The Role of Impulsivity, Attentional bias and Decision-Making Styles in Risky Driving Behaviors Among Male Drivers in Tehran

AUTHORS

Fatemeh Barati 1 , Abbas Pourshahbaz 1 , * , Masoud Nosratabadi 1 , Zahra Mohammadi 2

1 Department of Clinical Psychology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

2 Department of Clinical Psychology, School of Behavior Sciences and Mental Health (Tehran Psychiatric Institute), Iran University of Medical Sciences, Tehran, Iran

How to Cite: Barati F , Pourshahbaz A, Nosratabadi M, Mohammadi Z. The Role of Impulsivity, Attentional bias and Decision-Making Styles in Risky Driving Behaviors Among Male Drivers in Tehran, Int J High Risk Behav Addict. Online ahead of Print ; 9(2):e98001. doi: 10.5812/ijhrba.98001.

ARTICLE INFORMATION

International Journal of High Risk Behaviors and Addiction: 9 (2); e98001
Published Online: May 4, 2020
Article Type: Research Article
Received: September 11, 2019
Revised: February 24, 2020
Accepted: April 11, 2020
Crossmark
Crossmark
CHECKING
READ FULL TEXT

Abstract

Background: Road accidents are a major cause of deaths, injuries, and financial losses globally, especially in developing countries. Iran is one of the countries with a high rate of road accidents causing considerable damage in different domains. Therefore, in order to tackle this problem, we need to examine its causes.

Objectives: The aim of the present study was to examine the association of risky driving behavior with impulsiveness, attentional bias, and decision-making styles.

Methods: This was a descriptive-correlational study. The sample included 117 male drivers, aged 20 - 34 years, attending car insurance agencies in Tehran. The participants were selected using the convenience sampling method. The data were gathered using the Manchester Driver Behavior Questionnaire (DBQ), the Barratt Impulsiveness Scale (BIS), the Decision-Making Style Scale (DMS), and the Dot Probe Task to assess attentional bias. All the analyses were performed using SPSS, version 22.

Results: According to the results of the Pearson correlation coefficient, risky driving behavior was significantly correlated with impulsiveness subscales (P < 0.01) and attentional bias (P < 0.05). In addition, significant relationships were observed between risky driving behaviors and three decision-making styles, including rational (P < 0.05), spontaneous (P < 0.01), and avoidant (P < 0.01).

Conclusions: Based on the study results, impulsivity, decision-making styles, and attentional bias as factors influencing drivers’ cognitive skills related to driving, could explain the increase in the frequency of risky driving behavior.

Copyright © 2020, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

1. Background

Road accidents and physical injury and post-traumatic stress disorder (PTSD) are among the significant threats to the wellbeing of people around the world. About 1.2 billion people annually die in road accidents. According to the World Health Organization (WHO), if immediate preventive measures are not taken, road accidents will become the fifth leading cause of death by 2030. In Iran, as a developing country, around 19000 people die, and 800000 people are injured in road accidents each year (1). Three types of factors are involved in road accidents: human, road, and the environment. Human error is regarded as the most important factor in road accidents that directly or indirectly influences driving performance (2). Among the human factors, the role of psychological factors has attracted considerable attention. For example, in recent decades, several studies have examined the role of cognitive factors in safe driving and have shown that examining these factors could help reduce road accidents and improve road safety (3). Some previous findings have revealed the role of such factors as impulsiveness, attentional bias, and decision-making styles in risky driving behaviors (4-6).

Barratt et al. designed a comprehensive, systematic theory for impulsiveness, encompassing biological, environmental, and cognitive factors. They distinguished between the three components of impulsivity: (1) motor impulsiveness (tendency to act without planning in advance), (2) attentional impulsiveness (inability to concentrate on an immediate task or cognitive instability), and (3) non-planning impulsiveness (lack of planning and forethought) (7). Previous studies have shown that drivers with a high level of impulsivity tend to react to stimuli more quickly, and they are more likely to drive in a dangerous manner (2, 8, 9).

Attentional bias is another cognitive factor influencing driving safety (10). Attentional bias is the tendency to be focused on a stimulus despite one’s efforts to ignore it. Research evidence indicates the important role of automatic processes, including attentional bias in reinforcement, maintenance, and recurrence of different types of normal and abnormal behaviors (11).

Decision-making is another cognitive factor that plays a vital role in driving (12, 13). Decision making styles are different ways of determining the effects of each decision and finding a solution based on the available information and related considerations (12). Harren’s approach includes three different styles: rational (making decisions based on logic), dependent (making decisions based on others’ beliefs and expectations), and intuitive (making decisions based on feelings and emotions). Philips, Pazienza, and Ferrin added the avoidant style (tendency to avoid or postpone decision-making) to Harren’s model (14). Various studies have demonstrated associations between risky driving behaviors and psychological factors, such as impulsiveness, attentional bias, and decision-making styles (5, 15-17).

2. Objectives

Given the shortage of studies on this subject in Iran and the long history of exploring this issue in other countries, we decided to explore the role of cognitive factors in risky driving behaviors and to examine the association of impulsivity, attentional bias, and decision-making strategies with risky driving behaviors in Iranian drivers.

3. Methods

This was a descriptive-correlational study. The statistical population included all the male drivers in Tehran aged 20 - 34 years; among this population, 117 men attending car insurance companies in March 2018 in Tehran were selected as the study samples. The participants were selected using the convenience sampling method and based on the inclusion and exclusion criteria. The inclusion criteria were as follows: driving license obtained at least two years before the study and no history of brain damage, epilepsy, or psychiatric disorders. The exclusion criterion was a lack of consent to participate. After making the necessary arrangements, the drivers who met the inclusion criteria were included in the study. First, the Dot Probe Task was conducted, and then the questionnaires were given to the participants. Before collecting the data, the study objectives were explained to the participants, and they were reassured about confidential of their personal information. In addition, the participants were allowed to quit the study at any time. Data analysis was conducted using Pearson correlation coefficient and multiple regression analysis, and all the analyses were performed using SPSS, version 22.

3.1. Instruments

The Barratt Impulsiveness Scale (BIS): It has 30 items rated on a 4-point Likert-type scale. The items assess three factors, including attentional impulsiveness, motor, and non-planning impulsiveness (18). Various studies have shown the validity and reliability of this scale (19, 20). The Persian version of the BIS was validated by Ekhtiari et al. They found Cronbach’s alphas of 0.845 and 0.831 for the total scale among people with substance abuse disorder and healthy people, respectively (21). In the present study, a Cronbach’s alpha of 0.83 was obtained for the BIS.

The Manchester Driver Behavior Questionnaire (DBQ): This questionnaire assesses aberrant driving behaviors (errors and violations). It has 50 items that are rated on a 5-point Likert-type scale. Aberrant driving behavior is classified into four categories, including errors, lapses, intentional violations, and unintentional violations (22). Parker and Reason examined the reliability of the questionnaire among 80 drivers using an eight-week test-retest examination and found correlation coefficients of 0.81 and 0.75 for errors and violations, respectively (23). In the present study, the Persian version of the questionnaire was used that had been previously validated in Iran (24). We found a Cronbach’s alpha of 0.94 for the questionnaire.

The Dot Probe Task: This is a computer-based task used to assess attention and vigilance to a specific stimulus (in the present study, we used neutral pictures related to risky driving). This Dot Probe Task was first developed by MacLeod using words (25). In Iran, Sarfaraz et al. reconstructed it using the emotional faces of Iranian people (26).

The General Decision-Making Style Questionnaire (GDMSQ): The GDMSQ developed by Scott and Bruce was used to assess five different decision-making styles, including rational, intuitive, dependent, avoidant, and spontaneous. It has 25 items that are rated on a 5-point Likert-type scale (27). Loo et al. reported alphas ranging from 0.62 to 0.87 (28). Hadizadeh Moghadam and Tehrani found a Cronbach’s alpha of 0.78 for the total questionnaire and alphas ranging from 0.63 to 0.81 for its five subscales (29). In the present study, we found a Cronbach’s alpha of 0.64 for the total questionnaire and alphas ranging from 0.43 to 0.80 for the five subscales

4. Results

A total of 117 male drivers aged 20 - 34 years (mean = 26.43, SD = 3.87) participated in the present study. The participants had education levels from primary school to a Master’s degree, but most of them had a Bachelor’s degree. Among the study variables, non-planning impulsiveness (mean = 23, SD = 4.99) and attentional bias (mean = -3.6, SD = 32.32) had the highest and lowest means, respectively (Table 1).

Table 1. Means and Standard Deviations of Attentional Bias, Decision-Making Styles, and Impulsiveness
VariableMeanSD
Attentional impulsiveness16.494.16
Motor impulsiveness20.874.71
Non-planning impulsiveness234.99
Rational decision-making style17.803.58
Intuitive decision-making style17.863.30
Dependent decision-making style14.042.79
Spontaneous decision-making style11.853.98
Avoidant decision-making style11.493.55
Attentional bias-3.632.32

Pearson correlation coefficient was used to examine the relationship between risky driving behaviors and impulsiveness, attentional bias, and decision-making styles, the results of which are presented in Table 2. There were significant correlations between risky driving behaviors and impulsiveness subscales, including attentional impulsiveness (r = 0.519, P < 0.01), motor impulsiveness (r = 0.484, P < 0.01), and non-planning impulsiveness (r = 0.386, P < 0.01). In addition, a significant association was found between risky driving behaviors and attentional bias (r = 0.207, P < 0.05). Moreover, significant relationships were observed between risky driving behaviors and rational (r = -0.251, P < 0.05), spontaneous (r = 0.438, P < 0.01), and avoidant (r = 0.389, P < 0.01) decision-making styles, but no relationship was found between risky driving behaviors and dependent and intuitive styles.

Table 2. Correlation Coefficients between Risky Driving Behaviors and Impulsiveness Subscales, Decision-Making Styles, and Attentional Bias
Variable12345678910
1. Risky driving behavior1
2. Attentional bias0.207*1
3. Motor impulsiveness0.484**0.1401
4. Attentional impulsiveness0.519**0.1520.565**1
5. Non-planning impulsiveness 0.386**0.0920.556**0.480**1
6. Rational decision-making style-0.251**-0.120-0.348**-0.407**-0.421**1
7. Intuitive decision-making style-0.021-0.0410.137-0.062-0.205*0.311**1
8. Spontaneous decision-making style0.438**0.1060.503**0.358**0.391**-0.301**0.0751
9. Dependent decision-making style0.0980.0280.0290.1600.139-0.1520.1120.0551
10. Avoidant decision-making style0.389**0.2850.300**0.338**0.328**-0.245**0.0940.457**0.323**1

Multiple regression analysis was used to examine the effect of decision-making styles, impulsiveness, and attentional bias on risky driving behaviors. Among the variables examined, attentional impulsiveness had a significant effect on risky driving behaviors. The results of the regression analysis are presented in Table 3.

Table 3. Regression Analysis with Risky Driving Behavior as the Dependent Variable and Attentional Bias, Impulsiveness, and Decision-Making Styles as the Independent Variablesa
VariableSEBetaTSig.
Motor impulsiveness0.840.111.000.3
Attentional impulsiveness0.870.302.430.01
Non-planning impulsiveness0.76-0.04-0.350.7
Rational decision-making style1.06-0.08-0.670.5
Intuitive decision-making style0.98-0.07-0.690.4
Dependent decision-making style1.22-0.03-0.320.7
Spontaneous decision-making style0.920.161.220.2
Avoidant decision-making style1.020.121.070.2
Attentional bias0.130.030.350.7

aAdj. R2 = 0.26; R2 = 0.34; R = 0.58.

5. Discussion

The main objective of the present study was to examine the relationship of risky driving behavior with impulsivity, attentional bias, and decision-making strategies in Iranian drivers. In line with the previous findings, our findings showed positive associations between risky driving behaviors and attentional, motor, and non-planning impulsiveness (5, 16, 17, 30). There were also positive associations between risky driving behaviors and spontaneous and avoidant decision-making styles and a negative association between risky driving behaviors and the rational decision-making style (31-34). Finally, the results indicated a positive relationship between attentional bias and risky driving behaviors; this is also consistent with previous findings (15). Among all the impulsivity subscales, only attentional impulsivity significantly predicted risky driving behaviors (Beta = 0.30); this finding is in line with the results of previous studies on the effects of impulsivity on risky driving behaviors (35).

From biological and neuropsychological perspectives, people with an underactive BIS are less likely to recognize unpleasant stimuli and perceive them as threatening. People with an overactive BAS, due to being highly motivated to gain rewards, have difficulty in learning inhibitors, while people with an overactive BIS are highly sensitive to punishment (36). Sensitivity to reward may present itself in the form of traffic or rule violations that are observed in impulsive individuals, and sensitivity to punishment may present itself in the form of adjustment to the environment (37). In addition, damage to the orbitofrontal cortex (OFC) that is located in the ventromedial frontal cortex (VMF) leads to a type of motor impulsivity in which the person is not able to control their behavior and repeats a risky behavior despite learning the subsequent rewards or punishments. This is not true for a damage to the VMF that is limited to this region and does not spread out to the adjacent areas; people with this type of damage suffer from another type of impulsivity, called attentional impulsivity (38). As was pointed out in the Results section, and attentional impulsivity can predict risky driving behaviors. This finding can be explained from the cognitive perspective, according to which impulsivity refers to the lack of ability to inhibit impulses (36).

Various studies have reported that decision-making as a major cognitive function is related to behavioral inhibition (39) and that impairment in inhibitory control as an executive function, inability to refrain from instant rewards and impulsivity as an emotional state are powerful predictors of risky decision-making (40).

Regarding the relationship between decision-making styles and risky behaviors, it can be argued that risky behavior is characterized by dysfunction in attentional processing, meaning that people with risky behaviors only pay attention to affect-eliciting experiences such as winning or losing; therefore, they are not able to learn from their mistakes (41). On the other hand, it has been observed that decision-making problems in people with ventromedial damage is related to a kind of blindness to the consequences of actions in the future (i.e., paying more attention to instant gratification or less attention to harm) (42).

Finally, people with risky driving behaviors had increased response times in the Stroop test when presented with emotionally negative words. The reason behind this is that negative words require more attention compared to neutral words. Therefore, people with a higher response time in the Strop test tend to have more driving errors. This finding is explained by the fact that attentional bias results from the effects of emotions on cognition and that emotional state impacts driving conditions (15). In addition, the study results showed that negative emotional states influence the driver's traffic-dependent behavior and cognition. While negative emotions increase drivers’ perception of driving risks, at the same time, they increase their desire to engage in risky driving behaviors, such as speeding (43).

Overall, the study results indicated impulsivity, decision-making styles, and attentional bias as factors influencing drivers’ cognitive skills related to driving that can explain the increase in the frequency of risky driving behaviors.

Acknowledgements

Footnotes

References

  • 1.

    Pakgohar A, Tabrizi RS, Khalili M, Esmaeili A. The role of human factor in incidence and severity of road crashes based on the CART and LR regression: a data mining approach. Procedia Computer Science. 2011;3:764-9. doi: 10.1016/j.procs.2010.12.126.

  • 2.

    Dahlen ER, Martin RC, Ragan K, Kuhlman MM. Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving. Accid Anal Prev. 2005;37(2):341-8. doi: 10.1016/j.aap.2004.10.006. [PubMed: 15667821].

  • 3.

    Milos̆ević S, Milić J. Speed perception in road curves. Journal of Safety Research. 1990;21(1):19-23. doi: 10.1016/0022-4375(90)90044-c.

  • 4.

    Zheng T, Qu W, Zhang K, Ge Y. The relationship between attentional bias toward safety and driving behavior. Accid Anal Prev. 2016;96:22-8. doi: 10.1016/j.aap.2016.07.034. [PubMed: 27490776].

  • 5.

    Bıçaksız P, Özkan T. Impulsivity and driver behaviors, offences and accident involvement: A systematic review. Transportation Research Part F: Traffic Psychology and Behaviour. 2016;38:194-223. doi: 10.1016/j.trf.2015.06.001.

  • 6.

    Fishbein M, Cappella JN. The Role of Theory in Developing Effective Health Communications. Journal of Communication. 2006;56(suppl_1):S1-S17. doi: 10.1111/j.1460-2466.2006.00280.x.

  • 7.

    Mobini S, Pearce M, Grant A, Mills J, Yeomans MR. The relationship between cognitive distortions, impulsivity, and sensation seeking in a non-clinical population sample. Personality and Individual Differences. 2006;40(6):1153-63. doi: 10.1016/j.paid.2005.11.006.

  • 8.

    Schwebel DC, Severson J, Ball KK, Rizzo M. Individual difference factors in risky driving: the roles of anger/hostility, conscientiousness, and sensation-seeking. Accid Anal Prev. 2006;38(4):801-10. doi: 10.1016/j.aap.2006.02.004. [PubMed: 16527223].

  • 9.

    Arthur W, Doverspike D. Predicting motor vehicle crash involvement from a personality measure and a driving knowledge test. Journal of Prevention & Intervention in the Community. 2001;22(1):35-42. doi: 10.1080/10852350109511209.

  • 10.

    Xu Y, Li Y, Wang G, Yuan X, Ding W, Shen Z. Attentional bias toward safety predicts safety behaviors. Accid Anal Prev. 2014;71:144-53. doi: 10.1016/j.aap.2014.05.013. [PubMed: 24922613].

  • 11.

    Williams JM, Mathews A, MacLeod C. The emotional Stroop task and psychopathology. Psychol Bull. 1996;120(1):3-24. doi: 10.1037/0033-2909.120.1.3. [PubMed: 8711015].

  • 12.

    Muzheng G. Theory and methods of risky identification of driving behavior [dissertation]. University of Transportation of South-West; 2009.

  • 13.

    Azadeh A, Zarrin M, Hamid M. A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area. Accid Anal Prev. 2016;87:17-33. doi: 10.1016/j.aap.2015.11.007. [PubMed: 26651129].

  • 14.

    Harren VA. A model of career decision making for college students. Journal of Vocational Behavior. 1979;14(2):119-33. doi: 10.1016/0001-8791(79)90065-4.

  • 15.

    Sani SRH, Tabibi Z, Fadardi JS, Stavrinos D. Aggression, emotional self-regulation, attentional bias, and cognitive inhibition predict risky driving behavior. Accid Anal Prev. 2017;109:78-88. doi: 10.1016/j.aap.2017.10.006. [PubMed: 29049929].

  • 16.

    Pearson MR, Murphy EM, Doane AN. Impulsivity-like traits and risky driving behaviors among college students. Accid Anal Prev. 2013;53:142-8. doi: 10.1016/j.aap.2013.01.009. [PubMed: 23428428]. [PubMed Central: PMC5242231].

  • 17.

    Cheng ASK, Ting KH, Liu KPY, Ba Y. Impulsivity and risky decision making among taxi drivers in Hong Kong: An event-related potential study. Accid Anal Prev. 2016;95(Pt B):387-94. doi: 10.1016/j.aap.2015.12.021. [PubMed: 26748873].

  • 18.

    Bayle FJ, Bourdel MC, Caci H, Gorwood P, Chignon JM, Ades J, et al. [Factor analysis of french translation of the Barratt impulsivity scale (BIS-10)]. Can J Psychiatry. 2000;45(2):156-65. doi: 10.1177/070674370004500206. [PubMed: 10742875].

  • 19.

    Barratt ES. Perceptual-motor performance related to impulsiveness and anxiety. Percept Mot Skills. 1967;25(2):485-92. doi: 10.2466/pms.1967.25.2.485. [PubMed: 6080627].

  • 20.

    McLeish KN, Oxoby RJ. Measuring impatience: Elicited discount rates and the Barratt Impulsiveness Scale. Personality and Individual Differences. 2007;43(3):553-65. doi: 10.1016/j.paid.2007.01.002.

  • 21.

    Ekhtiari H, Rezvanfard M, Mokri A. [Impulsivity and its Different Assessment Tools: A Review of View Points and Conducted Researches]. Iranian Journal of Psychiatry and Clinical Psychology. 2008;14(3):247-57. Persian.

  • 22.

    Dionne G, Fluet C, Desjardins D. Predicted risk perception and risk-taking behavior: The case of impaired driving. Journal of Risk and Uncertainty. 2007;35(3):237-64. doi: 10.1007/s11166-007-9023-8.

  • 23.

    Parker D, West R, Stradling S, Manstead AS. Behavioural characteristics and involvement in different types of traffic accident. Accident Analysis & Prevention. 1995;27(4):571-81. doi: 10.1016/0001-4575(95)00005-k.

  • 24.

    Alavi SS, Mohammadi M, Soori H, Kalhori SM, Sepasi N, Khodakarami R, et al. Iranian Version of Manchester Driving Behavior Questionnaire (MDBQ): Psychometric‎Properties. Iranian J Psychiatry. 2016;37(1):11.

  • 25.

    MacLeod C, Mathews A, Tata P. Attentional bias in emotional disorders. J Abnorm Psychol. 1986;95(1):15-20. doi: 10.1037//0021-843x.95.1.15. [PubMed: 3700842].

  • 26.

    Sarfaraz MR, Taghavi SMR, Goudarzi MA, Kefayati MH. Theoretical Fundamental and Developing a Computerized Visual Probe Task For Attentional Bias in Social Anxiety Disorder. J Res Psychol Health. 2008;2(1):71-83.

  • 27.

    Baiocco R, Laghi F, D'Alessio M. Decision-making style among adolescents: relationship with sensation seeking and locus of control. J Adolesc. 2009;32(4):963-76. doi: 10.1016/j.adolescence.2008.08.003. [PubMed: 18848722].

  • 28.

    Loo R. A psychometric evaluation of the General Decision-Making Style Inventory. Personality and Individual Differences. 2000;29(5):895-905. doi: 10.1016/s0191-8869(99)00241-x.

  • 29.

    Hadizadeh Moghadam A, Tehrani M. A Study of The Relationship Between General Decision Making Styles Of Managers in Public Organizations. Journal of Public Administration. 2008;1(1):123-38.

  • 30.

    Cheng AS, Ng TC, Lee HC. Impulsive personality and risk-taking behavior in motorcycle traffic offenders: A matched controlled study. Personality and Individual Differences. 2012;53(5):597-602. doi: 10.1016/j.paid.2012.05.007.

  • 31.

    Schlösser T, Dunning D, Fetchenhauer D. What a Feeling: The Role of Immediate and Anticipated Emotions in Risky Decisions. Journal of Behavioral Decision Making. 2013;26(1):13-30. doi: 10.1002/bdm.757.

  • 32.

    Balogh KN, Mayes LC, Potenza MN. Risk-taking and decision-making in youth: relationships to addiction vulnerability. J Behav Addict. 2013;2(1). doi: 10.1556/JBA.2.2013.1.1. [PubMed: 24294500]. [PubMed Central: PMC3840427].

  • 33.

    Scott-Parker B, Weston L. Sensitivity to reward and risky driving, risky decision making, and risky health behaviour: A literature review. Transportation Research Part F: Traffic Psychology and Behaviour. 2017;49:93-109. doi: 10.1016/j.trf.2017.05.008.

  • 34.

    Kusev P, Purser H, Heilman R, Cooke AJ, Van Schaik P, Baranova V, et al. Understanding Risky Behavior: The Influence of Cognitive, Emotional and Hormonal Factors on Decision-Making under Risk. Frontiers in Psychology. 2017;8. doi: 10.3389/fpsyg.2017.00102.

  • 35.

    Bakhshani NM. Impulsivity: a predisposition toward risky behaviors. Int J High Risk Behav Addict. 2014;3(2). e20428. doi: 10.5812/ijhrba.20428. [PubMed: 25032165]. [PubMed Central: PMC4080475].

  • 36.

    Avila C. Distinguishing BIS-mediated and BAS-mediated disinhibition mechanisms: a comparison of disinhibition models of Gray (1981, 1987) and of Patterson and Newman (1993). J Pers Soc Psychol. 2001;80(2):311-24. doi: 10.1037/0022-3514.80.2.311. [PubMed: 11220448].

  • 37.

    Li J, Li Y, Liu X. The effects of motor impulsiveness and optimism bias on risky driving behavior in Chinese urban areas. IEEE. 2008:605-9. doi: 10.1109/itsc.2008.4732582.

  • 38.

    Ekhtiari H, Behzadi A. Prefrontal cortex, decision making deficits, and assessment instruments. Advances in Cognitive Science. 2001;3(3):64-86.

  • 39.

    Hare TA, Camerer CF, Rangel A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science. 2009;324(5927):646-8. doi: 10.1126/science.1168450. [PubMed: 19407204].

  • 40.

    Harle KM, Shenoy P, Paulus MP. The influence of emotions on cognitive control: feelings and beliefs-where do they meet? Front Hum Neurosci. 2013;7:508. doi: 10.3389/fnhum.2013.00508. [PubMed: 24065901]. [PubMed Central: PMC3776943].

  • 41.

    Reynolds BW, Basso MR, Miller AK, Whiteside DM, Combs D. Executive function, impulsivity, and risky behaviors in young adults. Neuropsychology. 2019;33(2):212-21. doi: 10.1037/neu0000510. [PubMed: 30589284].

  • 42.

    Elliott R, Dolan RJ, Frith CD. Dissociable functions in the medial and lateral orbitofrontal cortex: evidence from human neuroimaging studies. Cereb Cortex. 2000;10(3):308-17. doi: 10.1093/cercor/10.3.308. [PubMed: 10731225].

  • 43.

    Hu T, Xie X, Li J. Negative or positive? The effect of emotion and mood on risky driving. Transportation Research Part F: Traffic Psychology and Behaviour. 2013;16:29-40. doi: 10.1016/j.trf.2012.08.009.

  • COMMENTS

    LEAVE A COMMENT HERE: