The Influence of Music on Driver Stress1

The Influence of Music on Driver Stress1 DA VID L. WIESENTHAL2 LaMar.I'h Cel1lrefiJr Research on r'7o/enceand CO'!(licl Resolulion t()rk Universily Norlh }ork. Ol1lario. Canada DWIGHT A. HENNESSY Bl!{faloSlaleCollege(!f'lheSlale UniversilyofNel\' }C)rk BRAD TOTTEN LaMarsh Cel1lreforResearch on Violence and Co'!(licl Resolulion York Universily Norlh York. Onlario. Canada In order to examine the etlicacy of music in dealing with daily stressors, automobile drivers were randomly assigned to either a music or nonmusic group. The music group listened to their favorite music, while the nonmusic group abstained from aQYmusic or talk radio during their entire commute to or from school or work. Using a cellular telephone, state measuresof driver stress were obtained during a single commute in low- and highcongestion conditions. A Condition x Music Group interaction was found. Driver stress was greater in high congestion than in low congestion, but the nonmusic group demonstrated extreme levels of stress within high congestion. Listening to self-selected music appeared to limit driver stress only within highly frustrating and irritating tramc congestion. Driving as a Source of Stress Automobile driving is an event that is often interpreted as stressful (Gulian; Matthews, Glendon, & Davies, 1989;Hennessy & Wiesenthal, 1997).Within any IThis manuscript is basedon researchconducted by Dwight Hennessy in partial fulfillment ofth~ master's degree requirements of York University and supervised by David Wiesenthal. The author$ thank Clary Lay and Mike Ziegler who served on the thesis committee, as well as Bob Lambie and Torry Hoff for their assistance. Pilot research was assisted by the donation of cellular telephones b~ Motorola Canada and cellular airtime by Bell Mobility Canada.This researchwas partially supporteq by a grant from the Ministry of Transportation of Ontario. Opinions expressed in this report are thos~ of the authors and do not necessarily reflect the views and policies of the Ministry. 2Correspondence concerning this article should be addressed to David L. Wiesenthal, LaMarsh Centre for Research on Violence and Conflict Resolution, 217E York Lanes, York University, 4700 Keele Street, North York, Ontario M3J I P3, Canada. ' 1709 Journal of Applied Social Psychology, 2000, 30, 8, pp. 1709-1719. Copyright @ 2000 by V. H. Winston & Son, Inc. All rights reserved. '" 1710 WIESENTHAL ET AL. INFLUENCE OF MUSIC ON DRIVER STRESS driving encounter, there is a multitude of stimuli that may be perceived as undesirable or demanding, such as bad weather, time pressures, or slow-moving vehicles. According to Broome (1985), stress typically occurs when goals (e.g., getting to work on time or traveling at a desired pace) are blocked. Most regular commuters report facing numerous frustrations or irritations that lead to driver stress (Gulian, Matthews, et aI., 1989; Novaco, Stokols, & Milanesi, 1990). One of the most salient sources of driver stress that has been identified is traffic congestion (Gulian, Matthews, et aI., 1989; Novaco, Stokols, Campbell, & Stokols. 1979). Drivers interviewed in actual traffic conditions report greater driver stress in high than in low congestion, with drivers predisposed to stress reacting most negatively in congested conditions (Hennessy & Wiesenthal, 1997). Within high congestion, increased traffic volume forces a slower travel pace and creates the potential for negative interpretations of the situation. If the number of automobiles using the road system, in the absence of additional highway construction, continues to increase, driver stress levels are destined to escalate (Taylor, 1997). Indications of psychological and physiologicalstress, such as increased blood pressure and heart rate (Novaco et aI., 1979; Stokols, Novaco, Stokols, & Campbell, 1978),negative mood (Gulian, Debney,Glendon, Davies,& Matthews, 1989),emotional arousal (Hennessy& Wiesenthal, 1997),and poor general health (Hartley & EI Hassani, 1994),have been observedwithin undesirabledriving conditions. Traffic accidents have also been found to increase under conditions of driver stress (Selzer & Vinokur, 1974). Other consequences include increased aggression (Hennessy & Wiesenthal, 1999) and poor concentration (Matthews, Dom, & Glendon, 1991),which have been linked independentlywith further accident and violation probability (Hansen, 1988;Hartley & EI Hassani, 1994; Mihal & Barrett, 1976; Roy & Choudhary, 1985; Shinar, 1978). The danger of driver stress is amplified by the fact that it interacts within other life settings (Novaco et aI., 1990) to produce a syndrome of negative outcomes. Stress experienced while driving has been found to influence subsequent affect, health, and behavior at work and home (Gulian, Debney,et aI., 1989). Music and Stress Music therapy has been found to be an effective tool in controlling psychological stress through a variety of psychological and physiological processes, such as reductions in tension (Holland, 1995); arousal (Takeshi & Nakamura, 1991); anxiety (Hammer, 1996; Parente, 1989); negative affect (Hanser & Thompson, 1994); and blood pressure, heart rate, and skin conductance (Aldridge, 1993;Allen & Blascovich, 1994);and an increase in immune response (Bartlett, Kaufman, & Smeltekop, 1993). Music may also increase performance and perceptions of situational control (Anderson, Baron, & Logan, 1991; Stevens, 1990). According to Allen and Blascovich (\ 994), surgeons who 1711 listened to self-selected music while operating experienced a reduction in both blood pressure and pulse rate and, as a result, performed more effectively under the stressful conditions of surgery. Similarly, dental patients who listened to music while undergoing treatment rated control over their treatment as higher and displayed less pain and stress, which, in turn, facilitated furtl1er stress reduction in the specialist, who performed a more technically correct procedure (Anderson et aI., 1991). The utility of music as a stress-reduction tool is heightened by the fact that it is very simple to implement, inexpensive, and typically requires little to no training (Avants,Margolin, & Salovey, 1991). One mechanism through which music facilitates coping is as a distraction from stressful stimuli. Music has been found to briefly distract patients from the experience of pain and stress (McCaffery, 1990; Wostratzky, Braun~ & Roth, 1988). According to Hoyos (1988), attention capacity is a limited cognitive resource, divisible among multiple tasks. As the number of demands for attention increases, 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 stressful situation (Baron, 1986). As a result, the salience of the experienced stressor is reduced. However, under conditions of extreme demand or multiple stressors, cognitive overload (Milgram, 1970) can occur, where demands exceed cognitive resources, resulting in elevated stress (Wildevanck, MaIder, & Michon, 1978). Under conditions of overload, participants have been found to focus attention on the most salient demands and to ignore more peripheral requirements, such as music (Baron, 1986). Music also acts to facilitate relaxation, which relieves psychological and physiological arousal (Kroener, Diergarten, Diergarten, & Seeger, 1988). Those individuals listening to music have been found to report greater levels of relaxation during exposure to the stressors of both social density and excessive noise (Kroener et aI., 1988; Stratton, 1992). Anderson et al. (1991) have also found increased relaxation and decreased stress among dental patients exposed to music during their procedures. Corah, Gale, Pace, and Seyrek (198 I) provide contrary evidence that relaxed patients failed to display decreased stress when Iistening to music because of the possible operation of a floor effect for relaxation level. McCaffery (1990) found that both fast-tempo music (believed to increase physiological activity) and soft, relaxation music were equally effective in reducing stress. Allen and Blascovich (1994) found that fast-tempo music may only relieve stress when it is the individual's preferred musical taste. According to Stratton and Zalanowski (1984), ratings of relaxation are positively related to ratings of liking for musical selections. The option of permitting participants to choose the music they listen to may provide a heightened sense of perceived control in the presence of an uncontrollable stress agent, thereby strengthening the positive influence of music on stress (Anderson et aI., 1991). 1712 INFLUENCE OF MUSIC ON DRIVER STRESS WIESENTHAL ET AL. Predictions Despite a lack of agreement as to the exact mechanisms responsible for the influence of music on stress, it has been establishedthat music can alleviate stress. However, most research has been concentrated within a medical environment, where patients experience stressful medical conditions or stressful treatments. Comparatively less emphasis has been placed on the stress-reducingproperties of music within common everyday situations,such as automobile driving. Similarly, there has been little comparison of the influence of music between situations of varying degrees of stressfulness, such as low- and high-congestion conditions. According to Hennessy (1995), listening to music is one behavior that is often used by drivers to deal with demanding traffic conditions. It is predicted that greater stress will be reported in high than in low traffic congestion, and that participants who listen to music while driving will report decreased stress, particularly in high congestion, compared to those who do not listen to music. Method Participants The voluntary participants were 40 York University students and members of the North York business community. All of the participants traveled to or from school or work along Highway 401 in metropolitan Toronto, Ontario, Canada. Half of the participants were males and half were females; their ages ranged from 21 to 50 years of age, with an average age of 26.2 years. Apparatus Nokia cellular telephones (model number LX 12/C IS) were equipped with a cigarette-lighter power adapter for continuous in-automobile power access and a stationary antenna. A visor-mounted microphone provided hands-free capability. Dialing was automatically performed at the push of one button. Measures of Driver Stress The State Driver Stress Inventory (Hennessy & Wiesenthal, 1997) wasdeveloped to assess the situation-specific experience of driver stress, using a variation of the Driving Behavior Inventory-General Driver Stress questionnaire (Gulian, Matthews, et aI., 1989) and the Stress Arousal Checklist (Mackay, Cox, Burro\:Vs, & Lazzerini, 1978). The Driving Behavior Inventory-General (DBI-Gen) scale has been developed as a valid assessment of a general disposition, or trait susceptibility, to driver stress (Matthews et aI., 1991). The DBI-Gen consists of 16 1713 items such as, "When I get irritated I drive aggressively," "Trying but failing to overtake frustrates me," or "I get annoyed by driving behind other vehicles." The DBI-Gen has been found to be a robust and reliable self-report measure of driver stress (Glendon et aI., 1993). For the purpose of the present study,three items that did not pertain to highway driving were eliminated ("Annoyed when traffic lights change to red when 1 approach them," "I am more tense on new than familiar roads," and "I feel bothered when overtaking at a junction"). Two additional items were eliminated because pilot-study participants had difficulty understanding the key concepts ("Driving gives me a sense of power," and "I do not feel indifferent when overtaking other vehicles"). All items were also reworded to represent state rather than trait measures of stress; for example, "TryiIlg but failing to overtake is frustrating me," rather than "Trying but failing to overtake frustrates me." The scoring system was also changed from a 7- point scale to a IOO-pointscale to facilitate its administration to the driver in the automobile while in traffic. Previous research has found the DBI-Gen to maintain its stresspredictive properties under such revisions (Hennessy & Wiesenthal, 1997). In addition 10 items from the Stress Arousal Checklist (Mackay et aI., 1978) were included with the II DBI-Gen items. Half of the Stress Arousal Checklist items were positive mood items (relaxed, contented, peaceful, comfortable, and calm) and the other half were negative mood items (tense, bothered, nervous, uneasy, and distressed). Stress arousal items were also reworded to represent a state measure of stress; for example, "I am feeling tense," rather than simply "Tense." Responses were placed on a Likert-type scale ranging from a (strongly disagree) to 100 (strongly agree), indicating the extent to which participants agreed that each item pertained to their experience in the present driving situation. A manipulation check was added to determine if low- and high-traffic congestion conditions were, in fact, perceived as distinct ("Traffic conditions are congested"). Finally, 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") since it has been found to covary with driver stress (Hennessy, 1995).Previous research has found the State Driver Stress Inventory to demonstrate high reliability in both low-congestion (a = .92 to .97) and high-congestion (a = .90 to .95) conditions (Hennessy, 1998; Hennessy & Wiesenthal, 1997, 1999). Procedure The present study was designed to measure driver stress in actual low- and high-congested conditions, through the use of cellular telephones. Research participants were enlisted through course recruitment and personal contact. During an initial appointment, informed consent was obtained, and instructions regarding the experimental procedure and cellular-telephone operation were given. 1714 WIESENTHAL ET AL. Participants then provided information regarding their regular travel route along Highway 40], since all measures were administered during their usual daily commute. Highway 40] was chosen because it is the major traffic artery for metropolitan Toronto, with as many as 14 lanes divided into a series of express (core) and collector lanes. The average annual daily traffic on this highway for the metropolitan Toronto area is over 255,000 vehicles (Ontario Ministry of Transportation, 1992). 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. Two landmarks were then chosen; one that is unique to the selected low-congestion area, and one that is unique to the selected highcongestion area. The landmarks were to be subsequently used during their actual journey as a cue to initiate a cellular-telephone call to the experimenter. Both the low- and high-congestion telephone interviews were scheduled during a single journey. Two groups of drivers were formed: those who typically encounter high traffic volumes prior to low traffic volumes, and those who typically encounter low traffic volumes prior to high traffic volumes. This process allowed for the assessment of cumulative state driver stress through the comparison of the highcongestion-first group and the low-congestion-first group, and helped rule out state driver stress simply as a function of fatigue. Subsequently, each group was randomly divided into either a music or a nonmusic group, with a stipulation of equal gender representation in each group. The music group was instructed to select a cassette tape or compact disc of their favorite music to play during the entire trip. The nonmusic group was instructed specifically not to listen to music (or talk radio) during the entire journey. All participants were alone in their automobiles during the entire duration of the journey. Prior to initiating the 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 pretest telephone call. Participants were reminded of the response scale and were instructed to commence their journey as usual. Upon approaching their first designated landmark, participants telephoned the researcher, utilizing a single-button speed-dialing feature. Once a successful telephone contact was made, the State Driver Stress Inventory was administered verbally while the driver was engaged in the actual driving process. Upon completion of the first telephone interview,the cellular-telephone call was terminated and the participants continued driving until their second landmark was reached, which prompted the second telephone call. The State Driver Stress Inventory was again administered verbally. All measures were obtained between October and February in Toronto, Ontario, Canada. Participants were tested only on Tuesdays, Wednesdays, and Thursdays, since most participants were not available on weekends, and Mon- INFLUENCE OF MUSIC ON DRIVER STRESS 1715 50 48 46 !a 44 E 42 tf.I40 ~ 38 36 34 32 of Low ~ Hlllh Congestion Level Figure I. Mean state stress levels in low-congestion and high-congestion conditions between music and nonmusic groups. days and Fridays have been found to provide elevated driver stress levels (Gulian, Debney, et aI., 1989). In order to eliminate the possibility of poor weather increasing stress, participants were tested only on partly cloudy to sunny days. Results The automobile trips studied indicated that the two telephone calls were placed, on average, about] 6 min apart. Drivers were in their vehicles for at least one half hour per trip. Scoring on the State Driver Stress Inventory consisted of calculating the mean of the responses given on the 2] stress items (the five positive-mood items were reverse-keyed)in both highcongestionand lowcongestion.Higher scores are indicative of greater state driver stress. Cronbach's alphas for the state stress scores in low and high congestion were .90 and .93, respectively. A multivariate split-plot factorial analysis was performed with state stress levels and time urgency scores as dependent factors. The low-congestion and high-congestion conditions represented the within-participantscondition, and the music and nonmusic, as well as the female and male groups, represented the levels of the between-groups conditions. For state driver stress, no difference was found between females and males (M= 38.80, SD = ]7.56, and M= 39.08, SD = ]3.66, respectively), F(l, 36) = 0.87, P > .05. A significant interaction was obtained between congestion level and music groups, F(l, 36) = 4.37,p < .05. Because of the importance of the twoway interaction, main effects for congestion and music groups will not be presented. As predicted, greater state stress was reported in high congestion, although participants in the nonmusic group displayed elevated stress levels in the high-congestion condition (Figure] ). 1716 WIESENTHAL ET AL. INFLUENCE OF MUSIC ON DRIVER STRESS Time urgency scoresdid not differentiate between low- and high-congestion conditions (M= 48.78, SD = 23.96, and M= 49.54, SD = 23.75, respectively), F( 1,36) = 2.20, p > .05. Similarly, the music group reported equivalent levels of time urgency as did the nonmusic group (M = 53.20, SD = 24.16, and M = 52.85, SD = 23.28, respectively), F(I, 36) = 0.32, p > .05. Finally, female and male ratings of time urgency were similar (M = 52.33, SD = 25.19, and M = 46.38, SD = 22.21, respectively), F(I, 36) = 0.82,p > .05. One possible confound exists in the present study involving 1717 the choice of lis- tening to music that had previously been chosen by the driver. It may be that choice in and of itself is more important in producing the stress reduction than the actual playing of recorded music. It may also be that the distraction provided by the music engenders the stress reduction. These reasonable hypotheses need to be tested in future research contrasting some drivers listening to talking books (recorded literature), while other drivers listen to popular music. These are easily collectible data that could make the highways a safer environment. Discussion References Consistent with previous research (Hennessy & Wiesenthal, 1997, 1999), driver stress was greater in high congestion than in low congestion, demonstrating the importance of the driving situation as one important element in determining driver stress levels. Because of increased traffic volume and slower travel pace, high-congestion conditions represent greater potential for undesirable or demanding encounters, capable of taxing a driver's coping resources. The present findings further strengthen the power of the DBI-Gen as a valid and reliable predictor of driver stress, which has been shown to be capable of predicting both a trait susceptibility and state levels of driver stress (Gulian, Debney, et aI., 1989; Gulian, Matthews, et aI., 1989; Hennessy & Wiesenthal, 1997, 1999). The present findings also highlight the importance of music as a mechanism for coping with driver stress. Within high congestion, participants who did not listen to music displayed significantly greater stress than did those who listened to music. Previous research has shown music to alleviate stress experienced in highly arousing medical situations, such as dental surgery and cancer treatment (Aldridge, 1993; Anderson et aI., 1991), and in mildly stressful common situations where strangers awaiting an experiment felt more relaxed when they could listen to music as opposed to waiting in silence (Stratton, 1992). Music has been found to distract (Wostratzky et aI., 1988) and to relax (Kroener et aI., 1988) people during stressful encounters. During periods of high congestion, under conditions of increased attentional demand, listening to music may act to relax and distract drivers from highly undesirable circumstances. However, the positive influence of music may be limited. 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