Emotional and motivational uses of music in sports and exercise: A questionnaire study among athletes

Abstract

Music is present in many sport and exercise situations, but empirical investigations on the motives for listening to music in sports remain scarce. In this study, Swedish elite athletes (N = 252) answered a questionnaire that focused on the emotional and motivational uses of music in sports and exercise. The questionnaire contained both quantitative items that assessed the prevalence of various uses of music, and open-ended items that targeted specific emotional episodes in relation to music in sports. Results showed that the athletes most often reported listening to music during pre-event preparations, warm-up, and training sessions; and the most common motives for listening to music were to increase pre-event activation, positive affect, motivation, performance levels and to experience flow. The athletes further reported that they mainly experienced positive affective states (e.g., happiness, alertness, confidence, relaxation) in relation to music in sports, and also reported on their beliefs about the causes of the musical emotion episodes in sports. In general, the results suggest that the athletes used music in purposeful ways in order to facilitate their training and performance.

Keywords

arousal emotion exercise function of music motivation relaxation sports questionnaire

Introduction

There are many case reports of famous athletes who have used music to enhance their performance. For example, the celebrated Ethiopian distance runner Haile Gebrselassie synchronized his running pace with the tempo of the rhythmical pop tune ‘Scatman’ when he set a new world record for 2000 meters in February 1998 (Lister, 2005). Also, the American swimmer Michael Phelps, who won 7 gold medals and set 5 world records at the 2007 FINA World Championships, reportedly listened to hip-hop music before his races in order to get focused and psyched up (‘More questions with Michael Phelps’, 2007). Empirical investigations on the how’s and why’s of listening to music in sports remain scarce, but are important for gaining a better understanding of the potential benefits of music in sports. In the present study, we therefore report results from a questionnaire study focusing on elite athletes’ emotional and motivational uses of music in sports and exercise.

The emotional effects of music have received much attention recently, and evidence from many sources indicates that music is capable of inducing emotion in listeners (for reviews, see Juslin & Laukka, 2004; Juslin & Västfjäll, 2008).¹ Studies on people’s self-reports of their everyday music-listening habits have revealed that today’s music listeners actively use music as a resource to achieve different emotional purposes in everyday life. For example, studies using various methods like questionnaires (Juslin, Liljeström, Laukka, Västfjäll, & Lundqvist, 2011; Laukka, 2007; Saarikallio & Erkkilä, 2007; Thayer, Newman, & McClain, 1994; Wells & Hakanen, 1991), diary and experience sampling studies (Juslin, Liljeström, Västfjäll, Barradas, & Silva, 2008; North, Hargreaves, & Hargreaves, 2004; Sloboda, O’Neill, & Ivaldi, 2001), and qualitative interviews (DeNora, 2000; Ruud, 1997), have suggested that listeners frequently use music for the regulation of emotion and arousal and that music induces positive affective states in many everyday listening contexts. Evidence from sporting contexts is more limited, but a number of questionnaire studies have reported that athletes frequently listen to music in order to regulate both positive and negative affective states (Stevens & Lane, 2001; Terry, Dinsdale, Karageorghis, & Lane, 2006). Moreover, experimental studies have shown that athletes report increased positive affect and reduced negative affect in conditions where they listen to arousing music, compared to no music, during moderate to high intensity activity (e.g., Baldari, Macone, Bonavolontà, & Guidetti, 2010; Bishop, Karageorghis, & Kinrade, 2009).

With regard to the regulation of arousal, experimental studies in a variety of applied settings have suggested that loud, upbeat music increases arousal while soft and slow music reduces arousal (e.g., Bernardi, Porta, & Sleight, 2006; Brownley, McMurray, & Hackney, 1995; Copeland & Franks, 1991; Edworthy & Waring, 2006; Pelletier, 2004). Music can also reduce ratings of perceived exertion during training, especially during submaximal work intensities (Boutcher & Trenske, 1990; Yamashita, Iwai, Akimoto, Sugawara, & Kono, 2006). During high-intensity training, however, physiological bodily cues become a more dominant influence on attention and consequently music often has negligible effects on perceived exertion (see Rejeski, 1985; Tenenbaum, 2001).

Optimal levels of positive and negative affect and arousal are factors that are beneficial for achievement and motivation in sports (e.g., Hanin, 2007) as well as in other domains (e.g., Isen, 2008). Because music can be used for affect- and arousal-regulation purposes, much of the research on music in sports has focused on identifying possible benefits of using music in sports settings. In their review of this literature, Terry and Karageorghis (2006; see also Karageorghis & Terry, 2009) developed a conceptual framework for the benefits of music in sports and exercise. Among the potential benefits identified in the model were psychological and psychophysiological effects of music including increased positive affect and reduced negative affect (e.g., Bishop et al., 2009), pre-task activation or relaxation (e.g., Karageorghis, Drew, & Terry, 1996), and reduced levels of perceived exertion (e.g., Boutcher & Trenske, 1990). They also included dissociation from unpleasant bodily sensations (e.g., pain, fatigue), and increased likelihood of athletes experiencing flow states (i.e. states of optimal concentration and absorption with the activity at hand, see Csikszentmihalyi, 1990) as potential benefits in their model. The pain-reducing effects of music interventions have received much interest in clinical health care settings, and recent reviews have shown that music interventions may have positive effects on reducing anxiety and pain (Nilsson, 2008). Regarding flow, preliminary evidence has suggested that music may promote flow states in sports settings (Karageorghis, Jones, & Stuart, 2008; Pates, Karageorghis, Fryer, & Maynard, 2003).

Terry and Karageorghis’ (2006) model further included ergogenic, or performance-enhancing, effects of music like increased work output through synchronization of movement with the tempo of the music, enhanced acquisition of motor skills when the music matches the required movement patterns, and enhanced performance levels via combinations of all of the mechanisms described above. Several experimental studies have reported results suggesting that music may have ergogenic effects in sports, like increased endurance, strength and work output (e.g., Anshel & Marisi, 1978; Crust & Clough, 2006; Rendi, Szabo, & Szabo, 2008; Simpson & Karageorghis, 2006; Szabo, Small, & Leigh, 1999; Waterhouse, Hudson, & Edwards, 2010).

So far, there have been surprisingly few studies that explore how athletes actually use music in various sport and exercise settings, and as a consequence we have limited knowledge about which of the potential benefits of music are considered important by athletes. In a seminal study, Bishop, Karageorghis and Loizou (2007) conducted qualitative interviews with 14 young tennis players about their use of music listening as a pre-performance strategy. Additionally, 10 of the participants kept a diary wherein they recorded musical episodes during one week. The results indicated that participants consciously selected music to elicit various emotional states, and frequently reported consequences of music listening included increased positive affect and arousal. Also Gluch (1993), based on qualitative interviews with 6 athletes, gave examples of how athletes may use music to manipulate arousal levels and to assist in affect regulation during their pre-performance preparations.

In the present study, we intend to build on the previous work reviewed above and report results from a questionnaire study on Swedish athletes’ uses of music in sports. Following Juslin et al. (2011), we included items involving two kinds of self-report, namely semantic and episodic knowledge, based on a distinction in memory research (Robinson & Clore, 2002; Tulving, 1983). Self-reports that assess aggregated estimates (e.g., about the prevalence of various emotions and motives for listening in relation to music in sports) involve judgments based on semantic memory and are based on the conscious recollection of general beliefs and factual information independent of context and personal relevance. Most of the previous research on uses of music is based on semantic knowledge. However, retrospective and aggregated estimates are often prone to certain biases because the general beliefs that they are based on may be erroneous (Robinson & Clore, 2002). For example, when asked about how often one does feel happy when listening to music in various situations, it is possible that participants overestimate the frequency of experienced happiness based on general beliefs that ‘happiness’ is very typical of what people feel when listening to music (see Juslin et al., 2011). Self-reports of autobiographical episodes that are relatively close in time (e.g., about the most recent episode wherein the athletes experienced emotions in relation to music in sports) instead involve judgments based on episodic memory. Episodic memories are experiential in nature and are usually rich in information about the characteristics of the recalled episode. By asking the athletes about their uses of music in sports both in general (using quantitative ratings) and about their most recent emotional music episode in sports (using free response items) – and by comparing the answers obtained with the two different response formats – we aimed to obtain both more stable estimates about the prevalence of, and data that is richer in content about, different uses of music in sports and exercise settings.

Methods

Participants and procedure

A self-administered electronic questionnaire was sent to 438 Swedish athletes who practiced various individual sports on a national or international level. Table 1 presents the characteristics of the sample in terms of various background variables obtained in the questionnaire; 252 athletes (135 women and 117 men; mean age = 23 years; response rate = 58%) participated in the study.

Table 1.

Demographic details of the participating athletes

Variable	Count	%	Mean	Range	SD
Gender and age
Female	135	54%	23.3	16–54	6.3
Male	117	46%	22.4	16–33	4.6
Total	252	100%	23.0	16–54	5.5
Years of experience as an active athlete			12.9	3–27	5.1
1–10 years	89	35%	8.0
11–15 years	84	33%	13.2
≥ 16 years	72	29%	19.9
Number of training sessions/week			8.0 (median = 7)	3–16	2.5
Type of sport
- Endurance sports
Long-distance track	20	8%
Orienteering	26	10%
Biathlon	7	3%
- Middle distance running	21	8%
- Sprint track (incl. sprint hurdles)	46	19%
- Technique and precision sports
Throwing sports (shot put, javelin, discus, hammer)	38	15%
Jumps (long jump, triple jump high jump, pole vault)	42	17%
Combined events (heptathlon, decathlon)	19	8%
Badminton	3	1%
Archery	2	1%
Gymnastics	1	0.5%
Equestrianism	1	0.5%
- Unspecified track and field	17	7%

The participants were contacted using e-mail and were asked if they would like to participate in a survey concerning uses of music in sports. The addresses were provided by various national athletic associations and sports clubs, as well as social networking websites. The prospective participants were informed about the goal of the study, that their participation would be confidential, and that data would only be used for scientific purposes. ‘Survey Monkey’ was chosen as the most appropriate online survey package to communicate the questionnaire to the target audience (http://www.surveymonkey.com). The data collection was conducted as a part of the second author’s undergraduate research thesis.

Questionnaire

The questionnaire featured 24 items with varying response formats: forced-choice, quantitative ratings, and open-ended responses. Besides questions about various background variables (items 1–6; see Table 1), the questionnaire included questions about (1) the athletes’ everyday music listening habits (items 7–10), (2) semantic estimates of various motivational and emotional uses of music in relation to sports (items 11–16), and (3) episodic estimates about the most recent emotional episode that the athletes had experienced in relation to music in sports (items 17–24). The fixed response options were based on earlier empirical studies of motivational and emotional uses of music in everyday life settings (e.g., Juslin et al., 2011; Laukka, 2007; Saarikallio & Erkkilä, 2007), the theoretical framework of possible benefits of music in sport and exercise contexts developed by Terry and Karageorghis (2006), and previous work on athletes’ uses of music in sports (Bishop et al., 2007).

Music preferences were assessed by presenting the participants with a list of 8 different musical genres from which they were asked to choose the genre(s) that they most liked to listen to in various contexts. The responses were subsequently categorized according to Rentfrow and Gosling’s (2003) 4 broad dimensions of music preferences: uptempo and conventional music (‘pop music’, ‘Swedish dance band music’), energetic and rhythmic music (‘soul/rnb/hiphop’, ‘electronic dance music’), intense and rebellious music (‘hard rock’, ‘rock and alternative’), and reflective and complex music (‘classical music’, ‘jazz & blues’); see Juslin et al., 2011. The design of the questionnaire is explained in detail in the results section, and the complete questionnaire is available upon request from the authors.

Results

Everyday music listening

The participants were first asked to rate how important music is to them, in a general sense, in their everyday life on a 6-point scale (1 = not at all important, 6 = very important). The mean importance rating was 4.42 (SD = 1.32), which indicated that the participants generally considered music important, and the distribution of the answers (N = 252) was as follows: 6 (24%), 5 (31%), 4 (20%), 3 (13%), 2 (10%), and 1 (1%). The participants were then asked to estimate how often they usually listen to music, using an open-ended response. The answers (N = 248) were categorized into the following alternatives: 66% reported listening to music several times/day, 19% listened to music once/day, 13% listened a couple times/week, and 3% listened once/week or less. We next queried about what musical genres the participants liked to listen to in their everyday life, by choosing one or several genres from a list. Results revealed that 71% preferred uptempo and conventional music, 66% preferred energetic and rhythmic music, 63% preferred intense and rebellious music, and 16% preferred reflective and complex music.

Finally, the participants were asked to estimate approximately how often they experienced emotions in relation to music, by choosing among 4 response alternatives. Forty-six percent reported experiencing emotions ‘often’ (66–99% of the listening time), 44% reported experiencing emotion ‘sometimes’ (33–66% of the listening time), 10% answered ‘seldom’ (1–33% of the listening time), and no participant reported that they ‘never’ (0% of the listening time) experience emotions in relation to music (N = 252). Female participants reported a significantly higher prevalence of musical emotions than male participants, as indicated by a chi-square test. Fifty-three percent of the female participants reported experiencing emotions ‘often’, compared to 36% of the male participants (χ² = 6.95, df = 1, p = .008).

Uses of music in sports and exercise

First, the participants were asked to rate how important music was to them during practicing sports on a 6-point scale (1 = not at all important, 6 = very important). The mean importance rating was 3.70 (SD = 1.51) and the distribution of the answers (N = 239) was as follows: 6 (13%), 5 (20%), 4 (26%), 3 (17%), 2 (15%), and 1 (10%). Female participants (M = 3.94, SD = 1.53) rated music as significantly more important for practicing sports than did the male participants (M = 3.42, SD = 1.44) as indicated by a t-test (t ₂₃₇ = 2.69, d = 0.35, p = .008). Also, a t-test showed that music was rated as significantly more important in everyday life, than in a sporting context (t ₂₃₈ = 7.63, d = 0.51, p < .001). Not surprisingly, the importance ratings for music in everyday life and in sports were positively correlated (r = 0.47, p < .001), suggesting that athletes who value music in everyday life also are more likely to consider music to be important in sports.

Next, the athletes were asked to rate how often they listened to music during different situations (exercise sessions, warm-up, pre-event preparations, during competition, and after competition) in sports and exercise on 6-point scales (1 = very seldom, 6 = very often).² We conducted a mixed model ANOVA with situation as a repeated measure (5 levels) and gender as a between-subjects factor. We found significant main effects of situation (F_{4, 948} = 51.26, partial η² = 0.18, p < .001, Greenhouse-Geisser corrected) and gender (F_{1, 237} = 7.04, partial η² = 0.03, p = .009), but no interaction between the factors. Overall, women (M = 3.10, SD = 1.27) reported listening to music slightly more often than men (M = 2.69, SD = 1.12). The reported frequency of listening as a function of the different situations is shown in Figure 1. As indicated by the 95% confidence intervals shown in Figure 1, ‘pre-event preparations’ were reported significantly more often than ‘warm-up’ and ‘exercise sessions’, which in turn were reported significantly more often than ‘during competition’ and ‘after competition’ (N = 243).

Figure 1.

Relative frequency of music listening in different situations in sports and exercise in response to the question ‘How often do you listen to music in the following situations?’ as rated on a 6-point scale (1 = very seldom, 6 = very often). Error bars = 95% confidence intervals

We then asked the athletes about what type of music they prefer to listen to during sports by marking the most appropriate alternative from a fixed list of musical genres (they were only allowed to mark one alternative). Results showed that 32% preferred intense and rebellious music in sports, 28% preferred energetic and rhythmic music, 25% preferred uptempo and conventional music, and only 1% preferred reflective and complex music (14% preferred “other” music). The athletes were also asked to report how often they chose the music that they listened to during sports by themselves, by selecting among 5 response alternatives (N = 235). Most of the athletes made the choices of what music to listen to during sports by themselves: 31% reported that they ‘often’ (66–99% of the listening time) chose the music by themselves, 30% answered ‘always’ (100% of the listening time), 22% answered ‘sometimes’ (33–66% of the listening time), 13% answered ‘seldom’ (1–33% of the listening time), and 4% answered ‘never’ (0% of the listening time).

The athletes were next asked about their motivations for listening to music during sports. They were presented with a list of 15 different motives for listening, and were asked to rate how often they listened to music in sports for each motivation on 6-point scales (1 = very seldom, 6 = very often). The selection of motives was based on prior research on uses of music in everyday and sporting contexts (e.g., Bishop et al., 2007; Laukka, 2007; Saarikallio & Erkkilä, 2007; Terry & Karageorghis, 2006). The results are shown in Table 2 and suggest that the athletes intentionally used music for a wide range of motives during their sports practice. The most common motives were related to the control of arousal, emotion regulation, motivational aspects, performance aspects, and the experience of flow. All items received high ratings by at least some participants, suggesting that all motives were represented in our sample of athletes. Motives related to motor aspects of the performance received the lowest frequency estimates in our sample.

Table 2.

Relative frequency of emotional and motivational uses of music in sports and exercise, in response to the question ‘How often do you listen to music during your sports practice because of the following reasons?’ as rated on a 6-point scale (1 = very seldom, 6 = very often)

Rank	Motivation	Mean rating	Standard deviation
1.	To increase pre-event activation/to pump up	4.68	1.52
2.	To increase positive affect	4.22	1.59
3.	To get help with my motivation	3.70	1.69
4.	To perform better	3.68	1.75
5.	To experience ‘flow’/being in the zone	3.60	1.76
6.	To increase self-efficacy and self-confidence	3.34	1.74
7.	To increase my endurance	3.19	1.72
8.	To relax and calm down	3.13	1.67
9.	To help me concentrate	2.94	1.63
10.	To decrease negative affect	2.93	1.72
11.	For entertainment	2.84	1.56
12.	To decrease my perceived exertion	2.70	1.70
13.	To divert my attention from fatigue and pain	2.36	1.55
14.	To be able to synchronize my movements with the music	1.93	1.36
15.	To improve my acquisition of motor skills	1.68	1.06

Note: N = 245

Finally, we also asked the athletes to rate the relative frequency with which they feel various affects and emotions in response to music during sport and exercise from a list of 23 emotion terms in random order (on a 4-point scale; 1 = never, 2 = seldom, 3 = often, 4 = always). The emotion terms were based on earlier survey studies of emotional reactions to music in everyday life (e.g., Juslin et al., 2011; Laukka, 2007), complemented with terms more specific for sport and exercise contexts (e.g., Terry & Karageorghis, 2006). The results are shown in Table 3, and clearly indicate that positive emotions were most prevalent during sport. ‘Happy’, ‘alert’, and ‘confident’ were the most frequently reported terms, whereas ‘sad’ and ‘indifferent’ were the least frequently reported terms. A t-test conducted on the mean frequency ratings across all emotion terms, indicated that female participants (M = 2.14, SD = 0.48) reported somewhat higher overall frequencies of felt emotions in response to music than did male participants (M = 1.99, SD = 0.46), t(240) = 2.41, d = 0.32, p = .016.

Table 3.

Responses to the question ‘How common is it that you feel each of the following emotions in response to music in sport and exercise?’ in terms of the mean rating and standard deviation of each emotion term (1 = never, 4 = always)

1. Happy	3.14	(0.73)	13. Ecstatic	2.10	(0.90)
2. Alert	2.98	(0.87)	14. Interested	1.97	(0.85)
3. Confident	2.73	(0.92)	15. Moved	1.97	(0.88)
4. Relaxed	2.45	(0.86)	16. Relieved	1.70	(0.75)
5. Enjoying	2.40	(0.93)	17. Loving	1.70	(0.85)
6. Calm	2.37	(0.86)	18. Curious	1.65	(0.78)
7. Chills/thrills	2.35	(0.94)	19. Angry	1.54	(0.79)
8. Expectant	2.34	(0.94)	20. Solemn	1.52	(0.73)
9. Amused	2.21	(0.95)	21. Frustrated	1.32	(0.59)
10. Proud	2.19	(0.93)	22. Sad	1.31	(0.54)
11. Longing	2.12	(0.93)	23. Indifferent	1.27	(0.56)
12. Nostalgic	2.10	(0.89)

Note: N = 245

Emotional episodes in relation to music in sports

The last part of the questionnaire concerned emotional episodes in relation to sports, and the participants were asked to recall the latest episode in sports and exercise when they had experienced emotions in relation to music using mainly free-response questions. The free responses were subsequently coded by two independent coders, and the average inter-coder agreement (estimated in terms of Cohen’s Kappa) was к = 0.94.

The athletes were first asked to indicate how long ago the episode had taken place. The athletes’ free responses (N = 210) were coded into 3 categories, and the results showed that 27% referred to an episode that had taken place ‘just now up to a couple of days ago’, whereas 26% referred to an episode that had taken place ‘within the last month’ and 43% referred to episodes that had occurred ‘more than one month ago’. Five percent of the answers were not possible to categorize into time periods (e.g., ‘I cannot remember any such episode’).

Next, the participants were asked to describe what emotions they had experienced during their recalled episodes. The participants’ free responses (N = 210) were categorized into 12 categories and the results are shown in Figure 2. As can be seen, the most frequently reported emotions were alert (36%), happy (23%), calm/relaxed (8%) and confident (8%). Examples of responses in the ‘alert’ category were: ‘It gave me energy and a will to run faster’, ‘To wake up and be alert though I am drowsy in the morning’, and ‘Pumped up’. Examples of responses for the remaining main categories in Figure 2 were: Happy – ‘Happy, motivated, and elated’, ‘It was a feeling that made me feel joy in what I was doing’; Calm/relaxed – ‘I often calm down when I am listening’, ‘It keeps me calm and makes me think about things other than the competition’; Confident – ‘That I was invincible, that nothing could stop me’, ‘I felt strong and knew that no one could beat me on that day’; and Expectant – ‘Full of expectation’, ‘I can’t wait to start running’. The results were similar to the previous semantic estimates (see Table 3), though there were also some notable differences. For example, in the episodic estimates ‘alert’ was the by far most often reported response, whereas in the semantic estimates the most frequently reported emotion was ‘happy’. The episodes further revealed a category that was not present among the choices for the semantic estimates, namely ‘focused’ (3%), which refers to a state of cognitive focus on the activity at hand. Also, ‘frustration’ was among the 10 most frequently reported emotions for the episodes but not for the semantic estimates, though it must be noted that negative affect was rarely reported in both the episodes and the semantic estimates. 4.5% of the responses referred to emotions/affects other than in Figure 2, but each of these were only reported once; also 4.8% of the responses could not be categorized in terms of emotions (e.g., ‘I don’t know’).

Figure 2.

The ten most frequently reported emotion categories in 210 emotional episodes in relation to music in sports and exercise

The participants were then asked to report the duration of the emotional episode, and their free responses (N = 209) were categorized into 4 alternatives: 20% reported that the emotion lasted ‘less than 5 minutes’, 17% reported that it lasted ‘5–15 minutes’, 19% reported that it lasted ‘15 minutes to 1 hour’, and 29% reported that it lasted ‘more than 1 hour’. 15% of the answers could not be categorized in terms of durations. The athletes were further asked to rate how intense the experienced emotion was on a 6-point scale (1 = Not at all intense; 6 = Very intense). The mean intensity rating was 4.37 (SD = 1.17) – which indicates that on average the athletes reported fairly intense emotions/affects in their episodes – and the distribution of answers (N = 212) was as follows: 6 (18%), 5 (31%), 4 (30%), 3 (15%), 2 (4%), and 1 (2%). It can be noted that because the feelings reported by the participants were predominantly short (less than one hour) and fairly intense, together with the fact that they involved specific states rather than broad dimensional descriptions, it is likely that the reports mainly referred to emotions rather than moods, as commonly conceptualized (e.g., Beedie, Terry, & Lane, 2005; Scherer, 2005).

The participants (N = 212) further reported what genre of music they listened to during the emotional episode by marking the most appropriate option from a fixed list of alternatives, and the distribution of responses was similar to the semantic estimates: 38% reported listening to uptempo and conventional music, 30% listened to intense and rebellious music, 28% listened to energetic and rhythmic music, and 2% listened to reflective and complex music.

The participants were next asked to describe the situation in which the emotional episode took place, in terms of what they did and where they were. Their free responses were categorized into 5 categories, which received the following frequencies: ‘during training and warm-up’ (57%; ‘Jogging out in the woods’, ‘I was doing an early morning strength training session, I was alone and tired and the music made the training more fun’), ‘before competition’ (33%; ‘I’m lying on the couch getting a massage while concentrating on the upcoming race’, ‘In a hotel room before the competition’), ‘during competition’ (4%; ‘At the Swedish national championships’, ‘At an indoor competition’), and ‘after training/competition’ (3%; ‘It was after my debut, I was in the car’, ‘During the prize award ceremony’). Three percent of the answers could not be categorized into the above situations. As can be seen, the most common situations in the episodes are similar to the ones reported in the semantic estimates – during training/warm-up and before competition – whereas the episodes more seldom referred to situations that took place during competition or after the event.

The athletes were also asked to describe their opinion of how the experienced musical emotion affected their performance. The results are shown in Table 4 and suggest that the athletes attributed a wide variety of positive and performance enhancing effects to the musical emotion episodes. The most commonly reported effects were related to the control of arousal (‘increase level of activation/to pump up’), and aspects related to performance and motivation. Seven percent reported that the emotion had ‘no effect’ on their performance, and 1% reported that the emotion had adverse effects. These results show many similarities to the semantic estimates of various motivational and emotional uses of music in sports (see Table 2), which indicates that the athletes were able to recall episodes in which the reported motivations for using music in sports had had the intended effect.

Table 4.

Athletes’ views on the effects of emotion on their performance in 210 emotional episodes in relation to music in sports and exercise

Suggested effect	Frequency	Examples
1. Increase level of activation/to pump up	21%	‘I became pumped up’, ‘A bit more pepped up and more adrenaline’, ‘I got my pulse up before the game’
2. Increase endurance/fatigue management	19%	‘I forgot about being tired’, ‘Everything felt easier and my endurance increased’, ‘I felt less tired’
3. Increase performance	17%	‘It had a positive influence’, ‘It increased my capacity’, ‘I performed my task better’
4 Increase motivation	14%	‘I became motivated to go for it’, ‘A feeling of stronger motivation’, ‘It made it feel like it was worth the effort’
5. No effect	7%	‘Nothing special’, ‘It did not affect my race very much’
6. Feel more confident	5%	‘I got more confident and believed more in myself’, ‘It made it easy to create positive images of myself during the competition’
7. Increase focus and concentration	5%	‘I became more focused on the task at hand’, ‘I was able to focus my energy towards my goal to get a medal’
8. Positive affect	4%	‘I became happy’, ‘I got a lovely feeling’
9. Relax and calm down	3%	‘I was able to stay calm’, ‘It decreased my nervousness before competition’
10. Negative effect	1%	‘It was the wrong type of music, too calm and not energizing at all’

Finally, the participants were asked about what they thought caused the emotion in their reported episode. The large majority of responses referred to ‘aspects of the music’ (61%; ‘Good song’, ‘The music and what it produces’, ‘The beat of the music’, ‘The music takes you to a world of your own where you are the king’). Other causes mentioned by the athletes were: ‘memories’ (8%; ‘My associations to the music that was playing’, ‘The music made me remember good things’), ‘the situation’ (7%; ‘The atmosphere, the surroundings and the fact that it was a championship’, ‘Inspiring words from my coach’), ‘personal factors’ (7%; ‘That I was in good form and really wanted to win’, ‘My goals and dreams’), ‘the lyrics’ (6%; ‘Words in the lyrics’, ‘The words of the songs mean a lot’), ‘pre-existing mood’ (2%; ‘I already felt relaxed and at peace’, ‘The fact that I already was nervous’).

We also wanted to investigate which combinations of emotion, musical style, attributed effect on sporting performance, and situation occurred with a frequency higher than chance. To this end we conducted a configural frequency analysis using the exact binomial test (Bergman & El-Khouri, 2002; Lienert & Krauth, 1975). We included the 4 most frequently reported categories of emotions (alert, happy, calm/relaxed, confident), the 3 most frequently reported musical genres (uptempo and conventional, intense and rebellious, and energetic and rhythmic), the 4 most frequently attributed effects of the musical emotion (increased level of activation, increased endurance, increased performance, and increased motivation), and the 2 most frequent situations (during training, and before competition) in the analyses. Only one configuration occurred with frequency significantly higher than chance, namely ‘alert/energetic and rhythmic music/increased level of activation/before competition’ (observed frequency = 15, expected frequency = 3.39, χ² = 39.69, p < 0.001, Bonferroni-adjusted), and this combination could thus be called the most typical episode among the ones reported in our material.

Discussion

To summarize, the main results suggest that athletes often listen to music, and believe music to be important, in everyday as well as in sports settings. During sport, both semantic and episodic estimates suggested that the athletes most often listened to music during pre-event preparations, warm-up, and training, and less frequently during competition or after the event. The most frequently reported motives for listening to music in sports were to increase levels of activation, motivation, performance and positive affect. The athletes further reported that they mainly experienced positive affective states (e.g., alert, happy, calm/relaxed, confident) in relation to music in sports. These results extend previous findings which have mainly been based on qualitative interviews with few participants (e.g., Bishop et al., 2007), and suggest that emotional and motivational uses of music are an integral part of both training and preparation for competition for many athletes.

Like previous studies, the results indicate that music is often used during pre-event preparations (e.g., Bishop & Karageorghis, 2009), but less so during competition or after the event. This result could be expected because there are likely fewer opportunities for listening to music during competition in most sports. Also, many governing bodies of sport are currently banning the use of music in competition, which obviously further diminishes the possibilities of listening to music during competition (see Karageorghis & Terry, 2009). It should be noted that the prevalence of listening in various sporting situations is also influenced by the motives for listening. The most frequently reported motive in both the semantic and episodic estimates was to increase the level of activation, or to ‘pump up’, a listening strategy for optimizing the arousal level before the event, whereas motives relevant for after-event use, like relaxation, were less frequently reported. Also, most of the frequently-reported motives for listening, like increasing levels of motivation, positive affect, flow, and endurance can be seen as strategies for making training more enjoyable and effective. In general the picture presented by the current results is that the athletes reported using music in very purposeful ways to facilitate their training and performance. This impression is accentuated when looking at studies of everyday music listening where listening for entertainment is among the most frequently reported motives for listening (e.g., Laukka, 2007), whereas it was less frequently reported in the sports context of the present study. The results also give face validity to Terry and Karageorghis (2006) conceptual model of possible benefits of music in sports and exercise in the sense that the athletes reported using music for all of the reasons included in the model. However, motives related to motoric aspects received relatively lower frequency estimates than the other motives, and it remains to be investigated whether this was a characteristic unique to our sample (e.g., due to the specific sports included) or if motives related to motor aspects of the behavior are generally less frequently endorsed. Also, further experimental research is warranted to investigate how music may affect performance in sports in positive as well as in negative ways.

As in previous studies focusing on everyday listening contexts, the athletes reported that the emotions and affective states that they felt in relation to music in sport settings were mainly positively valenced (e.g., Juslin et al., 2011). However, a distinct feature of the current results was that all of the most frequently mentioned emotions and affects could be related to performance and motivation in sports. ‘Happy’ emerged as the most frequently-reported emotion in the semantic estimates, and optimal levels of positive affect are often considered beneficial for achievement and motivation in sports (e.g., Hanin, 2007). ‘Alert’ was the most frequently mentioned affective state in the episodic estimates. Alertness, in addition to being a positively-valenced affective state, may be conceived as including both a physiological arousal component and a cognitive component and, based on the current data, seems to be of primary importance in musical sporting episodes. This is not surprising because being alert implies a state of optimal arousal and a cognitive mindset of appropriate focus and concentration for successful performance. Feeling confident also emerged as an important affective state in relation to music in sports. Confidence in one’s own capability to perform a task in sports and other domains is crucial for the successful execution of, as well as the level of motivation and perseverance in, the task (e.g., Bandura, 1991). Feeling calm/relaxed was also frequently mentioned by the athletes, and is related to the regulation of both arousal levels and mood. As a final example, the athletes also frequently reported that they felt ‘enjoyment’ in relation to music in sports. Enjoyment of an activity is beneficial for developing an intrinsic motivation for the activity (Deci & Ryan, 2000). In contrast, emotional states that are relatively frequently occurring in relation to music in everyday listening but that have no obvious implications on performance and motivation (e.g., loving, nostalgic, sad; see Juslin et al., 2011) seem to occur less frequently in sporting than in everyday settings. Taken together the reported prevalence of emotions in relation to music in sports suggests that the athletes use music to induce affective states that are relevant and potentially beneficial to their sporting activities.

Our study further presented novel data about the athletes’ beliefs about the causes of the emotion in their reported musical emotion episodes in sports. The main finding here was that most of the athletes attributed the cause of the emotion to the broad category of ‘aspects of the music’, and only relatively small percentages of the episodes referred to situational and personal factors unrelated to the music itself. Juslin and Västfjäll (2008) recently proposed several psychological mechanisms by which music may evoke emotions, and it may be illuminating to compare the athletes’ answers with their model. Many answers included in the ‘aspects of the music’ category did mention music in very general terms only (e.g., ‘the music’), but some athletes explicitly mentioned musical features (e.g., ‘the beat of the music’, ‘increases in tempo’, ‘loud music with a good punch’). Such answers can be interpreted as referring to the brain stem reflexes mechanism, by which fundamental acoustic characteristics of the music are processed by the brain to indicate potentially important and urgent events. A few participants further mentioned features related to the musical structure (e.g., ‘the melody and tones of the music’) and such answers could instead refer to the musical expectancy mechanism which refers to a process whereby an emotion is induced in the listener because features of the music violates, delays, or confirms the listener’s expectations about the continuation of the music (e.g., Huron, 2006; Meyer, 1956). However, many of the responses included in the ‘aspects of the music’ category also referred to the music in terms of aesthetic preferences (e.g., ‘good music’, ‘music that I like’). Answers such as these are hard to interpret in terms of Juslin and Västfjäll’s (2008) mechanisms, but point out the need for further research on the relationships between music preferences and musical emotions.

Juslin and Västfjäll (2008) also included visual imagery, or the process whereby an emotion is induced in a listener because she conjures up visual images while listening to the music, as a mechanism in their model. Only a handful of responses were related to this mechanism (e.g., ‘I visualized myself on a sunny beach with a piña colada in my hand while the tune was playing’), and no answers explicitly referred to the emotional contagion mechanism (i.e., the process whereby emotions are induced by music because the listener perceives the emotional expression of the music and then mimics this expression internally). Eight percent of the athletes surveyed also mentioned that ‘memories’ were a likely cause of the musical emotions. Answers in this category can be interpreted both in terms of the episodic memory mechanism – through which an emotion is induced in the listener because the music evokes a particular event in the listener’s past (e.g., ‘the music made me remember good things’) – and the evaluative conditioning mechanism which refers to a process whereby an emotion is induced by a piece of music because that piece has been repeatedly paired with other positive or negative stimuli (e.g., ‘my associations to the music that was playing’). To conclude, the present results indirectly suggest that psychological mechanisms such as those proposed by Juslin and Västfjäll (2008) may be underlying musical emotion episodes in sports. However, future research should investigate the respective contribution of the different mechanisms in various contexts, including sport, in a more direct fashion.

The results also gave data on what type of music the athletes usually listened to during sports and exercise, and suggest that the athletes preferred uptempo and conventional, intense and rebellious, and energetic and rhythmic music, rather than reflective and complex music. This finding should also be interpreted in light of the motives for listening, because musical preferences interact with the listening situation and people’ s music selections represent an attempt to optimize their responses to that situation (e.g., North & Hargreaves, 2000). It is possible that different musical styles can be used to achieve the same emotional and motivational functions (e.g., Juslin et al., 2011; Schäfer & Sedlmeier, 2009), but some musical styles may be particularly appropriate for certain uses (e.g., Schwartz & Fouts, 2003). Because the athletes mainly listened to ‘pump up’ in a sport context, it seems natural that they would choose high-arousal music as opposed to calm music.³ This finding converges with previous studies on preferred music in sports settings which suggest that athletes predominantly listen to ‘motivational music’ (i.e., music which stimulates or inspires physical activity) during sports (Crust, 2008; Karageorghis, Priest, Terry, Chatzisarantis, & Lane, 2006). One limitation of the present study, and most research on music preferences, is the fact that broad categories of different musical genres (e.g., Rentfrow & Gosling, 2003) may not capture the essence of the musical preferences since different pieces of music within the same broad category may be very different. A solution to this problem would be to add descriptions of the music in terms of musical features such as tempo and intensity, and also to include ratings of liking, familiarity, and other subjective evaluations of the music. Such an approach would give a more fine grained description of the musical piece in question, and has been advocated by Karageorghis et al (2006) in the domain of sports psychology.

The present study expands upon earlier qualitative studies and provides the first estimates of the prevalence of various emotional and motivational uses of music among elite athletes. However, the present data also have several limitations. Most obviously the data consist of retrospective self-reports which may be subject to various biases such as demand characteristics and recall biases. Unlike many previous studies, we assessed both semantic and episodic estimates in order to achieve more stable estimates as well as richer data about the athletes’ emotional and motivational uses of music. However, future studies on athletes’ uses of music should also try to incorporate data that are not based on self-report (e.g., behavioral observations), and self-report data that are not based on retrospective appraisals (e.g., diary and experience sampling studies). Also, though the response rate of the present study was acceptable, it is still possible that the prevalence estimates may be inflated because the athletes who chose to participate may have been particularly interested in music. Further, we found that female athletes reported slightly higher levels of emotion in relation to music in sports than male athletes, which is in accord with previous studies of everyday music listening (e.g., Juslin et al., 2011). Our study did not focus on individual differences, but future studies could include personality as a variable of interest because there are studies suggesting that motives for listening and emotional responses to music may be affected by personality factors (e.g., Chamorro-Premuzic & Furnham, 2007; Juslin et al., 2011; Rawlings & Leow, 2008). Finally, our sample included athletes from a wide array of sports, but the number of athletes within each sport was rather small which prohibited the comparison of listening strategies between different sports. However, the different requirements and challenges of different types of sports render the question of between-sports differences in uses of music an interesting topic for future research.

Footnotes

Notes

Biographies

Petri Laukka is an associate professor of psychology at Stockholm University. His main research interests revolve around emotion science (especially nonverbal communication of affect) and music psychology; and draw on methods from social and cognitive psychology as well as social neuroscience.

Lina Quick holds a master’s degree in education from Stockholm University, specializing in physical education and psychology. She is a former track and field, and bobsleigh, elite athlete and currently teaches physical education at an upper secondary school in Hudiksvall, Sweden.

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