The link between personality, aggressive driving, and risky driving outcomes – testing a theoretical model

Chraif, Mihaela; Aniţei, Mihai; Burtăverde, Vlad; Mihăilă, Teodor

doi:10.1080/13669877.2015.1042500

Cited by 25 publications

(20 citation statements)

References 62 publications

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“…These studies have reported that low levels of agreeableness can predict high levels of risky driving outcomes, including crashes. 15-17,19,21,32,35-37,40,42-43 In contrast, research by Brown et al (2016) and Sween et al (2017) found no significant relationships between Agreeableness and RDBs. 20,41 There may be a number of reasons for these disparate findings.…”

Section: Discussionmentioning

confidence: 85%

“…Sensitivity analyses were conducted, and the findings for sensation seeking and driving anger remained consistent with the pooled r. The lower and higher pooled r in the sensitivity analysis for sensation seeking were 0.26 (95% CI: 0.21, 0.31), after omitting the Hartos et al 38 and 0.29 (95% CI: 0.25, 0.34) after omitting Falco et al, 23 respectively. For driving anger, a lower pooled r was found in the sensitivity analysis of 0.26 (95% CI: 0.12, 0.39) after omitting the Chraif et al 19 and a higher pooled r of 0.45 (95% CI: 0.17, 0.73) after omitting Falco et al 23 (Table 3).…”

Section: Resultsmentioning

confidence: 97%

“…This finding has been supported by several studies which have shown that those high in neuroticism show more risky driving behaviours. 17,19,21,34-35,37,39,42 In contrast, two studies reported that neuroticism had no relationship with RDBs. 6,41 The most likely reason for this discrepancy may be that these studies did not have sufficient sample sizes to answer the questions being studied.…”

Section: Discussionmentioning

confidence: 92%

“…15 Of the many PCs identified as potential predictors of RDBs, the big five personality factors (including extraversion, agreeableness, conscientiousness, neuroticism, and openness), sensation seeking, and driving anger have garnered the most support to date. 16 However, despite the fact that several studies have reported significant correlations (positive/negative) between PCs and RDBs, 16-19 a number of other studies did not find RBDs were significantly related to PCs, such as: agreeableness, 20 neuroticism, 6 extraversion, 20 openness, 21 sensation seeking, 22 and driving anger. 23 In a meta-analysis conducted by Demir et al 24 they reported that driving anger had significant associations with aberrant driving behaviors (based on Driver Behavior Questionnaire - DBQ) factors.…”

Section: Introductionmentioning

confidence: 95%

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Meta-analysis of the correlation between personality characteristics and risky driving behaviors

et al. 2019

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: Background: A systematic review and meta-analysis was performed to determine the relationships risky driving behaviors (RDBs) have with the big five personality factors, sensation seeking and driving anger. Methods: The PubMed, EMBASE, Web of Science, Scopus, Psychinfo, and the Cochrane Library databases were systematically searched. All original studies were retrieved that assessed the relationships RDBs had with the big five personality factors, sensation seeking, and driving anger. Heterogeneity between studies was examined using the Cochran Q statistic and I2 tests. After applying Fisher’s r-to-z transformation, the correlation coefficients (r) were summarized from each study and 95% confidence intervals (CIs) were estimated. Results: Overall, 22 studies were included in the meta-analysis, which included 11211 participants. The results showed that RDBs had a significant negative relationship with agreeableness (r -0.27; 95% CI, -0.36, -0.19; P less than 0.0001), but significant positive relationships with neuroticism (r 0.16; 95% CI, 0.03, 0.29; P=0.584), sensation seeking (r 0.28; 95% CI: 0.23, 0.33; P less than 0.0001) and driving anger (r 0.39; 95% CI: 0.14, 0.64; P=0.002). Conversely, RDBs were not significantly related to extraversion (r -0.01; 95% CI, -0.08, 0.05; P=0.705), conscientiousness (r -0.05; 95% CI, -0.21, 0.12; P=0.584), or openness (r -0.06; 95% CI, -0.12, 0.00; P=0.065). Conclusions: Therefore, it appears that individuals most likely to engage in risky driving behaviors would be low in agreeableness, but high in neuroticism, sensation seeking and driving anger.

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Section: Discussionmentioning

confidence: 85%

Section: Resultsmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 95%

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Meta-analysis of the correlation between personality characteristics and risky driving behaviors

et al. 2019

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“…Previous research has largely focused on three out of five Five-Factor Model (FFM) personality factors which does not account for the breadth of factors that comprise personality within the FFM (Bone & Mowen, 2006;Chraif et al, 2016;Dahlen et al, 2005;Sârbescu & Maricutoiu, 2019;Găianu et al, 2020). Prior studies also tend to use only one personality measure, which is inadequate in accounting for differences between measures that may pick up different relationships between the relevant personality constructs (Bone & Mowen, 2006;Chraif et al, 2016;Găianu et al, 2020;Dahlen et al, 2005;Sârbescu & Maricutoiu, 2019). The present study aimed to fill these gaps in breadth and consistency by using multiple personality measures to gain an in-depth view of the relevant personality factors and their corresponding subfactors and their impact on aggressive driving behavior.…”

Section: Introductionmentioning

confidence: 99%

Understanding Aggressive Driving: The Role of Personality and Individual Differences

Velazquez

Mouloua

2021

Proceedings of the Human Factors and Ergonomics Society Annual

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The goal of the present study was to examine the role of personality and individual differences on aggressive driving. It was hypothesized that personality and individual differences would be significantly related to aggressive driving behavior. A sample of n = 252 participants from a southeastern university and surrounding community were required to complete a series of driving questionnaires; the ADBQ, DBQ, and CFQ-D; and a series of personality questionnaires; the IPIP-NEO-PIR and BFI. Our results indicated that personality factors and individual differences significantly predicted aggressive driving outcomes. These results provided a preliminary personality based characteristic profile of the aggressive driver. These results also support the use of trait anger and trait cooperation independently from the subscales they are derived from (Neuroticism and Agreeableness) to predict aggressive driving behaviors. Theoretical and practical implications are discussed.

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Recognition and interpretation of aggressive driving behavior for heavy‐duty vehicles based on artificial neural network and SHAP

Cheng,

Chen,

et al. 2023

Hum Ftrs & Erg Mfg Svc

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Aggressive driving significantly impacts traffic safety, and heavy‐duty vehicle drivers are more liable for causing serious crashes. This paper analyzes drivers' aggressive driving behavior from the vehicle type perspective and identifies the influencing factors of aggressive driving behavior through artificial neural network (ANN) and Shapley additive explanations (SHAPs). Using Kaggle's open‐source aggressive driving data, we establish an ANN model to identify driving styles, where road conditions, environmental conditions, and vehicle parameters are independent variables and driving style is a dependent variable. The following measurements, including accuracy, recall, precision, and F1 score, are used to evaluate the model's performance, and the neural network got 85.33%, 82.32%, 84.16%, and 0.8308, respectively. To illustrate the influence of independent variables, the SHAP algorithm is used to analyze the model's feature importance. It was found that illumination and weather conditions influenced the model's performance along with the vehicle length. The number of lanes relates to driving style, and there were more aggressive driving behaviors on two‐lane roads than on single‐lane roads. Besides, heavy‐duty vehicle drivers were more likely to drive aggressively in wet road conditions and indulge in aggressive driving behaviors at night. Particularly, drivers of heavy‐duty vehicles were more likely to drive aggressively, provided that the vehicle in front was also a heavy‐duty vehicle. These findings inform heavy‐duty vehicle drivers to reduce aggressive driving behavior. The information is suitable for inclusion in driver education programs, thus improving traffic safety.

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The link between personality, aggressive driving, and risky driving outcomes – testing a theoretical model

Cited by 25 publications

References 62 publications

Meta-analysis of the correlation between personality characteristics and risky driving behaviors

Meta-analysis of the correlation between personality characteristics and risky driving behaviors

Understanding Aggressive Driving: The Role of Personality and Individual Differences

Recognition and interpretation of aggressive driving behavior for heavy‐duty vehicles based on artificial neural network and SHAP

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