Effects of music on training intensity, perceived effort, and aerobic performance

Project description

Music is widely used in various forms of exercise and athletic training, and relatively strong effects of music upon athletic performance are documented. It has been reported to increase task-specific performance, increase heart rate and oxygen uptake during exercise, and to decrease pain and fatigue, for example. The mechanisms underlying such effects are poorly understood, however, partly because previous research has failed to disentangle possible components of music in this regard. This project will help reveal and disentangle mechanisms mediating music’s effects upon athletic performance. Such knowledge can indicate under which conditions music will be effective and direct the design of appropriate training schemes involving music or other sound patterns. If little difference is found between music proper and simple rhythmic patterns, it would open possibilities for developing dynamic, task-specifically tailored sound patterns for athletic achievement.

It has been proposed
(1) that music functions as a motivator, so as to lure participants to make a greater effort (Karageorghis, Jones, & Stuart, 2008). Another conjecture is
(2) that music functions as a distractor that decreases the influence of stress caused by fatigue (Yamashita, Twai, Aktmoto, Sugawara, & Kono, 2006), a notion supported by findings of changes in levels of lactate, norepinephrine, and perceived effort (Szmedra & Bacharach, 1998). Another apparent function of rhythmic music is
(3) to act as a pacemaker for rhythmic activities, such as exercise-to-music, running, and spinning.

With regard to motivational and distracting functions of music, there are several studies demonstrating direct neurophysiological and neuroendocrine effects merely from passive listening (e.g., Blood & Zatorre, 2001; Brown, Martinez, & Parsons, 2004). Music has been shown to affect both emotionally expressive behaviour and heart rate (Witvliet & Vrana, 2007). The design and the general scarcity of neuropshysiological studies prevent conclusions about how or why music exerts these effects, however.

Behavioural studies provide some clues, demonstrating that familiarity, that is, previous exposure to the same musical selection, artist, or style, is the single most important predictor of rated preference (Schellenberg, Peretz, & Vieillard, 2008; Schiölde, 2005; Szpunar, Schellenberg, & Pliner, 2004). Therefore, it would seem that recognition is an important criterion for eliciting the brain’s reward system, which resonates with possible ultimate biological functions of music (reviewed in Madison, in press). As these issues are outside the present scope, it suffices to note that familiarity is a factor that must be controlled in the design.
The inclination to synchronise one’s movement with a rhythmic sound signal is very strong (Madison, 2006), and humans have a general capacity to synchronise very accurately even across a range of variability in the sound signal (Madison & Merker, 2004; 2005).

A major problem for interpreting the effects of music on rhythmic exercise is therefore that previous studies have failed to control, or have at least not reported, the extent to which the tempo of the music actually corresponded to the participants’ action movements. A notable exception is Mertesdorf (1994), who devised a rhythmic sound pattern whose tempo was controlled by the participants’ movements. One can infer, however, that synchronisation in many cases could not have been possible, at least not for a substantial proportion of the session time, since tempo has predominantly been divided in coarse ranges, such as fast and slow (Rendi, Szabo, & Szabo, 2006; Szabo, Small, & Leigh, 1999) or fast, medium, and slow (Edworthy & Waring, 2006; Karageorghis et al., 2008; Karageorghis, Jones, & Low, 2006), or have been unsystematically sampled (Atkinson, Wilson, & Eubank, 2004; Copeland & Franks, 1991). While synchronisation of movements with the musical beat may be beneficial and rewarding, it is conceivable that music with a tempo different from the action performed would not only be distracting, but may also be impeding and seriously annoying. This might be a reason for the sometimes reported null effects (e.g., Tenenbaum et al., 2004; Yamashita et al., 2006).

The lack of control over the “synchronisation factor” makes it very difficult to identify and interpret the mechanisms involved in the aforementioned empirical effects of music, and provides very little ground for theoretical interpretations. The approach proposed in this project is therefore to hold the synchronisation factor constant by maintaining synchronisation at all times. A particularly suitable form of activity for this is aerobic exercise-to-music. As comparison conditions we will use various levels of “impoverished” synthetic music, which consists of a rhythmic structure copied from the original music, but which lacks variation in pitch and timbre, as well as all rhythmic embellishments. Research in this area has primarily been concerned with treadmill running and spinning, as reviewed above, and few have studied exercise-to-music (Abernethy & Batman, 1994).

5. Research plan

Design considerations

Aerobic exercise is simple and general, and requires no prior skills, which means that the results will be generalisable to a wide range of other behaviours.

Substantial differences in body mass and oxygen uptake characteristics between women and men, but also in motivation, necessitate that sex is treated as an independent variable. This will enable us to disentangle possible interactions between sex and the other variables.

The introduction indicates the necessity to control
(1) whether participants synchronise or not, and
(2) whether a signal that might induce rhythmic movement is present.

Since none of these variables are part of the research questions they need not be varied, but should preferably be held constant or balanced out. Synchronisation is extremely difficult to manipulate and assess when no objective measures are available (such as mechanical detection of physical movement) and any such measure is impractical in an aerobic exercise setting. Therefore synchronisation was held constant by using a form of exercise in which synchronisation is intrinsic: exercise-to-music. Likewise, we cannot manipulate music (as opposed to silence or some other sound) without also manipulating the presence of a signal that might induce rhythmic movement, and the only option is therefore to keep such a signal present at all times (which is also a practical requirement for exercise-to-music).

A blind or double blind design is not possible, since the nature (if not the purpose) of the stimulus material will be apparent to both staff and participants. That effects of the stimuli on the staff may be mediated to the participants, or vice versa, is problematic but unavoidable. To avoid experimenter bias, coaches will be
(1) rotated among conditions (i.e. the four exercise groups),
(2) encouraged to act consistently across sessions, and
(3) held as naïve as possible about the theoretical background for the choice of conditions.

As mentined, familiarity is known to have very large effects upon preference, and hence potentially on both neuroendocrine levels and motivation. This means that we may have large individual differences due to unknown differences in participants’ familiarity with supposedly familiar music included in a programme. Such differences may also pertain to coaches, which all in all makes it very hard to interpret results. We therefore use only unfamiliar music, which enables us to make coaches equally familiar with all programmes prior to the experiment. Familiarity enters nicely into the design anyway, in terms of repeated exposure across sessions.

Design

This is basically a mixed factorial design, with musical component and sex as between-participants factors in 4 and 2 levels, respectively, and familiarity as a within-participants factor. The longitudinal setting makes it possible to define the number of levels of familiarity post-hoc, however, from 2 (e.g. first vs. last session, sessions 1-n/2 vs. n/2-n), to the full number of sessions (yet to be specified).

The design presupposes that music has some effect, as shown by previous research, and cannot, therefore, assess this effect in relation to entirely without music. The critical comparison is between the more or less rich (or impoverished) sound structures.
The ultimate dependent variable is performance with respect to the present goal, which for aerobic exercise is to increase oxygen uptake capacity by means of medium-to-high intensity exercise (+60% of VO2 max). The best proxy for exercise intensity is heart rate (HR). The main proximal dependent measures will therefore be VO2 max (only two measurements) and HR, augmented by perceived effort (PE, Borg scale). Secondary dependent measures are ratings of participants’ satisfaction with the sound stimuli, with their own performance, etcetera.

Stimuli for the sound programmes (primary independent variable)
Great care will be taken to fine-tune the sound stimuli in consultation with the coaches, since they convey the main independent variable musical component. They will be devised according to the following. The starting point will be a music programme that has already been successfully used for some time, and all programmes will have the same sequence of tempi.

The first ”music proper” programme will be a compilation of commercially available music that have had a very limited spread to the public, thus being unfamiliar to most people. This approach has been successfully applied in a number of studies in which previous exposure was undesirable (Madison, 2001; 2003; 2006).
The second programme will be rendered in a sequencer program (e.g. Qubase), and will feature arbitrary melodic structures, repeated as in music proper. This is thought to facilitate learning and hence also familiarity.

The third programme will also be rendered in a sequencer program, and will feature arbitrary melodic structures that are not repeated, i.e. a continuous variation throughout the programme. If learning and familiarity were essential, we would expect a slower increase in preference across sessions – and perhaps also in performance – as compared to programmes 1 and 2.

The fourth programme will consist of a standard rhythmic structure, like a drum machine track, that only varies in tempo according to the original music sequence, and which features minimal variation to be learned.

The kind of stimuli in programmes 2-4 have also been applied before (Madison, 2000a; 2000b). It might be necessary to insert additional sound cues into this version in order for the coaches to orient themselves, in which case the same cues will be used in all stimulus sequences.

Participants

Healthy adults are recruited by advertisements and other available means in Umeå, offering a free one-semester aerobic exercise program at IKSU. It will be made clear that it is a research project and that participants are expected to be cooperative, follow instructions, wear a heart rate monitor during sessions, and provide subjective ratings. Participants will be offered a detailed record of their own performance, including VO2 max before and after, provided they have completed at least 80 percent of the sessions and measurements.

Procedures

Once enrolled, participants will be randomly assigned to one of four groups, each with 25-50 participants, while maintaining a similar sex ratio in all groups. Each group will exercise for 1 h 2-3 times per week for 7-11 weeks (detailed schedule to be set in consultation with all staff involved). VO2 max and resting HR will be measured at the beginning and end of the experiment. HR will be measured continuously during each session, beginning with a 2-min rest. All measurements are individual, and HR values will be stored to computer files in real time at a sampling rate of 1 Hz, once obtained through radio signals from sensors strapped around the chest (Activio AB, Stockholm, Sweden).

Experienced exercise-to-music coaches will be recruited among the IKSU staff to lead the sessions. The organiser of coaching staff has been contacted and has deemed it feasible to host the project at IKSU, with regard to staff, locales, and other standard equipment. The project will provide all additional resources, such as sound stimuli, the HR measuring system, etcetera. An experimenter will be present to give additional instructions, make sure participants apply HR sensors correctly, monitor the Activio system, and administer the rating scales.

An ethical approval will be sought if necessary, but since this procedure is associated with a substantial cost it has not been done beforehand. We do not anticipate any ethical problems with the present proposal.

6. Preliminary results, expected outcomes
No preliminary results have been obtained, mainly because the scope and character of this project is such that its questions cannot be answered on a smaller scale than that devised. However, its elements are proven in other contexts and is unlikely to pose any unforeseen problems: exercise-to-music, measurement of HR and VO2 max, and rendering of synthetic sound stimuli is all standard procedure, extensive experience of which exists within the staff.

The central hypotheses are concerned with changes in training intensity, perceived effort and satisfaction across the 7-10 weeks of exercise, compared over the four programmes. Small or no differences between the programmes – in particular at the end of the experiment – would indicate the musical components unique for music proper are unnecessary for its utilisation in athletic contexts. Substantive differences between music proper and the other programmes would indicate that some essential musical components have not been isolated in this design, and that future research is needed to identify them. Differences between programmes 2-4 would clearly indicate which musical components that have effects upon athletic performance.

Results will be published in international journals. We anticipate that at least five papers will be required to report the minimal outcomes of the study, targeted for athletic, sports, fitness, and more general psychology journals. These papers will be of significant theoretical importance for the field. The connection with music calls for papers in specialised music journals. The relatively rich design and the additional explorative dependent measures might warrant additional publications, depending on the results. It might for example be possible to compare participants’ gains with other forms of exercise, either as already published or to be reported in collaboration with researchers studying such exercise.

In addition to this, the published results may have impact on training and exercise practises, inasmuch as they indicate the relative contribution of musical components and suggest mediating mechanisms. If little difference is found between music proper and simple rhythmic patterns, it would open possibilities for developing dynamic, task-specifically tailored sound patterns for athletic achievement. Without the bounds set by commercially available or typical music, one could design sound patterns with specific properties, such as a variable tempo tailored for a specific athletic task or for an individual athlete. Generalised rhythmic patterns for arousal, relaxation, and synchronisation have been proposed (Madison, 2008) and await practical applications.

7. References
Abernethy, P. & Batman, P. (1994). Oxygen-consumption, heart-rate and oxygen pulse associated with selected exercise-to-music class elements. British Journal of Sports Medicine, 28, 43-46.
Atkinson, G., Wilson, D., & Eubank, M. (2004). Effects of music on work-rate distribution during a cycling time trial. International Journal of Sports Medicine, 25, 611-615.
Blood, A. J. & Zatorre, R. J. (2001). Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proceedings of the National Academy of Sciences, 98, 11818-11823.
Brown, S. W., Martinez, M. J., & Parsons, L. M. (2004). Passive music listening spontaneously engages limbic and paralimbic systems. Neuroreport, 15, 2033-2037.
Copeland, B. L. & Franks, B. D. (1991). Effects of types and intensities of background music on treadmill endurance. Journal of Sports Medicine and Physical Fitness, 31, 100-103.
Edworthy, J. & Waring, H. (2006). The effects of music tempo and loudness level on treadmill exercise. Ergonomics, 49, 1597-1610.
Karageorghis, C. I., Jones, L., & Low, D. C. (2006). Relationship between exercise heart rate and music tempo preference. Research Quarterly for Exercise and Sport, 77, 240-250.
Karageorghis, C. I., Jones, L., & Stuart, D. P. (2008). Psychological effects of music tempi during exercise. International Journal of Sports Medicine, 29, 613-619.
Madison, G. (2000a). Properties of expressive variability patterns in music performances. Journal of New Music Research, 29, 335-356.
Madison, G. (2000b). What does 'natural' variability in music performances mean to listeners? International Journal of Psychology, , .
Madison, G. (2001). Different kinds of groove in jazz and dance music as indicated by listeners' ratings. In Proceedings of the VII International Symposium on Systematic and Comparative Musicology and III International Conference on Cognitive Musicology (pp. 108-112). Jyväskylä, Finland: Department of Musicology, University of Jyväskylä.
Madison, G. (2003). Perception of jazz and other groove-based music as a function of tempo. In R. Kopiez, A. C. Lehmann, I. Wolther, & C. Wolf (Eds.), Proceedings of the 5th triennial ESCOM conference (pp. 365-367). Hannover, Germany: School of music and drama.
Madison, G. (2006). Experiencing groove induced by music: consistency and phenomenology. Music Perception, 24, 201-208.
Madison, G. (2008). A core mechanism of temporal entrainment as revealed by an auditory illusion. In review
Madison, G. (in press). Cause and affect. A functional perspective on music and emotion. In D.Melcher & F. Bacchi (Eds.), Art and the senses ( Oxford University Press.
Madison, G. & Merker, B. (2004). Human sensorimotor tracking of continuous subliminal deviations from isocrony. Neuroscience Letters, 370, 69-73.
Madison, G. & Merker, B. (2005). Timing of action during and after synchronization with linearly changing intervals. Music Perception, 22, 441-459.
Mertesdorf, F. L. (1994). Cycle exercising in time with music. Perceptual and Motor Skills, 78, 1141.
Rendi, M., Szabo, A., & Szabo, T. (2006). Performance enhancement with music in rowing sprint. Sport Psychologist, 22, 175-182.
Schellenberg, E. G., Peretz, I., & Vieillard, S. (2008). Liking for happy- and sad-sounding music: Effects of exposure. Cognition and emotion, 22, 218-237.
Schiölde, G. (2005). Bättre och bättre dag för dag. Effekter av komplexitet och upprepning på musikpreferenser. Master's thesis Department of Psychology.
Szabo, A., Small, A., & Leigh, M. (1999). The effects of slow- and fast-rhythm classical music on progressive cycling to voluntary physical exhaustion. Journal of Sports Medicine and Physical Fitness, 39, 220-225.
Szmedra, L. & Bacharach, D. W. (1998). Effect of music on perceived exertion, plasma lactate, norepinephrine and cardiovascular hemodynamics during treadmill running. International Journal of Sports Medicine, 19, 32-37.
Szpunar, K. K., Schellenberg, E. G., & Pliner, P. (2004). Liking and memory for musical stimuli as a function of exposure. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 370-381.
Tenenbaum, G., Lidor, R., Lavyan, N., Morrow, K., Tonnel, S., Gershgoren, A., Meis, J., & Johnson, M. (2004). The effect of music type on running perseverance and coping with effort sensations. Psychology of Sport and Exercise, 5, 89-109.
Witvliet, C. V. O. & Vrana, S. R. (2007). Play it again Sam: Repeated exposure to emotionally evocative music polarises liking and smiling responses, and influences other affective reports, facial EMG, and heart rate. Cognition and emotion, 21, 3-25.
Yamashita, S., Twai, K., Aktmoto, T., Sugawara, J., & Kono, I. (2006). Effects of music during exercise on RPE, heart rate and the autonomic nervous system. Journal of Sports Medicine and Physical Fitness, 46, 425-430.