Accident Analysis and Prevention 73 (2014) 236–241
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Hostility, driving anger, and dangerous driving: The emerging role of hemispheric preference Yori Gidron a, *, Esma Gaygısız b , Timo Lajunen c a
Faculty of medicine & pharmacy, the Free University of Brussels—VUB, Belgium Dept. of psychology, Middle Eastern Technical University, Turkey c Dept. of psychology, Norwegian University of Science and Technology, Trondheim, Norway b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 2 May 2011 Received in revised form 8 August 2014 Accepted 11 September 2014 Available online xxx
Background: Various studies have implicated psychosocial variables (e.g., hostility) in risk of dangerous driving and trafﬁc accidents. However, whether these variables are related to more basic neurobiological factors, and whether such associations have implications for the modiﬁcation of psychosocial risk factors in the context of driving, have not been examined in depth. This study examined the relationship between hemispheric preference (HP), hostility and self-reported dangerous driving, and the ability to affect driving anger via hemisphere activating cognitive exercises (HACE). Methods: In Study 1, 254 Turkish students completed questionnaires of hostility, HP and driving behavior. In Study 2, we conducted a “proof of concept” experimental study, and tested effects of left, right and neutral HACE on driving anger, by exposing N = 650 Turkish students to written scenarios including either logical (left hemisphere), visuo-spatial (right hemisphere) or “mild doses” of both types of contents (control). Results: In Study 1, left-HP was associated with higher hostility and with more dangerous driving, and hostility mediated the relationship between L-HP and reported driving behavior. In Study 2, only rightHACE led to immediate signiﬁcant reductions in self-reported driving anger. Conclusions: Left-HP is related to hostility and to dangerous driving, and it may be possible to partly reduce driving anger by right-HACE. Future studies must replicate these ﬁndings with objective measures, more enduring interventions and longer follow-ups. ã 2014 Published by Elsevier Ltd.
Keywords: Hostility Driving anger Dangerous driving Hemispheric preference Cognitive exercises
1. Introduction Trafﬁc accidents (TA) are a complex multi-factorial public health problem, resulting from environmental, vehicle and human factors. Of the many human factors previously associated with TA, one, namely hostility, has received relatively a lot of attention. Hostility is the relative stable tendency to behave antagonistically, think cynically and feel anger across contexts (Barefoot, 1992). Hostility was found to correlate with self-reported TA and dangerous driving (e.g., Gidron et al., 2003). Furthermore, in prospective studies, hostility predicted TA and dangerous driving (e.g., Norris et al., 2000). These ﬁndings have important implications for TA, because of two reasons. First, they may serve to help identify in advance people at risk of dangerous driving and of TA, for closer monitoring and prevention. Second, though mainly based on correlation designs, these ﬁndings propose to conduct
* Corresponding author. E-mail address: [email protected]
(Y. Gidron). http://dx.doi.org/10.1016/j.aap.2014.09.011 0001-4575/ ã 2014 Published by Elsevier Ltd.
intervention trial studies aimed at reducing hostility to possibly reduce TA. Such interventions have been developed for other contexts (Cardiac patients; Gidron et al., 1999). Of greater importance, anger-management interventions have been developed and shown to be effective speciﬁcally in high-anger drivers (Deffenbacher et al., 2002). However, though statistically signiﬁcant, the effect sizes of cognitive-behavioral interventions on reducing anger or hostility are often limited (e.g., Gidron et al., 1999). It is possible that more basic neurobiological factors underlie or “drive” the relationship between hostility and dangerous driving. Such factors could not only help to explain the origin of such hostility and dangerous driving in part, but may also guide additional, and possibly more effective neuro-scientiﬁcally-based forms of intervention to prevent dangerous driving. Past studies have associated hostility with excessive right hemisphere activity (e.g., Demaree and Harrison, 1997). Behaviorally, hostility, and particularly anger expression can be divided into anger-out, the tendency towards explosive anger expression, and anger-in, the tendency to inhibit anger expression (Spielberger et al., 1985). In contrast to Demaree
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and Harrison (1997), one study found that left hemisphere activity was associated with anger-out (Hewig et al., 2004). Anger-out may be more relevant to dangerous driving since it can be manifested externally by observable behaviors including rude gestures, honking with the horn, and even aggressive acts towards drivers, all closely related to and possibly leading to dangerous driving. Such externally manifested hostility may also provoke other drivers, resulting in a possible vicious circle of hostile driving. However, it remains unknown whether left or right hemisphere functions are related to dangerous driving, and whether hostility, the broader personality construct which includes anger and aggression, plays a role in this relationship. Hemispheric preference (HP) or cerebral asymmetry reﬂects the relatively stable tendency to activate or use more certain functions of one hemisphere versus the other (e.g., Davidson, 2004). Recently, left-HP was indeed discussed as related to anger/hostility (Hofman, 2008). The present research examined the relationship between HP, hostility and driving anger, and dangerous driving. In Study 1, we examined the relationship between HP, hostility and self-reported dangerous driving behavior, beyond the effects of age and gender. Following the ﬁnding in Study 1 that left-HP was associated with both hostility and dangerous driving, Study 2 reﬂected a “proof of concept”, and examined the effects of cognitive exercises aimed to minimally activate the right hemisphere in contrast to the left hemisphere, on driving anger. 2. Study 1 2.1. Method 2.1.1. Participants and procedure The data were collected from 254 university student volunteers in Ankara, Turkey (158 males and 96 females). Two-hundred and four participants had a driving license. Only the driving license holders were included in the ﬁnal analyses about hemispheric preference, hostility and aberrant driving, whereas the whole sample was used for assessing the reliability of the instruments. The participants were assured for their anonymity and conﬁdentiality. The participants ﬁlled out questionnaires assessing aberrant driver behavior (Driver questionnaire by Reason et al., 1990), a scale assessing hemispheric preference (HP), the brief New–Buss hostility scale (Gidron et al., 2001), and demographic variables, as described below. Among the drivers with a driving license, 68% were men, 32% were women. Participants had a mean age of 21.8 years (range 18– 28 years, SD = 1.85 years). The mean lifetime mileage was 9541.75 km (range 0–300,000 km, SD = 30,334.5 km) and mean driving experience time was 2.6 years (range 0–7 years, SD = 1.5 years). The average annual mileage was 3094.6 km (range 0–100,000 km, SD = 9168.0 km). 2.1.2. Measures 22.214.171.124. Demographic measures. Respondents answered questions about their age, gender, student status, the number of years a full driving license had been held, lifetime mileage driven, and annual mileage. 126.96.36.199. Driver behavior questionnaire (DBQ). The Driver behavior questionnaire (DBQ) with extended violations was used to measure self-reported violations and errors (Reason et al., 1990). Violations were deﬁned as “deliberate deviations from those practices believed necessary to maintain the safe operation of a potentially hazardous system.” Errors can be deﬁned as a “failure of planned actions to achieve their intended consequences that can involve the unwitting deviation of action from intention (slips and
lapses) or departure of planned actions from some satisfactory path toward desired goals (mistakes).” Hence, the violations are committed deliberately but errors are done involuntarily. Moreover, violations and mistakes are potentially risky whereas slips and lapses are harmless. The extended version of the DBQ (Lawton et al., 1997) used in this study included aggressive violations (3 items; e.g., to sound your horn to indicate your annoyance), ordinary violations (8 items; e.g., pull out of junction so far that the driver with right of way has to stop and let you pass), mistakes (8 items; e.g., misjudging the speed of another vehicle when overtaking), and lapses (8 items; e.g., forget where you left your car in a car park). Participants were asked to indicate how often they committed each of the 28 behaviors in the previous year on a six-point scale (0 = never, 5 = very often). The Turkish translation and the factor structure of the DBQ had been validated in studies conducted among both professional and non-professional drivers (see Özkan et al., 2006). In the present sample, the alpha reliabilities of the “slips and lapses”, “mistakes”, “ordinary violations” and “aggressive violations” were 0.86, 0.91, 0.89, and 0.75, respectively. 188.8.131.52. Hemispheric preference (HP) scale. The hemispheric preference (HP) scale (Wegner and Wells, 1985) was used to assess HP. This is a valid 12-item test, for which each item has four response options: two reﬂect mostly left-HP functions (verbal, logical), and two reﬂect mostly right-HP functions (visual, creative). The left-HP index is computed by subtracting the total number of right-HP responses from the total left-HP ones, dividing this fraction by their total, and multiplying it by 100. Thus, higher scores on the HP index reﬂect left-HP. 184.108.40.206. The brief New–Buss hostility scale. The brief New–Buss hostility scale (Gidron et al., 2001) was translated to Turkish and used as a measure of trait hostility. The New–Buss hostility scale includes 8 items to which participants reply by using a 5-point scale (1 = extremely uncharacteristic of me, 5 = extremely characteristic of me). The original aggression questionnaire by Buss and Perry (1992), from which the New–Buss was derived, has been translated to Turkish and used in Turkey before (see Güleç et al., 2008). Moreover, Gidron et al. (2001) reported that the New– Buss hostility scale was cross-culturally valid against multiple criteria including deviant driving, other measures of anger/ hostility and atherosclerosis in men. In the present study, the internal alpha reliability coefﬁcient of the scale was 0.75. 220.127.116.11. Statistical analysis. First, we tested correlations between all background measures and the main study variables. Second, we tested whether HP and hostility correlated with each other and with dangerous driving using Pearson correlations. Finally, we tested a mediation model, by examining whether after statistically controlling for hostility, HP still correlated with driving behavior, using analyses of covariance since HP was dichotomized at the median. The latter was done, to increase interpretability of the results, due to hypothesized differences between left and right-HP participants (Davidson, 2004). 3. Results Groups of HP were created by splitting the HP scores at the median. No age differences were found between participants with right-HP (M = 25.02, SD = 9.01 years) and those with left-HP (24.62, SD = 8.73 years), t(160) = .27, p > .05. Similarly, the distribution of men and women was not signiﬁcantly different between right-HP and left-HP participants (x2(1) = .23, p > .05). Table 1 depicts the means (SD) of participants on hostility and DBQ subscales, according to their HP group. As shown in Table 1,
Y. Gidron et al. / Accident Analysis and Prevention 73 (2014) 236–241
Table 1 Means and standard deviations (SD) of participants classiﬁed by hemispheric preference (HP) on hostility and driving behavior subscales. Variable
Hostility DBQ-aggression DBQ-violations DBQ-lapses DBQ-mistakes
relationships (see Fig. 2), while HP was not a mediator between hostility and DBQ subscales. 4. Discussion
21.49 1.44 1.42 1.13 1.03
5.56 1.19 1.00 0.76 0.78
22.86* 1.77* 1.65* 1.47* 1.46*
5.55 1.15 1.07 0.98 1.10
Note: HP: hemispheric preference; DBQ: driving behavior questionnaire; *p < .05; (all tests are 2-tailed).
left-HP participants scored signiﬁcantly higher on hostility than right-HP participants (t(163) = 2.97, p = .003). Concerning DBQ subscales, left-HP participants scored signiﬁcantly higher on aggressive violations (t(149) = 2.02, p = .045), ordinary violations (t(149) = 2.26, p = .025), lapses (t(149) = 2.15, p = .033), and on driving mistakes (t(96) = 2.47, p = .015) than right-HP participants. Fig. 1 depicts the relationship between HP and each of the DBQ subscales. Hostility was, as expected, positively correlated with aggressive violations (r =0.215, p = .008), ordinary violations (r = .246, p = .002), driving lapses (r = .333, p < .001) and with driving mistakes (r = .326, p < .001). We then tested whether hostility mediated the relationship observed between HP and DBQ subscales. Using a series of analyses of covariance, controlling for hostility, HP was no longer signiﬁcantly associated with aggressive violations (p = .147), ordinary violations (p = .107), driving lapses (p = .206) and only tended to be associated with driving mistakes (p = .075). In contrast, hostility remained signiﬁcantly related to each DBQ subscale, when HP was statistically controlled for (p levels ranging from 0.024 to 0.000). Thus, hostility mediated the HP-DBQ
Fig. 1. Relationship between hemispheric preference (HP) and driver behavior questionnaire (DBQ) subscales.
This study may be among the ﬁrst to begin to identify the neural factors possibly underlying the epidemiological relationships between psychological risk factors and dangerous driving. We examined the relationship between hemispheric preference (HP) and hostility, with self-reported dangerous driving, using valid measures. We observed a positive correlation between hostility and self-reported dangerous driving behavior, in line with previous studies (Gidron et al., 2003; Norris et al., 2000). Furthermore, left-HP was positively correlated with both hostility and with self-reported dangerous driving behavior. Importantly, hostility emerged as a mediator in the relationship between left-HP and self-reported dangerous driving behavior. A ﬁnal series of analyses ruled out the possibility that left-HP mediated the hostility–dangerous driving relationship. The mediating role of hostility is depicted as a model in Fig. 2. This could mean that the possible effects of hostility on driving stem from a more basic neuropsychological process of left-HP, whose possible effects on driving operate via hostility. Past studies on the relationship between anger and hostility and HP or hemispheric lateralization have been inconsistent. Some studies found hostility to be related to right-HP (Demaree and Harrison, 1997) while others found hostility to be related with leftHP (e.g., Hewig et al., 2004). This may stem from the fact that hostility and anger include an experiential component of negative affect, possibly linked to behavioral inhibition and to the right hemisphere, and a different behavioral component of antagonism (and anger-out) possibly linked to approach behavior and to the left hemisphere (Davidson, 2004; Costa et al., 1989). Indeed, one can view the right hemisphere as reﬂecting behavioral inhibition and the left hemisphere as reﬂecting behavioral activation. In line with such classiﬁcation, a more recent review proposes that factors such as anger (and perhaps hostility), as well as risk taking and positive affect, which reﬂect “approach oriented” and interpersonal activities, are more mapped onto the left hemisphere. In contrast, anxiety and depression, which reﬂect more intra-personal inhibition or withdrawal, are more mapped onto the right hemisphere (Hofman, 2008). The fact that also dangerous driving, which may be manifested by “aggressive approach” behaviors between drivers, correlated with left-HP, supports and extends the validity of our ﬁnding that hostility is related to left-HP. However, the main limitation of this study was its use of a crosssectional correlation design. These ﬁndings need to be replicated in a prospective or experimental design, to verify whether HP and hostility predict and cause dangerous driving. An experimental approach in studying this topic would also help to clarify whether HP has a causal role in driving hostility/anger and in its modulation, and this was the aim of Study 2.
Fig. 2. The relationship between hemispheric preference (HP), hostility and dangerous driving.
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5. Study 2
Study 1 found that left-HP was related to hostility and to selfreported dangerous driving. Furthermore, hostility mediated the relationship between left-HP and self-reported dangerous driving. Given our results in Study 1 showing an association between hostility and left-HP, and since hostility includes approach oriented behaviors, hostility can be expected to be related to the left hemisphere’s functions or activity, and partly be under its control (Hewig et al., 2004; Hofman, 2008). Due to the phenomenon of inter-hemispheric inhibition (e.g., Sullivan, 2004), it is possible that by activating the right hemisphere, levels of hostility and driving related anger (possibly mediated by the left hemisphere) may decline. Activating a hemisphere could be done by electrical stimulation using repetitive transcranial magnetic stimulation (rTMS). However, while relatively accurate and clearly stimulating the brain, such an approach is costly and logistically not feasible as a possible en mass intervention, given the prevalence of road hostility and dangerous driving behavior. Such an approach may also carry certain health and ethical constraints concerning its safety and control over one’s behavior. Alternatively, exposing people to cognitive exercises was also found to activate a hemisphere as measured by an EEG, though this depended on the quality of individual performance (Papousek and Schulter, 2004). Furthermore, in a randomized controlled trial in early schizophrenia, cognitive exercise therapy led to less loss of gray matter in various cortical regions and this mediated the effects of such exercises on improved cognition (Eack et al., 2010). Finally, Nombela et al. (2011) found that cognitive training for patients with Parkinson’s Disease led to brain activity patters during the stroop test which resembled more healthy controls’ brain activity patterns. Together, these studies show that cognitive exercises can actually yield important changes in the brain. Performing hemisphere-speciﬁc cognitive exercises is not at all costly and is under people's full control. To preliminarily test this possibility and a causal relationship between HP and driving-anger, Study 2 investigated the feasibility of exposing people to reading material that aimed to activate one of the hemispheres (left, right) or both (control), and its subsequent effects on driving anger levels. This preliminary study constituted merely a “proof of concept” study. Since we observed in Study 1 that left-HP was positively associated with hostility, it was expected that an exercise aimed at right-hemisphere activation may reduce driving anger compared to other conditions, via inter-hemispheric inhibition (Sullivan, 2004).
6.2.1. Background These included participants’ age, gender, dominant hand for writing, as well as estimated lifetime and annual millage (in km) and years of driving experience. We included here the measure of HP used in Study 1 (Wagner and Wells, 1985), as a covariate variable (see below).
6. Methods 6.1. Participants The sample initially included 657 students of various undergraduate programs at the Middle East Technical University in Ankara, Turkey. Student volunteers were recruited in classrooms, dormitories and in the campus in general. Participants (except the students helping in data collection) did not receive any ﬁnancial reward. The only criteria for participating were: (1) willingness to take part, (2) a valid driving license and (3) student status. We excluded those without a driving license (N = 7). This resulted with a sample of 650 students, of whom 62.6% were male, 37.4% were female. Participants had a mean age of 28.8 (range 18–64 years, SD = 10.56 years). The mean estimated lifetime mileage was 74,785.4 km (range 0–5,000,000 km, SD = 300,533.8 km) and mean driving experience time was 7.5 years (range 0–38, SD = 8.2 years). The average estimated annual mileage was 7124.8 km (range 0–150,000 km, SD = 14,713.1 km).
6.2.2. Driving anger This was assessed with the Driving Anger Scale (DAS; Deffenbacher et al., 1994), which originally includes 33 driving related situations, initially derived from 53 such situations. In its development, it showed high internal reliability (Cronbach’s Alpha = .90). In the present study, we derived from it three subscales based on a study by Lajunen et al. (1998), which included anger from others’ Reckless Driving (Cronbach’s Alpha = .91), Direct Hostility (Cronbach’s Alpha = .83), and anger when Progress is Impeded (Cronbach’s Alpha = .84). The overall Cronbach’s Alpha of these three subscales in the present study was also high (0.91). 6.2.3. Interventions These interventions formed a “proof of concept” or feasibility study, to examine whether it is possible to develop hemisphereactivating cognitive exercises (HACE) and whether they have any preliminary effects on driving anger. Participants were randomly assigned to one of three groups of HACE: left-HACE, right HACE or a neutral (control) exercise. In all three conditions, participants read one paragraph, always about the same topic and of approximately the same length (10 lines). The topic was about lakes. For the leftHACE, participants read a paragraph describing lakes from a logical and analytic perspective: how they are formed, their shape and what they serve for people and animals. For the right-HACE, the paragraph described lakes from a detailed visuo-spatial perspective: their form, the scenery, the water, birds ﬂying around them, etc. These instructions followed known differences between hemispheric functions, where the left one mediates more analytic thinking while the right one mediates more intuitive and visuo-spatial processes (e.g., Goel et al., 2007). Finally, the “hemispherically neutral” control condition included information about a lake without too many analytic/logical or too many visuo-spatial details, and represented a balance between the left- and right-HACE conditions. 6.2.4. Design and procedure This study used a mixed experimental design, where Time (pre, post intervention measure) was a within-subjects factor and Group (left-HACE, right-HACE or control) was a between subjects factor. Students entered the class, and were informed that this study is part of their learning experience, but that their participation is totally voluntary. They then completed the baseline DAS and general background information and were randomly assigned to either the left-HACE, the right-HACE or neutral condition. After reading their respective paragraph (‘intervention’), they completed again the DAS, as well as the HP test, used as a covariate. 6.2.5. Statistical analysis First, we examined group equality at baseline, using an analysis of variance (ANOVA) for continuous data (e.g., age) and chi-square tests for categorical data (e.g., gender). Second, we used a mixeddesign ANOVA, where Time (pre, post intervention) was the within-subjects factor and Group (left-HACE, right-HACE or control) was the between-subjects factor. Our main interest was the Time Group interaction which was followed by simpleeffects tests. In the main ANOVA, we controlled for annual millage and sex, and retested it with adding scores of HP as an additional covariate, to control for its effects.
Y. Gidron et al. / Accident Analysis and Prevention 73 (2014) 236–241 Table 2 Means and standard deviations (SD) of hemisphere-activating cognitive exercise (HACE) groups on total driving anger scale (DAS) scores.
7. Results 7.1. Equality of groups at baseline First, no statistically signiﬁcant differences were found on continuous scores between groups (for all ANOVAS, p > .05). Similarly, no group differences were found in distribution of gender and of left/right handed participants (all ps > .05). Finally, left and right handed participants did not differ on DAS scores or on HP scores (all ps > .05). Hence, effects of these variables were not statistically controlled for in the following analyses. Nevertheless, since annual mileage (reﬂecting road exposure) and gender usually have a strong inﬂuence on driver behavior, we added them as covariates, to be more rigorous. 7.2. Effects of hemisphere-activating cognitive exercises (HACE) on driving anger Using a mixed-design ANOVA, controlling for sex and annual millage, we found a trend for a signiﬁcant Time Group interaction in relation to DAS scores (F(2,602) = 2.44, p = .088). When adding participants’ score on hemispheric preference (HP) as an additional covariate, this interaction became signiﬁcant (F (2,579) = 3.59, p = .028). We then followed this interaction by a simple-effects analysis, which revealed that in the left-HACE group, Time had no effect (F(1,196) = 0, NS), in the control group, Time had no effect (F(1,198) = .82, p > .05), while only in the rightHACE group, Time had a statistically signiﬁcant effect on driving anger, controlling for sex and annual millage (F(1,204) = 3.99, p < .05). A similar pattern was seen when adding HP as another covariate. Table 2 depicts the means and SDs of DAS scores before and after the interventions and Fig. 3 shows this graphically. We then examined which of the three DAS subscales was affected by the right-HACE. The Time Group interaction only tended to be signiﬁcant for the DAS subscale of being irritated by Slow Driving (F(2,602) = 2.48, p = .084). In contrast, the Time Group interaction was not signiﬁcant for Reckless Driving (F (2,601) = 1.64, p = .195) or for Direct Hostile Behavior (F (2,598) = .947, p = .388). Indeed, concerning the Slow Driving subscale, only in the right-HACE group, did scores decrease over time (p = .05), but not in the left-HACE group (p = .72) or in controls (p = .27). These results became more prominent when adding HP as a covariate. 8. Discussion This preliminary study examined the feasibility to inﬂuence drivers’ anger levels, by using an intervention based on a neuroscientiﬁc rationale. We show here that right-HACE led to
Group Left-HACE Pre Post Right-HACE Pre post Control Pre Post
SD: standard deviation; HACE: hemisphere-activating cognitive exercises; *p < .05.
statistically signiﬁcant reductions in DAS scores, while left-HACE and neutral exercises did not. These results were limited to one DAS-subscale, that of facing a slow driving vehicle. These ﬁndings are partly in line with our ﬁndings in Study 1 and support our hypothesis that right-HACE will reduce driving anger, possibly due to inter-hemispheric inhibition of the left hemisphere (e.g., Sullivan, 2004). However, these results only partly support those of Study 1, since if indeed the left hemisphere accounts for and modulates anger and hostility, then the left-HACE group would have reported temporary increases in DAS scores, but this did not occur. Furthermore, these ﬁndings must be taken with great caution due to the use of very minimal HACE interventions, and since assessment of driving anger was done only seconds after the intervention, with no follow-up. We shall now discus in greater detail the theoretical and practical applications of our ﬁndings from both studies, and their limitations. 9. General Discussion The two studies presented here investigated the role of HP in hostility/anger, a psychological risk factor of dangerous driving and TA. Study 1 showed that left-HP was related to both hostility and to self-reported dangerous driving, while Study 2 shows that it may be partly possible to reduce driving anger by exposure to a cognitive exercise (visuo-spatial description) which may activate the right hemisphere. The fact that hostility emerged in Study 1 as a possible mediator in the relationship between left-HP and dangerous driving has several theoretical and preventive implications. First, these ﬁndings suggest that hostility may be linked to a much more basic neural factor, namely left-HP, whose effects are even manifested early in life (Davidson, 2004; Davidson and Fox 1989). Second, these ﬁndings also inform us that the role of hostility in driving may partly originate from such neural HP
Fig. 3. Effects of hemisphere-activating cognitive exercises (HACE) on driving anger.
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tendencies. The fact that hostility mediated the relationship between left-HP and self-reported dangerous driving behavior suggests that left-HP may be manifested partly by antagonistic behaviors (e.g., general rudeness, non-cooperativeness) and cynical cognitions (e.g., “others are out there to get me”), possibly leading to dangerous driving behavior (e.g., dangerous speeding, overtaking unsafely). If replicated, these ﬁndings have implications for the identiﬁcation and for possible prevention of dangerous driving behavior by affecting psychological risk factors via neuro-modulation. First, measures of HP may be less prone to inﬂuences of social desirability than those of hostility since the former may be less “contaminated” by social values and judgment than measures of hostility. In addition, HP can also be measured by neuropsychological tests (the line bisection test) or by an electroencephalogram (Davidson, 2004), which are not self-report measures. Thus, pending replication of our ﬁndings with other measures of HP or hemispheric lateralization, it may be more beneﬁcial to screen for HP rather than for hostility, to identify potentially dangerous drivers (using both measures may even be better). Second, our ﬁndings have possible implications for neuro-modulation of dangerous driving. Study 2 aimed to preliminarily examine whether simple cognitive exercises, aimed at activating one of the hemispheres, could alter driving anger. We found that reading a paragraph containing visuo-spatial content, aimed at activating the right hemisphere, led to signiﬁcant immediate reductions in driving anger, particularly towards slow drivers. These ﬁndings were unaffected by drivers’ sex, annual millage or their own HP. These ﬁndings support those of Papousek and Schulter (2004), (Eack et al., 2010) and Nombela et al. (2011) showing that cognitive exercises actually increase hemispheric activity or alter brain structures, but raise multiple questions. First, can neuro-modulation, via repetitive transcranial magnetic stimulation (rTMS) or via HACE, alter both psychological risk factors (e.g., hostility) and actual dangerous driving? Second, if replicated, what types and doses of right-HACE are needed, and how long do their effects remain? Future studies need to address these many issues. Once these questions are answered and pending replication of our preliminary results, performing daily HACE has no costs, and can be done by drivers, empowering them and helping people take part in accident reduction. This could have serious implications for public health. The two studies obviously have several limitations. First, we included only self-reported measures of HP and driving behavior. HP can be measured with more objective and still inexpensive measures including the line bisection method (e.g., van Vugt et al., 2000). Driving behavior may either be observed (e.g., by an investigator present in a participant’s vehicle), may be measured by a simulator, or by a “black box” inside the vehicle and recording driving behaviors. Second, Study 1 was cross-sectional and its ﬁndings need to be replicated using a prospective design, and test whether HP predicts dangerous driving and even TA with objective measures of driving. Third, Study 2 used a very minimal HACE intervention, without verifying the neuronal effects of the interventions, and with no follow-up. Thus, this requires replication using longer HACE interventions and follow-ups, and objective measures of neuronal activation and driving. Nevertheless, both studies examined a novel neuroscientiﬁc approach to understanding the role of psychological risk factors in TA, and Study 2 used an experimental design to test such underlying processes. Should these ﬁndings be replicated using other methodologies, these would support the validity of the
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