Introduction

The increase in motorization and mobility has brought attention to road safety and the role of driver behavior in road traffic crashes (RTCs). Many studies have focused on exploring the human factors affecting driving behavior that can affect global patterns of traffic and pose risks to other road users [1–3]. Several methods have been used for gathering and analyzing data on driver behavior, including surveys, naturalistic driving studies, simulation studies, and event data recorders. Of note, surveys are the most common method for gathering information on a wide range of driver behaviors. However, these methods could be used alone or in combination to gain a comprehensive view of driver behavior and help researchers to understand the underlying causes of accidents and to develop interventions to improve safety.

The Driver Behavior Questionnaire (DBQ) is a widely used instrument to examine drivers’ self-reported aberrant behaviors that increase the risk of RTCs [4]. The original version of the DBQ, developed by Reason et al. (1990), consists of 50 items classified into three dimensions: violations, errors, and lapses [5]. Violations are distinct from errors and lapses as they cover behaviors that deliberately contravene safe driving practices, while errors are defined as a failure of a planned sequence of mental or physical activities in the selection of an action to achieve the intended goal [6]. Lapses are defined as an unwitting deviation of action from intention [5]. The DBQ instrument evaluates the driver behavior under a theoretical framework and reflects the metacognitive skills of the drivers.

Driving anger, which refers to the emotional state of displeasure, fury, or rage experienced by drivers, has also been a focus in the driving safety literature. It is considered a special case of cognitive distraction and has been linked to personality traits and common road situations such as heavy traffic, impeding events, and the behavior of other road users [7]. Similar to cognitive distraction, driving anger can withdraw attention from the information necessary for safe operation of a vehicle, leading to a mental impairment. Studies have found anger to be one of the most important factors involved in unsafe driving [8, 9]. The Driving Anger Scale (DAS) is widely used to measure the propensity of drivers to become angry while encountering potentially anger-provoking driving situations [7]. It can measure six types of driving anger: hostile gestures, slow driving, traffic obstruction, illegal driving, and police presence anger. Anger can interfere with cognitive processes such as attention and judgement, leading to excessive confidence and lower risk perception among angered drivers [10, 11]. It is unclear whether anger leads to RTCs due to increased cognitive load and unintentional failures or due to deliberate unsafe driving behaviors.

A close relationship has been found between anger and driving behavior, but it is complex and not always positive [12, 13]. Studies have found that drivers with higher levels of anger are more likely to commit violations on the road [9, 14–16]. However, the relationship between anger and errors is mixed, with some studies finding a positive association and others finding no significant association [16–18]. Some researchers have found different associations between different types of driving anger and driving aberrations [13]. These findings highlight the importance of investigating the relationship between anger and aberration on a subscale level. Furthermore, the association between socio-demographic variables and aberrant driving behaviors is an important aspect to consider when investigating the factors that contribute to road traffic crashes. The type of driver, such as professional versus non-professional, as well as factors like age, gender, and driving experience, can all have a significant impact on aberrant driving behaviors and should be considered in studies exploring this topic [19–22].

In Lebanon, road traffic injuries are the leading cause of unintentional injury and death with an estimated fatality rate of 18.1 per 100,000 population [23]. According to the statistics issued by the Lebanese Ministry of Interior, 2666 RTCs were recorded in 2020 leading to 337 fatalities [24]. Of note, driver behavior was one of the main reported causes of the RTCs in the country. In addition, the transportation system is facing several problems such as bad road infrastructure, a lack of public transportation, an increasing number of vehicles, traffic congestion, and RTCs. In addition, it is well known that traffic congestion in urban areas can lead to discomfort and road rage among drivers. Since driving anger was found in the literature very likely to be associated with aberrant driving behaviors leading to RTCs among drivers [25], therefore, it is of great interest to examine the effects of driving anger on driving behavior among Lebanese drivers. This is reasonable driver behavior explains a significant amount of variance in traffic accidents than do vehicle, roadway, or environmental factors and so far, studies on road user behaviors in Lebanon are scarce and no previous research in Lebanon has investigated such kind of relationship. However, it is important to note that the Driving Anger Scale (DAS) and Driver Behavior Questionnaire (DBQ) subscales have different psychological characteristics and using overall scores from these scales may mask the real associations at the subscale level [25]. Therefore, for a more accurate understanding of the relationship between driving anger and aberrant driving, DAS and DBQ subscales will be used in this study, rather than overall scores. This will allow for a consideration of both the effect of anger on unintentional cognitive failure "errors" and deliberate infringements of accepted principles of safe driving "violations". The findings of this study are expected also to contribute to driver behavior research by providing a more detailed understanding of how anger and aberrant driving behaviors are related. Such in-depth exploration is needed to help researchers and policymakers understand which interventions are more effective and to determine the best approach to apply practical driving safety education. In addition, investigating the association between driving anger and sociodemographic characteristics has strong substantial impacts on driver selection and driver education which in turn could improve road safety in the country.

The present study aims to investigate, based on self-reported data, the relationship between socio-demographic variables, driving anger, and the self-reported aberrant behavior among Lebanese drivers and to determine which anger dimension is linked to driving behavior.

Materials and methods

Results and discussion

DBQ and DAS subscales

For DBQ subscales, the α-values ranged between 0.68 and 0.814, indicating good internal consistency (Table 1). The overall reliability of the DBQ-L scale was good (α = 0.85). Of the four subscales, the highest mean score was for aggressive violations followed by ordinary violations, lapses, and errors. With regards to DAS, the α-values obtained from subscales ranged between 0.87 and 0.93, indicating an excellent internal consistency. The overall reliability of the DAS-A scale was good (α = 0.93).

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Table 1. Summary statistics for the DBQ and DAS subscales among Lebanese drivers.

https://doi.org/10.1371/journal.pone.0283293.t001

Correlation between driver anger and driver behavior (DBQ-L) subscales

Aggressive violations were found to be positively correlated to hostile gesture (r = 0.140), slow driving (r = 0.184), discourtesy (r = 0.071), police presence (r = 0.163) and traffic obstruction (r = 0.092).Similarly, ordinary violations subscale was positively correlated to discourtesy (r = 0.101), police presence (r = 0.215), traffic obstruction (r = 0.061), slow driving(r = 0.177) and illegal driving (r = 0.112). Meanwhile, lapses were only positively correlated to police presence (r = 0.216) and traffic obstruction (r = 0.114). Errors were positively correlated to anger prompted by the police presence(r = 0.284) and slow driving (r = 0.111). Interestingly, only one correlation was found between the anger instigated by illegal driving and the violation subscale (Table 2).

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Table 2. Pearson correlations between DAS and DBQ-L subscales.

https://doi.org/10.1371/journal.pone.0283293.t002

DBQ-L and socio-demographic variables

Gender differences revealed that men reported a higher tendency to commit aggressive violations (p = 0.048), and ordinary violations (p = 0.049), compared to females (Table 3). The four dimensions of aberrant driver behavior (aggressive violations, ordinary violations, errors, and lapses) were significantly affected by the occupation and the educational level of the surveyed drivers. Drivers with lower levels of education (secondary education or less) were more likely to be involved in aberrant driving behaviors, such as aggressive violations, ordinary violations, errors, and lapses. Ordinary violation (r = -0.559, p < 0.001) and lapses (r = -0.544, p < 0.001), were negatively correlated with age. Younger drivers were more likely to be involved in aberrant driving behaviors, such as ordinary violations, and lapses. However, errors (r = 0.442, p < 0.001) were positively associated with age and had a different pattern where errors decreased for young drivers.

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Table 3. DBQ-L and sociodemographic characteristics of the Lebanese drivers.

https://doi.org/10.1371/journal.pone.0283293.t003

Additionally, aggressive violations (p<0.001), ordinary violations (p<0.001), errors (p<0.001) and lapses (p = 0.016<0.001) increased with annual mileage. Despite the decrease of violations (r = -0.142, p<0.001) and lapses (r = -0.135, p<0.001) with increasing driving experience, errors were found increasing with driving experience (r = 0.161, p<0.001).

Hierarchical regression

As a result of the hierarchical regression exploring the factors associated with aggressive violations, the first model that included in its first step of regression analysis the sociodemographic factors, explains 16% of the variation and was statistically significant (p<0.001) (Table 4). Older age ((β = -0.084, 95% CI (-0.127: -0.009), p = 0.018) and female gender ((β = -0.181, 95% CI (-0.353: -0.089) p = 0.048) were protector factors against committing aggressive violations. However, being a professional driver ((β = 0.126, 95% CI (0.029–0.527), p = 0.001) and increasing annual mileage ((β = 0.058, 95% CI (0.033–0.174), p = 0.045) were positively associated with the involvement of driver in aggressive violations. In the second step, the six subscales of DAS were included in the model in addition to the demographic variables which additionally explain 11% of the model and it is also statistically significant. Anger prompted by hostile gesture (β = 0.125, 95% CI(0.030–0.169), p = 0.047), discourtesy (β = 0.015, 95% CI(0.009–0.190), p = 0.014), police presence (β = 0.114, 95% CI (0.103–0.352), p<0.001), traffic obstruction (β = 0.152, 95% CI(0.137–0.312), p = 0.014), and slow driving (β = 0.142, 95% CI(0.109–0.484), p<0.001), were found positively associated with aggressive violation. In terms of ordinary violation, the first model explains 9.8% of the variation (p<0.001). Being female, increasing age, and higher educational level were found protective factors reducing the risk of drivers’ involvement in traffic violations. On the contrary, extensive years of driving experience, increased annual mileage, and being a professional driver were associated with violations among drivers. The second step explains 15.4% of the variation with 5.1% further explanation than demographic variables. All the DAS subscales instigated by hostile gestures(β = 0.145, 95% CI (0.037–0.325), p = 0.04), discourtesy(β = 0.099, 95% CI (0.076–1.176), p = 0.009), traffic obstruction(β = 0.116, 95% CI (0.078–0.194), p<0.001, police presence(β = 0.151, 95% CI (0.034–0.578), p<0.001), illegal(β = 0.075, 95% CI (0.036–0.097), p = 0.039) and slow driving(β = 0.114, 95% CI (0.042–0.431), p<0.001 were found to be associated with of ordinary violations. The variation of errors was explained with 11.3% by demographic variables. Larger driving experience and education higher than secondary level were protectors from erroneous driving behavior. Conversely, older age, increasing annual mileage, and working as a professional driver were positively associated with the errors among drivers. The inclusion of DAS subscales increased the explanation of errors by 6.2%. Anger originated from police presence (β = 0.227, 95% CI (0.130–0.685), p<0.001) and slow driving (β = 0.164, 95% CI (0.101–0.972), p = 0.045) were positively associated with erroneous driving behavior. However, no association was found between the remaining DAS subscales such as hostile gestures, traffic obstruction, discourtesy, illegal driving, and the errors committed while driving.

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Table 4. Summary of hierarchical multiple regression results of DAS associations with aberrant driver behavior.

https://doi.org/10.1371/journal.pone.0283293.t004

Regarding Lapses, the first model including only socio-demographic variables explained 5.6% of the variation. Alike the errors dimension, larger driving experience and education higher than secondary level were negatively associated with lapses and increasing annual mileage and working as a driver were negatively associated with erroneous driving behavior. Conversely, they were associated with errors among drivers. However, the second step which comprised DAS dimensions described additionally 4.7% of the lapses. Only anger provoked by the presence of police (β = 0.167, 95% CI (0.119–1.068), p<0.001), traffic obstruction (β = 0.086, 95% CI (0.046–0.651), p = 0.007) and the slow driving (β = 0.087, 95% CI (0.045–0.823), p = 0.01) were found positively associated with lapses.

Discussion

Driving behavior is a complex and multidisciplinary research domain and aberrant driving behaviors that threaten the safety of road users should be avoided. This could not be achievable without unveiling the factors that reside behind such behavior. This study conducted on Lebanese driver sample revealed that several factors, including age, gender, occupation, education, annual mileage, and driving experience, were associated with aberrant driving behaviors, specifically aggressive and ordinary violations. Younger age, male gender, being a professional driver, and lower educational level were found to be positively associated with a higher tendency to commit these types of violations. Additionally, the study found that errors were positively associated with older age, increasing mileage, and working as a driver, while larger driving experience and higher education were negatively associated with erroneous behavior. Furthermore, the study identified specific dimensions of driving anger (hostility, discourtesy, police presence, traffic obstruction, and slows driving) that were associated with aggressive violations. All the DAS subscales were found associated with ordinary violations and some DAS subscales were found to be positively correlated with errors and lapses. Overall, the study highlights the need for understanding the complex factors that contribute to aberrant driving behaviors in order to develop effective interventions to improve road safety.

In terms of socio-demographic variables, gender, age, education level, and occupation were found to be associated with aberrant driving behaviors. Specifically, the study found that males had a higher tendency to commit aggressive and ordinary violations, while no significant difference in self-reported driving errors was found across gender. This could be related to the fact that men have a higher tendency to force others to get out of the way and consider it a submissive action. Similar results were found in previous studies where it was also stated that males exhibited driving violations more frequently than females [5, 29–32]. Our results in terms of errors are consistent with the findings of the study conducted by Reason et al. [5]. Of note, other studies have reported a higher tendency in females to report lapses and errors which was not found among Lebanese drivers [5, 30, 32, 33]. Although the stereotype is that men are more focused on one task while driving and women are more cautious and able to multitask, this study found that women were more likely to commit errors and shortcomings related to space perception while driving. This finding may be due to Lebanese women’s desire to conceal their weaknesses while driving in order to avoid stereotypes. Another possible explanation is that women tend to be more cautious while driving, which may lead to fewer errors.

As for age, our study revealed a decreased pattern of aggressive and ordinary violations with increased age. Younger age was found to be positively correlated with an increase in both violations scores (ordinary and aggressive). This could be related to the increased maturity with age, which might mellow drivers and make them less likely to adopt aggressive driving behavior. Consistently with other studies, our findings showed that men and younger drivers are more likely to display aggressive violations while driving. Additionally, older age was found to be positively associated with self-reported errors. This could be related to the decline in cognitive and physical abilities that often comes with age. It highlights the importance of interventions and programs aimed at older drivers to help improve their driving skills and safety on the road. Overall, this study provides important insights into the socio-demographic factors associated with aberrant driving behaviors and the need to address these factors in order to improve road safety for all road users [34].

The study found that being a professional driver was positively associated with a higher tendency to commit aggressive and ordinary violations. One possible explanation is that professional drivers often have higher workloads and tight time schedules, which may lead to increased stress levels and a greater likelihood of engaging in risky driving behaviors [35]. In other words, they were more exposed to higher traffic volumes on the road and to a situation-specific emotional state that could affect their behavior. This was consistent with the results of a study conducted in Qatar that reported a higher likelihood of risky driving among professional drivers [36]. The study also highlighted the importance of addressing this issue, as professional drivers play a significant role in the traffic system of Lebanon, and there is a need to improve the ’Traffic Safety Culture’ among Lebanese professional drivers. Additionally, it is important to examine and understand the personal acceptance of risky driving behaviors among professional drivers in order to develop effective interventions to improve road safety [37].

Additionally, a higher educational level (university degree or above) was found to be a protective factor from committing ordinary violations, lapses, and errors while driving. In other words, education could provide the driver with the necessary knowledge and skills to navigate the road safely and make better decisions while driving. Furthermore, the study highlights the importance of investing in educational programs and awareness campaigns targeting younger, less educated drivers and professional drivers to improve road safety in Lebanon.

In terms of driving-related variables, our findings showed that all dimensions of risky behavior (errors, lapses, aggressive and ordinary violations were positively associated with the increased annual mileage, whereas violations increased with larger driving experience. Comparable results were reported by a study conducted among Australian drivers [6]. However, beginner drivers lack confidence in their driving performance and are still in the phase of confidence-building. Hence, the limited driving experience in handling various traffic situations makes them more anxious to perpetrate a traffic violation [38]. When they get more experience, they will feel more familiar with the traffic environment and increase, therefore, their involvement in traffic violations. Similarly, a study concerning the traffic safety culture of professional drivers in Qatar indicated that experienced professional drivers are more likely to perform risky driving behaviors [36].

As for the driving errors dimension, it was also found affected by driver characteristics. This was consistent with other studies [18, 39, 40]. More specifically, age, education as well as driving experience were found to have the highest effect on driving error in our present research. Remarkably, errors in our study exhibited a different pattern where it was found that errors increased with age indicating that older drivers are more likely to make driving errors. This could be explained that young drivers have better mental and physical characteristics than older drivers reducing their likelihood of committing errors. In comparison with our findings, a previous study has found that errors decrease for young drivers but remained quite unchangeable with age within the older samples [6]. Both drivers’ experience and education were protective factors from erroneous behavior indicating that a more experienced and more educated driver is less likely to perform driving errors. This finding probably means that both of these characteristics help drivers to properly manage a potentially dangerous situation and protect themselves from committing an error. It is noteworthy that there is confusion and disparity in the literature in terms of age and experience and their impact on aberrant driver behavior. A specific insight was provided by Wells and al. [41], who reported that older drivers had consistently lower violation scores than younger drivers. In this case, the effects of age on errors could be explained by the fact that novice drivers are still in the learning phase, hence improving their skills and reducing their driving errors. A driving simulator study about errors and violations during training of pre-licensed drivers showed similar results [42]. At a later age, acquired driving skills can be weakened and a further increase in errors could be expected.

Our study also showed that aberrant driver behavior subscales were positively correlated to anger subscales such as hostile gestures, illegal driving, slow driving, discourtesy, police presence, and traffic obstruction. Different anger triggers were found to have differing impacts on aberrant driving behaviors in our study. This result is consistent with the finding of a study conducted by Zhang et al. [13]. Similar to other studies, our findings suggested that the relationship between driving anger and driver behavior depends on different natures of anger or situational characteristics, respectively [13, 43–45].

Based on the frustration-aggression hypothesis, aggressive driving is a result of anger or frustration caused by thwarted goals [46]. Our study also found that anger prompted by hostile gestures; discourtesy, police presence; traffic obstruction, and slow driving were positively associated with aggressive violations. This finding is consistent with the driving anger factors reported by Zhang and Chan’s study [13], which either block the goal to drive safely, the ‘‘general survival goal”, or the arrival goal. Previous studies showed that hindrance anger trigger was associated with aggressive driving [13, 44]. In addition, the relationship between anger and aggressive expressions has been reported in numerous studies [17, 47]. Hence, driving anger was positively associated with aberrant driving behaviors in the sense of deliberate infringements that are most aggressive and targeted at other road users. Angry drivers attempt to influence other drivers, either to achieve their driving goals or to take revenge for other road users’ driving behaviors. These results are alarming especially because the anger–aggression correlation might have become stronger in more recent years, given the increasing traffic congestion problem worldwide.

For ordinary violations, all the DAS subscales instigated by hostile gestures, discourtesy, traffic obstruction, and police presence, illegal and slow driving were found positively correlated with ordinary violations [17, 47]. Many studies highlighted such kind of correlation between anger and violations. This highlights the importance of all aspects of anger originating from any driving situation described in the 33 items of DAS in leading to traffic violations and also stressed the importance to mitigate factors triggering anger on road.

In this study, we found that only anger originated from police presence and slow driving was positively associated with erroneous driving behavior. Apart from triggering aggressive violations and deliberate traffic infractions, anger can negatively impact driving behavior, since research has demonstrated that anger could compromise the cognitive performance of drivers including judgment and reasoning which may rise the possibility of making errors [48]. Of note, the effects of driving anger on errors have been explored also in simulation-based studies where Jeon et al. found that angry drivers made more errors than the control group [49], and Stephens et al. showed that drivers who had exhibited a higher level of anger in a simulated driving situation were also more projected to miss dangerous traffic hazards [50]. Furthermore, a recent meta-analysis found a significant correlation of 0.179 between driving anger and errors [12]. However, previous investigations have also reported weak or non-significant relationships between driving anger and errors [51].

With regards to lapses, our findings revealed that anger provoked by the presence of police, traffic obstruction, or slow driving could lead to lapses while driving. These results were consistent with the findings of a study conducted about dimensions of driving anger and their relationships with aberrant driving among Chinese drivers which demonstrated that the three dimensions of driving anger have different relations with aberrant driving behaviors [13].

Conclusion

This study found that driving anger and its dimensions were positively associated with aggressive and ordinary violations, as well as driving errors. The results suggest that anger can distract drivers from processing important information while driving, leading to deliberate and aggressive behaviors and an increase in driving errors. However, the impact of driving anger was found to depend on the triggers of anger. To address this issue and reduce the likelihood of aberrant driving behavior, it is important to provide drivers with training in coping strategies to manage their anger while driving. This could include techniques such as deep breathing, visualization, and cognitive reframing, as well as strategies for avoiding or managing anger triggers.

Declarations

Supporting information

Acknowledgments

The authors acknowledge all drivers who participated in this study as well as the students of traffic major in IPNET Lebanese Higher Institute of Technical & Professional, Bir Hassan who helped us in the data collection.