped participated to the study. Results revealed three sub-types of moped riders (namely risky, worried and careful moped riders), which differ significantly for risky driving behaviors, attitudes toward traffic safety, risk perception, and self-reported accident involvement. Importantly, the results of the present study showed that the personality and behavioral characteristics of the three sub-groups of moped riders substantially resembled those identified by previous studies with vehicle drivers of different ages; thus, empirically supporting the notion that certain combinations of personality characteristics are associated with risk driving tendencies and behaviors in both young moped riders and car drivers. Safe driving interventions can tackle risky driving beliefs and behavioral tendencies in young moped riders and car drivers by tailoring their messages according to the personality sub-types of the target groups.

Effects of socio-demographic, personality and mental health factors on traffic violations in Chinese bus drivers

The present study aims to determine the association between bus drivers' socio-demographic characteristics, personality traits, mental health and traffic violations. This case-control study included 596 bus drivers who were recruited during October 2014 to May 2016, including 295 drivers with traffic violations and 301 drivers without traffic violations. The bus drivers' personality traits and mental health were assessed by the Eysenck Personality Questionnaire (EPQ) and the Symptom Checklist (SCL-90-R). Drivers aged 26-35 years were 72% less likely to be involved in traffic violations compared to drivers aged ≤25 years (OR:0.284,95%CI:0.137-0.586). Drivers with ≤2 years driving experience were associated with almost a three-fold increased risk of traffic violations compared to ≥21 years driving experience (OR:3.174,95%CI:1.097-9.187). The OR value decreased with the increase of annual income (OR:4.631,95%CI:2.667-8.042;OR:3.569,95%CI:2.038-6.251;OR:3.781,95%CI:1.999-7.151). Occasionally drinking drivers and regularly drinking drivers, compared to nondrinking drivers, exhibited a higher risk of traffic violations (OR:2.487,95%CI:1.521-4.065;OR:3.271,95%CI:1.387-7.716).Extroversion and neuroticism were identified as significant factors associated with traffic violations (OR:1.262,95%CI:1.145-1.393;OR:1.159,95%CI:1.060-1.267).Somatization increased eleven-fold risk of bus drivers' traffic violations (OR:11.185,95%CI:4.563-27.419). The results revealed that bus drivers' traffic violations were mainly affected by specific socio-demographic characteristics, personality traits and mental health, which increase the risk of traffic violations.

Among substance-abusing traffic offenders, poor sleep and poor general health predict lower driving skills but not slower reaction times

Background

Traffic accidents are a significant health issue in Iran. Explanations for such accidents have included single consideration of the role of poor sleep and negative psychological trait and state variables. In this study, we examined whether and to what extent sleep, general health, and aggression can concomitantly predict driving behavior.

Methods

A total of 360 male traffic offenders (driving under substance use; mean age: 31 years) participated in this study. They completed the questionnaires covering sociodemographic, sleep-related, and behavior-related variables. In addition, their visual and acoustic reaction times were objectively tested.

Results

Poor sleep, poor general health, and higher aggression scores were associated with self-rated poor driving behavior. Poor sleep was directly associated with poor driving behavior and indirectly via poor general health and aggression. In contrast, visual and acoustic reaction times were unrelated to sleep, general health, aggression, or self-rated driving behavior.

Conclusion

To our knowledge, this is the first study in Iran to assess concomitantly poor sleep, poor general health, and higher aggression scores as independent predictors of poor driving behavior among a larger sample of substance-abusing traffic offenders. Furthermore, visual and acoustic reaction times were unrelated to sleep, general health, aggression, and driving behavior. Finally, importantly, poor sleep predicted both directly and indirectly poor driving behavior.

Personality factors and safety attitudes predict safety behaviour and accidents in elevator workers

Elevator accidents happen frequently and cause much loss. Personality factors and safety attitudes have been proved effective in predicting accidents in traffic and the workplace. The present study aimed to explore the effect of personality factors and safety attitudes in elevator accidents. A survey was carried out on 383 elevator installers and repairers in China, measuring personalities (conscientiousness, agreeableness and trait anxiety), safety attitudes (compliant and proactive), safety behaviours and accidents (occupational injuries). Approximately 60% of the elevator workers had been injured in the past 6 months. The structural equation model suggested that conscientiousness could predict compliant safety behaviour both directly and indirectly through safety attitude and could predict proactive safety behaviour. Agreeableness could predict compliant safety behaviour. Trait anxiety could predict occupational injuries. Recruiters should choose elevator workers who are conscientious, agreeable and of low trait anxiety. Safety trainings for elevator workers should focus on culturing their safety attitude.

Aberrant Driving Behaviour, Risk Involvement, and Their Related Factors Among Taxi Drivers

The current study aims to investigate the aberrant driving behaviour and risk involvement of Iranian taxi drivers. The sample comprised 405 Iranian taxi drivers, who were recruited with a cross-sectional design, using a self-completion questionnaire survey during October and November 2016. We contribute to the literature by understanding how and to what extent the socioeconomic, demographic, driving, and aberrant driving behaviours influence risk involvement (accident involvement and traffic tickets). The validated 27-item Driver Behaviour Questionnaire (DBQ) was applied to measure aberrant driving behaviour. The results from valid observations (n = 381) explored a four-factor solution (including errors, ordinary violations, lapses, and aggressive violations) of the DBQ. The results also showed that being a single driver, having a high annual driving mileage, and a high number of daily taxi trips were positively associated with accident involvement. Furthermore, there was a positive correlation between the more ordinary violations and aggressive violations and accident involvement. Establishing better training and qualification mechanisms for taxi drivers could be considered by traffic safety experts in order to reduce ordinary and aggressive violations.

Factors contributing to intercity commercial bus drivers' crash involvement risk

The aim of this study was to examine the influence of demographic, environmental, and occupational factors as well as behavioral characteristics of intercity bus drivers on their crash involvement risk. A total of 107 intercity bus drivers from Tehran, Iran, participated in the study. Logistic regression model suggested that smokers, those who drive during night to morning, less experienced drivers, and those who operate older buses are more likely to be involved in crashes. In addition, a 1-unit increase in the weekly driving hours might significantly increase the drivers' crash involvement risk. The model results also indicated that hazard monitoring, fatigue proneness, and thrill seeking might be considered other significant predictors of crash involvement risk. Implications of results are discussed.

Modeling of passengers' safety perception for buses on mountainous roads

This study had developed a passenger safety perception model specifically for buses taking into consideration the various factors, namely driver characteristics, environmental conditions, and bus characteristics using Bayesian Network. The behaviour of bus driver is observed through the bus motion profile, measured in longitudinal, lateral, and vertical accelerations. The road geometry is recorded using GPS and is computed with the aid of the Google map while the perceived bus safety is rated by the passengers in the bus in real time. A total of 13 variables were derived and used in the model development. The developed Bayesian Network model shows that the type of bus and the experience of the driver on the investigated route could have an influence on passenger's perception of their safety on buses. Road geometry is an indirect influencing factor through the driver's behavior. The findings of this model are useful for the authorities to structure an effective strategy to improve the level of perceived bus safety. A high level of bus safety will definitely boost passenger usage confidence which will subsequently increase ridership.

The traffic climate in China: The mediating effect of traffic safety climate between personality and dangerous driving behavior

Traffic safety climate is defined as road users' attitudes and perceptions of traffic in a specific context at a given point in time. The current study aimed to validate the Chinese version of the Traffic Climate Scale (TCS) and to explore its relation to drivers' personality and dangerous driving behavior. A sample of 413 drivers completed the Big Five Inventory (BFI), the Chinese version of the TCS, the Dula Dangerous Driving Index (DDDI) and a demographic questionnaire. Exploratory factor analysis and confirmatory factor analysis were performed to confirm a three-factor (external affective demands, internal requirements and functionality) solution of the TCS. The reliability and validity of the Chinese version of TCS were verified. More importantly, the results showed that the effect of personality on dangerous driving behavior was mediated by traffic climate. Specifically, the functionality of the TCS mediated the effect of neuroticism on negative cognitive/emotional driving and drunk driving, while openness had an indirect impact on aggressive driving, risky driving and drunk driving based on the internal requirements of the TCS. Additionally, agreeableness had a negative direct impact on four factors of the DDDI, while neuroticism had a positive direct impact on negative cognitive/emotional driving, drunk driving and risky driving. In conclusion, the Chinese version of the TCS will be useful to evaluate drivers' attitudes towards and perceptions of the requirements of traffic environment in which they participate and will also be valuable for comparing traffic cultures and environments in different countries.

The relationship between personalities and self-report positive driving behavior in a Chinese sample

Driving behaviors play an important role in accident involvement. Concretely speaking, aberrant driving behaviors would cause more accidents, and oppositely positive driving behaviors would promote to build safety traffic environment. The main goals of this study were to explore the positive driving behavior and its relationship with personality in a Chinese sample. A total of 421 licensed drivers (286 male and 135 female) from Beijing, China completed the Positive Driver Behavior Scale (PDBS), the Driver Behavior Questionnaire (DBQ), the Dula Dangerous Driving Index (DDDI) and the Big Five Inventory (BFI) on a voluntary and anonymous basis. The results showed that the Chinese version of the PDBS has both reliability and validity and that the PDBS was significantly correlated with the BFI. Specifically, the PDBS was negatively correlated with neuroticism (r = -0.38) and positively correlated with extraversion, agreeableness, conscientiousness and openness to experience (the correlation coefficient ranged from 0.36 to 0.55). In contrast with previous research, age was negatively correlated with the PDBS (r = -0.38) in our sample, which may have resulted from less driving experience or a lack of available cognitive resources.

Effects of altruism and burnout on driving behavior of bus drivers

Personality traits predict driving behaviors. However, the mechanism underlying this relationship has not been adequately investigated in professional drivers. The current study investigated the relationship between altruistic personality and aberrant driving behaviors, and the potential role of burnout. A total of 194 bus drivers completed questionnaires including measures of altruism, burnout and aberrant driving behaviors (aggressive violations, ordinary violations, errors, and lapses). The results showed that altruism was negatively correlated with burnout, and with all the four subcategories of aberrant driving behavior. Burnout fully mediated the relationship between altruism and aggressive violations, and partially mediated the relationship between altruism and lapses. These findings can be applied in the bus drivers' selection and interventions for burnout in order to improve the safety of public transport.

The Role of Personality Traits through Habit and Intention on Determining Future Preferences of Public Transport Use

A complex set of factors may affect transportation mode choice. While earlier studies have often considered objective factors in determining preferences of public transport use as a sustainable transportation, subjective factors such as personality traits are underexplored. Therefore, this study aimed to investigate the influence of personality traits on the number of future public transport use. Additionally, “car habit” and “intention toward using public modes” were considered to be important. For this purpose, a case study from departure passengers at Imam Khomeini International Airport (IKIA, Tehran, Iran) was conducted between January and February 2015 at IKIA. Results of structural equation modeling (SEM) shows that only neuroticism and extraversion personality traits were significant in determining future public transportation mode choice. However, the model indicates that these traits indirectly influence intention and car habit. Neuroticism was found to have a total effect of −0.022 on future public transport use, which represents a negative association with public transport use, while extraversion positively influenced future public transport use with a total effect of 0.031. Moreover, the results found interestingly that car access had a better fit to the data than the number of cars in household (NCH); both had significant positive effect on car habit, but only car access had a significant influence on intention. Furthermore, the effect of socio-demographic variables such as age, gender, educational level, income level, and body mass index (BMI) were determined to be significant in identifying choice of future transport mode to airports, which is explained in the discussion section of this paper.

The role of personality traits and driving experience in self-reported risky driving behaviors and accident risk among Chinese drivers

The purpose of this study was to explore the role of personality traits and driving experience in the prediction of risky driving behaviors and accident risk among Chinese population. A convenience sample of drivers (n=511; mean (SD) age=34.2 (8.8) years) completed a self-report questionnaire that was designed based on validated scales for measuring personality traits, risky driving behaviors and self-reported accident risk. Results from structural equation modeling analysis demonstrated that the data fit well with our theoretical model. While showing no direct effects on accident risk, personality traits had direct effects on risky driving behaviors, and yielded indirect effects on accident risk mediated by risky driving behaviors. Both driving experience and risky driving behaviors directly predicted accident risk and accounted for 15% of its variance. There was little gender difference in personality traits, risky driving behaviors and accident risk. The findings emphasized the importance of personality traits and driving experience in the understanding of risky driving behaviors and accident risk among Chinese drivers and provided new insight into the design of evidence-based driving education and accident prevention interventions.

A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area

Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries.

Poor mental health status and aggression are associated with poor driving behavior among male traffic offenders

BACKGROUND

In Iran, traffic accidents and deaths from traffic accidents are among the highest in the world, and generally driver behavior rather than either technical failures or environmental conditions are responsible for traffic accidents. In the present study, we explored the extent to which aggressive traits, health status, and sociodemographic variables explain driving behavior among Iranian male traffic offenders.

METHOD

A total of 443 male driving offenders (mean age: M =31.40 years, standard deviation =9.56) from Kermanshah (Iran) took part in the study. Participants completed a questionnaire booklet covering sociodemographic variables, traits of aggression, health status, and driving behavior.

RESULTS

Poor health status, such as symptoms of depression, anxiety, insomnia, and social dysfunction, and also higher levels of trait aggression explained poor driving behavior. Multiple regressions indicated that poor health status, but not aggression, independently predicted poor driving behavior.

CONCLUSION

Results suggest that health status concerns are associated with poor driving behavior. Prevention and intervention might therefore focus on drivers reporting poor mental health status.

Mental health status, aggression, and poor driving distinguish traffic offenders from non-offenders but health status predicts driving behavior in both groups

BACKGROUND

In Iran, traffic accidents and deaths from traffic accidents are among the highest in the world, and generally, driver behavior rather than technical failures or environmental conditions are responsible for traffic accidents. In a previous study, we showed that among young Iranian male traffic offenders, poor mental health status, along with aggression, predicted poor driving behavior. The aims of the present study were twofold, to determine whether this pattern could be replicated among non-traffic offenders, and to compare the mental health status, aggression, and driving behavior of male traffic offenders and non-offenders.

METHODS

A total of 850 male drivers (mean age =34.25 years, standard deviation =10.44) from Kermanshah (Iran) took part in the study. Of these, 443 were offenders (52.1%) and 407 (47.9%) were non-offenders with lowest driving penalty scores applying for attaining an international driving license. Participants completed a questionnaire booklet covering socio-demographic variables, traits of aggression, health status, and driving behavior.

RESULTS

Compared to non-offenders, offenders reported higher aggression, poorer mental health status, and worse driving behavior. Among non-offenders, multiple regression indicated that poor health status, but not aggression, independently predicted poor driving behavior.

CONCLUSION

Compared to non-offenders, offenders reported higher aggression, poorer health status and driving behavior. Further, the predictive power of poorer mental health status, but not aggression, for driving behavior was replicated for male non-offenders.