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The influence of music on mild driver aggression
Transportation Research Part F 6 (2003) 125–134 www.elsevier.com/locate/trf
The influence of music on mild driver aggression David L. Wiesenthal a, Dwight A. Hennessy
b,*
, Brad Totten
a
a
b
LaMarsh Programme for Research on Violence and Conflict Resolution, York University, Canada Department of Psychology, State University of New York College at Buffalo, Buffalo, NY 14222, USA Received 28 February 2002; received in revised form 8 August 2002; accepted 29 October 2002
Abstract Automobile drivers were randomly assigned to either a ‘‘music’’ or ‘‘non-music’’ group. The music group listened to their favorite music, while the non-music group abstained from any music or talk radio, during their entire commute to or from schoolnwork. Using a cellular telephone, state measures of driver aggression, time urgency, and stress arousal were obtained during a single commute in low and high congestion conditions. No predictors of mild aggression were found in low congestion. In high congestion, a music X time urgency interaction was found. Mild aggression was lower among those listening to music but only at low levels of time urgency. Results are interpreted in terms of the distractibility and relaxation effects. Ó 2003 Elsevier Ltd. All rights reserved. Keywords: Aggression; Transportation; Time urgency; Music
1. The influence of music on driver stress Mild driver aggression has been defined as any intentionally harmful action within the driving context, including horn honking, swearing, and using hand gestures (Hauber, 1980; Hennessy & Wiesenthal, 1999; McGarva & Steiner, 2000). Compared to more extreme acts of roadway violence (e.g. fighting, chasing, and shooting) mild driver aggression is a fairly common response to frustration, irritation, and hassles (Hennessy & Wiesenthal, 2001b). Recent research has found that traffic congestion can be a powerful precursor to roadway aggression, largely due to increased stress, arousal, and time urgency (Gulian, Matthews, Glendon, Davies, & Debney, 1989; Hennessy, 2000; Hennessy & Wiesenthal, 1999; Shinar, 1998). As traffic congestion increases, other
*
Corresponding author. Tel.: +1-716-878-5532; fax: +1-716-878-6228. E-mail address: hennesda@buffalostate.edu (D.A. Hennessy).
1369-8478/$ - see front matter Ó 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S1369-8478(03)00020-2
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drivers are viewed as an obstacle to reaching a destination in a desired time frame, leading to stress induced anger and frustration (Shinar, 1998; Stokols, Novaco, Stokols, & Campbell, 1978). Music has been found to reduce stress, anger, agitation, and arousal due, in part, to distraction (McCaffery, 1990; Wiesenthal, Hennessy, & Totten, 2000b; Wostratzky, Braun, & Roth, 1988). According to Hoyos (1988), as the number of demands for attention increase, the amount of resources available to any single source is decreased. Music acts as a distracter in that it assumes a portion of cognitive or attentional resources that might otherwise be directed toward a negative or demanding stimulus (Baron, 1986). As attention to music increases, cognitive resources are diverted from negative stimuli, thus reducing negative affect and behavior. Within the driving environment, frustration and provocation from other drivers represent common negative events that have been found to increase the likelihood of mild aggression (Hennessy & Wiesenthal, 2001a; McGarva & Steiner, 2000; Wiesenthal, Hennessy, & Gibson, 2000a). By redirecting attention from such conditions, music should consequently minimize the motivation, justification, and objective behind mild driver aggression. Music may also influence negative behavior through relaxation (Kroener, Diergarten, Diergarten, & Seeger, 1988; Stratton, 1992). Under demanding or undesirable conditions, heart rate, blood pressure, general arousal and negative affect have been found to increase (Everly, 1989; Novaco, Stokols, Campbell, & Stokols, 1979; Selye, 1974). These in turn have been linked to increased aggressive behaviors in a variety of settings, such as crowding (Worchel & Teddlie, 1976), excessive noise (Donnerstein & Wilson, 1976), exercise (Zillmann, Katcher, & Milavsky, 1972), and traffic congestion (Hennessy, 2000). However, music has been found to reduce both physiological and psychological stress and arousal (Hammer, 1996; Hanser & Thompson, 1994; Holland, 1995; Parente, 1989; Takeshi & Nakamura, 1991), particularly when it is preferred or self selected musical varieties (Allen & Blascovich, 1994; Anderson, Baron, & Logan, 1991; Stratton & Zalanowski, 1984). The ability of music to reduce these processes in the driving environment should also lead to decreased driver aggression. Arguably, the strongest evidence of a link between music and aggression has emerged from the field of music therapy. Music has been consistently found to reduce agitation, anger, negative thoughts, and aggression (Bright, 1986; Caspy, Peleg, Schlam, & Goldberg, 1988; Montello & Coons, 1998; Sidorenko, 2000). Nonetheless, this effect has been demonstrated most prominently in clinical and elderly samples with behavioral or cognitive disorders (e.g. Gardiner, Furois, Tansley, & Morgan, 2000; Gerdner, 2000; Lou, 2001; Montello & Coons, 1998). Currently it is not clear if this influence is directly generalizable to every day situations, such as vehicular driving. Contrary evidence has begun to suggest that aggressive lyrics and symbols in rock, heavy metal and rap music may actually increase anger and aggressive tendencies (Barongan & Hall, 1995; Gowensmith & Bloom, 1997; Litman, 1997). This research has typically utilized overtly aggressive lyrics that are not the norm across the majority of musical genres. Further, they have relied heavily on laboratory based manipulations which lack contextual elements that can impact aggression in applied settings, such as personal interactions and aggressive cues (Berkowitz, 1993). In order to understand the potential impact of music on driver aggression, situational realism is important. According to Hennessy and Wiesenthal (1999), roadway aggression is dependent on the interaction of the driver with their social and physical environment. While previous methods have been used to collect driver responses immediately following a commute, such as tape recorders (Underwood, Chapman, Wright, & Crundall, 1999) and diaries (Gulian, Glendon,
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Matthews, Davies, & Debney, 1990), the present study was designed as a more direct examination of the influence of self selected music on the frequency of mild driver aggression in actual low and high traffic congestion conditions. 1.1. Hypotheses 1. Music will only influence mild driver aggression in high congestion. 2. Mild driver aggression will be predicted by the interaction of time urgency X music, in that time urgency will increase mild driver aggression among drivers not listening to music. 3. Mild driver aggression will be predicted by the interaction of arousal X music. Specifically, aroused drivers will exhibit elevated driver aggression among drivers not listening to music.
2. Method 2.1. Research participants The present study included 20 female and 20 male participants that commuted daily to York University or the surrounding community. All were recruited as voluntary participants through posted signs, personal contact, and referrals. The ages ranged from 20 to 50 years, with an average of 25.60 years (M ¼ 25:95 years for females and M ¼ 25:25 years for males). 2.2. Apparatus Nokia cellular telephones (model number LX12/C15) were equipped with a cigarette lighter power adapter for continuous in-automobile power access. A visor mounted microphone provided hands-free capability. A single button speed dial function was standard on all telephones. 2.3. Measures 2.3.1. State driver aggression The State Driver Aggression Questionnaire (Hennessy & Wiesenthal, 1997, 1999) was developed to measure the frequency of mild aggressive behaviors in actual driving situations and was designed to be administered verbally. Responses were placed on a Likert scale ranging from 0 ¼ ‘‘not at all’’ to 100 ¼ ‘‘very frequently’’, indicating how frequently each behavior was used in the specific driving situations during the previous 5 min. Items included horn honking out of frustration, flashing high beams out of frustration, swearing/yelling at other drivers, purposely tailgating, and using obscene gestures. An aggregate mild driver aggression score was calculated as the mean response to the five individual items separately in low and high congestion. Higher scores indicated a greater use of mild aggressive driving behaviors in that condition. 2.3.2. Arousal, time urgency, and perceived control The Stress Arousal Checklist (Mackay, Cox, Burrows, & Lazzerini, 1978) is a self report measure of situational stress and arousal (Duckro, Korytnyk, & Vandenberg, 1989). It consists of
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34 adjectives (15 arousal and 19 stress items) that are rated on a four-point scale to indicate current feelings. Due to time constraints in administration during actual driving conditions, the present study used only 10 arousal items. Responses were placed on a Likert-type scale ranging from 0 ¼ ‘‘strongly disagree’’ to 100 ¼ ‘‘strongly agree’’ indicating the extent to which participants agreed that each item pertained to their experience in the present driving situation. Using the same 0–100 scale, three items were used to tap time urgency, (‘‘I am in a hurry’’, ‘‘I am concerned about getting to my destination on time’’, and the reverse-keyed item ‘‘I have a flexible time schedule’’) and one item was included to examine perceived control (‘‘I feel I have control over this driving situation’’). A time urgency score was calculated as the mean response to the two positive keyed and one reverse keyed items. Finally, a manipulation check was added to determine if low and high traffic congestion conditions were, in fact, perceived as distinct (‘‘Traffic conditions are congested’’). 2.4. Procedure Instructions regarding the experimental procedure and cellular telephone operation were given during the initial appointment. Participants then provided information regarding their regular travel route along Highway 401, since all measures were administered during their usual daily commute. Highway 401 was chosen because it is the major traffic artery for Metropolitan Toronto, with as many as 14 lanes, divided into a series of express and collector lanes. For each participant, two areas along their regular commuting route were chosen: one that is typically lowest and one that is typically highest in traffic congestion. These would represent the two areas in which participants would later initiate cellular telephone calls to the experimenter to complete the questionnaires. Both the low and high congestion telephone interviews were scheduled during a single journey. Two counterbalanced groups of drivers were formed: those that typically encountered high prior to low traffic volumes, and those that encountered low prior to high volumes. Drivers were further randomly assigned to either a ‘‘music’’ or ‘‘non-music’’ group, with a stipulation of equal gender representation in each group. The music group were instructed to select a cassette tape or compact disc (no radio was allowed) of their favorite music to play during their entire trip. As a point of note, all participants self selected music in the ‘‘pop’’, ‘‘top 40’’ or ‘‘country’’ categories. The non-music group was instructed specifically not to listen to music (or talk radio) during their entire journey. All participants were alone in their automobiles for the duration of their journey. Prior to initiating their commute, participants were allowed to make a practice cellular telephone call to the experimenter, in order to ensure that the telephone was functioning properly and to avoid any confusion regarding its use while actually driving. No measurement took place during the pre-test telephone call. Participants were reminded of their task and instructed to commence their journey as usual. Upon approaching their first target area (which was designated during the initial meeting with the experimenters), participants telephoned the researcher, utilizing a single button speed dial feature. Once a successful telephone contact was made the State Driver Aggression Questionnaire was administered verbally, along with the stress arousal, time urgency, perceived control and manipulation check questions. Upon completion of the first telephone interview, the telephone call was terminated and the participants continued driving until their second target area was reached, which prompted the second telephone call.
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All questions were again administered verbally, after which the telephone call was terminated. All measures were obtained on weekdays between October and February in Toronto, Ontario. No measurements were collected during rain or snow in order to avoid confounding by poor weather.
3. Results In both low and high congestion, an aggregate mild driver aggression score was calculated as the mean response to the five individual items. A Paired Sample t-Test was conducted to determine if mild driver aggression differed across congestion conditions. The reported frequency of aggression was greater in high than in low congestion (M ¼ 12:10, SD ¼ 12:60 and M ¼ 4:45, SD ¼ 7:94 respectively; tð39Þ ¼ 5:90, p < :05). Descriptive statistics for mild driver aggression, stress arousal, time urgency, and perceived control appear in Table 1. A median split was used to categorize participants as low or high on stress arousal, time urgency, and perceived control in both low and high congestion. Separate ANOVAs were conducted to determine unique predictors of mild driver aggression in low and Table 1 Descriptive statistics for state driver aggression, stress arousal, time urgency, and perceived control in low and high congestion Aggression (HC) Aggression (LC) Time urgency (HC) Time urgency (LC) Control (HC) Control (LC) Stress arousal (HC) Stress arousal (LC)
M
SD
Minimum
Maximum
12.10 4.45 49.94 48.78 70.00 79.62 42.35 33.35
12.60 7.94 23.75 23.96 26.16 20.26 18.20 14.75
0.00 0.00 0.00 0.00 0.00 5.00 5.00 1.67
46.00 28.00 90.00 91.67 100.00 100.00 73.89 64.44
Note: n ¼ 40; HC ¼ high congestion, LC ¼ low congestion.
Fig. 1. Mean driver aggression levels between low and high time urgent drivers within music and non-music conditions.
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high congestion conditions, with music, arousal, time urgency, perceived control, and gender as main effect predictors. Consistent with hypothesis 1, there were no significant predictors of mild driver aggression in the low congestion condition. Hypothesis 2 was confirmed in that mild driver aggression was predicted by the interaction of time urgency X music, although the form was not as expected (F ð1; 24Þ ¼ 6:63, p < :05). In high congestion conditions, drivers listening to music demonstrated lower levels of mild aggression, but only at low levels of time urgency. As time urgency increased, aggression increased to match the levels of those that did not listen to music. Hypothesis 3 was not confirmed. Arousal did not predict mild aggression levels (Fig. 1).
4. Discussion As expected, music had an influence on mild driver aggression in high congestion but not low congestion. This is likely due to the fact that overall levels of driver aggression were much lower in low congestion than in high congestion. As a result, the lack of influence of music on mild driver aggression may reflect a floor effect in low congestion. Previous research has demonstrated that drivers are more likely to exhibit adverse psychological and physiological reactions to high congestion conditions, such as increased heart rate, blood pressure, arousal, frustration and negative mood, that can significantly increase aggressive tendencies (Guar, 1988; Hennessy & Wiesenthal, 1997; Novaco, 1991; Stokols et al., 1978). Further, high congestion provides greater sources of frustration and irritation, and, consequently, greater opportunities to engage in mild driver aggression (Hennessy, 2000; Hennessy & Wiesenthal, 1999). Within high congestion, the non-music group demonstrated consistently elevated levels of aggression across low and high time urgency. In contrast, drivers listening to music reported lower levels of mild aggression, but only in association with a low degree of time urgency. In this respect, it is possible that music may provide a degree of distraction from potential irritating and frustrating traffic stimuli, but only when other salient personal stressors, such as time concerns, are minimal. Under low time urgency, drivers may have had greater opportunity and impetus to focus their attention on music rather than external demands of driving. Music has been found to obscure peripheral environmental stimuli in cognitive and motor tasks (Furnham & Bradley, 1997; Poulton, 1979). As a result they may have been less likely to notice potential sources of frustration, anger, and threat in the congested traffic environment, leading to lower levels of aggression. However, under time pressure, individuals typically focus greater attention on the most salient available stimuli (Stern, 1999). For drivers under more intense time constraints, attention resources may have switched away from music to the current driving demands in order to more accurately cope with and achieve time limited goals (see Haigney, Taylor, & Westerman, 2000). Consequently music would not have the same ability to distract. This would represent a condition similar to those in the non-music group that experienced no distraction in either low or high time urgency. It is possible that the increased focus on the driving situation and, in particular, other drivers, may have increased the personal perception of frustration, irritation, anger, threat and provocation which have been linked to elevated driver aggression (Gulian, Matthews, Glendon, Davies, & Debney, 1989; Hennessy & Wiesenthal, 1999; McGarva & Steiner, 2000; Novaco, 1991; Wiesenthal et al., 2000a).
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Another explanation may be that music provided a mood enhancing effect among drivers with minimal time urgency. According to Wiesenthal et al. (2000b), music can reduce stress and negative affect in the traffic environment. However, high congestion has been found to be a strong precursor to psychological stress, irritation, and anger (Gulian, Debney, Glendon, Davies, & Matthews, 1989; Hennessy & Wiesenthal, 1997), which can subsequently increase driver aggression (Hennessy & Wiesenthal, 1999). Further, this tendency is typically compounded by elevated time demands (Hennessy & Wiesenthal, 1999; Hennessy, Wiesenthal, & Kohn, 2000). In contrast to low time urgent drivers, it is possible that the combined impact of congested traffic conditions and heightened time urgency supplanted the mood enhancing effects of music; thus creating stressful conditions similar to drivers without music and increasing the likelihood of mild driver aggression. Contrary to expectation, the present study failed to find an interactive influence of music and arousal on mild driver aggression. This may be due to the fact that aggression was most prevalent in high congestion, in which arousal is typically higher for all drivers. It is possible that the restricted measurement of arousal in the present study was not sensitive enough to demonstrate adequate variability in overall arousal levels between drivers. The current evaluation of arousal was also limited to psychological interpretation, while previous links between arousal and aggression have also focused on physiological processes. Further, the impact of arousal on aggression may depend on more complex relationships with other individual factors, such as stress susceptibility, daily hassles, and coping styles. Further research is needed to more accurately understand the process of arousal-linked aggression. 4.1. Limitations and future research The present findings support the importance of the situation in understanding mild aggression. Specifically, the relationship between music and mild aggression was only evident in high congestion and only in association with time urgency. However, the present study used only self selected music with no control over the content. According to Rubin, West, and Mitchell (2001), there is evidence that individuals with pre-existing aggressive tendencies may be attracted to aggressive lyrics and thus demonstrate elevated aggression while listening to music. Further research is needed to understand how personal differences interact with different musical styles to influence driver aggression. Another limitation of the present study was the fact that the chosen traffic conditions were intentionally polar, yet drivers experience a wide range of congestion conditions. Future research is needed to understand the relationship between music and stress in a greater variety of traffic conditions over several commutes with multiple measurements during each trip. Similarly, each participant was interviewed during a single commute. The interaction of thoughts, feelings, and behaviors may have been more complex than a single measure would allow. A more detailed analysis of daily routines, hassles, and general behavior patterns may be required to more clearly understand the impact of music and aggression. Finally, while the present study has suggested that music may distract drivers from irritating stimuli in the driving environment and thus reducing aggressive behavior, Brodsky (2002) has recently recommended that music may act to distract drivers to the point of reduced performance and increased violations. Due to the fact that the present study did not include performance indices, future research is needed to understand how music, time urgency, and resulting aggression interact to influence driver performance.
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Acknowledgements This manuscript is based, in part, on research conducted by Brad Totten in partial fulfilment of the BachelorÕs degree requirements of York University. The research was supervised by Professor David Wiesenthal. Pilot research was assisted by the generous donation of cellular telephones by Motorola Canada and cellular air time by Bell Mobility Canada. This research was partially supported by a grant from the Ministry of Transportation of Ontario. Opinions expressed in this report are those of the authors and do not necessarily reflect the views and policies of the Ministry. References Allen, K., & Blascovich, J. (1994). Effects of music on cardiovascular reactivity among surgeons. Journal of the American Medical Association, 272, 882–884. Anderson, R. A., Baron, R. S., & Logan, H. (1991). Distraction, control, and dental stress. Journal of Applied Social Psychology, 21, 156–171. Baron, R. S. (1986). Distraction-conflict theory. Progress and problems. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 19, pp. 1–40). New York: Academic Press. Barongan, C., & Hall, G. C. N. (1995). The influence of misogynous rap music on sexual aggression against women. Psychology of Women Quarterly, 19, 195–207. Berkowitz, L. (1993). Aggression: Its causes and consequences. Boston: McGraw Hill. Bright, R. (1986). The use of music therapy and activities with demented patients who are deemed ‘‘difficult to manage’’. The elderly uncooperative patient [Special issue]. Clinical Gerontologist, 6, 131–144. Brodsky, W. (2002). The effects of music tempo on simulated driving performance and vehicular control. Transportation Research Part F, 4, 219–241. Caspy, T., Peleg, E., Schlam, D., & Goldberg, J. (1988). Sedative and stimulative music effects: Differential effects on performance impairment following frustration. Motivation and Emotion, 12, 123–138. Donnerstein, E., & Wilson, D. (1976). The effects of noise and perceived control upon ongoing and subsequent aggressive behavior. Journal of Personality and Social Psychology, 34, 774–781. Duckro, P. N., Korytnyk, N. X., & Vandenberg, B. R. (1989). The Stress-Arousal Checklist as a measure of situational stress versus simple arousal. Psychological Reports, 64, 239–242. Everly, G. S. (1989). A clinical guide to the treatment of the human stress response. New York: Plenum. Furnham, A., & Bradley, A. (1997). Music while you work: The differential distraction of background music on the cognitive test performance of introverts and extroverts. Applied Cognitive Psychology, 11, 445–455. Gardiner, J. C., Furois, M., Tansley, D. P., & Morgan, B. (2000). Music therapy and reading as intervention strategies for disruptive behavior in dementia. Clinical Gerontologist, 22, 31–46. Gerdner, L. A. (2000). Effects of individualized versus classical ‘‘relaxation’’ music on the frequency of agitation in elderly persons with AlzheimerÕs disease and related disorders. International Psychogeriatrics, 12, 49–65. Gowensmith, W. N., & Bloom, L. J. (1997). Effects of heavy metal music on arousal and anger. Journal of Music Therapy, 34, 33–45. Guar, S. D. (1988). Noise: Does it make you angry? Indian Psychologist, 5, 51–56. Gulian, E., Debney, L. M., Glendon, A. I., Davies, D. R., & Matthews, G. (1989). Coping with driver stress. In F. McGuigan, W. E. Sime, & J. M. Wallace (Eds.), Stress and tension control (Vol. 3, pp. 173–186). New York: Plenum. Gulian, E., Matthews, G., Glendon, A. I., Davies, D. R., & Debney, L. M. (1989). Dimensions of driver stress. Ergonomics, 32, 585–602. Gulian, E., Glendon, A. I., Matthews, G., Davies, D. R., & Debney, M. (1990). The stress of driving: A diary study. Work and Stress, 4, 7–16. Haigney, D. E., Taylor, R. G., & Westerman, S. J. (2000). Concurrent mobile (cellular) phone use and driving performance: Task demand characteristics and compensatory processes. Transportation Research Part F, 3, 113–121.
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The influence of music on mild driver aggression David L. Wiesenthal a, Dwight A. Hennessy
b,*
, Brad Totten
a
a
b
LaMarsh Programme for Research on Violence and Conflict Resolution, York University, Canada Department of Psychology, State University of New York College at Buffalo, Buffalo, NY 14222, USA Received 28 February 2002; received in revised form 8 August 2002; accepted 29 October 2002
Abstract Automobile drivers were randomly assigned to either a ‘‘music’’ or ‘‘non-music’’ group. The music group listened to their favorite music, while the non-music group abstained from any music or talk radio, during their entire commute to or from schoolnwork. Using a cellular telephone, state measures of driver aggression, time urgency, and stress arousal were obtained during a single commute in low and high congestion conditions. No predictors of mild aggression were found in low congestion. In high congestion, a music X time urgency interaction was found. Mild aggression was lower among those listening to music but only at low levels of time urgency. Results are interpreted in terms of the distractibility and relaxation effects. Ó 2003 Elsevier Ltd. All rights reserved. Keywords: Aggression; Transportation; Time urgency; Music
1. The influence of music on driver stress Mild driver aggression has been defined as any intentionally harmful action within the driving context, including horn honking, swearing, and using hand gestures (Hauber, 1980; Hennessy & Wiesenthal, 1999; McGarva & Steiner, 2000). Compared to more extreme acts of roadway violence (e.g. fighting, chasing, and shooting) mild driver aggression is a fairly common response to frustration, irritation, and hassles (Hennessy & Wiesenthal, 2001b). Recent research has found that traffic congestion can be a powerful precursor to roadway aggression, largely due to increased stress, arousal, and time urgency (Gulian, Matthews, Glendon, Davies, & Debney, 1989; Hennessy, 2000; Hennessy & Wiesenthal, 1999; Shinar, 1998). As traffic congestion increases, other
*
Corresponding author. Tel.: +1-716-878-5532; fax: +1-716-878-6228. E-mail address: hennesda@buffalostate.edu (D.A. Hennessy).
1369-8478/$ - see front matter Ó 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S1369-8478(03)00020-2
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drivers are viewed as an obstacle to reaching a destination in a desired time frame, leading to stress induced anger and frustration (Shinar, 1998; Stokols, Novaco, Stokols, & Campbell, 1978). Music has been found to reduce stress, anger, agitation, and arousal due, in part, to distraction (McCaffery, 1990; Wiesenthal, Hennessy, & Totten, 2000b; Wostratzky, Braun, & Roth, 1988). According to Hoyos (1988), as the number of demands for attention increase, the amount of resources available to any single source is decreased. Music acts as a distracter in that it assumes a portion of cognitive or attentional resources that might otherwise be directed toward a negative or demanding stimulus (Baron, 1986). As attention to music increases, cognitive resources are diverted from negative stimuli, thus reducing negative affect and behavior. Within the driving environment, frustration and provocation from other drivers represent common negative events that have been found to increase the likelihood of mild aggression (Hennessy & Wiesenthal, 2001a; McGarva & Steiner, 2000; Wiesenthal, Hennessy, & Gibson, 2000a). By redirecting attention from such conditions, music should consequently minimize the motivation, justification, and objective behind mild driver aggression. Music may also influence negative behavior through relaxation (Kroener, Diergarten, Diergarten, & Seeger, 1988; Stratton, 1992). Under demanding or undesirable conditions, heart rate, blood pressure, general arousal and negative affect have been found to increase (Everly, 1989; Novaco, Stokols, Campbell, & Stokols, 1979; Selye, 1974). These in turn have been linked to increased aggressive behaviors in a variety of settings, such as crowding (Worchel & Teddlie, 1976), excessive noise (Donnerstein & Wilson, 1976), exercise (Zillmann, Katcher, & Milavsky, 1972), and traffic congestion (Hennessy, 2000). However, music has been found to reduce both physiological and psychological stress and arousal (Hammer, 1996; Hanser & Thompson, 1994; Holland, 1995; Parente, 1989; Takeshi & Nakamura, 1991), particularly when it is preferred or self selected musical varieties (Allen & Blascovich, 1994; Anderson, Baron, & Logan, 1991; Stratton & Zalanowski, 1984). The ability of music to reduce these processes in the driving environment should also lead to decreased driver aggression. Arguably, the strongest evidence of a link between music and aggression has emerged from the field of music therapy. Music has been consistently found to reduce agitation, anger, negative thoughts, and aggression (Bright, 1986; Caspy, Peleg, Schlam, & Goldberg, 1988; Montello & Coons, 1998; Sidorenko, 2000). Nonetheless, this effect has been demonstrated most prominently in clinical and elderly samples with behavioral or cognitive disorders (e.g. Gardiner, Furois, Tansley, & Morgan, 2000; Gerdner, 2000; Lou, 2001; Montello & Coons, 1998). Currently it is not clear if this influence is directly generalizable to every day situations, such as vehicular driving. Contrary evidence has begun to suggest that aggressive lyrics and symbols in rock, heavy metal and rap music may actually increase anger and aggressive tendencies (Barongan & Hall, 1995; Gowensmith & Bloom, 1997; Litman, 1997). This research has typically utilized overtly aggressive lyrics that are not the norm across the majority of musical genres. Further, they have relied heavily on laboratory based manipulations which lack contextual elements that can impact aggression in applied settings, such as personal interactions and aggressive cues (Berkowitz, 1993). In order to understand the potential impact of music on driver aggression, situational realism is important. According to Hennessy and Wiesenthal (1999), roadway aggression is dependent on the interaction of the driver with their social and physical environment. While previous methods have been used to collect driver responses immediately following a commute, such as tape recorders (Underwood, Chapman, Wright, & Crundall, 1999) and diaries (Gulian, Glendon,
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Matthews, Davies, & Debney, 1990), the present study was designed as a more direct examination of the influence of self selected music on the frequency of mild driver aggression in actual low and high traffic congestion conditions. 1.1. Hypotheses 1. Music will only influence mild driver aggression in high congestion. 2. Mild driver aggression will be predicted by the interaction of time urgency X music, in that time urgency will increase mild driver aggression among drivers not listening to music. 3. Mild driver aggression will be predicted by the interaction of arousal X music. Specifically, aroused drivers will exhibit elevated driver aggression among drivers not listening to music.
2. Method 2.1. Research participants The present study included 20 female and 20 male participants that commuted daily to York University or the surrounding community. All were recruited as voluntary participants through posted signs, personal contact, and referrals. The ages ranged from 20 to 50 years, with an average of 25.60 years (M ¼ 25:95 years for females and M ¼ 25:25 years for males). 2.2. Apparatus Nokia cellular telephones (model number LX12/C15) were equipped with a cigarette lighter power adapter for continuous in-automobile power access. A visor mounted microphone provided hands-free capability. A single button speed dial function was standard on all telephones. 2.3. Measures 2.3.1. State driver aggression The State Driver Aggression Questionnaire (Hennessy & Wiesenthal, 1997, 1999) was developed to measure the frequency of mild aggressive behaviors in actual driving situations and was designed to be administered verbally. Responses were placed on a Likert scale ranging from 0 ¼ ‘‘not at all’’ to 100 ¼ ‘‘very frequently’’, indicating how frequently each behavior was used in the specific driving situations during the previous 5 min. Items included horn honking out of frustration, flashing high beams out of frustration, swearing/yelling at other drivers, purposely tailgating, and using obscene gestures. An aggregate mild driver aggression score was calculated as the mean response to the five individual items separately in low and high congestion. Higher scores indicated a greater use of mild aggressive driving behaviors in that condition. 2.3.2. Arousal, time urgency, and perceived control The Stress Arousal Checklist (Mackay, Cox, Burrows, & Lazzerini, 1978) is a self report measure of situational stress and arousal (Duckro, Korytnyk, & Vandenberg, 1989). It consists of
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34 adjectives (15 arousal and 19 stress items) that are rated on a four-point scale to indicate current feelings. Due to time constraints in administration during actual driving conditions, the present study used only 10 arousal items. Responses were placed on a Likert-type scale ranging from 0 ¼ ‘‘strongly disagree’’ to 100 ¼ ‘‘strongly agree’’ indicating the extent to which participants agreed that each item pertained to their experience in the present driving situation. Using the same 0–100 scale, three items were used to tap time urgency, (‘‘I am in a hurry’’, ‘‘I am concerned about getting to my destination on time’’, and the reverse-keyed item ‘‘I have a flexible time schedule’’) and one item was included to examine perceived control (‘‘I feel I have control over this driving situation’’). A time urgency score was calculated as the mean response to the two positive keyed and one reverse keyed items. Finally, a manipulation check was added to determine if low and high traffic congestion conditions were, in fact, perceived as distinct (‘‘Traffic conditions are congested’’). 2.4. Procedure Instructions regarding the experimental procedure and cellular telephone operation were given during the initial appointment. Participants then provided information regarding their regular travel route along Highway 401, since all measures were administered during their usual daily commute. Highway 401 was chosen because it is the major traffic artery for Metropolitan Toronto, with as many as 14 lanes, divided into a series of express and collector lanes. For each participant, two areas along their regular commuting route were chosen: one that is typically lowest and one that is typically highest in traffic congestion. These would represent the two areas in which participants would later initiate cellular telephone calls to the experimenter to complete the questionnaires. Both the low and high congestion telephone interviews were scheduled during a single journey. Two counterbalanced groups of drivers were formed: those that typically encountered high prior to low traffic volumes, and those that encountered low prior to high volumes. Drivers were further randomly assigned to either a ‘‘music’’ or ‘‘non-music’’ group, with a stipulation of equal gender representation in each group. The music group were instructed to select a cassette tape or compact disc (no radio was allowed) of their favorite music to play during their entire trip. As a point of note, all participants self selected music in the ‘‘pop’’, ‘‘top 40’’ or ‘‘country’’ categories. The non-music group was instructed specifically not to listen to music (or talk radio) during their entire journey. All participants were alone in their automobiles for the duration of their journey. Prior to initiating their commute, participants were allowed to make a practice cellular telephone call to the experimenter, in order to ensure that the telephone was functioning properly and to avoid any confusion regarding its use while actually driving. No measurement took place during the pre-test telephone call. Participants were reminded of their task and instructed to commence their journey as usual. Upon approaching their first target area (which was designated during the initial meeting with the experimenters), participants telephoned the researcher, utilizing a single button speed dial feature. Once a successful telephone contact was made the State Driver Aggression Questionnaire was administered verbally, along with the stress arousal, time urgency, perceived control and manipulation check questions. Upon completion of the first telephone interview, the telephone call was terminated and the participants continued driving until their second target area was reached, which prompted the second telephone call.
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All questions were again administered verbally, after which the telephone call was terminated. All measures were obtained on weekdays between October and February in Toronto, Ontario. No measurements were collected during rain or snow in order to avoid confounding by poor weather.
3. Results In both low and high congestion, an aggregate mild driver aggression score was calculated as the mean response to the five individual items. A Paired Sample t-Test was conducted to determine if mild driver aggression differed across congestion conditions. The reported frequency of aggression was greater in high than in low congestion (M ¼ 12:10, SD ¼ 12:60 and M ¼ 4:45, SD ¼ 7:94 respectively; tð39Þ ¼ 5:90, p < :05). Descriptive statistics for mild driver aggression, stress arousal, time urgency, and perceived control appear in Table 1. A median split was used to categorize participants as low or high on stress arousal, time urgency, and perceived control in both low and high congestion. Separate ANOVAs were conducted to determine unique predictors of mild driver aggression in low and Table 1 Descriptive statistics for state driver aggression, stress arousal, time urgency, and perceived control in low and high congestion Aggression (HC) Aggression (LC) Time urgency (HC) Time urgency (LC) Control (HC) Control (LC) Stress arousal (HC) Stress arousal (LC)
M
SD
Minimum
Maximum
12.10 4.45 49.94 48.78 70.00 79.62 42.35 33.35
12.60 7.94 23.75 23.96 26.16 20.26 18.20 14.75
0.00 0.00 0.00 0.00 0.00 5.00 5.00 1.67
46.00 28.00 90.00 91.67 100.00 100.00 73.89 64.44
Note: n ¼ 40; HC ¼ high congestion, LC ¼ low congestion.
Fig. 1. Mean driver aggression levels between low and high time urgent drivers within music and non-music conditions.
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high congestion conditions, with music, arousal, time urgency, perceived control, and gender as main effect predictors. Consistent with hypothesis 1, there were no significant predictors of mild driver aggression in the low congestion condition. Hypothesis 2 was confirmed in that mild driver aggression was predicted by the interaction of time urgency X music, although the form was not as expected (F ð1; 24Þ ¼ 6:63, p < :05). In high congestion conditions, drivers listening to music demonstrated lower levels of mild aggression, but only at low levels of time urgency. As time urgency increased, aggression increased to match the levels of those that did not listen to music. Hypothesis 3 was not confirmed. Arousal did not predict mild aggression levels (Fig. 1).
4. Discussion As expected, music had an influence on mild driver aggression in high congestion but not low congestion. This is likely due to the fact that overall levels of driver aggression were much lower in low congestion than in high congestion. As a result, the lack of influence of music on mild driver aggression may reflect a floor effect in low congestion. Previous research has demonstrated that drivers are more likely to exhibit adverse psychological and physiological reactions to high congestion conditions, such as increased heart rate, blood pressure, arousal, frustration and negative mood, that can significantly increase aggressive tendencies (Guar, 1988; Hennessy & Wiesenthal, 1997; Novaco, 1991; Stokols et al., 1978). Further, high congestion provides greater sources of frustration and irritation, and, consequently, greater opportunities to engage in mild driver aggression (Hennessy, 2000; Hennessy & Wiesenthal, 1999). Within high congestion, the non-music group demonstrated consistently elevated levels of aggression across low and high time urgency. In contrast, drivers listening to music reported lower levels of mild aggression, but only in association with a low degree of time urgency. In this respect, it is possible that music may provide a degree of distraction from potential irritating and frustrating traffic stimuli, but only when other salient personal stressors, such as time concerns, are minimal. Under low time urgency, drivers may have had greater opportunity and impetus to focus their attention on music rather than external demands of driving. Music has been found to obscure peripheral environmental stimuli in cognitive and motor tasks (Furnham & Bradley, 1997; Poulton, 1979). As a result they may have been less likely to notice potential sources of frustration, anger, and threat in the congested traffic environment, leading to lower levels of aggression. However, under time pressure, individuals typically focus greater attention on the most salient available stimuli (Stern, 1999). For drivers under more intense time constraints, attention resources may have switched away from music to the current driving demands in order to more accurately cope with and achieve time limited goals (see Haigney, Taylor, & Westerman, 2000). Consequently music would not have the same ability to distract. This would represent a condition similar to those in the non-music group that experienced no distraction in either low or high time urgency. It is possible that the increased focus on the driving situation and, in particular, other drivers, may have increased the personal perception of frustration, irritation, anger, threat and provocation which have been linked to elevated driver aggression (Gulian, Matthews, Glendon, Davies, & Debney, 1989; Hennessy & Wiesenthal, 1999; McGarva & Steiner, 2000; Novaco, 1991; Wiesenthal et al., 2000a).
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Another explanation may be that music provided a mood enhancing effect among drivers with minimal time urgency. According to Wiesenthal et al. (2000b), music can reduce stress and negative affect in the traffic environment. However, high congestion has been found to be a strong precursor to psychological stress, irritation, and anger (Gulian, Debney, Glendon, Davies, & Matthews, 1989; Hennessy & Wiesenthal, 1997), which can subsequently increase driver aggression (Hennessy & Wiesenthal, 1999). Further, this tendency is typically compounded by elevated time demands (Hennessy & Wiesenthal, 1999; Hennessy, Wiesenthal, & Kohn, 2000). In contrast to low time urgent drivers, it is possible that the combined impact of congested traffic conditions and heightened time urgency supplanted the mood enhancing effects of music; thus creating stressful conditions similar to drivers without music and increasing the likelihood of mild driver aggression. Contrary to expectation, the present study failed to find an interactive influence of music and arousal on mild driver aggression. This may be due to the fact that aggression was most prevalent in high congestion, in which arousal is typically higher for all drivers. It is possible that the restricted measurement of arousal in the present study was not sensitive enough to demonstrate adequate variability in overall arousal levels between drivers. The current evaluation of arousal was also limited to psychological interpretation, while previous links between arousal and aggression have also focused on physiological processes. Further, the impact of arousal on aggression may depend on more complex relationships with other individual factors, such as stress susceptibility, daily hassles, and coping styles. Further research is needed to more accurately understand the process of arousal-linked aggression. 4.1. Limitations and future research The present findings support the importance of the situation in understanding mild aggression. Specifically, the relationship between music and mild aggression was only evident in high congestion and only in association with time urgency. However, the present study used only self selected music with no control over the content. According to Rubin, West, and Mitchell (2001), there is evidence that individuals with pre-existing aggressive tendencies may be attracted to aggressive lyrics and thus demonstrate elevated aggression while listening to music. Further research is needed to understand how personal differences interact with different musical styles to influence driver aggression. Another limitation of the present study was the fact that the chosen traffic conditions were intentionally polar, yet drivers experience a wide range of congestion conditions. Future research is needed to understand the relationship between music and stress in a greater variety of traffic conditions over several commutes with multiple measurements during each trip. Similarly, each participant was interviewed during a single commute. The interaction of thoughts, feelings, and behaviors may have been more complex than a single measure would allow. A more detailed analysis of daily routines, hassles, and general behavior patterns may be required to more clearly understand the impact of music and aggression. Finally, while the present study has suggested that music may distract drivers from irritating stimuli in the driving environment and thus reducing aggressive behavior, Brodsky (2002) has recently recommended that music may act to distract drivers to the point of reduced performance and increased violations. Due to the fact that the present study did not include performance indices, future research is needed to understand how music, time urgency, and resulting aggression interact to influence driver performance.
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