Predicting aggressive driving behavior from anger and negative cognitions

Transportation Research Part F 15 (2012) 710–718

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Transportation Research Part F journal homepage: www.elsevier.com/locate/trf

Predicting aggressive driving behavior from anger and negative cognitions Sundé M. Nesbit a,⇑, Judith C. Conger b a b

Department of Psychology, University of Northern Iowa, 439 Baker, Cedar Falls, IA 50614-0505, United States Department of Psychological Sciences, Purdue University, 703 Third Street, West Lafayette, IN 47907, United States

a r t i c l e

i n f o

Article history: Received 29 August 2011 Received in revised form 1 June 2012 Accepted 16 July 2012

Keywords: Driver aggression Driving anger Dysfunctional attitudes Cognitive distortions

a b s t r a c t The purpose of the current study was to evaluate the anger experience and expression, as well as cognitive distortions, of individuals who self-report higher and lower levels of driver aggression. Fifty-seven higher driver aggression participants and 73 lower driver aggression participants completed measures of trait anger, driving anger, anger expression, angry thoughts while driving, hostile thoughts, and dysfunctional attitudes. The present study results suggest that higher aggression drivers demonstrate a different pattern of affective experience, problematic cognitive tendencies, and subsequent negative outcomes in comparison to those reporting lower levels of aggression. Future research should continue to investigate patterns of negative cognitions for aggressive drivers, in order to inform treatment and prevention strategies for this societal concern. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction Aggressive driving represents a significant problem in our society today, as the number of individuals taking to the wheel each day increases. Although it is difficult to accurately approximate the prevalence of aggressive driving, a review of the literature shows alarmingly high estimates (reaching upwards of 34%) of annual driver aggression in the United States (Galovski, Malta, & Blanchard, 2006). Extreme cases of aggression on the roadways, such as physical assaults, are rare; however, most drivers engage in milder forms of aggressive driving behavior, such as yelling or honking the horn, on a regular basis. Although most surveyed motorists tend to not describe themselves as aggressive drivers, many do admit to engaging in specific behaviors that could be deemed aggressive (e.g., 41% of surveyed drivers reported honking at other drivers within the past month, 22% admitted to tailgating others; AAA Foundation for Traffic Safety, 2008). Aggressive driving may be as common as other risky driving behaviors, such as texting/email use while driving (about 33% reported doing this over past month), drunk driving (21% within past month), and lack of seatbelt use (23% over past month; AAA Foundation for Traffic Safety, 2011). Although a majority of states have passed laws regulated these other behaviors, it has been very difficult to define aggressive driving in an explicit way so as to allow states to enact legislation punishing this behavior. The Governors Highway Safety Association (2012) reported that only fifteen states have passed laws regulating aggressive driving on the roadways. As a result of increasing levels of aggression and the challenges with identifying these behaviors, more researchers are devoting attention to this area.1 The concepts of anger and aggression will first be defined, before the implications of these concepts within driving situations can be discussed. Anger has been defined as a self-perceived phenomenological state that is negative in nature (Spielberger, Jacobs, Russel, & Crane, 1983). This emotional experience is often thought to be triggered by provoking ⇑ Corresponding author. Tel.: +1 319 273 6776; fax: +1 319 273 6188. E-mail address: [email protected] (S.M. Nesbit). On May 30, 2012, the search term ‘aggressive driving’ was typed into a PsycINFO search, producing 217 results; the substantial majority of these (94%) were published after the year 2000. 1

1369-8478/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.trf.2012.07.003

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contextual cues and result in various responses that can be cognitive, behavioral, and even physiological in nature (Berkowitz, 1993; Ekman, Levenson, & Friesen, 1983; Salzinger, 1995). In contrast, aggression is defined as a behavior or set of behaviors intended to harm another person (Berkowitz, 1993). For the purposes of this paper, driver aggression is considered to be an instance of hostile aggression (Berkowitz, 1993), because it is correlated with the experience of anger; see Nesbit, Conger, and Conger (2007) for a quantitative review focusing on this relationship. Much of the research in this area has focused on internal, dispositional contributions that predispose a driver to engage in aggressive behavior. Trait anger and hostility have been clearly associated with aggressive driving and other negative driving outcomes (Galovski & Blanchard, 2002; Lajunen & Parker, 2001). Deffenbacher and colleagues have linked trait driving anger, a propensity to experience anger in driving specific situations, to aggressive driving behavior (e.g., Deffenbacher, Huff, Lynch, Oetting, & Salvatore, 2000). Higher aggression drivers also show higher rates of psychopathology and psychiatric diagnoses, including Intermittent Explosive Disorder (Malta, Blanchard, & Friedenberg, 2004) and Attention Deficit Hyperactivity Disorder (Nada-Raja et al., 1997). The role of cognition in negative driving outcomes has received more limited attention, in comparison to focusing on dispositional affect such as anger and hostility; it has relatively recently become the primary target of investigations in this area (see Galovski et al., 2006, for more information about the paucity of research in this area). The association between cognition and behavior has been posited in multidimensional theories of anger (e.g., Berkowitz & Harmon-Jones, 2004), attribution theories (e.g., Heider, 1958; Wiener, 2001), and appraisal theories of anger and stress (e.g., Lazarus, 1991). In fact, Lazarus argued that the appraisal process is more relevant to the resulting negative mood state (such as stress and/or anger) than any combination of person or environmental factors. However, he acknowledged that this process and reactions to stress vary from person to person, and noted that personality variables likely contribute to the frequency of these appraisals and to the resulting coping strategies that are used (Lazarus, 1991). Ellis (1962) also described behavioral and emotional consequences as a function of activating events and beliefs about such events. He believed that activating events, or events that may either advance or hinder an individual’s goals, interact with thoughts and ideas about such events; therefore, it is the combination of events and beliefs that result in emotional and behavioral responses. Thus, it can be postulated that those who report a greater frequency of problematic driving behavior and anger on the roadways are likely to experience unique cognitive tendencies when compared to individuals who do not. Some support for this has come from the application of attribution theories to explaining driver aggression. For example, Wickens, Wiesenthal, Flora, and Flett (2011) experimentally manipulated levels of intentionality (the degree to which an act was intentional or accidental) and controllability (whether the act could have been controlled by the perpetrator or not) within a hypothetical provoking driving situation, and found that perceptions of responsibility mediated the relationship between attributions of causality and subsequent experience of angry mood and aggressive behaviors, thus supporting Wiener’s (2001) attributional theory of social conduct. This is also consistent with findings from Britt and Garrity (2006), who found that attributions of causality, along with hostile and blame attributions, predicted aggressive behavior and experience of anger within provoking driving situations. Further complicating this area of study is the difficulty in evaluating negative cognitions within driving situations. There are broad, relatively context-independent measures that assess irrational beliefs and hostile thinking available within the literature. For example, the Hostile Automatic Thoughts Scale (HAT; Snyder, Crowson, Houston, Kurylo, & Poirier, 1997) was developed to assess hostile thinking within everyday interactions with others. However, one of the unique facets of driving situations is that drivers often report irritation with other drivers even though they often do not verbally communicate with them. Deffenbacher, Petrilli, Lynch, Oetting, and Swaim (2003) acknowledged the influence of cognitions and the lack of availability of cognitive measures pertaining to the driving context specifically when they developed the Driving Angry Thoughts Questionnaire (DATQ). They found that their newly developed measure predicted driver aggression and risky driving behavior; further, it accounted for variance above and beyond a more general measure of angry thoughts such as the HAT (Deffenbacher, Filetti, Richards, Lynch, & Oetting, 2003). The purpose of this study was to evaluate the anger experience and expression, as well as cognitive distortions, of individuals who self-report higher and lower levels of driver aggression. Male and female undergraduate students completed various self-report measures assessing trait anger experience and expression, driving anger, hostile thoughts, driving-specific negative thoughts, and dysfunctional attitudes. It was first expected that measures of problematic thoughts would be associated with measures of anger experience and negative expression of anger. Second, participants reporting more frequent episodes of driver aggression were expected to report a different pattern of affective and cognitive responses than those reporting fewer episodes. More specifically, higher aggression participants were expected to report higher levels of trait anger, more problematic anger expression, and higher levels of hostile thoughts, dysfunctional attitudes, and driving-specific negative thoughts than lower aggression participants. 2. Method 2.1. Participants and procedure One hundred ninety Introductory Psychology students across two Midwestern universities completed measures of anger experience and expression, along with cognitive measures, a driving survey, and a demographics questionnaire. All measures were administered to large groups of students (ranging from 10 to 50 students) in exchange for course credit. Participants

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were selected for this study based on their responses to a 6-item subscale on a larger, 25-item driving survey (based on Deffenbacher et al., 2000; see description of subscale in Measures). Out of the larger sample, 130 students were selected based on higher (75th) and lower (25th) percentiles of driver aggression responses.2 Participants in the higher aggression group (n = 57; M = 10.28, SD = 6.51) all had indicated a frequency of five or more acts of verbal, physical, and/or car-related aggression within the past year, whereas participants in the lower aggression group (n = 73; M = .41, SD = .50) all reported one or fewer acts of aggression within the past year. The average participant in this subsample was M = 18.85 years old (SD = .99) and had been driving for M = 3.64 years (SD = 1.02). Eighty-eight percent of the students identified themselves as Caucasian, 5% as African American, 5% of Asian descent, 2% as Hispanic, and 2% of other or mixed ethnic backgrounds. Approximately 68% of the sample (n = 52) consisted of female participants (45%, or n = 26 in the higher aggression group). 2.2. Measures3 2.2.1. Driving survey The driver aggression subscale of the Driving Survey is a 6-item measure of the frequency of key aggressive behaviors that may occur while driving a vehicle (adapted from Deffenbacher et al., 2000). The items involved ratings of the following historic behaviors: frequency of purposefully damaging a vehicle (e.g., purposefully kicked or dented a fender), injuring oneself while engaging in an act of aggression (e.g., slammed hand onto the steering wheel), injuring someone else in the vehicle while engaged in an act of aggression (e.g., threw something at or hit a passenger), arguing with a passenger, arguing with another driver, and physically aggressing toward another driver. Items were rated based on occurrence within the past year, on a 0 to 9 or more frequency scale (a = .79). The driving survey also included questions involving lifetime history of vehicular collisions and receipt of speeding tickets. These items were rated based on occurrence over the lifetime of driving, on a 0 to 9 or more frequency scale. 2.2.2. Trait Anger Scale The Trait Anger Scale (TAS; Spielberger, 1999) is a 10-item measure of an individual’s global or chronic tendency to experiencing anger. Individuals higher in trait anger were expected to interpret a wide variety of situations as being anger provoking and to react to situations with an elevated level of state anger (Spielberger, 1999). Items were rated on a 4-point rating scale, ranging from 1 = almost never to 4 = almost always (a = .84). 2.2.3. Driving Anger Scale The Driving Anger Scale (DAS; Deffenbacher, Oetting, & Lynch, 1994) is a 14-item measure of the tendency to become angry while driving. Each item represents a problematic driving scenario, and the respondent is asked to rate each item on a 5-point rating scale measuring the degree of anger experienced, ranging from 1 = not at all to 5 = very much (a = .94). Research has shown moderate correlations between the TAS and DAS (.27 < r < .33; Deffenbacher et al., 2000), although the current study correlation was found to be slightly higher, r = .38 in the screening sample. 2.2.4. Anger Expression Scale The Anger Expression Scale (AXEX; Spielberger, 1999) is a 32-item measure of the expression or control of anger. Like the TAS, items were rated on a 4-point rating scale. The AXEX is comprised of four subscales, including the 8-item Anger Expression-Out scale (a = .74; measures the degree to which anger is expressed in verbally or physically aggressive behavior), the 8item Anger Expression-In scale (a = .75; evaluates the tendency to suppress or withhold angry feelings), the 8-item Anger Control-Out scale (a = .86; assesses the degree to which angry feelings are controlled but outwardly expressed), and the 8-item Anger Control-In scale (a = .89; measures the degree to which an angry individual is able to calm down and reduce their anger). 2.2.5. Driving Angry Thoughts Questionnaire The Driving Angry Thoughts Questionnaire (DATQ; Deffenbacher, Petrilli et al., 2003) is a 65-item measure of common thoughts people have when they become angry while driving. Each participant was asked to rate the frequency of experiencing each item within driving situations on a 5-point rating scale, ranging from 1 = not at all to 5 = all the time. This questionnaire was comprised of five subscales: Judgmental and Disbelieving Thinking (e.g., They shouldn’t be allowed to drive; a = .94); Pejorative Labeling and Verbally Aggressive Thinking (e.g., I hate drivers like that; a = .94); Revenge and Retaliatory Thinking (e.g., I’m going to get back at them; a = .96); Physically Aggressive Thinking (e.g., I want to beat them up; a = .95); and Coping Self-Instruction (e.g., Nothing I can do about it, so take it easy; a = .87). 2.2.6. Hostile Automatic Thoughts Scale The Hostile Automatic Thoughts Scale (HAT; Snyder et al., 1997) is a 30-item measure designed to assess generalized angry or hostile thoughts. Each participant was asked to rate the frequency of experiencing each item on a 5-point rating scale, 2 The distribution of driver aggression scores was not normally distributed (skewness = 2.87, kurtosis = 12.60). Therefore, this variable was dichotomized based on percentiles. 3 Internal consistencies for questionnaires administered during the screening session are reported for the entire sample of students (N = 190).

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ranging from 1 = not at all to 5 = all the time. This questionnaire was created to evaluate thoughts indicative of trait anger. The HAT is comprised of three subscales: Physical Aggression (a = .93; e.g., I want to hit this person), Derogation of Others (a = .92; e.g., This person is a loser), and Revenge (a = .95; e.g., I want to get back at this person). Deffenbacher, Petrilli et al. (2003) reported that the HAT total and subscale scores were highly related to trait anger, .47 < r < .51, and moderately related to driving anger, .21 < r < .26. 2.2.7. Modified Dysfunctional Attitudes Scale The Modified Dysfunctional Attitudes Scale (DYS; Calhoon, 1996) is a 55-item measure of cognitive vulnerability to negative affect and dysfunctional beliefs. The DYS was developed to assess cognitive biases (e.g., I should be able to please everybody) in a student population, with higher scores indicating a greater frequency of cognitive biases. Each item was rated on a 7-point rating scale, ranging from 1 = disagree totally to 7 = agree totally. The DYS was comprised of two subscales: Performance Evaluation (a = .91; e.g., People will probably think less of me if I make a mistake), and Need for Approval (a = .85; e.g., what other people think about me is very important).4 2.2.8. Demographics The demographics sheet asked participants to report their gender, ethnicity, year in school, whether their language of origin was English,5 and whether they considered themselves to have a problem with driving anger. 3. Results 3.1. Prevalence of negative driving outcomes More individuals in the higher aggression group (31.6%, n = 18) disclosed having a problem with anger while driving, whereas 13.7% of those in the lower aggression group (n = 10) endorsed this item. There was significant association between problem and aggression group status, v2(1) = 6.04, p = .014. This seems to represent the fact that based on the odds ratio those reporting higher amounts of aggressive driving were 2.88 times more likely to report a problem with anger than those reporting lower amounts of aggressive driving. The most commonly reported aggressive act in the higher aggression group was arguing with a passenger while driving (94.7%, n = 54), followed by arguing with another driver (73.7%, n = 42), injuring someone else in the vehicle while engaged in an act of aggression (63.2%, n = 36), purposefully damaging a vehicle (59.6%, n = 34), injuring oneself while engaging in an act of aggression (54.3%, n = 31), and physically aggressing toward another driver (54.3%, n = 31). Higher and lower aggression groups were significantly different in terms of negative driving outcomes. Lower aggression participants were less likely to have received at least one speeding ticket (34.2%, n = 25), in comparison to the higher aggression participants (63.2%, n = 36), v2(1) = 10.87, p = .001. In addition, 49.3% (n = 36) lower aggression participants reported experiencing at least one vehicle collision, whereas 72.2% (n = 44) higher aggression participants were involved in at least one car collision. This difference was significant, v2(1) = 10.84, p = .001. This seems to represent the fact that based on the odds ratios those reporting higher amounts of aggressive driving were 3.29 times more likely to report receipt of a speeding ticket and 3.47 times more likely to report involvement in a vehicle collision than those reporting lower amounts of aggressive driving. 3.2. Relationships between cognitive and affect measures As shown in Table 1, there were several significant correlations between the cognitive measures and the anger experience and expression scales in the subsample of participants. Various DATQ subscales (Judgmental and Disbelieving Thinking, Revenge and Retaliatory Thinking, Pejorative Labeling and Verbally Aggressive Thinking, and Physically Aggressive Thinking) were correlated with anger experience measures (either trait anger, measured by the TAS, or trait driving anger, measured by the DAS). The Physical Aggression and Revenge subscales on the HAT were correlated with the TAS, as were the Performance Evaluation and Need for Approval subscales on the DYS. However, the only subscale that was correlated with the DAS across both generalized cognitive measures was the Revenge subscale on the HAT. Three DATQ subscales were significantly correlated with Anger Expression-Out and the Coping subscale of the DATQ was significantly correlated with Anger ControlIn; further, varying DATQ subscales and the Physical Aggression and Revenge subscales on the HAT were negatively correlated with controlled expressions of anger (Anger Control-In and Anger Control-Out). The Performance Evaluation subscale was positively correlated with Anger Expression-In, and negatively correlated with Anger Control-Out; beyond that, the DYS was not significantly related to any of the anger expression subscales.

4 A 9-item subscale, labeled Imperatives, was not included in the analyses for this study because its reported (Calhoon, 1996) and current internal consistencies were low (a = .60 in current study). 5 Although six participants indicated that English was their second language, all participants in this sample indicated that their primary language of communication was English.

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Table 1 Correlations between cognitive and affective scales. Cognitive scales

Affective experience and expression scales DAS

AX-O

AX-I

.31* .47* .48* .47* .10

.23 .42* .41* .41* .02

.17 .19 .27 .19 .13

.23 .41* .44* .37* .24

.01 .24 .37* .40* .29*

.21 .10 .32*

.40* .26 .41*

.38* .26 .36*

.19 .28 .26

.34* .15 .37*

.40* .15 .34*

.18 .22

.45* .31*

.19 .08

.35* .24

.32* .25

.26 .20

DATQ JD PLVA RR PA Coping

.30* .47* .48* .25 .21

HAT Physical Aggression Derogation of Others Revenge DYS Performance Evaluation Need for Approval

TAS

AC-O

AC-I

Notes. For affective experience and expression scales, DAS = Driving Anger Scale, TAS = Trait Anger Scale, AX-O = Anger Expression Out, AX-I = Anger Expression In, AC-O = Anger Control Out, AC-I = Anger Control In. For cognitive scales, DATQ = Driving Angry Thoughts Questionnaire, JD = Judgmental/ Disbelieving Thinking, PLVA = Pejorative Labeling and Verbally Aggressive Thinking, RR = Revenge and Retaliatory Thinking, PA = Physically Aggressive Thinking, Coping = Coping Self-Instruction, HAT = Hostile Automatic Thoughts Scale, DYS = Modified Dysfunctional Attitudes Scale. Total n = 130; n = 57 for higher driver aggression group, n = 73 for lower driver aggression group. * p < .001 (adjusted for family-wise error).

3.3. Prediction of group status from affective and cognitive measures To evaluate the ability of affective and cognitive scales to discriminate between drivers who engaged in high levels of aggression and those who did not, a direct discriminant function analysis was performed for the subsample of participants. Discriminant function analysis has the potential to provide a greater degree of accuracy in group classification and is better for use with smaller sample sizes, when compared to logistic regression (Grimm & Yarnold, 1995). Membership into high versus low driver aggression groups was predicted using the DAS, TAS, AXEX subscales (Anger In, Anger Out, Anger Control Out, Anger Control In), DATQ subscales (Judgmental and Disbelieving Thinking, Pejorative Labeling and Verbally Aggressive Thinking, Retaliatory Thinking, Physically Aggressive Thinking, Coping Self-Instruction), HAT subscales (Physical Aggression, Derogation of Others, Revenge), DYS subscales (Performance Evaluation, Need for Approval) as predictors of membership in driver aggression groups. See Table 2 for group means and standard deviations on these measures. In addition, driving frequency was added as a predictor, given that the two groups differed on their rated frequencies of driving, t(128) = 3.22, p = .002; the high driver aggression group reported driving nearly every day, whereas the low driver aggression group reported driving just over 2–3 times per week. Discriminant function analysis is fairly sensitive to violations of key assumptions, including presence of outliers, homogeneity of variance–covariance matrices, and multicollinearity (Tabachnik & Fidell, 2007). In order to prepare data for this analysis, bivariate correlations for predictor variables were examined for strength. Two sets of predictors produced correlations above r = .70 (Anger Control-In with Anger Control-Out, and the Physical Aggression and Revenge thoughts subscales on the HAT). As a result of their overlap, two composite score variables were created for the Anger Control and the two HAT subscales for use in future analyses, as recommended by Tabachnik and Fidell (2007). Next, tolerance tests were conducted using all predictor variables, in order to assess for multicollinearity. All predictors produced tolerance statistics <.20 with corresponding VIF values <5 (Bowerman & O’Connell, 1990), suggesting that the predictors were free from significant overlap. Predictors that demonstrated significant skew statistics across driver aggression groups were the Trait Anger Scale; Physically Aggressive Thinking, Revenge and Retaliatory Thinking, and Coping Self-Instruction subscales of the DATQ; and the composite predictor from the HAT. Each of these was transformed to reduce the influence of skew and outliers in the distribution. Box’s M test was nonsignificant, M = 143.89, F(120, 44,992) = 1.05, p = .341, suggesting homogeneity of the covariance matrices. Finally, cases in the dataset were evaluated for potential multivariate outliers; all Mahalanobis distance values were within acceptable limits, per criteria recommended by Tabachnik and Fidell (2007). The resulting function was significant, v2(15) = 48.70, p < .001, and explained 97% of the variance in the prediction of high versus low driver aggression. According to guidelines noted by Tabachnik and Fidell (2007), predictor-function correlations above .33 were used as the cutoff for determining significance. As shown in Table 3, TAS and DAS scores, Anger ExpressionOut and Anger Control-Out were significantly correlated with the function. Further, subscales measures of driving-specific thoughts (such as Revenge and Retaliatory, Physically Aggressive, and Pejorative Labeling as measured by the DATQ) were more highly correlated with the function than were the more generalized hostile and dysfunctional measures of thoughts (Revenge and Physically Aggressive thoughts, measured by the HAT; Performance Evaluation thoughts, measured by the DYS). However, both sets of thoughts were significantly correlated with the function. As expected, frequency of driving was also correlated with the function. Analysis of group centroids indicated that high scores on the function were associated

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S.M. Nesbit, J.C. Conger / Transportation Research Part F 15 (2012) 710–718 Table 2 Group means and standard deviations on affective and cognitive scales. Scale

Higher driver aggression

Lower driver aggression

M

SD

M

SD

48.14 21.30

9.95 5.63

41.84 16.88

12.24 4.58

17.37 18.89 22.95 22.02

4.16 4.67 5.00 5.56

15.15 18.07 25.23 24.03

3.75 3.47 4.31 3.71

Cognitive scales DATQ JD PLVA RR PA Coping

59.96 43.95 31.21 13.75 21.88

16.78 12.01 12.55 6.58 7.27

54.88 36.29 21.97 9.66 21.88

16.29 13.00 8.95 2.96 7.02

HAT Physical Aggression Derogation of Others Revenge

21.39 34.88 22.75

8.59 9.15 8.91

17.25 32.93 17.90

7.97 9.75 8.77

DYS Performance Evaluation Need for Approval

90.82 53.18

19.12 11.31

80.25 48.99

21.06 11.95

Affective experience and expression scales DAS TAS AXEX Anger Expression-Out Anger Expression-In Anger Control-Out Anger Control-In

Notes. DAS = Driving Anger Scale, TAS = Trait Anger Scale, AXEX = Anger Expression Scale. DATQ = Driving Angry Thoughts Questionnaire, JD = Judgmental/ Disbelieving Thinking, PLVA = Pejorative Labeling and Verbally Aggressive Thinking, RR = Revenge and Retaliatory Thinking, PA = Physically Aggressive Thinking, Coping = Coping Self-Instruction, HAT = Hostile Automatic Thoughts Scale, DYS = Modified Dysfunctional Attitudes Scale. Total n = 130; n = 57 for higher driver aggression group, n = 73 for lower driver aggression group.

with high aggression drivers (high aggression = .79; low aggression = drivers in this sample.

.62). Overall, the function correctly classified 79.2% of

4. Discussion One purpose of this study was to evaluate the relationships among measures of problematic thoughts (both general and driving-specific) and measures of anger experience and expression of anger. Anger experience and the expression of anger outward were positively associated with verbally aggressive and retaliatory thoughts toward other drivers. In addition, drivers who were able to control their anger (either inward or outward) had a reduced likelihood of thinking these same types of thoughts, measured by the DATQ. Both attribution theories (Wiener, 2001) and appraisal theories (Lazarus, 1991) predict a strong relationship between cognitive or appraisal style, and subsequent affect and behavioral outcomes. These findings are consistent with such theories, in that the experience and expression of anger is indeed associated with dysfunctional appraisals, and can result in problematic outcomes. We also wanted to investigate whether aggressive drivers could be differentiated from non-aggressive drivers on measures of trait anger experience, anger expression styles, and negative cognitions. Previous research suggests that aggressive drivers are at risk for negative driving outcomes (Mizell, 1997), and our findings were consistent with this fact. The majority of participants in the higher aggression group had been in at least one collision (72%) and had received a speeding ticket (63%). In comparison, participants reporting fewer aggressive acts also reported fewer collisions (49%) and speeding tickets (34%). With the mean age being 19 years old, this sample represents a population of drivers who have only been driving for a short period of time and are thus at elevated risk for motor vehicle collisions. Results suggest that styles of maladaptive thinking may differentiate drivers who demonstrate a higher frequency of aggressive driving behaviors from those who do not. Aggressive drivers in this sample reported high levels on various DATQ subscales (such as Pejorative Labeling and Verbally Aggressive, Revenge and Retaliatory, and Physically Aggressive thoughts), suggesting that they experience a greater frequency of these angry thoughts while driving than those who reported lower amounts of aggressive driving behavior. Further, high aggression drivers in this study reported higher levels of generally hostile thoughts and dysfunctional attitudes (as measured by the HAT and DYS, respectively). It appears that the tendency to evaluate other drivers in a negative manner is positively associated with the likelihood of engaging in aggressive acts for young drivers. These negative evaluations may be contextually-specific, occurring solely within driving situations (i.e., the Revenge and Retaliatory Thinking, Physically Aggressive Thinking, and Pejorative Labeling and Verbally Aggressive Thinking subscales on the DATQ). This is consistent with findings by Deffenbacher, Petrilli et al. (2003), who labeled these same three

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Table 3 Results of Discriminant Function Analysis Using Affective and Cognitive Scales to Predict High versus Low Driver Aggression. Predictor

Correlations with discriminant functions

DATQ – RR Trait Anger Scale DATQ – PA DATQ – PLVA HAT – Composite (REV + PA) Driving frequency Anger Expression – Out Driving Anger Scale DYS – Performance Evaluation Anger Control – Composite (CO + CI) DYS – Need for Approval DATQ – JD HAT – Derogation of Others Anger Expression – In DATQ – Coping

.63* .62* .61* .43* .42* .40* .40* .40* .37* .36* .25 .22 .15 .15 .01

Standard discriminant function coefficients .41 .54 .51 .13 .02 .52 .17 .18 .01 .24 .08 .06 .23 .21 .39

Function

Eigenvalue

Canonical R

Wilks’s k

v2

df

p

1

.50

.58

.67

48.70

15

<.001

Notes. For cognitive scales, DATQ = Driving Angry Thoughts Questionnaire, JD = Judgmental/Disbelieving Thinking, PLVA = Pejorative Labeling and Verbally Aggressive Thinking, RR = Revenge and Retaliatory Thinking, PA = Physically Aggressive Thinking, Coping = Coping Self-Instruction, HAT = Hostile Automatic Thoughts Scale, REV = Revenge, PA = Physical Aggression, DYS = Modified Dysfunctional Attitudes Scale, CO = Anger Control-Out, CI = Anger-Control-In. Total n = 130; n = 57 for higher driver aggression group, n = 73 for lower driver aggression group. * p < .01.

subscales as the ‘‘three most aggressive forms of angry cognitions’’ (p. 390), and found associations between these DATQ subscales and measures of anger experience and driver aggression. Or they can be more broadly focused (i.e., the Revenge and Physical Aggression subscales on the HAT, and the Performance Evaluation Scale on the DYS), and reflect a tendency to evaluate others in vengeful or aggressive ways. Previous research (Deffenbacher, Petrilli et al., 2003) found that both general and specific styles of angry/hostile thinking predicted aggressive and risky driving behavior; however, the DATQ produced larger effect sizes in comparison to the more general forms of hostile thinking measured by the HAT. In the current study, the DATQ subscales were more highly correlated with the discriminant function than were the HAT or DYS subscales. Nonetheless, aggressive drivers in this sample reported more of both styles of thinking. Further, driver aggression groups may differ in their experience and expression of anger. In the discriminant function, anger experience (TAS and DAS scores), angry/hostile thoughts and maladaptive anger expression (Anger Out) predicted membership in the higher driver aggression group; the ability to control one’s anger (a composite score of Anger ControlOut and Anger Control-In) was a significant negative predictor of aggression group membership. Surprisingly, general trait anger (measured by TAS scores) was more strongly correlated with the discriminant function than DAS scores. Although Deffenbacher and colleagues (e.g., Deffenbacher, Filetti et al., 2003) have focused on trait driving anger as a key predictor of aggressive thoughts and behavior while driving, Nesbit et al. (2007) reported in a quantitative review of the literature that both trait anger and trait driving anger are equally associated with driver aggression. Contrary to what was expected, reported coping thoughts, as measured by the Coping Self-Instruction Scale on the DATQ, did not differentiate driver aggression groups. In fact the groups had identical average levels of coping thoughts, even though they differed in their ability to control their anger. (Anger Control-Out, a measure of the ability to adaptively cope with anger, was a significant, negative predictor of group membership; those in the lower aggression group reported higher scores on this scale.) This is inconsistent with findings by Deffenbacher, Petrilli et al. (2003); they reported significant correlations between this cognitive coping subscale and measures of trait anger and driver aggression. Curiously, they also reported a nonsignificant correlation between the Coping Self-Instruction subscale and the DAS. These findings are somewhat disparate from those of Nesbit and Conger (2011), who found that participants higher in trait driving anger articulated fewer anger control thought statements when imagining involvement within a provoking driving situation. One possible explanation for this is that this particular subscale may be more sensitive to situational cues than some of the other subscales. The mood-state hypothesis, developed by Persons and Miranda (1992) argues that cognitions are easier to access when a persons’ affective state is manipulated; in other words, participants may be better able to report individual cognitions when they are angry in the moment. This may explain the discrepancy in findings from this current study and Nesbit and Conger (2011). However, it does not fully account for other (significant) findings that were generated from this study; therefore, additional research is needed in this area. The Anger In scale was not a significant predictor of aggression group membership according to the discriminant function analysis. In their comparisons of higher and lower driving anger groups, findings by Deffenbacher and colleagues have been inconclusive regarding this subscale. Deffenbacher, Filetti et al. (2003) and Deffenbacher et al. (2000) found group differences in Anger In, such that higher anger drivers reported a greater likelihood of withholding their anger. However, Deffenbacher, Lynch, Filetti, Dahlen, and Oetting (2003) did not find this difference between groups, and reported that other AXEX subscales distinguished between higher and lower anger drivers more significantly.

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It is important to note that these findings were based on a sample of participants who report higher frequencies of aggressive driving behavior. Deffenbacher and colleagues (e.g., Deffenbacher, Filetti et al., 2003; Deffenbacher et al., 2000) have consistently found these differences when comparing higher and lower anger drivers (using the DAS) and drivers who acknowledged problems with driving anger. In this sample, only 32% of the students in the higher aggression group reported a problem with driving anger; yet all reported behaviors that could potentially put themselves and other drivers at risk. This is an interesting finding, and one that supports a warning made by Galovski et al. (2006); many aggressive drivers may be unable to recognize their own driving as aggressive or problematic. Those in the high aggression group reported driving more often than those within the low aggression group. One could hypothesize that those who drive more often are more likely to get involved in provoking situations simply by spending more time behind the wheel with increased exposure to a variety of driving contexts. Other researchers have also found that driving frequency increases likelihood of driver aggression (e.g., Wickens et al., 2012); while others have found that demographic variables such as gender moderate the relationship between exposure and driver aggression (e.g., Lajunen & Parker, 2001; Wickens et al., 2012). However, Deffenbacher and colleagues have consistently found that drivers who report higher levels of trait driving anger travel the same amount (with regard to both distance and time) as low anger drivers. Yet these drivers were 3.5–4.0 times more likely to be physically and/or verbally aggressive, and were 1.5–2.0 times more likely to engage in risky behavior behind the wheel (e.g., Deffenbacher, Filetti et al., 2003; Deffenbacher et al., 2000). It is still not clear how exposure plays a role in instigating driver aggression; therefore, future research should continue to examine the impact of driving frequency upon incidence of aggressive driving and associated problematic cognitions. There are some limitations that should be considered in this study. All data were correlational and was collected based upon participants’ self-report. As a result, it is unclear whether these data might have been influenced by social desirability and fallibility of memories of negative driving outcomes. For example, the higher aggression participants in this study reported frequencies of aggressive acts that were somewhat elevated. When averages for the frequency items were calculated, they were generally similar to that reported by Deffenbacher et al. (2000). Much of the literature conducted on driver aggression to this point has relied upon self-report, and one could argue that internal emotional states, such as anger, are most accessible to the individual experiencing them. However, Nesbit et al. (2007) reported that the relationship between self-report measures of driving anger and driver aggression are subject to significant common method variance; it seems very likely that self-report measures of maladaptive cognitions would also be affected by this. It is important to expand the methodology used to study aggressive driving experiences, in order to advance our understanding of cognitive experience while driving. For example, use of in vivo technology, such as a driving simulator, would allow for the ‘online’ measurement of cognitive and affective responses. Further, use of a driving simulator could open up opportunities for measurement of specific, contextually-driving driving behaviors and physiological responding. Further, participants in this study were introductory psychology students within a university setting. For inclusion in this set of studies, participants had to have driving experience; due to their age, they have not been driving for an extended period of time. These students may not be representative of the general population of drivers as the majority has had little driving experience, nor do they represent a clinical population of angry drivers. It is certainly important to evaluate maladaptive thinking in combination with emotional experience and expression on more experienced samples of drivers, in order to better generalize these findings. The limited driving experience for a young group of drivers certainly may attenuate any conclusions that we can make for drivers of varying ages; however, this sample, due to their age and inexperience with driving, represents a larger group of drivers who are more likely to engage in risky and aggressive driving behaviors. For example, young drivers, ages 16–20, make up a small subset of the driving population in the US (about 7%), yet they account for a high percentage of collisions due to aggressive behaviors, such as speeding (about 22%; National Highway Traffic Safety Administration, n.d.). The results of this study are an important step in the systematic evaluation of cognitive responses for young drivers, and the relationship between negative cognitions, affect, and subsequent behavior. This study found that groups of participants higher and lower in driver aggression report different patterns of affective experience and expression, along with dysfunctional attitudes and negative cognitions. First, college student drivers who reported problematic or aggressive driving behaviors also tended to have higher levels of trait and driving anger, congruent with other published findings linking aggressive driving behavior to dispositional levels of anger (e.g., Lajunen & Parker, 2001). Second (and consistent with published results by Deffenbacher, Petrilli et al., 2003), these individuals also are more likely to experience angry thoughts while driving, as well as a greater frequency of general hostile thoughts and dysfunctional attitudes in their day-to-day lives. This is consistent with appraisal theory (Lazarus, 1991) and Ellis’ A-B-C model (Ellis, 1962) upon which rational emotive therapy was based. The experience and expression of anger is indeed associated with dysfunctional appraisals; Lazarus (1991) would predict that this appraisal process would explain individual differences in anger experience. Thus, it is not surprising that both general and context-specific styles of thinking are correlated with dispositional tendencies toward anger experience and expression. Finally, higher aggression drivers in this sample were more likely to express their anger in an outward manner; this is in contrast to those reporting lower rates of driver aggression, who were more likely to utilize anger control styles in an effective way. Like appraisal theories, multidimensional theories of anger (like the cognitive neo-associationistic perspective on emotion; e.g., Berkowitz & Harmon-Jones, 2004) predict that the evaluative process is linked to both emotional and behavioral reactions to a situation or stimulus. Based on this theoretical perspective, an angry individual is likely to perceive that they have control over the situation and will advance toward the reduction of the hindrance.

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This study provides additional evidence to support the role of cognitions contributing to problematic driving behavior. Further identification of patterns of negative cognitions may be helpful in identifying treatment strategies and prevention techniques for the reduction of aggressive behavior behind the wheel resulting from the experience of negative affect. Research by Deffenbacher and colleagues has evaluated the efficacy of specific treatment strategies (relaxation and cognitive-relaxation) in the reduction of anger responses while driving (Deffenbacher, Filetti, Lynch, Dahlen, & Oetting, 2002), and found that they were effective in reducing aggressive driving behavior. These treatment strategies involved self-regulation techniques along with the application of relaxation strategies in previously identified provoking driving situations. 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