The effect of motivational music on sub-maximal exercise

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indicate that both motivational and oudeterous music can significantly ... music conditions elicited increased in-task affect and generated equally positive ...
European Journal of Sport Science, June 2005; 5(2): 97 /106

ORIGINAL ARTICLE

The effect of motivational music on sub-maximal exercise

DAVE ELLIOTT1, SAM CARR2, & DUNCAN ORME1 1

St Martin’s College, Lancaster, UK, and 2School of Health, University College Northampton, UK

Abstract This study examined the effect of motivational music on a 20-min sub-maximal cycle task. Eighteen untrained student volunteers (10 males, 8 females) were required to partake in three experimental conditions: no music, oudeterous (nonmotivational) music, and motivational music. Participants’ in-task affective states and rate of perceived exertion were assessed on rating scales during the trials and the distance traveled for each trial was recorded. In addition, participants’ attitudes towards the exercise experience were assessed on rating scales administered post-trial. The results of the study indicate that both motivational and oudeterous music can significantly increase distance traveled when compared to the control condition. However, no significant differences were observed between the two music conditions and the increased exercise intensity associated with musical accompaniments was not associated with an increased perception of effort. Both music conditions elicited increased in-task affect and generated equally positive post-task attitudes towards the exercise experience. No significant Gender /Trial interactions were identified for any of the dependent measures.

Keywords: Motivational music, intensity, RPE, affect

Key points 1. Both music types (motivational and oudeterous) elicited similar responses in terms of exercise intensity. 2. Both music types (motivational and oudeterous) elicited similar responses in terms of perceptions of effort and affective responses. 3. Results do not provide support for the superiority of motivational music over oudeterous music. 4. This study adds to extant research that promotes the use of music within the sport and exercise environment.

Introduction Although there appears to be a belief that music can have a positive influence upon exercise participants (Gfeller, 1988; Karageorghis, Terry, & Lane, 1999; Kodzhaspirov, Zaitsev, & Kosarev, 1986), this conviction is not fully supported by research evidence. For example, whilst a pool of research has indicated that music can enhance physical performance

(Copeland & Franks, 1991; Karageorghis, Drew, & Terry, 1996; Szabo, Small, & Leigh, 1999), this finding has not been consistent (Dorney, Goh, & Lee, 1992; Pujol & Langenfeld, 1999; Schwartz, Fernhall, & Plowman, 1990). Similarly, investigations into the effects of music on rate of perceived exertion (RPE) have also been inconclusive. Although a number of studies have reported that music can induce significant reductions in RPE when exercising at moderate workloads (Boutcher & Trenske, 1990; Pujol & Langenfeld, 1999; Szmedra & Bacharach, 1998), others have indicated that music has little impact on RPE (Schwartz, Fernhall, & Plowman, 1990; Wales, 1986). The ability of music to improve affective responses has proved to be more encouraging. Evidence suggests that particular musical idioms can enhance mood during exercise (Boutcher & Trenske, 1990; Hayakawa, Miki, Takada, & Tanaka, 2000; Kodzhaspirov et al., 1986; Lee, 1989). From the examples given, it would appear that empirical support for the application of music within the exercise environment is somewhat tenuous; definitive conclusions cannot be drawn regarding the effect of music on physical performance and

Correspondence: Sam Carr, School of Health, University College Northampton, UK. E-mail: [email protected] ISSN 1746-1391 print/ISSN 1536-7290 online # 2005 European College of Sport Science DOI: 10.1080/17461390500171310

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RPE. Addressing this issue, Karageorghis and Terry (1997) and Karageorghis et al. (1999) have claimed that many of the investigations undertaken within this context have suffered from methodological weaknesses. Furthermore, it is also maintained that researchers have generally afforded insufficient consideration to the selection of the musical composition employed within experimental inquiry (Karageorghis & Terry, 1997). In response, Karageorghis et al. (1999) have advanced the conceptual framework for the prediction of responses to motivational asynchronous music in exercise and sport. This framework identifies four fundamental factors that require attention when selecting musical accompaniment to physical activity: rhythm response, musicality, cultural impact, and association. In theory, attending to these factors should result in music that can be categorized as being motivational. In a further development, The Brunel Music Rating Inventory (BMRI), a 13-item scale specifically designed to measure the motivational qualities of music for use within the exercise environment, has been advanced (Karageorghis et al., 1999). The authors suggest that employing the BMRI to select music for appropriately designed experimental investigation will provide more positive and consistent results, whilst also increasing the generalizability of research findings. A number of studies have applied the BMRI to select music for experimental conditions, and results have generally proved to be encouraging. Motivational music appears to improve affective states and reduce perceptions of effort during sub-maximal exercise (Karageorghis & Jones, 2000) and to induce pre-task and in-task flow states (Karageorghis & Deeth, 2002). Furthermore, although the conceptual framework for the prediction of responses to motivational asynchronous music in exercise and sport does not currently predict physical responses to motivational music, preliminary research suggests that motivational music may enhance physical performance. For example, motivational music has been found to increase the time to voluntary exhaustion whilst performing an aerobic cycle task (Karageorghis & Jones, 2000) and to improve isometric muscular endurance (Karageorghis & Lee, 2001). However, Elliott, Carr, and Savage (2004) demonstrated that although motivational music increased sub-maximal exercise intensity compared to a control condition, when compared to an oudeterous music condition no significant differences were found. At present, the number of studies utilizing the BMRI to assess the effects of music upon physical activity is limited and further investigation is warranted. Framed within the context of developing cardio-respiratory fitness in healthy adults, this study examined whether motivational music can provide

benefits to exercise participants. Specifically, through the application of the BMRI, the investigation aimed to discern if motivational music provokes increases in sub-maximal exercise intensity (measured via distance traveled). This study also examined participants’ perception of the exercise experience. Godin (1994) has indicated that affective dimensions play a major role in the intention to adopt exercise behavior, with both what (perceived exertion) and how (affect) individuals feel being important constituents of the affective experience (Hardy & Rejeski, 1989). In essence, if the exercise experience is perceived positively, there should be an increase in the likelihood of the behavior being repeated. If motivational music can provoke increases in exercise intensity it would be prudent to examine whether this has any impact upon affective responses. Hence, post-task attitudes towards the exercise experience were also measured. In summary, the study examined the effect of motivational music upon (a) sub-maximal exercise intensity, (b) affective responses as measured by intask affect and RPE, and (c) post task attitudes. Given that the findings (e.g., see Elliott et al., 2004) regarding the beneficial effects of motivational music have not always been supportive, no specific hypotheses were advanced and the investigation was exploratory in nature.

Method Music rating procedure The first part of the experiment involved participants rating the motivational quality of 20 selected songs. Music selection It has been suggested that musical tempo can influence how a piece of music is appraised (LeBlanc et al., 1988). Furthermore, musical tempo may directly influence how individuals physically respond to music (Brown, 1980). As such, failure to standardize tempo may threaten the internal validity of both the music rating and experimental procedures. Therefore, all musical selections possessed relatively similar tempi. There has been some disagreement regarding the selection of an appropriate musical tempo; in this study tempo was determined in accordance with the proposals of both Iwanaga (1995) and LeBlanc et al. (1988). According to Iwanaga (1995), individuals prefer tempi that are congruent with heart rate (HR), whereas LeBlanc et al. (1988) claim that irrespective of HR, individuals prefer music of a fast disposition. Addressing the recommendations of Iwanaga (1995), in this study it

The effect of motivational music on sub-maximal exercise was possible that HR would vary both during and between experimental conditions; therefore, an approximation was calculated based upon the mean age predicted HR of experimental participants and the median exercise intensity (70%HR max). Based upon this calculation, all tracks possessed a tempo of approximately 140 beats per minute (bpm). In relation to the view of LeBlanc et al. (1988), this particular tempo has been classified as possessing a high preference rating. Although tempi were reasonably similar, the accentuation of the tempo differed between selections. It was therefore assumed that this would influence the motivational qualities of this element of the music. The inclusion of contrasting musical idioms within music research has received criticism (Karageorghis & Terry, 1997), as this may also influence experimental outcomes. In this study, all tracks were of a similar style, being classified as popular electronic dance music (www.wordiq.com). Furthermore, because the referential meaning of lyrics can impact upon responses to music, the majority of tracks included a vocal component (Gfeller, 1988). By utilizing musical selections of a particular idiom, it was possible to select participants who deemed the music to be culturally appropriate and display a liking for this style of music. To ensure a degree of familiarity with the music, all compositions had recently appeared in the British music charts and had been released on compilation compact discs that purported to contain current ‘‘dance hits.’’ Participants Participants involved in the music rating procedure were 35 undergraduates undertaking sport-related degrees in the UK: 18 males (M /20.4 years, SD / 2.6) and 17 females (M /20.1 years, SD /1.9). All participants were born and raised in the UK. They also had experience of performing exercise to music and expressed a liking of popular electronic dance music. Measures To assess differences between the motivational qualities of each track, the BMRI was employed. This 13-item measure is designed to assess overall motivational quality of musical selections by evaluating the sub-scales of rhythmic response (4 items), musicality (2 items), cultural impact (4 items), and extra-musical association (3 items) for a given track. Each of the 13 items was rated on a 10-point Likerttype scale, ranging from 1 (not at all motivating ) to 10 (extremely motivating ). Examples of items to be rated for each sub-scale are tempo (to assess rhythmic response), melody (to assess musicality), the artist (to assess cultural impact), and lyrics associated with

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sport (to assess association). A motivational quotient for each musical selection is calculated by following procedures suggested by Karageorghis et al. (1999). Specifically, participants each obtain a raw score for how motivating they find each sub-scale for each musical selection. This raw score for each sub-scale is then multiplied by a weighting coefficient identified by Karageorghis et al. (1999). This is so that the hierarchical importance of each sub-scale is reflected in the final motivational quotient. The four weighted sub-scales are then summed in order to identify a total motivational quotient for each musical selection. Motivational quotients can range from a low of 3.33 to a high of 33.33. It has been demonstrated that the BMRI possesses adequate reliability, validity, and factor structure (Karageorghis et al., 1999). Procedures To reduce the amount of time required to rate the musical selections, a 45 s portion of each composition was recorded onto a SKY, C90 ferric audiocassette: however, it was ensured that each sample contained the major constituents of each composition. For the rating procedure, 20 copies of the BMRI were administered to each participant. In accordance with the recommendations of Karageorghis et al. (1999), participants were informed that each musical selection should be rated with the specific task of sub-maximal cycling in mind. A brief explanation of the rating scale was provided, including further instructions regarding the meaning of each of the 13 items. The first musical selection was played to the participants through a Panasonic RXES25 portable stereo system. The tape was then stopped to allow each individual to complete the rating procedure for that composition. The subsequent musical selections were then played and rated in an identical manner. Scoring the motivational qualities of the musical selections Upon completion of the rating procedure, the motivational quotient for each musical selection was calculated using the recommended procedure (Karageorghis et al., 1999). The motivational quotients for the 20 musical selections in this study ranged from a low of 9.0 (SD /3.3) to a high of 27.6 (SD /5.9); the median motivational quotient of the 20 tracks was 18.49. The highest five quotients were deemed to reflect the most motivational music; for these five tracks quotients ranged from 23.9 (SD / 5.2) to 27.6 (SD /5.9). The mean motivational quotient for these tracks was calculated as 25.5

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(SD /1.63). The mean value of the motivational tracks was situated on the boundary of the upper quartile quotient range. The lowest five quotients were deemed to reflect oudeterous music; these five tracks possessed quotients ranging from 9.0 (SD / 3.3) to 11.5 (SD / 5.2). The mean motivational quotient for these tracks was 10.3 (SD /2.12). The mean value of the oudeterous tracks was situated in the lower quartile quotient range. To determine if gender differences were evident within the rating procedure, comparisons were made. The mean quotient for the five motivational tracks , as rated by males, was 25.39 (SD /2.2) and for females 27.4 (SD /1.7) The mean quotient for oudeterous tracks , as rated by males, was 11.44 (SD /2.1) and for females 9.7 (SD /2.2). No significant (p B/ 0.05) differences were evident between scores of males and females. Furthermore, the rank orders of motivational quotients in motivational and oudeterous groups of tracks were identical for males and females. Hence, the five musical selections with the highest motivational quotients (motivational music) were recorded in full onto an audiotape. Similarly, the five selections with the lowest motivational quotients (oudeterous music) were recorded onto an identical audiotape.

Experimental details Participants Participants in the experiment were 18 undergraduates undertaking sport-related degrees in the North of the UK: 8 males (M /21.2 years SD /0.9) and 10 females (M /20.7 years, SD /1.1). All participants were raised in the UK and had expressed a liking of popular electronic dance music. Although not sedentary, all participants had previous experience of performing sub-maximal exercise on cycle ergometers; however, none of those involved adhered to the ACSM (1998) guidelines relating to developing or maintaining cardio-respiratory fitness. Participants involved in the music rating procedure were not permitted to take part in the experimental conditions as it has been suggested that this may compromise the internal validity of experimental investigation (Karageorghis et al., 1999). Measures Rate of Perceived Exertion (RPE). Borg’s (1982) 15point RPE scale was utilized to monitor perceived exertion. The RPE consists of perceived workloads ranging on a semantic continuum from very, very light to very, very hard . The RPE has been demonstrated as a valid and reliable measure of perceived exertion

(Skinner, Hustler, Bergsteinova, & Buskirk, 1973). Five RPE measurements were taken during each trial (at 4, 8, 12, 16, and 19 min). Duplicating the RPE scoring procedure of Boutcher and Trenske (1990), upon completion of each trial a mean RPE score was obtained by simply summing the values selected and dividing by the number of readings taken. Affect. The Feeling Scale developed by Rejeski (1985) was applied to monitor in-task affect. The 11-point scale ranges from /5 (feeling very good ) to /5 (feeling very bad) with semantic anchors at 2point intervals. Five measurements were taken during each trial (at 4, 8, 12, 16, and 19 min). Upon completion of each trial, an average affect score was obtained by simply summing the values selected and dividing by the number of readings taken. The scale has been found to be a valid and internally reliable measure of affective states during exercise performance (Hardy & Rejeski, 1989). Exercise Intensity. Given that the study focused upon cardio-respiratory fitness, with regards to intensity parameters, duration, and modality, the investigation adhered to the recommendations of the American College of Sports Medicine (1998). That is, participants were required to perform three 20 min cycle ergometer trials, during which it was possible to vary work intensity within the parameters of 60 / 80% HRmax. To determine exercise intensity the distance cycled by participants in each 20 min trial was recorded in kilometers. This information was obtained via the built-in cycle computer of the Monark 818E Ergomedic Ergometer. Attitudes towards the exercise experience. To gauge participants’ attitudes towards each trial and whether they would consider repeating the behavior, a series of statements were presented. Participants were required to rate each statement on a 7-point scale ranging from 1 (not at all true ) to 7 (very true ) and a total score was calculated by summing the four responses. The measure consisted of three positive statements (‘‘I enjoyed that exercise session’’; ‘‘That exercise session made me feel good’’; ‘‘I would consider repeating that exercise session’’) and one reversed statement (‘‘That was a boring exercise session’’). Cronbach’s alpha coefficient was applied to assess internal consistency of these items. The alpha value was 0.72. Thus, the scale was considered to be internally reliable (Pallant, 2001). Equipment Participants performed all trials on a Monark 818E Ergomedic cycle ergometer. Music was played through a Sony WMEX521 cassette Walkman and

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participants were required to wear Panasonic RPHV297, in-ear headphones during each trial.

resistance. During the procedure participants were given practice in the use of the relevant rating scales.

Pre-test procedure

Experimental trials

Prior to experimental conditions, participants were required to attend a pre-test session. This introduction was primarily designed to ascertain individuals’ relative workloads, to impart information regarding the relevant scales, and to provide task familiarization. To determine relative resistance, a procedure was devised that would ensure that participants worked within aerobic parameters. Firstly, HRmax was calculated for each participant using the age-estimated equation (220-age). The authors acknowledge that predictive equations such as age-estimated HRmax lack precision and such predictions are acknowledged to provide an estimate of HRmax that is accurate to approximately9/10 beats per minute (McArdle, Katch, & Katch, 1996). However, it was felt that the accuracy of this procedure was sufficient for the purposes of this study. From the obtained HRmax value, the following thresholds were determined: 60% HRmax and 80% HRmax. It is worth stating that the latter parameter differs slightly to the recommendations presented by the ACSM (1998). This is because it has been suggested that working at high intensities may reduce the impact of external stimuli (Rejeski, 1985). Evidence presented by Wilmore and Costill (1994) indicates that intensities greater than 80% HR max should be considered as being high; as such, this figure was selected as the upper intensity parameter for this study. With the relevant data compiled, participants were instructed to begin pedaling at a cadence of 50 rpm, with a minimum resistance of 1kg, all agreed that this was a comfortable work rate. This period lasted for 3 min and HR was recorded at the end of each minute. If, at the end of minute three, HR was below the 60% HR max value, extra resistance was added and participants were required to work at 50 rpm for a further 3 min. This process continued until the target HR was obtained. The resistance load that enabled participants to obtain approximately 60% HR max at a cadence of 50 rpm was recorded. With this resistance maintained, participants were then required to increase their work-rate to 70 rpm, for a further 2 min; this was to act as a further warm-up. Once completed, participants were asked to work at maximum velocity for a period of 3 min (resistance maintained) at this intensity. Although participants were working close to 80% HR max, none were able to exceed this threshold value. Upon completion of the above procedure, a 2 min rest period was permitted, after which participants were required to complete a 10 min familiarization task. This was performed at the previously determined

Participants were required to perform in three submaximal exercise trials: no music (where participants listened to the noise created by playing a blank tape), oudeterous music, and motivational music. To control for order effects, trial order was counterbalanced. Specifically, each participant was allocated to one of six possible counterbalancing orders. In conference with participants, attendance times were allocated; this time was maintained throughout trials. Participants were also asked to refrain from eating or drinking caffeine-based products three hours prior to testing. For the music conditions volume was standardized to level of 70% of maximum. This level was loud enough to prevent external noise from being perceived, but was not considered to be uncomfortably loud. All participants agreed that the volume selected was at a comfortable listening level. For the no music condition, in which a blank tape was played, volume was set at 100%. To reduce personal goal setting, data concerning distance traveled during each trial was withheld from participants. All exercise trials followed an identical measurement procedure. After applying the Polar HR monitor and adjusting the cycle seat height to the pre-determined height, participants were required to perform a 3 min warm-up. The warm-up was performed at a cadence of 50 rpm, with resistance of either 0.5 kg or 1kg. Following this, each participant’s relative resistance was then applied to the cycle ergometer. Dependent upon the condition, the appropriate audiotape (no music/oudeterous music/ motivational music) was inserted into the cassette player and the headphones were applied. Participants were then instructed to pedal for 20 min at a self-selected cadence, the cassette player was activated, and the experimental trial began. During each trial measures of affective state and RPE were taken, with participants simply pointing to which number most closely reflected their current state. Although HR was not considered to be a dependent measure, it was nevertheless monitored throughout each trial to verify that participants were working below the prescribed 80% HRmax. Completion of the 20 min trial was followed by a 3 min cool-down, performed at a self-selected intensity. To assess post-task attitudes, participants were immediately provided with the series of post-task attitude statements and were instructed to rate these accordingly. A duplicate copy of these attitude statements was administered to participants after a

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period of 24 hr had elapsed and they were instructed to complete the items again to determine if their attitudes had changed. Statistical analysis Statistical differences between dependent variables (distance traveled, RPE, affect, and post-task attitudes) were assessed through a series of repeated measures analyses of variance (ANOVA). Specifically, this method allowed each variable to be assessed as an autonomous construct, examining firstly the main effect of the experimental trials on the dependent variables, and secondly any Trial x Time interactions that enabled assessment of how the dependent variables fluctuated over time in each experimental condition.

the condition main effect, post-hoc comparisons were conducted using the Sidak adjustment for multiple comparisons. Comparisons revealed that participants in the motivational music condition (M /9.94 km, SD /1.89), compared to the no music condition (M /8.93 km, SD /1.76), had traveled significantly farther (p B/.05, d /.55). In addition, participants also traveled significantly farther in the oudeterous music condition (M / 9.85, SD /1.67), compared to the no music condition (p B/.05, d /.53). No significant differences were identified between the motivational music and oudeterous music conditions.

ANOVA

In-task affect. Participants’ levels of in-task affect over 20 min were also analysed with condition (no music/oudeterous music/motivational music) as a within-participants factor. This time the sphericity assumption was not met, so the Huynh-Feldt correction was applied. The main effect for condition was again significant, F (2, 30) /6.65, p B/.02, h2 /.29. However, no significant Time /Condition interaction was identified. For the condition main effect, post-hoc comparisons, using the Sidak adjustment for multiple comparisons, revealed that participants in the motivational music condition (M /2.24, SD /1.46), compared to the no music condition (M /0.29, SD /1.96), reported significantly higher levels of in-task positive affect (p B/.04, d /1.12). In addition, when compared to the oudeterous music condition (M /1.62, SD /1.37), the motivational music condition elicited a higher level of positive affect that approached a significant difference (p /.07, d /.79). No significant difference was identified between oudeterous music and no music conditions.

Distance traveled . Total distance traveled over 20 min was analyzed with condition (no music/oudeterous music/motivational music) as a within-participants factor. The sphericity assumption was satisfied, so no statistical correction was applied. The main effect for conditions was significant, F (2, 30) / 5.60, p B/.01, h2 /.27. However, no significant Time /Condition interaction was identified. For

Mean RPE. Participants’ mean RPE level over 20 min was also analyzed. The sphericity assumption was satisfied, so no statistical correction was applied. The main effect for condition was statistically insignificant, F (2, 32) /1.13, p /.33, h2 /.07, suggesting that mean RPE did not differ as a function of the condition to which participants had been exposed.

Results Descriptive statistics Descriptive statistics across the three conditions (no music, oudeterous music, and motivational music) are displayed in Table I. These descriptive statistics show means and standard deviations for distance traveled, RPE, affect, and post-task attitudes. It is interesting to note that the mean distances covered over the three conditions can also be expressed in terms of energy expenditure. This indicates that during both music conditions, participants were working at approximately 122 W as opposed to 108 W in the no music condition.

Table I. Means and standard deviations for distance traveled, in-task affect, RPE, and post task attitudes in each experimental condition. Condition Motivational Music Oudeterous Music No Music

*A Scale/Attitude Scale. 1 /Immediately post task. 2 / 24 hours post task.

Distance

Affect

RPE

A. scale 1*

A. scale 2*

M/9.94km SD/1.89 M/9.85km SD/1.67 M/8.93km SD/1.76

M /2.24 SD /1.46 M /1.62 SD /1.37 M /0.29 SD /1.96

M /12.1 SD/1.4 M /11.8 SD/1.7 M /11.6 SD/1.6

M /22.00 SD/3.70 M /17.81 SD/6.33 M/8.86 SD/6.33

M/21.73 SD/4.10 M/17.93 SD/4.81 M/7.93 SD/7.96

Rate of Perceived Exertion

The effect of motivational music on sub-maximal exercise 14 12 10 8 6 4 2 0

motivational odeterous no music

4

8

12

16

20

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tions, compared to the no music condition (M / 7.93, SD /7.69), reported more positive attitudes 24 h post-exercise (motivational versus no music, p B/.01, d/2.34; oudeterous music versus no music p B/.01, d/1.60). No significant difference was identified between the motivational and oudeterous music conditions.

Time in Minutes

Figure 1. Interaction of time /condition on RPE.

Discussion

However, results did reveal a significant Time / Condition interaction on RPE, F (2, 30) /3.65, p B/ .05, h2 /.10. This interaction effect is displayed in Figure 1. Specifically, Figure 1 demonstrates that all conditions appear to exhibit similar levels of RPE up to minute eight. Following this, both music conditions appear to demonstrate increasing RPE values, whilst the no music condition exhibits a stable RPE level. By minute nineteen it can be seen that the increase in RPE levels in the two music conditions has elevated RPE to a level well above that of the no music condition. This suggests that fluctuation in RPE over time may be dependent upon experimental condition. That is, in the music conditions participants began to become consciously aware of their increased work output (i.e., they registered higher RPE scores) after around 8 /10 min of cycling. Prior to this, participants perceived all conditions to be similar in terms of effort exertion.

The results of this study indicate that when compared to a control condition, both motivational and oudeterous music elicited significant increases in distance traveled (exercise intensity) during a 20 min cycle trial. No significant differences were evident between the two music conditions. Two distinct mechanisms can be advanced to account for the similarity of distance traveled during the music conditions. Firstly, it has been theorized that people have a tendency to respond to the rhythmic qualities of music (Brown, 1980), of which tempo is an important constituent. Founded on this assumption, Karageorghis and Terry (1997) have suggested that during continuous sub-maximal activity, individuals may synchronize to musical tempo. It is possible that whilst the music used in this study was considered asynchronous (there were no specific instructions to match physical movement with musical tempo), a form of synchronization nevertheless occurred. Examination of the non-significant Time /Condition interaction for distance traveled offers some support for this hypothesis, as pedaling rates were reasonably constant throughout both music conditions. It is conceivable that the characteristics of the particular musical idiom utilized within this study (i.e., all samples possessed a prominent electronic bass beat) might be conducive to synchronization effects. That is, given that tempo was relatively consistent between the music conditions, if participants were simply synchronizing to the beat then similarities in distance traveled would be expected. It is also worth noting that although individual participants’ distances varied, this does not necessarily imply that synchronization did not occur as individuals may have adopted dissimilar forms of rhythmic patterning. Although the importance of the synchronization response has been recognized within the sport science literature (Anshel & Marisi, 1978; Hohler, 1989; Karageorghis & Terry, 1997), empirical evidence to support the hypotheses is limited. A second explanation for the similarity in distance traveled between music conditions arises from the belief that music has a dissociation effect (Boutcher & Trenske, 1990; Karageorghis & Terry, 1997; Potteiger, Schroeder, & Goff, 2000), where individuals focus upon external, rather than internal

Post-exercise attitudes. Participants’ immediate postexercise attitudes to each condition were also analyzed. The sphericity assumption was satisfied, so no statistical correction was applied. The main effect for condition was significant, F (2, 30) /19.54, p B/.01, h2 /.56. Post-hoc comparisons, using the Sidak adjustment for multiple comparisons, revealed that participants in the motivational music (M /22.00, SD /3.70) and oudeterous (M /17.81, SD /6.33) music conditions, compared to the no music condition (M/8.06, SD /7.40), reported more positive attitudes immediately post-exercise (motivational versus no music, p B/.01, d/1.25; oudeterous music versus no music p B/.01, d /1.43). No significant difference was identified between the motivational and oudeterous music conditions. Participants’ post-exercise attitudes were again assessed 24 h after completion of each trial. The sphericity assumption was not satisfied for this analysis, so the Huynh-Feldt correction was applied. The main effect for condition was significant, F (2, 28) /19.92, p B/.01, h2 /.58. Post-hoc comparisons, using the Sidak adjustment for multiple comparisons, revealed that participants in the motivational music (M /21.73, SD /4.10) and oudeterous (M /17.93, SD /4.81) music condi-

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stimuli (Morgan, 1978). The dissociation effect of music has been explained in relation to theories of limited attention capacity, such as Rejeski’s (1985) parallel processing model (Boutcher & Trenske, 1990; Szabo et al., 1999). According to Rejeski (1985), the amount of information that can be processed at a given time is limited and attending to one stimulus may prevent processing of other stimuli outside of the attention span. In this instance, attending to musical stimuli may block the transmission of the internal sensations associated with physical activity, for example, fatigue and effort sense (Karageorghis & Terry, 1997). Consequently, it is hypothesized that adopting an external focus can reduce perception of effort, improve affect (Boutcher & Trenske, 1990; Rejeski, 1985), and lead to improved physical performance (Okwumabua, Meyers, Schleser, & Cooke, 1983). In this study, measures of RPE and in-task affect provide some support for the above notion, as the presence of music did appear to influence these components. Regarding RPE, when compared to the control condition results indicate that despite increases in objective exercise intensity, there was no corresponding increase in mean perception of effort in either music condition. This implies that the presence of music did interfere with effort sense. However, although there was no effect on mean RPE, Time /Condition interaction was evident for RPE. Specifically, changes in RPE were observed from minute eight, whereupon RPE progressively increased as the music trials continued. The final measure of RPE, taken at minute nineteen, revealed that RPE was approximately two points higher (RPE 13) in both music conditions compared to the no music condition (RPE 11). This finding is somewhat intriguing because there was no corresponding increase in actual exercise intensity from minute eight. Music trials elicited constantly elevated workload over the no music condition throughout the 20-min period. Evidence has indicated that the distractibility of external stimuli such as music, is load dependent (Boutcher & Trenske, 1990). Specifically, when exercise approaches aerobic capacity, physiological cues become more salient, thus minimizing the impact of external stimuli (Boutcher & Trenske, 1990; Iwanaga, 1995). Although participants in this study were all working aerobically, during both music conditions HR measurements indicated that subjects’ workloads were approaching the 80% HRmax limit. It is possible that from minute eight, physiological factors, such as the accumulation of acidic byproducts or localized muscular fatigue began to compete with the external stimuli, thereby limiting the dissociative effects of music. It would appear that as the trials progressed participants’ attention be-

came increasingly directed towards physiological cues, explaining the progressive increase in effort sense. However, this increase in RPE did not appear to negatively impact the affective state of participants, with measures of in-task affect revealing that both music conditions provoked significantly more positive mood. Although motivational music elicited the greatest increase in affect, differences between the music conditions were not deemed to be statistically significant. Interestingly, despite the changes in RPE from minute eight, results identified no corresponding Time /Condition interaction for affective states, indicating that increased perception of effort was not registered as being unpleasant. This outcome should not necessarily be considered as an anomaly because Hardy and Rejeski (1989) have indicated that although RPE and affect are related they are not isomorphic constructs. Similar findings have been presented by Boutcher and Trenske (1990), who found that when working at moderate workloads (75% HRmax) music did not significantly reduce RPE; however, during the same experimental conditions affect was significantly elevated. It has been proposed that affective responses to music may not be a sole product of its dissociation qualities and that the act of music listening can in itself provoke emotional responses (Boutcher & Trenske, 1990). This view is shared by Waterman (1993) who states that an important function of music is to provide an emotional experience to listeners. It is feasible that in this instance both music conditions produced a positive emotional reaction, with the slightly more positive response being a function of the motivational music. It is also possible that despite progressive increases in RPE, the elevations were not of sufficient magnitude to negatively influence affect. More substantial increases in RPE may well be more detrimental to feeling states. The degree of support for the dissociation effects of music can be advanced as an alternative explanation for the increases in exercise intensity in this study because it has been suggested that the adoption of an external focus can encourage increased work-rate (Weinberg, Smith, & Gould, 1984). Although there is support for this hypothesis (Okwumabua et al., 1983; Pennebaker & Lightner, 1980), application to this study is somewhat problematic. As previously discussed, changes in RPE would imply that there was a weakening of the dissociation effect as the trials progressed, however this deterioration had no apparent effect on exercise intensity. Although requiring further investigation, the authors suggest that the increase in exercise intensity was a product of synchronization. It is possible that RPE was initially influenced by the dissociation

The effect of motivational music on sub-maximal exercise effect of music, yet from minute eight the power of this mechanism decreased, as internal cues became more salient. Regarding affective responses, it is feasible to suggest that these were influenced through an interaction of both dissociation and emotional capacity of music. The final part of this study examined how participants perceived each exercise trial. Results indicate that both music conditions evoked similarly positive attitudes towards the task, both immediately and 24 hr post-task. It should be acknowledged that the instrument utilized to assess attitudes, although demonstrating internal consistency and face validity, certainly requires further psychometric examination (Hewstone, Stroebe, & Stephenson, 1996). Nevertheless, in association with measures of in-task affect, these findings would indicate that participants perceived exercising to music to be a positive experience. More importantly, it appeared that these positive evaluations were maintained 24 h postexercise. Given the importance of affective responses for exercise adherence (Wankel, 1993), this may have important implications. Conclusion The results of this study provide support for the use of music as a means of elevating sub-maximal exercise intensity, manipulating effort sense, improving in-task affect and inducing positive attitudes towards the exercise experience. However, these findings do not entirely concur with predictions presented in the conceptual framework for the prediction of responses to motivational asynchronous music in exercise and sport (Karageorghis et al., 1999). The results of this study suggest that music need not necessarily be classified as motivational to provide benefits to the exercise participant. In this instance, affording sufficient consideration to factors such as tempo and cultural appropriateness provoked positive responses. In practice, the results of this study indicate that carefully selected music can lead to increases in distance traveled during a twenty-min cycle task. Hence, music may be beneficial to exercisers involved in cardio-respiratory fitness regimes. Furthermore, because the increase in distance traveled constituted a 13% increase in energy expenditure (108 W in the no music condition compared to 122 W in both music conditions) results may have implications for those involved in weight-loss and fitness programs. Despite an increase in exercise intensity, music also appeared to improve the affective experience. Given that elevated affect during exercise is associated with increased enjoyment (Abele & Brehm, 1993), a response that can positively impact upon the likelihood of repeating a

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specific behavior (Wankel, 1993), it is possible that appropriately selected music may also improve the likelihood of adherence to exercise.

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