The Impact of Commuter Stress on Workplace Aggression
Dwight A. Hennessy1
Buffalo State College
Immediately following their regular commute to work, participants completed questionnaires regarding state driver stress and anger during that commute. Then, immediately following completion of that work day, they completed a state version of the
Workplace Aggression Scale. As state driver stress increased, the frequency of both
expressed hostility and obstructionism increased (independently) during that work
day, but only among male employees. In contrast, overt aggression during that work
day was greatest among males who were higher in physical aggressiveness as a
general trait characteristic. The present study highlights the interactive nature of
traffic and workplace environments, in that negative experiences in the traffic environment may spill over for some individuals to influence nondriving events.

Workplace aggression has been defined as the purposeful infliction of
physical, verbal, or psychological harm on current or previous coworkers or
on organizations in which an individual is currently employed or was previously employed (Baron & Neuman, 1996). While workplace aggression can
take many forms, Neuman and Baron (1998) have proposed a three-factor
approach that distinguishes between expressed hostility, obstructionism, and
overt aggression. Expressed hostility typically involves the verbal and symbolic release of angry feelings, discontent, or negative attitudes toward others
(e.g., yelling, ostracism, character assassination). Obstructionism includes
actions designed to impede another’s performance or progress intentionally,
often in an attempt to damage the image or reputation of specific employees
or the organization (e.g., work slowdowns, inaction, employee sabotage).
Acts of overt aggression entail predominantly physical actions directed
toward an individual or their personal and corporate property (e.g., physical
assault, property damage).
Previous research has uncovered a number of personal (e.g., Type A,
vengefulness, anger, stress) and organizational (e.g., workforce diversity,
overload, unfair treatment) factors that interactively heighten aggression and
violence in the workplace (see Barling, 1996; Baron, Neuman, & Geddes,
1999; Douglas & Martinko, 2001; Folger & Skarlicki, 1998; Neuman &
Baron, 1998). However, recent attention has also focused on the issue of
1
Correspondence concerning this article should be addressed to Dwight A. Hennessy,
Department of Psychology, Buffalo State College, 1300 Elmwood Avenue, Buffalo, NY 14222.
E-mail: hennesda@buffalostate.edu

2315
Journal of Applied Social Psychology, 2008, 38, 9, pp. 2315–2335.
© 2008 Copyright the Authors
Journal compilation © 2008 Wiley Periodicals, Inc.

 2316 DWIGHT A. HENNESSY
spillover in which workplace attitudes and behaviors are influenced by nonwork factors (Leiter & Durup, 1996). The notion is that unresolved daily
hassles from one domain can persist, even when no longer in conscious
awareness, and add to the pressures of subsequent hassles in other life contexts (Kohn & Macdonald, 1992; Lazarus, 1981; Taylor, 1991).
These after-effects can continue to do psychological and physiological
damage, and may intensify over time, as they accumulate with other previously unresolved stress reactions (Glass & Singer, 1972). While there
is greater evidence of spillover from the workplace to subsequent
environments—including elevated stress, social withdrawal, and conflict at
home (Koizumi, Sugawara, & Kitamura, 2001; Repetti, 1989; Thompson,
Kirk-Brown, & Brown, 2001)—negative experiences at home have been
found to magnify job overload, occupational stress, psychological distress,
and arguments/conflicts in the workplace (Barnett, Marshall, & Pleck, 1992;
Behson, 2002; Bolger, DeLongis, Kessler, & Wethington, 1989; Jenkins,
1996; Jones & Fletcher, 1996; Leiter & Durup, 1996). The latter issue is
particularly pressing, given that numerous studies have independently identified conflict and workplace stress as prevalent antecedents to workplace
aggression and violence (Denenberg & Braverman, 1999; Glomb, 2002;
Jenkins, 1996; Neuman & Baron, 1998; Rai, 2002).
Notwithstanding the importance and prevalence of the home environment in an individual’s total life space, there is comparatively little information on the potential impact of other domains on workplace reactions (e.g.,
daily commuting). The driving environment is a common context that has
been found to elicit elevated levels of stress and arousal, particularly in highly
frustrating conditions (Hennessy & Wiesenthal, 1999; Hennessy, Wiesenthal,
& Kohn, 2000; Novaco, Stokols, & Milanesi, 1990; Rasmussen, Knapp, &
Garner, 2000; Stokols & Novaco, 1981; Wiesenthal, Hennessy, & Totten,
2000).
Within any driving encounter, there are a multitude of stimuli that may be
perceived or interpreted as stressful (e.g., bad weather, time pressures, slowmoving vehicles, traffic congestion). According to Broome (1985), traffic
stress typically occurs when goals, such as getting to work on time or traveling at a desired pace, are blocked. Most regular commuters report facing
numerous frustrations or irritations that can lead to driver stress (Gulian,
Matthews, Glendon, Davies, & Debney, 1989; Novaco et al., 1990). In fact,
a recent workplace survey found that traffic congestion was the most commonly reported source of daily stress among UK employees (BBC News,
2000).
This issue is particularly pressing, considering that 60% of those over the
age of 16 in the United States are part of the labor force, and 88% of this
group commute to work via personal vehicle (76% alone), with a median

 COMMUTER STRESS AND AGGRESSION

2317

commute time of approximately 20 min in each direction (U.S. Census,
2000). While the consequences of commuter stress are individual and varied,
such conditions have been linked to a number of negative outcomes, such as
increased blood pressure and heart rate (Novaco, Stokols, Campbell, &
Stokols, 1979; Schaeffer, Street, Singer, & Baum, 1988; Stokols, Novaco,
Stokols, & Campbell, 1978); negative mood (Gulian, Debney, Glendon,
Davies, & Matthews, 1989); emotional arousal (Hennessy & Wiesenthal,
1997); poor concentration levels (Matthews, Dorn, & Glendon, 1991);
driving errors, lapses, and violations (Westerman & Haigney, 2000); traffic
offenses (Matthews, Tsuda, Xin, & Ozeki, 1999); traffic collisions (Legree,
Heffner, Psotka, Martin, & Medsker, 2003; Selzer & Vinokur, 1974); and
aggression (Hennessy & Wiesenthal, 1999).
Stress experienced while driving is embedded in, and interacts with, the
total life settings of home, work, and leisure (Gulian, Matthews et al., 1989;
Novaco et al., 1990). There is growing evidence to suggest that driver stress is
influenced by stressors experienced in other life contexts that accumulate and
carry forward to the driving environment (Burns & Rotton, 2004; Gulian,
Matthews et al., 1989; Hennessy et al., 2000). Unresolved hassles (e.g., poor
weather, sleep problems, conflicts at work or home) may exacerbate situational problems faced in the traffic environment, and increase the potential
for driver stress and related pathologies (Gulian, Glendon, Matthews, Davies,
& Debney, 1990; Gulian, Matthews et al., 1989; Wickens & Wiesenthal,
2005). However, much less is known regarding the potential impact of the
traffic environment on subsequent domains (e.g., the workplace).
A notable exception by Schaeffer et al. (1988) examined the potential
physiological and behavioral outcomes following participants’ actual
commute to work. Those who experienced greater impedance in traffic
showed elevated systolic and diastolic blood pressure, and greater errors on
a subsequent proofreading task. Schaeffer et al.’s study demonstrated that a
difficult or demanding commute can have an impact on post-commuting
stress and performance.
Another study by White and Rotton (1998) utilized an experimental
manipulation in which participants were assigned to either a drive (i.e., drive
their vehicle between two designated locations), ride (i.e., ride a bus over the
same route), or control group. They found that, following the commute,
those who drove or rode the bus demonstrated lower frustration tolerance
and persistence in completing unsolvable puzzles, as compared to the control
group.
Finally, Van Rooy (2006) measured mood while participants drove a
predetermined route, and examined its impact on subsequent employee
evaluations. Results indicated that longer driving distances and higher traffic
congestion led to more negative evaluations of unqualified job candidates,

 2318 DWIGHT A. HENNESSY
which suggests that workplace behavior can be influenced by a previous
commute. Hence, the present study is designed to extend previous research to
examine the possible spillover effect of commuter stress, specifically on acts
of workplace aggression. Given that most acts of workplace aggression
involve verbal, passive, or indirect actions (Baron & Neuman, 1996; Glomb,
2002), it is predicted that drivers experiencing greater state levels of driver
stress will exhibit greater expressed hostility and obstructionism during that
work day.

Method
Participants
Participants consisted of 114 students (70 female, 44 male) from Buffalo
State College who were employed off campus and commuted to work via
personal automobile. Their mean age was 20.3 years (SD = 4.2; range = 18–
55). The typical mean work week was 6.44 days (SD = 1.08; range = 4–7); the
mean number of hours worked per week was 25.57 hr (SD = 8.63;
range = 10–55); and the typical mean daily commute time was 20.76 min
(SD = 16.35; range = 4.50–78.00). This mean commute time is consistent with
the U.S. Census (2002) for the metropolitan Buffalo (NY) area of 20.7 min,
and is similar to cities of similar populations (e.g., Memphis, TN, 21.4 min;
Fresno, CA, 21.2 min; Nashville, TN, 21.0 min; Tucson, AZ, 20.4 min).

Measures
Aggression Questionnaire (AQ; Buss & Perry, 1992). The AQ is a 29-item
self-report measure of overall trait aggressiveness. The AQ consists of four
subscales that measure physical aggressiveness (9 items), verbal aggressiveness (5 items), anger proneness (7 items), and hostility (8 items).
Participants were asked to rate how characteristic each item generally is of
them on a 5-point Likert-type scale ranging from 1 (extremely uncharacteristic) to 5 (extremely characteristic). The AQ has demonstrated high internal
consistency (a = .92; Williams, Boyd, Cascardi, & Poythress, 1996) and good
test–retest reliability (r = .80) over a 9-week period. Subscale scoring consisted of mean response to subscale items, with higher scores representing
greater trait aggressiveness.
Survey of Recent Life Experiences (SRLE; Kohn & Macdonald, 1992).
The SRLE is a self-report measure of exposure to daily hassles. Participants
were asked to indicate the extent to which each item has been part of their

 COMMUTER STRESS AND AGGRESSION

2319

lives over the past month. Responses were rated on a 6-point scale ranging
from 0 (not at all) to 5 (very much). Scoring consisted of the mean of the 41
items. Higher scores indicate greater experience of hassles over the past
month. The SRLE has been found to have high internal consistency (a = .92)
and to predict state driver stress (Hennessy et al., 2000).
State driver stress. State driver stress was measured using a variation of
the Driving Behavior Inventory–General (DBI-Gen) driver stress questionnaire (Gulian, Matthews et al., 1989). The DBI-Gen consists of 16 items
designed to measure a susceptibility to stress while driving. Each item represents a situation that is often experienced by highly stressed drivers. Consistent with Hennessy and Wiesenthal (1997), items were revised to represent
state experiences from their current commute. Participants were asked to rate
how much they agree with each item on a 6-point scale ranging from 0 (totally
disagree) to 5 (totally agree). Hennessy and Wiesenthal found similar revisions to predict actual stress levels measured in both low and high traffic
congestion. Scoring consisted of the mean of the 16 items, with higher scores
indicating greater trait driver stress susceptibility.
Short Form Driving Anger Scale (DAS; Deffenbacher, Oetting, & Lynch,
1994). The DAS includes 14 items that measure a single driver anger dimension. The items present common driving scenarios that have been found to
elicit varying degrees of anger. The short form of the DAS has been found to
demonstrate good reliability (a = .80; Deffenbacher, Huff, Lynch, Oetting, &
Salvatore, 2000). For the purpose of the present study, participants were
asked to imagine that each scenario had just happened during that commute
and to rate the level of anger they would have experienced on a 5-point scale
ranging from 1 (none at all) to 5 (very much). Scoring consisted of the mean
of the 14 items, with higher scores representing greater state driver anger.
Workplace Aggression Scale (WPAS; Neuman & Baron, 1998). The
WPAS was developed as an overall measure of the self-report prevalence of
workplace aggression. The scale consists of three factors representing unique
categories of aggression: (a) Expressed Hostility involves 15 items representing verbal and symbolic release of feelings of anger, discontent, or negative
attitudes toward others (e.g., staring, obscene gestures, belittling); (b)
Obstructionism involves 9 items based on actions intended to impede
another’s performance (e.g., failing to return phone calls, work slowdowns,
showing up late for meetings); and (c) Overt Aggression involves 8 items that
focus on physical actions toward an individual or their property (e.g., attack
with a weapon, threats of physical violence, sabotaging company property
needed by the target).
For the present study, the WPAS was revised to represent a more “state”
measure of the prevalence of aggression during the current work day. Participants were asked to rate the extent to which they personally initiated each

 2320 DWIGHT A. HENNESSY
form of aggression during that current target work day on a 6-point scale
ranging from 0 (not at all) to 5 (nearly all the time). Subscale scoring consisted
of the mean response to the respective subscale items, with higher scores
representing greater state workplace aggression during that work day.

Procedure
The researchers initially met with participants to gain informed consent
and to explain the research procedure fully. During this meeting, participants
completed demographic questions, along with the AQ and SRLE to measure
their trait aggressiveness and daily hassles, and were also provided with two
sealed envelopes containing the state driving questions and the state version
of the WPAS, respectively, to be completed at the appropriate times during
their target commute. They were instructed to drive to work as usual on their
target work day and, upon arrival in the parking lot, open the first sealed
envelope and complete the State Driver Stress and Anger scales while still in
their vehicle (and then return them to the envelope). Subsequently, following
that work day, they were to open the second envelope while in their vehicle in
the parking lot (prior to embarking on the commute home) and complete the
state version of the WPAS.
The questionnaires were then returned the next day to the Psychology
Department. In order to avoid any pressure on participants to violate the
exact order of the steps in the procedure, instructions during the initial
meeting emphasized that there were no penalties if they did not complete the
questions in either the post-commute or post-work conditions specifically as
arranged. In such instances, they were asked simply to return all materials
and to report them as incomplete.

Results
Using MANOVA, an overall gender effect was found across the battery
of questionnaires, F(10, 73) = 3.12, p < .05. Table 1 contains all betweensubject tests for gender, intercorrelations, means, and alpha reliabilities for
each individual questionnaire. Men scored significantly higher on all scales,
except for state driver anger and daily hassles. Overall, all measures demonstrated moderate to high reliability, although trait physical aggression and
trait anger showed the weakest consistency.
In order to examine the influences of state driver stress on workplace
aggression, separate hierarchical entry multiple regressions were conducted
for expressed hostility, obstructionism, and overt aggression. The procedure

 EH
OB
OV
PHYS
VERB
ANG
HOST
HASS
SDS
SDA

1.97
1.92
0.66
2.44
2.65
2.47
2.62
2.87
2.33
3.12

0.83
0.92
0.56
0.75
0.79
0.67
0.90
0.45
0.85
0.74

SD

2.21
2.38
0.95
2.60
2.83
2.67
2.92
2.79
2.42
3.09

M

0.94
1.04
0.77
0.81
0.86
0.75
1.03
0.43
0.77
0.87

SD

Male

1.79
1.64
0.48
2.34
2.53
2.34
2.43
2.95
2.28
3.14

M
0.70
0.74
0.21
0.70
0.72
0.59
0.76
0.46
0.89
0.64

SD

Female

.89
.87
.85
.67
.85
.61
.85
.90
.86
.87

a
15.44**
12.69**
17.92**
5.16*
11.32**
8.13**
11.75**
0.00
6.69*
1.18

F(1, 82)
—
.613**
.460**
.309**
.461**
.344**
.442**
.203
.499**
.446**

1

3

4

5

6

7

—
.405**
—
.109
.413**
—
.324**
.336** .607**
—
.377**
.385** .586** .788**
—
.478**
.351** .403** .685** .760**
—
.076
-.010
.189
.331** .216
.162
.351**
.237
.321** .662** .444** .488**
.401**
.213
.275
.523** .383** .411**

2

—
.405**
.187

8

—
.661**

9

Note. IV = independent variable; EH = expressed hostility; OB = obstruction; OV = overt aggression; PHYS = trait physical aggression;
VERB = trait verbal aggression; ANG = trait anger; HOST = trait hostility; HASS = hassles; SDS = state driver stress; SDA = state driver anger.
*p < .05. **p < .01.

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.

M

Gender
as IV

Intercorrelations, Mean Gender Differences, Means, and Reliabilities for State Workplace Aggression Subscales, Trait
Aggression Subscales, Daily Hassles, and State Driving Measures

Table 1

COMMUTER STRESS AND AGGRESSION

2321

 2322 DWIGHT A. HENNESSY
Table 2
Regression Model for Workplace Expressed Hostility
b
Intercept
Demographics
Age
Gender

t

DF

.105

5.44**

.220

5.72**

.059

4.92*

.101

16.58**

2.501
-0.009
-1.460

-0.56
-3.09**

Personal factors
Hostility
Anger
Physical aggression
Verbal aggression
Daily hassles

0.241
-0.307
0.207
0.019
0.129

1.92
-1.59
1.83
0.10
0.80

State driving
Driver anger
Driver stress

0.106
-0.888

0.84
-3.31**

Interaction effects
Gender ¥ Driver Stress

DR2

0.781

4.07**

*p < .05. **p < .01.

was to enter demographics (i.e., age, gender) in Step 1; personal aspects (i.e.,
physical aggression, verbal aggression, anger, hostility, daily hassles) in Step
2; state driving factors (i.e., stress, anger) in Step 3; and to add all crossproduct interactions stepwise in Step 4.
Both expressed hostility (R2 = .48), F(10, 85) = 7.96, p < .01 (see Table 2),
and obstructionism (R2 = .39), F(10, 79) = 5.14, p < .01 (see Table 3) were
predicted by the Gender ¥ Driver Stress interaction. Specifically, both
expressed hostility (see Figure 1) and obstruction (see Figure 2) during that
work day were more prevalent among male drivers who experienced high
levels of stress during their commute to work. Overt aggression was predicted by the interaction of gender and trait physical aggressiveness
(R2 = .42), F(10, 83) = 6.16, p < .01 (see Table 4), where overt aggression
during that work day was greatest among males with an elevated trait physical aggressiveness (see Figure 3). The figures were generated by using their
respective regression equations to compute hypothetical data points for men

 COMMUTER STRESS AND AGGRESSION

2323

Table 3
Regression Model for Workplace Obstructionism
b
Intercept

t

DR2

DF

.144

7.34**

.149

3.46**

.070

4.38*

.031

4.04*

1.191

Demographics
Age
Gender

-0.003
-0.595

-0.14
-0.99

Personal factors
Hostility
Anger
Physical aggression
Verbal aggression
Daily hassles

0.195
0.263
-0.163
-0.195
0.078

1.27
1.07
-1.15
-0.92
0.36

State driving
Driver anger
Driver stress

0.242
-0.499

1.49
-1.53

Interaction effects
Gender ¥ Driver Stress

0.477

2.01*

Hostility

*p < .05. **p < .01.
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Low

Women
Men

Moderate

High

State Driver Stress

Figure 1. Workplace hostility as a function of State Driver Stress ¥ Gender.

 2324 DWIGHT A. HENNESSY
1.6
Obstructionism

1.4
1.2

Women
Men

1
0.8
0.6
0.4
0.2
0
Low

Moderate

High

State Driver Stress

Figure 2. Workplace obstructionism as a function of State Driver Stress ¥ Gender.

Table 4
Regression Model for Workplace Overt Aggression
b
Intercept
Demographics
Age
Gender
Personal factors
Hostility
Anger
Physical aggression
Verbal aggression
Daily hassles
State driving
Driver anger
Driver stress
Interaction effects
Gender ¥ Driver Stress
**p < .01.

t

DR2

DF

.178

9.84**

.138

3.45**

.006

0.35

.103

14.80**

1.426
0.002
-0.991
0.067
0.090
-0.606
-0.085
-0.023
-0.036
0.069
0.546

0.21
-2.70**
0.73
0.64
-2.59**
-0.66
-0.17
-0.38
0.67
3.84**

 COMMUTER STRESS AND AGGRESSION

2325

Overt Aggression

1.2
1

Women
Men

0.8
0.6
0.4
0.2
0
Low

Moderate

High

Trait Physical Aggression

Figure 3. Overt workplace aggression as a function of Trait Physical Aggression ¥ Gender.

and women separately across state driver stress levels (Figures 1 and 2) or
trait physical aggression levels (Figure 3) at 1 SD below the mean (low), the
mean (moderate), and 1 SD above the mean (high).

Discussion
Overall, the present findings suggest that some form of spillover from the
traffic environment to the workplace environment is possible. As expected,
state driver stress was related to subsequent acts of workplace aggression, but
only for males and only in the form of expressed hostility and obstructionism.
Further, this outcome was detected after controlling for trait aggression and
daily hassles, which indicates that such acts of aggression were not simply a
result of aggressive personalities or an excessive stress load.
Commuter stress is a serious issue that can have significant physical and
psychological consequences. But of particular concern is the fact that it may
potentially influence the cognitive processes involved in attention, information processing, and appraisal that are essential to effective coping (Matthews, 2002). It is possible that efforts to deal with traffic stress may exhaust
coping resources needed to deal with subsequent stressors in the workplace
environment, while simultaneously priming individuals to construe workplace constraints as more demanding and stressful, consequently increasing
the possibility of aggressive responses. According to Viitasara and Menckel
(2002), such aggression and violence are strongly influenced by immediate
contextual factors, but broader situational factors help shape the nature and
outcome of those actions. In the present study, it is likely that broader
situational factors for male commuters in the workplace included previously
experienced traffic difficulties.

 2326 DWIGHT A. HENNESSY
Interestingly, driver anger did not predict workplace aggression, despite
the well established general link between anger and aggression (see Berkowitz, 1993) and the strong relationship between state driver stress and
state driver anger in previous studies (Hennessy, Wiesenthal, Wickens, &
Lustman, 2004). A potential reason is that anger is an affective state, based
on the interpretation of arousing conditions (see Geen, 1990). In the absence
of the source of arousal, the affective reaction of anger may diminish. This
outcome is consistent with Van Rooy and Rotton (2003), who found that
arousal and negative affect increased during a commute, but returned to
pre-commute levels relatively quickly following its completion. It also confirms the findings of White and Rotton (1998) and Van Rooy (2006) that
arousal and negative affect do not appear to spill over, despite the fact that
post-commute performance can be significantly influenced by a negative
commute.
In the present study, it is likely that, as with other sources of daily hassles,
any unresolved issues in the traffic environment (including anger-provoking
events) may have continued to influence and intensify subsequent workplace
reactions to potential stressors, even though their immediate (or “state”)
effects may have become indistinguishable in conscious awareness. This
notion is the crux of the spillover effect: that unresolved difficulties from one
domain accumulate and unconsciously influence the interpretation of, and
intensify negative reaction to, stressors in subsequent domains (Leiter &
Durup, 1996).
It is important to point out that in their investigation of spillover in the
opposite direction from the workplace to the subsequent traffic environment,
Wickens and Wiesenthal (2005) found that job stress increased the severity of
traffic stress measured in actual low congestion conditions. While, this may
initially appear as contradictory to the research mentioned previously on the
rapid dissipation of arousal and affect, Wickens and Wiesenthal’s findings
are consistent with hassles spillover. In higher congestion, where they found
no evidence of spillover, there are typically greater demands for immediate
attention resources needed to deal with the higher volume of traffic, closer
proximity of other vehicles, and slower pace of driving. As a result, drivers in
high congestion may be distracted from other potential hassles, including
previous work issues, leaving the traffic environment as the focal point of
driver stress (Wiesenthal, Hennessy, & Totten, 2003).
In contrast, during low congestion, where they did identify evidence of
spillover, any stressors from work may continue to influence drivers because
there are fewer sources of immediate stress from the traffic environment
itself. However, it is also important to highlight that Wickens and Wiesenthal
(2005) did not measure behavioral outcomes following the work day and that
stress effects were not measured following the commute. Nonetheless, their

 COMMUTER STRESS AND AGGRESSION

2327

findings confirm that stress has the potential to carry forward to subsequent
environments, but that the environment itself (in association with individual
factors) likely influences the nature of this spillover.
Another finding of note in the present study is the fact that the spillover
effects from traffic stress to workplace aggression appeared only for men.
This is consistent with Rutter and Hine (2005), who found that male employees reported engaging in all three forms of workplace aggression more frequently than did female employees. Previous research has also provided
evidence of gender differences in spillover, in that the sources and reactions to
work and family stressors and their ultimate outcomes across domains sometimes differ between men and women, although the exact nature of this
gender effect is mixed and not fully clear (Grzywacz & Marks, 2000; Maume,
2001; Thompson et al., 2001). However, Bolger et al. (1989) found that, for
men only, conflicts at home were followed by greater work stress the next
day.
Further, according to Almeida, Wethington, and Kessler (2002), men are
more prone than are women to report workplace stress as a major daily
hassle. In this respect, men may be more inclined to accept workplace aggression as an appropriate coping response to stress, particularly if the consequences of previous acts of aggression have been “successful” in solving
disputes or have provided some form of instrumental social reward, such as
respect or control of coworkers (Campbell, Muncer, & Gorman, 1993).
Douglas and Martinko (2001) emphasized the importance of including
personal factors in understanding workplace aggression. While this is not to
minimize the impact of social and organizational antecedents, it is individuals
who must interpret these workplace experiences. One such factor is a vengeful attitude, which can lead individuals to interpret actions of others as
threatening and to harm the perpetrator to gain power, control, defense, or a
sense of justice (Baumeister, 1997; Black, 1983; Daly & Wilson, 1988; Elster,
1990). Previous research has found that men are more likely to hold aggressive attitudes and to express revenge-motivated aggression (Stuckless &
Goranson, 1992; Wiesenthal, Hennessy, & Gibson, 2000).
Another related factor is anger rumination, which is the tendency to dwell
on angry events, to recall instigating or anger-provoking events from the
past, and to focus excessively on the causes of anger from such events
(Maxwell, 2004; Sukhodolsky, Golub, & Cromwell, 2001). According to
Bushman, Bonacci, Pedersen, Vasquez, and Miller (2005), such rumination
can lead to triggered displaced aggression in which a minor provocation (e.g.,
that experienced in the workplace) may result in displaced aggression because
of a previous provocation that was not dealt with directly (e.g., that experienced in traffic). Previous research has demonstrated that anger rumination
is more prevalent in men than in women (Knobloch-Westerwick & Alter,

 2328 DWIGHT A. HENNESSY
2006). Further, Denson, Pedersen, and Miller (2006) argued that both vengeful thoughts and anger rumination may be part of the cognitive mechanisms
of trait-displaced aggression in which individuals are more prone to express
their aggression toward targets, in another context, who were not the initial
source of their provocation or instigation.
Finally, Wilson and Daly (1985) argued that male aggression may be a
function of evolutionary fitness, where such actions provide long-term benefits of prestige, power, control, and admiration (especially among younger
men in reproductive competition). As these attributes among males come to
be respected as a symbol of masculinity, their value is exaggerated through
gender roles that legitimize male aggression (see Eagly & Wood, 1999). To
the extent that the workplace is an arena in which men have traditionally
attempted to demonstrate their masculinity (i.e., power, strength, provision
of resources), more stereotyped masculine roles and aggression should be
evident. Hence, the tendency for men to show greater spillover from traffic to
the workplace environment may be a function of broader personal factors
more typically found in men that might influence their cognitions about the
instigating traffic context and subsequent triggering events in the workplace.
Ultimately, this can alter their perceptions of those events, the potential
rewards of aggression, and their decisions to express aggression toward
coworkers (see Anderson & Bushman, 2002).
The potential for difficulties from one life context to carry forward to
other domains, typically without conscious awareness of the spillover
process, can have profound effects on the understanding and treatment of a
wide range of problems, including workplace aggression. Despite growing
interest in the reciprocal influence of work and family factors, there is still a
great deal that is unknown about the process and product of spillover effects.
The present study attempted to promote an important direction into this
research area in that the transition between home and work for the majority
of the workforce involves the traffic environment, which on its own is a
salient source of daily stress and hassles. However, the present study involved
only a single measure of state stress and workplace aggression. State sources
of driver stress are often transient, and reactions can vary temporally and, as
such, may not be tapped within a single time period. Similarly, workplace
aggression is more accurately represented as a process involving a range of
overlapping and repeated behaviors (Viitasara & Menckel, 2002). Future
research should examine the continuing influence of state stressors on workplace behavior through multiple measurements over an extended period of
time.
In a similar respect, there are also numerous personal and organizational
factors that have been found to influence workplace aggression that were not
included in the present study. Future research should examine a broader mix

 COMMUTER STRESS AND AGGRESSION

2329

of potential stressors from within the workplace (e.g., differences in job type,
conflict, time pressures), the home environment (e.g., family conflict, time
schedules, social support), the traffic context (e.g., time urgency, perceived
control, traffic conditions), and the individual (e.g., vengeance, masculinity,
rumination).
Most notable is the fact that the present study included a substantial
portion of younger part-time employees. While Dupré, Inness, Connelly,
Barling, and Hoption (2006) found that workplace aggression occurs
among younger part-time employees and that it is similar in many ways to
that of older employees, it is possible that the nature of the traffic–work
spillover may be quantitatively or qualitatively unique among these two
populations.
Similarly, the present study failed to find an age effect on aggression,
despite the fact that previous research has found that younger employees
engage in workplace aggression more frequently than do older employees
(Baron et al., 1999). This discrepancy is likely a result of the fact that the age
range was comparatively restricted in the present study, although younger
participants are more representative of the part-time population that was
central here, but seldom are included in other workplace studies. Nonetheless, future research is needed to understand the generalizability of the
present findings to a broader range of older and full-time employees.
Finally, there is evidence that the work–home spillover process is different
from the home–work process, and that spillover can also lead to positive
outcomes (Grzywacz & Marks, 2000). One reason why Wickens and Wiesenthal (2005) found inconsistent spillover effects in the post-work commute
may be that there were fewer instigating stimuli in comparison with the
workplace environment used in the present study, or that there is greater
anticipation of positive experiences (e.g., seeing family, relaxing) when traveling home, as compared to traveling to work (e.g., work demands, employee
conflicts). Future research should investigate how interpretations and actions
in the traffic environment are impacted by positive and negative experiences,
and how this environment alters thoughts, feelings, and actions in the subsequent work or home domain.

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