1. Performance and Perceptual Effects of Music
Tempo and Experimental Paradigm
Jeremy Morris & Brian H. Jackson, Ph.D.
Department of Exercise Science | Pacific University | 2043 College Way | Forest Grove, OR 97116
Exercise Science Department, Dr. Brian Jackson, College of Arts & Sciences Undergraduate Research Funding, Family and Friends
Methods
Music Tempo & Heart Rate (HR)
Waterhouse and colleagues4 found that one’s heart rate was affected by the tempo of the music they
were listening to while performing a cycling task. An increase in music tempo (10%) resulted in an
increased HR, while a decreased tempo (10%) resulted in a lowering of HR. However, HR increased
significantly when music tempo was higher, whether it was the song’s actual tempo or the track’s tempo
was artificially increased. In a more recent study, the opposite was found where those that listened to
slow/soft music actually had a higher HR. The research found that soft/slow music lowers arousal
physiologically during submaximal exercise, thus increasing performance and HR1.
In the current society, health and fitness are at an all-time premium3.
Large amounts of money are being spent on shoes, supplements,
and other training aids that are proposed to improve performance.
However, one training tool that many swear by and cannot do without
is music. Can music affect one’s performance? A number of studies
have been performed to determine music’s influence on the body and
mind.
Music Tempo & Perception of Exertion
Music tempo has also been shown to affect the level of effort that one believes they are putting forth.
Yamashita and colleagues5 found that when performing a cycle ergometer task at a 40% max level
(low intensity), those listening to music were found to have a lower perception of effort (i.e., believed
the task to be easier) than those without music. However, this effect was not found when participants
performed at a higher intensity (60%).
Time Estimation
One hypothesis for why music may play a role in physical performance is that it may distract you from the
task. The cognitive-time model suggests that the more information processing that is required, the more
the internal cognitive timer is distracted2.According to Sucala, as the information load increases (as with
the addition of music), the timer becomes distracted, and we are less able to keep up with time2. This
distraction could be beneficial to someone performing a tedious exercise task.
Experimental Paradigm & Time Estimation
Time estimation is experimentally studied using two main paradigms, retrospective and prospective. In
the prospective paradigm, participants are informed in advance that they will be asked to make
judgments regarding the perceived duration of elapsed time. In the retrospective paradigm, participants
are asked their perceptions of elapsed time without advance notice6.
To determine whether music tempo and/or experimental paradigm
(prospective or retrospective) affect HR, perception of fatigue, and
perception of time (time estimation) in a physical task.
Participants: 24 healthy volunteers (12 male, 12 female), ranging 18-51 years of age
The following steps were followed for each trial (repeated 3 times):
1. Check HR (trial did not begin until HR returned to resting/baseline)
2. Instructions (based on paradigm):
a. Prospective: Participants informed that after the trial, they would be asked to estimate how
long the trial lasted
b. Retrospective:
i. 1st trial – Given no prior information/instructions
ii. 2nd or 3rd trial – Participants informed that they would be asked to provide their
motivation level following the trial
3. Participants instructed to pedal at a comfortable rate for the duration of the trial, and music started
(headphones).
4. Recorded distance person pedaled, RPM & HR at specific time, and RPE (every 3 minutes)
5. Follow up questions
1. Karageorhis, C.I. & Terry, P.C. (2014). The psychophysical effects of music in sport and exercise: A review.
Journal of Sport Behavior, 20(1), 54-68.
2. Mailov, L. (2011). The effects of musical tempo on time perception and memory. The University of
Buckingham, 1-19.
3. Schie, N. A., Stewart A., Becker, P. & Rogers, G.G. (2008). Effect of music on submaximal cycling. South
African Journal of Sports Medicine, 20(1), 28-31.
4. Waterhouse, J., Hudson, P. & Edwards, B. (2009). Effects of music tempo upon submaximal cycling
performance. Scandinavian Journal of Medicine & Science in Sports, 20, 662-669.
5. Yamashita, S., Iwai, K., Akimoto, T., Sugawara, J. & Kono, I. (2006). Effects of music during exercise on RPE,
heart rate and the autonomic nervous system. The Journal of Sports Medicine and Physical Fitness, 46(3),
425-430.
6. Ziv, N. & Elad O. (2010). Music and time: The effect of experimental paradigm, musical structure and
subjective evaluations on time estimation. Psychology of Music, 39(2), 182-195.
MORRIS, J. & JACKSON, B.H. (2015). Performance and perceptual effects of music tempo and
experimental paradigm. Department of Exercise Science, Pacific University, OR. There has been a
great deal of value placed on physical performance in recent years, with athletes searching for anything that
will give them a competitive advantage, and the “weekend warrior” looking for ways to improve their
health/fitness.3 Music has become a popular strategy in both arenas. However, given the various dimensions
of music (e.g., tempo, volume, genre), it has been difficult to determine what aspects of music, if any, affect
performance. Previous research has shown a connection between music tempo and performance4, but further
examination is needed to determine the extent/cause of that relationship. Purpose: The purpose of this study
is to examine the effect that music tempo has on task performance, HR, and perceptions (i.e., fatigue and
time estimation) in either a retrospective or prospective testing design. Methods: Participants were asked to
perform three bouts of a cycling task, while listening to no music, slow music, or fast tempo music.
Participants’ heart rate, speed, and perceptions of exertion were recorded within each condition. In addition,
participants were asked to estimate the amount of elapsed time in either a prospective (knowing in advance
that they were going to be asked) or retrospective (not knowing that they would be asked) manner. Data
Analysis: 3 x 2 x 5 (Music Condition x Paradigm x Time) repeated measures ANOVAs were used to analyze
each dependent measure. A univariate analysis of variance was used for time estimation. Results: No
significant interaction or main effects for HR, distance, RPE, or time estimation. There was a significant
interaction of music condition and time for RPM. Participants’ revolutions per minute (RPM) were affected by
music, however that same change was not found in the resulting distance, suggesting the change was not
sustained throughout the trial. Conclusion: Music was not found to have a consistent effect on performance
in this contrived research environment. Future studies should examine “real world” exercise environments, to
determine music’s effect when participants are intrinsically motivated to perform.
Possible reasons for differences
It is hypothesized that because RPM was a moment-in-time measure (pace measured at that moment),
and distance was a cumulative measure, music only had a momentary effect. When RPM measurements
were collected (every 3 minutes), participants seem to have pedaled more slowly or quickly (depending
on condition), but did not continue this through the remainder of the time block. Participants may not have
actively thought about the music and the task itself until the researcher stood by them to take the
measurements.
Contrary to previous research (and our hypotheses), performance was not affected by music tempo. The
distance pedaled, heart rate (HR), and perception of exertion (RPE) were found to be statistically the
same no matter what music tempo was being listened to. Participants’ revolutions per minute (RPM) was
found to be affected by music over time, as participants increased their revolutions across the trial in the
fast music condition and decreased their revolutions in the slow music condition. This was an encouraging
result, until we recognized that distance pedaled had not changed across the same period of time (see
Figure 2). If participants were pedaling faster, their distance should have also increased.
 No significant interactions or main
effects were found for:
o HR
o Distance
o RPE
o Time Estimation
 Significant interaction of Music Condition
and Time for RPM (see Figure 1)
 3 x 2 x 5 (Music Condition x Paradigm
x Time) repeated measures ANOVAs
for each dependent measure:
o Distance
o RPM
o HR
o RPE
 Univariate Analysis of variance
oTime Estimation
Figure 2. Distance pedaled within music conditions for each 3-
minute time interval.
Figure 1. RPM average in all three music conditions (no music,
slow tempo, and fast tempo) at the 6 min and 12 min marks. The
music conditions differed in the way that RPM changed over time
(F=6.302, p=.003).
Background
Purpose
Data Analysis
Results
Selected References
Acknowledgements
Conclusion
Experimental Paradigms: Participants were assigned to one of the following groups, representing the
time estimation paradigm in each trial:
o Group A: Prospective, Retrospective, Prospective
o Group B: Retrospective, Prospective, Retrospective
Music Conditions: Participants performed a trial with each of the following music conditions
(counterbalanced order). Songs were obscure (to limit recognition) and non-vocal (in order to remove
effect of lyrics):
o Slow Tempo (~110 bpm)
o Fast Tempo (~150 bpm)
o No Music (noise cancellation)
Borg RPE Scale: Used to measure participants’ perception of exertion.
o Numbers ranging from 6 to 20 (6 = not doing exercise, 20 = maximal exertion)
The current research found that music tempo, while engaged, influences RPM while pedaling on a
recumbent bike. This experiment tested participants in a contrived setting where they were to pedal on a
stationary bike with no real incentive/motivation other than to assist the researcher and to have a
possibility of randomly winning a gift card. This is most likely why participants were not as engaged in the
task/music until attention was shown to them (measurements). However, in a “real-world” exercise
scenario, the person is exercising for their benefit, therefore potentially more engaged throughout. Future
research should examine music’s effect on performance/perceptions in an actual exercise environment.
Task: Pedal at a comfortable pace on recumbent bike for three 15 minute trials, while listening to a
series of songs (headphones)