F. I. T. Cutting Edge text

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. Speculating on the mechanism by which these benefits accrued, the 
researchers suggested that music allowed participants to relax, reducing muscle tension, and 
thereby increasing blood flow and lactate clearance, while decreasing lactate production in 
working muscle. The reduction in RPE for music vs. no music was ~10%, a figure replicated 
in a subsequent study by Nethery (2002), who found that perceived exertion was lower in an 
asynchronous music condition when compared to a video condition and two control 
conditions comprising no music and sensory deprivation.
Crust and Clough (2006) examined the ergogenic properties of asynchronous 
motivational music, compared to drumbeat only and no music, during an isometric muscular 
endurance task. The drumbeat used was the same as that in the motivational track, but 
without the other constituents of music (melody, harmony, lyrics). Participants endured for 
longer in response to motivational music when compared to the other two conditions. This 
highlighted the collective importance of the various constituents of music in determining 
participants‟ responses; a point that has been emphasized strongly in a recent review (North 
& Hargreaves, 2008).

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The Role of Music 14 
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Research has shown that the beneficial effects of asynchronous music are reduced once 
exercise intensity exceeds the anaerobic threshold. For example, using the Wingate test (a 
maximal cycle ergometer effort over 30 s), Pujol and Langenfeld (1999) found that music had 
no positive influence on performance; a finding that supports the load-dependent hypothesis. 
In a subsequent study using a treadmill and outdoor running task at 90% VO
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, Tenenbaum et al. (2004) showed that while motivational 
asynchronous music did shape interpretations of fatigue symptoms, it did not reduce 
perceptions of effort. 
Tempo is generally considered to be a key determinant of the aesthetic response to a piece 
of music and is an important musical constituent to consider when prescribing music for 
exercise (Crust, 2008; Edworthy & Waring, 2006; Karageorghis & Terry, 1997). 
Accordingly, a recent series of studies led by the second author has investigated the 
relationship between exercise heart rate and preference for music tempo. Previous 
investigations by Iwanaga (1995a, 1995b) had suggested a positive and linear relationship 
between heart rate and music-tempo preference. However, methodological limitations 
inherent in these studies, such as lack of a heart rate manipulation and self-regulation of 
music tempo, detracted from the ecological validity of the findings. Karageorghis and his 
collaborators sought to re-examine Iwanaga‟s findings having strengthened the methods used.
In the first study, participants reported their preference for slow (80 bpm), medium (120 
bpm) and fast (140 bpm) tempo music selections while walking on a treadmill at 40%, 60%, 
and 75% of maximal heart rate reserve (maxHRR). Participants expressed a strong preference 
for fast and medium tempo music over slow music regardless of work intensity. Also, an 
interaction effect was found, whereby participants reported a preference for either fast or 
medium tempo music during low and moderate exercise intensities, but preferred fast tempo 
music during high intensity exercise (Karageorghis, Jones, & Low, 2006). 

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The Role of Music 15 
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Karageorghis, Jones, and Stuart (2008) extended this approach to study the psychological 
impact of entire music programs, rather than just excerpts of music. They administered 
medium tempi, fast tempi, mixed tempi (tracks arranged in the order medium-fast-fast-
medium-fast-fast) conditions and a no-music control condition, while participants worked at 
70% maxHRR on a treadmill. Dependent measures were music preference, intrinsic 
motivation, and global flow. The researchers expected the mixed-tempi condition to yield the 
most positive psychological effects because it was well aligned with the selected work 
intensity, and there was also less likelihood of participants experiencing boredom or 
irritation. However, findings showed that it was actually the medium-tempi condition that 
elicited the most positive psychological outcomes.
Based on the findings of their first two studies, Karageorghis and colleagues suggested 
that there may be a step change in preference between 70% and 75% maxHRR, reflected by a 
stronger preference for fast tempi music at the higher heart rate. The step change in 
preference parallels the anaerobic threshold, which is characterized by a greater reliance on 
anaerobic pathways for energy production. Moreover, at these moderate-to-high intensities 
participants become more acutely aware of fatigue-related cues (cf. Rejeski, 1985). 
These findings led us to question the positive linear relationship between heart rate and 
preferred music tempo that Iwanaga had proposed (Karageorghis & Terry, 2009). We 
hypothesized that the relationship between these variables is quartic in nature, with three 
inflection points (see Figure 17.4). During the early stages of an exercise bout, when RPE is 
low, the relationship is linear, whereas at moderate-to-high exercise intensities, music of fast 
and medium tempi is preferred equally. Beyond 70% maxHRR, fast tempi are preferred and 
the linearity of the relationship resumes. Once exercise intensity exceeds 80% maxHRR, 
there is a “ceiling effect” for tempo preference. The reason for this is that relatively few 
tracks are recorded at very high tempi and so our band of most familiar tempi is 80-140 bpm. 

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The Role of Music 16 
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Also, given the automatic attentional switching that occurs at high exercise intensities, it is 
unlikely that music of any tempo can be attended to selectively (Hernandez-Peon, 1961; 
Rejeski, 1985). In other words, silence 
is
possibly “golden” during very high intensity 
exercise. This notion does, however, require further empirical investigation. 
We recently tested the hypothesized quartic relationship between exercise heart rate and 
music tempo preference (Karageorghis, Jones, Priest et al., in press) using six exercise 
intensities (40-90% maxHRR) and four music tempi (slow, medium, fast, very fast). Results 
generally supported a quartic relationship between heart rate and preferred music tempo, 
although in the early stages of exercise, the preference was for music of a higher tempo than 
we had predicted. Moreover, between 70% and 80% of maxHRR, rather than a “ceiling 
effect”, we observed a dip in music tempo preference. This has been termed the “Clarke dip” 
after a precocious undergraduate, Adam Clarke, who predicted it during the early stages of 
the research project, despite the second author‟s forecast to the contrary. 
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