Listening to Preferred Music Improved Running Performance without Changing the Pacing Pattern during a 6 Minute Run Test

veral studies have investigated the e ects of music on both submaximal and maximal exercise performance at a constant work-rate. However, there is a lack of research that has examined the e ects of music on the pacing strategy during self-paced exercise. The aim of this study was to examine the e ects of preferred music on performance and pacing during a 6 min run test (6-MSPRT) in young male adults. Twenty healthy male participants volunteered for this study. They performed two randomly assigned trials (with or without music) of a 6-MSPRT three days apart. Mean running speed, the adopted pacing strategy, total distance covered (TDC), peak and mean heart rate (HRpeak, HRmean), blood lactate (3 min after the test), and rate of perceived exertion (RPE) were measured. Listening to preferred music during the 6-MSPRT resulted in signi cant TDC improvement (D10%; p=0.016;e ect size (ES)=0.80). A signi cantly faster mean running speed was observed when

running speed, the adopted pacing strategy, total distance covered (TDC), peak and mean heart rate (HRpeak, HRmean), blood lactate (3 min after the test), and rate of perceived exertion (RPE) were measured. Listening to preferred music during the 6-MSPRT resulted in signi cant TDC improvement (D10%; p=0.016;e ect size (ES)=0.80). A signi cantly faster mean running speed was observed when listening to music compared with no music. The improvement of TDC in the present study is explained by a signi cant overall increase in speed (main e ect for conditions) during the music trial. Music failed to modify pacing patterns as suggested by the similar reversed “J-shaped” pro le during the two conditions. Blood-lactate concentrations were signi cantly reduced by 9% (p=0.006, ES=1.09) after the 6-MSPRT with music compared to those in the control condition. No statistically signi cant di erences were found between the test conditions for HRpeak, HRmean, and RPE. Therefore, listening to preferred music can have positive e ects on exercise performance during the 6-MSPRT, such as greater TDC, faster running speeds, and reduced blood lactate levels but has no e ect on the pacing strategy. Keywords:RPE; work-rate distribution; blood lactate; aerobic exercise 1. Introduction Pacing refers to the pattern in which athletes distribute work and energy throughout an exercise task [1]. It is well-documented that pacing strategies [1–3] and the choice of the appropriate pacing Sports2020,8, 61; doi:10.3390 /sports8050061 /journal/sports

Sports2020,8, 61 2 of 10 strategy have an impact on performance. Success in short-duration performances [4] and in middle- and long-distance running events can be in uenced by the pacing strategy [5]. Coaches and researchers have described a variety of pacing strategies such as the negative, all-out, positive, even, parabolic-shaped (U, J, reverse J), and variable pacing strategies [1]. Previous studies showed that exercise performance and pacing strategies depend on speci c factors such as knowledge of the endpoint [6], performance level, competitors [7], and music [8,9]. Many studies have shown the bene cial e ects of music on sport-speci c performance, particularly during aerobic events [9–11]. The use of music as an ergogenic aid may enhance performance by in uencing exercise intensity (i.e., running speed and heart rate) and rating of perceived e ort (RPE) [9,11,12]. In addition, Karageorghis et al. [12] reported that the careful application of music can lead to a number of bene ts that include lower perceived exertion (RPE), greater energy e ciency, and faster time trial performances. Maddigan et al. [9] reported music-induced increases in running duration, breathing frequency, and respiratory exchange ratio, a decrease in RPE, as well as a faster heart rate recovery compared to the control condition. They rationalized that music provided a divergent stimulus that modi ed central nervous system control of volitional fatigue. Furthermore, Bigliassi et al. [13] postulated that selected music characteristics such as rhythm, familiarity, and music selection have the potential to in uence exercise performance. Cole and Maeda [14] found that listening to preferred instead of non-preferred music had a greater positive e ect on the 12 min Cooper test in young healthy females but not in males. RPE as a marker of subjective perception of e ort during exercise is thought to be part of a regulatory motor program that incorporates a number of physiological parameters and psychological and a ective components [15]. Accordingly, Edworthy and Warring [11] reported that listening to fast music during exercise may lower RPE by directing attention away from physical fatigue toward music, which seems to allow athletes to sustain

e ort during exercise is thought to be part of a regulatory motor program that incorporates a number of physiological parameters and psychological and a ective components [15]. Accordingly, Edworthy and Warring [11] reported that listening to fast music during exercise may lower RPE by directing attention away from physical fatigue toward music, which seems to allow athletes to sustain higher exercise intensity. Lima-Silva et al. [16] suggested that the manipulation of external cues, such as music, is able to modify RPE during exercise and consequently it may in uence the adopted pacing strategy and performance level. Numerous studies have examined the e ects of music on RPE and cardiorespiratory variables such as heart rate, arterial pressure, and oxygen uptake [3,8,17]. However, there is a paucity of studies that have examined the e ects of music and its relationship with particularly anaerobic metabolism such as blood lactate concentration [9,18]. Maddigan et al. [9] reported a near-signi cant increase (p=0.08) in the blood lactate concentration (12.5%) with the music and running conditions. They suggested that music contributes to greater intensity of e ort in relationship with the increase of psycho-physiological parameters. In this context, Borg [17] reported that heart rate and blood lactate together could predict RPE more precisely than either variable taken alone. The choice of the type and intensity of exercise are other factors that may in uence the e ects of music on tness performance. Van Dyck and Leman [19] suggested that the ergogenic e ect of music declines with increasing intensity levels. They stated that “at high-intensity levels, physiological cues seem to dominate the exerciser's processing capacity, while at more moderate levels; both musical and physiological cues can be processed in parallel.” Indeed, Elliott et al. [20] reported that music could have a positive e ect especially during low-to-moderate intensity exercise (i.e., below the anaerobic threshold). Although numerous studies have examined the e ects of music by using low-to-moderate exercise at constant work load and high-intensity exercise [11,21], little is known on the distribution of self-selected work rate during self-paced exercise [8,16]. Listening to music can increase

reported that music could have a positive e ect especially during low-to-moderate intensity exercise (i.e., below the anaerobic threshold). Although numerous studies have examined the e ects of music by using low-to-moderate exercise at constant work load and high-intensity exercise [11,21], little is known on the distribution of self-selected work rate during self-paced exercise [8,16]. Listening to music can increase the distance covered during a 15 min self-paced maximal run on a treadmill [10] and improve cycling speed during the rst 3 km of a 10 km cycling time trial [8]. Most studies that examined the e ects of music on pacing have used externally imposed music [8,16], but a few studies have examined the e ects of listening to preferred music. Moreover, the majority of studies have used cycling and running on a treadmill to examine the e ect of music on performance [8,16,21,22]. However, to our knowledge, there are no studies that evaluated the e ects of preferred music on both pacing strategy and physical performance during outdoor self-paced running tests.

Sports2020,8, 61 3 of 10 Therefore, the aim of this study was to examine the e ects of listening to preferred music on various performance (i.e., total distance covered (TDC), running speed, pacing) and physiological measures (i.e., blood lactate concentration, heart rate) in young healthy male adults. With reference to Barwood [10] and Atkinson et al. [8], we hypothesized that listening to preferred music improves TDC, running speed, and pacing with concomitant changes in physiological parameters (e.g., blood lactate). 2. Materials and Methods 2.1. Subjects Based on a medium-sized e ect of listening to music on exercise performance reported by Maddigan et al. [9], an a priori power analysis was calculated withG*Power (Version 3.1.9.2, University of Kiel, Kiel, Germany) using the f test family (repeated measures, within factors) and 2 experimental conditions (music versus control). The analysis revealed that a total sample size ofN=19 would be su cient to nd signi cant and medium-sized e ects of condition (e ect sizef=0.6, =0.05) with an actual power of 0.80. Thus, 20 healthy male physical education students aged 22 1.3 years (body mass: 75.1 7.7 kg; body height: 1.8 0.3 m; body mass index [BMI]: 23.2 1.4 kg m 1 , estimated VO2 max: 50.4 3.4 mL min 1 kg 1 ) volunteered to participate in this study. Study participants were active in various sports such as combat sports, basketball, football, and athletics. On average, participants were physically active 16 h wk 1 . Participants regularly participated in physical education classes including ball games, swimming, athletics, gymnastics, combat sports, music, and dance. None of the subjects reported any current or ongoing neuromuscular diseases or musculoskeletal injuries speci c to the ankle, knee, or hip joints. They were asked not to take any dietary or performance supplements that may have a ected their performance during testing. Participants performed tests at the same time of day with two experimental conditions in a counterbalanced order separated by at least 72 h. Participants were asked to maintain similar diets 24 h before each trial, which was established from the food diary. Participants were then asked to

dietary or performance supplements that may have a ected their performance during testing. Participants performed tests at the same time of day with two experimental conditions in a counterbalanced order separated by at least 72 h. Participants were asked to maintain similar diets 24 h before each trial, which was established from the food diary. Participants were then asked to avoid ca einated products and alcohol 24 h prior to each session and to avoid physical activity 48 h before each session. Written informed consent was obtained from all participants after verbal and written explanation of the experimental design and potential risks of the study. The present study was conducted according to the latest version of the Declaration of Helsinki and the protocol was fully approved by the local Ethics Committee of our university (UR13JS01) before the commencement of the tests. All participants were fully familiarized with the applied procedures. They could withdraw from the study at any time of the experiment without providing reason. 2.2. Procedures Participants were required to participate in three test sessions. All tests were completed within a two-week period and each test was separated by at least 72 h. Before the tests started, subjects completed a standard 15 min period of warm-up, including 3–5 min of light jogging, lateral displacements, dynamic stretching, and jumping. During the rst session, all subjects performed the Vameval test to assess their maximal aerobic speed (MAS) and estimate VO2max (maximal aerobic capacity). During the two last sessions, subjects performed in a random order, a 6 min self-paced run test under two di erent conditions: listening to preferred music during the test or without music (WM). For each test trial, participants had to run for 6 min as fast as they could to cover the longest possible distance. The participants were asked to select their preferred music, for when they participate in aerobic exercise. For the music condition, all preferred tracks were played using the same device with the same mp3 player, keeping the same moderate volume for all participants (around 50% of maximum). 2.3. Preferred Music The music played for

could to cover the longest possible distance. The participants were asked to select their preferred music, for when they participate in aerobic exercise. For the music condition, all preferred tracks were played using the same device with the same mp3 player, keeping the same moderate volume for all participants (around 50% of maximum). 2.3. Preferred Music The music played for each participant was self-selected. Indeed, the participants were asked to select a minimum of 10 min of music, speci cally those with which they felt more inclined to

Sports2020,8, 61 4 of 10 exercise aerobically. All songs chosen by the participants were characterized by a fast rhythm (120–140 beats min 1 ). One investigator quanti ed the average tempo for each song selected to verify that it was within the required tempo range using “Free BPM Detector” software. Music was played from an mp3 player with headset during the music trial with comfortable and moderate volume intensity. During the no music trial, the mp3 player and headset were used as well, but no music was played. 2.4. Measurements 2.4.1. Vameval Test The Vameval test begins with a running speed of 8.5 km h 1 and increases by 0.5 km h 1 every minute until exhaustion. The participants adjusted their running speed to the auditory signals at 20 m intervals, delineated by marks placed at 20 m intervals along a 400 m athletics track. The test ended when the subject could no longer maintain the required running speed dictated by the audio beep, for two consecutive occasions. The measured heart rate at the end of the test must be similar to the predicted maximal heart rate, which was estimated according to the formula of Tanaka et al. [23]. MAS corresponds to the last-stage speed completed [24]. 2.4.2. 6 Min Self-Paced Run Test The purpose of the 6 min self-paced running test (6-MSPRT) was to cover the longest distance within 6 min [25]. Before the test started, participants performed a standard 10 min warm-up that included walking, running, and dynamic stretching exercises. Thereafter, participants rested for three minutes in an upright position before the 6 min run test started. During the two test trials, participants were asked to cover the longest possible distance on a 400 m outdoor athletics track. As a reference, 20 cones were placed every 20 m on the track to measure the distance covered by each participant every 30 s. Running speed was then calculated for these same intervals. The distribution of work rate during the test was assessed by measuring running speed every 30 s. Total distance covered was also determined (m). Heart rate was

As a reference, 20 cones were placed every 20 m on the track to measure the distance covered by each participant every 30 s. Running speed was then calculated for these same intervals. The distribution of work rate during the test was assessed by measuring running speed every 30 s. Total distance covered was also determined (m). Heart rate was continuously recorded during the two last trials of the test using a heart rate monitor (Polar team 2, New York, NY, USA). Both peak heart rate (HRpeak) and mean heart rate (HRmean) values were observed during the 6-MSPRT. Three minutes after each test trial, blood lactate concentration was measured by using a Lactate Monitor (lactate pro 2, Akray, Japan). RPE was registered with the help of the 6–20 Borg scale (Borg, 1985). 2.5. Statistical Analyses Data were expressed as means and standard deviations (SD). Normality of data was assessed and con rmed using the Kolmogorov–Smirnov test. The paired Student's t-test was used to compare total distance covered over the 6 min run test. In addition, RPE, HRpeak, HRmean, and blood lactate concentrations were recorded at post-tests. A two-way ANOVA (two conditions (music vs. control) 12 times (every 30 s over the 6 min run)) was computed for 30 s running speed intervals. E ect sizes (ESs) were computed to indicate the magnitude of the ndings (Cohen's d). ESs were classi ed according to Hopkins et al. [26] as trivial 0.2, small>0.2–0.6, moderate>0.6–1.2, large>1.2–2.0, and very large>2.0 magnitudes. The level of signi cance was set atp 0.05. All analyses were carried out using SPSS 16 for Windows (SPSS, version 16 for Windows. Inc., Chicago, IL, USA). 3. Results There was a signi cant increase in TDC with music compared with control (1566.55 179.73 m vs. 1422.35 178.76 m;D10%;p=0.016; ES=0.80) during the 6-MSPRT. Figure ects of listening to preferred music vs. control on speed at each 30 s during a 6 min run test. No signi cant condition time interactions were observed (p=0.539; ES=0.010). However, our results showed a signi cant (p=0.012; ES=0.154) main e ect of condition (between the two sessions).

(1566.55 179.73 m vs. 1422.35 178.76 m;D10%;p=0.016; ES=0.80) during the 6-MSPRT. Figure ects of listening to preferred music vs. control on speed at each 30 s during a 6 min run test. No signi cant condition time interactions were observed (p=0.539; ES=0.010). However, our results showed a signi cant (p=0.012; ES=0.154) main e ect of condition (between the two sessions). Pacing strategies

Sports2020,8, 61 5 of 10 were not modi ed by listening to music since participants adopted the same reversed “J-shaped” pro le without signi cant increases in speed at the end of the 6-MSPRT (no end spurt) in the two conditions (Figure).Sports 2020, 8, x FOR PEER REVIEW 5 of 10 were not modified by listening to music since participants adopted the same reversed “J-shaped” profile without significant increases in speed at the end of the 6-MSPRT (no end spurt) in the two conditions (Figure 1). Figure 1. The overall effect of listening to preferred music on speed during the 6 min run test. * Significant main effect of condition (p < 0.05). No significant pre- to post-test 6-MSPRT differences were recorded for HRpeak, HRmean, and RPE during the two trials (Table 1). However, a significant decline in blood lactate concentration was observed with music compared to the control condition (Δ9%, p = 0.006, ES = 1.09). There were no significant HR differences between the two conditions during the (6-MSPRT). Table 1. The effects of listening to preferred music vs. control on heart rate, and rating of perceived exertion during and after the 6 min run test. Control Music p value ES HRpeak (beat/min) 191.3 ± 8.2 190.4 ± 8.5 0.619 - HRmean (beat/min) 178.7 ± 9.5 179.1 ± 7.1 0.791 - RPE post-test 16.9 ± 1.3 17.3 ± 1.5 0.379 - Lactate (mmol/L) 17.3 ± 1.4 15.9 ± 1.3 0.006 * 1.09 Data were expressed as means ± standard deviations; ES: effect size, RPE post-test: Rating of perceived exertion after the test, HR: heart rate; * Significant difference between music and control conditions (p < 0.01). 4. Discussion The purpose of this study was to examine the influence of listening to preferred music during a 6 min self-paced run test on speed distribution (pacing), blood lactate, HRpeak, HRmean, and RPE. The main findings of this investigation were that preferred music, compared to no music, improved TDC with an increase in running speed throughout the 6-MSPRT. A significant decrease in blood lactate at 3 min after the end of the

Preferred music improved running performance without altering pacing strategy.