Effects of Self-Selected Motivational Music During Warm-Up on Time- of-Day Variations in Anaerobic Performance Among Female Handball Players

Effects of Self-Selected Motivational Music During Warm-Up on Time- of-Day Variations in Anaerobic Performance Among Female Handball Players | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Effects of Self-Selected Motivational Music During Warm-Up on Time- of-Day Variations in Anaerobic Performance Among Female Handball Players Houda Bougrine, Imed Gandouzi, Ismail Dergaa, Julien Maitre, Abdulwahed Ahmed Alaizari, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6617578/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract This study examined how self-selected music during warm-up influences time-of-day (TOD) effects on short-term maximal performance in female handball players. Eighteen female athletes (age: 16.16 ± 0.38 years, height: 1.67 ± 0.9 m, BMI: 20.28 ± 3.2 kg/m²) completed eight randomized sessions under two warm up conditions: with (Yes-MUS) or without (No-MUS) listening to self-selected motivational music, at four distinct times of day (08:00, 11:00, 15:00, and 18:00). A minimum recovery period of 48 hours was provided between sessions. During each session, oral temperature (OT), countermovement jump (CMJ), medicine ball throw (MBT), 20-meter sprint (20m-ST), and Illinois agility test (IAT) were recorded. The findings indicated that OT and all physical performances improved from 08 :00h to 18:00h (all p < 0.001). The amplitude of diurnal variation was attenuated in the Yes-MUS condition for CMJ (5.7% vs. 2.3%), MBT (13% vs. 6.6%), 20m-ST (5.9% vs. 3.3%), and IAT (7.1% vs. 4.7%) compared to No-MUS. Likewise, OT variation remained unchanged across conditions (both 3.2%). Compared to No-MUS condition, performance improvements under the Yes-MUS were significant at all times : 08:00 (all p < 0.001), 11:00 (CMJ, MBT: p < 0.01; 20m-ST, IAT: p < 0.001), 15:00 (CMJ : p < 0.01, MBT : p < 0.05, 20m-ST : p < 0.001, IAT : p < 0.001), and 18:00 (CMJ : p < 0.05, MBT : ns, 20m-ST : p < 0.05, IAT : p < 0.01). These findings suggest that self-selected motivational music during warm-up blunts diurnal performance variations and enhances anaerobic capacity in female athletes, particularly during suboptimal morning hours. Listening to music during warm-up may be an effective strategy to counteract diurnal declines in performance and optimize training outcomes among female athletes. Biological sciences/Physiology Biological sciences/Psychology Health sciences/Health care Adolescent Athletics Chronobiology Circadian Rhythms Exercise Performance Motor Skills Psychometrics Psychophysiology Team Sports Figures Figure 1 Introduction Circadian rhythms, endogenous biological oscillations regulated by the central biological clock, regulate numerous physiological processes 1 . These rhythms are modulated by external, psychobiological, internal, and chronobiological factors 2 – 4 , influencing body temperature 5 , 6 , and hormonal regulation (e.g., cortisol, melatonin) 7 . Such fluctuations extend to skeletal muscle, altering molecular clock mechanisms 8 . These variations have been shown to influence maximal strength output 9 – 11 and the ability to perform repeated sprints 12 , thereby contributing to time-of-day-dependent variations in neuromuscular performance 13 . Indeed, athletic performance whether endurance or strength-based fluctuate with the TOD 14 – 18 . Maximal short-duration efforts, heavily reliant on anaerobic metabolism, demonstrate pronounced performance differences between morning and evening 15 , 19 – 22 , with peak performance typically occurring in the late afternoon or early evening (16:00–20:00) 23 – 25 compared to morning performance (06:00–10:00) 18 , 23 – 25 . These fluctuations are primarily driven by peripheral (muscular) rather than neural adaptations 26 . While factors such as such as active warm-up, fasting, controlled environmental conditions, and consistent morning training can mitigate these diurnal variations 18 , research on female athletes remains limited, particularly in team-sport contexts 27 , 28 . Thus, optimizing training and competition timing is especially relevant for female athletes. In parallel, music has emerged as a potential modulator of athletic performance. Listening to music during exercise has been shown to reduce perceived exertion, improve motivation and arousal, and support better motor coordination 29 . Music acts as a cognitive distractor 30 , 31 , helping to reduce effort perception, while also stimulating neural activity 32 , 33 , improving running economy and overall physical output 34 , 35 . Its ergogenic effects span endurance exercise 36 , sprint performance 37 , and resistance training 38 – 40 . Music has also been reported to influence mental states, helping athletes to energize, relax, or increase confidence and self-esteem 36 , 38 , 40 . Importantly, music may also attenuate time-of-day-related performance declines, particularly during suboptimal morning periods 41 – 43 . While some studies report enhanced power output during anaerobic tasks when music is used during warm-up 41 , 44 , others report inconsistent results 32 , 45 . These discrepancies may be attributed to differences in exercise type, individual music preferences, or psychological factors such as self-confidence and arousal 18 , 46 . For instance, results on anaerobic threshold performance show, for example, that there is no increase in the threshold, although performance is improved in women 47 , whereas its impact on supramaximal efforts remains contested 45 , 48 . The impact of rhythm and tempo on physical performance remains an area of uncertainty, with mixed findings in the literature 49 . Thus, while music clearly interacts with multiple physiological and psychological domains, the precise mechanisms remain insufficiently understood, justifying continued investigation 50 , 51 . Taken together, the existing literature confirms that TOD significantly influences short-term maximal performance, and that music offers promising benefits. However, studies integrating both variables remain scarce, especially among female populations. To the best of the authors’ knowledge, no study has yet examined the combined effects of TOD and self-selected motivational music during warm-up on short-term anaerobic performance in female athletes. This study therefore aims to evaluate the effects of self-selected motivational music during warm-up at four TODs (08:00, 11:00, 15:00, and 18:00) on short-term maximal performance in female athletes. The study specifically investigates whether motivational music can attenuate the typical diurnal decline in performance, particularly in the morning, and offers practical insights into how female athletes can use chronobiological and psychological strategies to optimize physical performance throughout the day. We hypothesize that music will blunt diurnal performance fluctuations, with the most pronounced effects during morning sessions. Methods Participants The study protocol adhered to the principles outlined in the Declaration of Helsinki regarding human experimentation and the ethical guidelines and procedural standards for Human Chronobiology research 52 . The study protocol adhered to the ethical principles of the Declaration of Helsinki for research involving human subjects and received approval from the local research ethics committee of the High Institute of Sport and Physical Education of El Kef, University of Jendouba, Jendouba, Tunisia, under the reference (ISSEPK-0033/2024). It also complied with the ethical and procedural requirements for the conduct of sports medicine and exercise science research 53 . Written informed consent was secured from parents/guardians of minor participants, with additional verbal assent from the athletes following a detailed explanation of the study's objectives, methodology, potential risks, and benefits. The sample size estimation for the study was performed using G*Power software 54 , following the recommendations of Beck 55 . An alpha level of 0.05 and a target statistical power of 0.80 were chosen. The anticipated effect size, set at 0.3, was based on a prior similar study 56 and the consensus among the authors. The calculations indicated that a minimum of 16 athletes was necessary to reduce the likelihood of a Type II error. To minimize the impact of potential dropouts, 37 subjects were initially assessed, of which 26 met the inclusion criteria. However, two participants later withdrew, and six athletes were excluded due their menstural cycles, resulting in a final study sample of 18 athletes. The sample consisted of 18 female handball players (age: 16.16 ± 0.38 years, height: 1.67 ± 0.9 m, weight: 57.68 ± 13.1 kg, BMI: 20.28 ± 3.2 kg/m²) from the same regional team, each with over three years of experience in handball (4.66 ± 0.48 years). On average, these athletes participated in 3.77 ± 0.42 training sessions per week. To qualify for participation in the study, female athletes were required to meet several inclusion criteria. These included being aged between 16 and 18 years, having a minimum of three years of prior handball training experience, and regularly attending at least two training sessions per week. Additionally, participants were expected to have no history of menstrual irregularities within the past six months, and to be free from injury within the preceding four months. Further, they must not have been using hormonal contraceptives such as pills, patches, injections, implants, or intrauterine devices within the past six months. Exclusion criteria were rigorously applied to ensure the integrity of the study. Athletes were excluded if they had any medical condition or illness that could impair test performance or if they were under medication for a chronic medical issue. Other exclusions included, the use of medications (such as stimulants, narcotics, or psychotropic drugs), dietary supplements, or restrictive diets potentially affecting hormonal balance within the last three months. Athletes with sleep disorders characterized by Pittsburgh Sleep Quality Index (PSQI) scores exceeding 5, those consuming alcohol or tobacco, or those displaying extreme morning or evening chronotypes were also omitted. Athletes who had any diseases and abnormalities of the ear or hearing were exclude from the study. All participants menstrual cycle lengths (28,16 ± 1,65 days) and phases were assessed using the My calendar® Period Tracker 57 . In order to further mitigate the impact of menstrual cyle phases and in line with outlined studies 58,59 , the experimental sessions were performed throughout only follicular and luteal phases. Experimental procedure To comprehensively examine the effects of self-selected motivational music and TOD on anaerobic athletic performance among female athletes, 18 female handball athletes participated in this research. The testing occurred over eight separate sessions, spaced at least 48 hours apart, to reduce the risk of fatigue-related carryover effects. These sessions were randomized across four different times of day (08 :00h, 11:00h, 15:00h, and 18:00h) and carried out under two distinct conditions either with motivational music integrated during the warm-up (Yes-MUS) or without it (No-MUS). A recovery period of at least 48h was taken between sessions. Prior to the main experiment, two familiarization sessions were conducted to minimize learning effects and to ensure accurate data collection (Fig. 1). These sessions were evenly distributed between the two extreme times of day, aligning approximately with the circadian rhythm peaks and troughs of short-term performance and oral temperature 60,61 . The intermediate times (11:00h, 15:00h) were incorporated to ensure evenly spaced intervals throughout the study 62 . Each session followed a strict protocol, beginning with oral temperature measurements to account for physiological and circadian states. Participants then completed a 10-minute low-intensity warm-up. Two minutes after the testing lineup included a counter mouvement jump test (CMJ), a medecine ball throw test (MDBT), 20-meter sprint test (20m-ST), and the Illinois agility test (IAT). A 5-minute recovery period was provided between tests to mitigate fatigue. The study was conducted from January to March 2024 at the athletes' standard indoor training court under consistent environmental conditions, with an average temperature of 22°C and approximately 47% relative humidity. Athletes meeting the inclusion criteria provided informed parental consent and adhered to strict guidelines. They avoided energy drinks, anti-inflammatory, and antioxidant substances during the study period, followed regular training schedules while avoiding intense exercise, and maintained consistent dietary habits. Prior to morning sessions, body mass was recorded using a Tanita electronic scale (Tokyo, Japan). Regarding the warm-up protocol, athletes completed two different warm-up protocols. The routine started with 3 minutes of jogging at a moderate speed (8–10 km/h), followed by 3 minutes of dynamic stretches targeting the main muscle groups. This was succeeded by a 2-minute session of sprinting drills, such as ankling, high knees, back kicks, and skipping, and another 2 minutes of sprinting. Participants then engaged in a 10-minute warm-up, either in silence (No-MUS) or while listening to their favorite motivational music (Yes-MUS). After each warm-up session, a 2-minute rest break was provided. Regarding Music Protocol, participants selected their preferred music based on established guidelines from prior studies on music preference and exercise performance before the familiarization and testing phases 63–66 . During the familiarization phase, each participant choosen their favorite track, which were labeled for use during experimental sessions. The selected music was self-chosen and rated for motivational qualities using the Brunel Music Rating Inventory-2 67 . To maximize stimulation, tracks had a minimum tempo of 120 beats per minute (bpm) 68 , with an average tempo of 136.5 ± 12.78 bpm. During testing, participants listened to their chosen playlists through headphones connected to their personal mobile devices, with the volume standardized at 80 dB using the Decibel sound level meter app. For No-Music (NoM) conditions, participants wore headphones with no music to ensure consistent testing conditions across sessions. For music conditions, tracks played continuously throughout the warm-up, with looping enabled for shorter songs to cover the full 10-minute duration. Circadian typology and sleep quality questionnaires Circadian typology was determined through the Horne and Östberg self-assessment questionnaire, which evaluates sleep and activity patterns on a 19-item scale 69 . To further mitigate the influence of circadian typology, only participants identified with an intermediate chronotype were included in this study and extreme chronotypes (morning or evening) were excluded. Eligible participants scored between 42 and 58 (49,5 ± 4,56), indicating an intermediate chronotype. Moreover to assess the sleep quality, all athletes demonstrated normal sleep patterns, averaging 7.22 ± 0.54 hours of nightly sleep, and achieved an average PSQI score of 2.08 ± 0.83 in the month preceding the experimental procedures, based on the validated Arabic version of the PSQI 70 . 2.1. Oral temperature (OT) The resting oral temperatures were taken with a calibrated digital clinical thermometer (Omron, Paris, France; accuracy ± 0.05°C) inserted sublingually for at least 3 min after a 10-min period of resting while seated. 2.2. The 2 kg Medicine Ball Throw Test (MDBT) Medicine ball throw is the most widely known and indirect test used to evaluate the power of the upper limbs in team sports 71,72 . The players throw the medicine ball as vigorously, far and straight forward as they can, while keeping their back flush against the wall, and their elbows in towards their sides during the push maneuver. Three maximal throws for distance were performed using a measuring tape and measurements were recorded in meters from the wall to where the medicine ball landed 73 . The best throw was retained for our anlaysis. With a recovery period of ten seconds between three repetiotions the best performance was retained for our statistical analysis. 2.3. 20 m Sprint performance (20m-ST) The 20-m sprint test was administered as a test of acceleration and sprint ability. Linear speed was measured by a 20m sprint with timing gates (Witty, Microgate®, Bolzano, Italy) setup at 0, 5 and 20m to measure the 0–5 m and 0–20 m intervals. Timing gates were placed at the approximate hip height for all players as previously recommended 74 . Players were instructed to initiate the sprint when ready and cover the set distance as fast as possible. The subjects completed three trials of sprint, with a minimum of 3-min rest between each trial. The best performance from each of the 3 trials was used for analysis. 2.4. Illinois Agility test (IAT) The Illinois Agility Test incorporates acceleration, deceleration, change of direction, and sprinting. The change of direction Illinois Agility Test was reported to have high reliability and validity for team sports 75,76 . The length of the course is 10m and the width is 5m where four cones are used to mark the start, finish, and the two turning points. Four more cones are placed down the center an equal distance apart (spaced 3.3m apart). The duration of their performance was quantified using timing gates (Witty, Microgate®, Bolzano, Italy) positioned at the beginning and end points, and the superior outcome from the two trials was documented. Players were given instructions to maximize their running speed while following the designated course in the specified direction to reach the endpoint. 3. Statistical analysis STATISTICA software (StatSoft, France) was used to evaluate the data that were collected for this investigation. The means ± SD (standard deviation) values were calculated for each variable. A normal distribution of all the data was verified by the Shapiro-Wilk test. To examine the impact of TOD, a two-way repeated measures ANOVA (2 Music and 4 TOD) was used. Tukey's HSD (Honestly Significant Difference) Post hoc test was used to assess for significant differences between means when appropriate. The effect size statistic (ηp2) was used to determine the magnitude of the difference between age-groups. The criteria as follows were applied, according to 77 , to determine the effect sizes: a minor effect size was 0.01, a moderate effect size was 0.06, and a large effect size was 0.14. The study used Cohen's d analysis, a standardized effect size, to analyze the magnitude of differences between variables. The variables were categorized as follows by 78 : trivial (d ≤ 0.20), small (0.20 < d ≤ 0.60), moderate (0.60 < d ≤ 1.20), large (1.20 < d ≤ 2.0), very large (2.0 4.0). A significant level was considered as a p ≤ 0.05. Results Oral temperature Two-way Anova revealed a moderate significant main effect for TOD [F (3,51) = 35.2, p < 0.001, ηp² = 0.67], However, there were no significant effects observed for MUS [F (1,17) = 1.7, p = 0.2, ηp² = 0.09] or for the interaction between MUS and TOD [F (3,51) = 0.2, p = 0.91, ηp² = 0.009]. Bonferroni test indicated that core temperature was considerably higher at 18:00h compared to 8:00 h across No-MUS and Yes-MUS (both p < 0.001). The morning-to-afternoon differences in core temperature showed amplitudes of 3.2% under both testing conditions (No-MUS and Yes-MUS) (Table 1 ). Table 1 Values (mean ± SD) of Oral temperature, Countermouvement jump (CMJ), Medecine ball throw Test (MSBT), 20 m sprint test (20m-ST), and Illinois Agility test (IAT) scores registered during the four times of the day (8:00 h, 11:00h, 15:00h, and 18:00h.) across two testing conditions: with listening to music (Yes-MUS), and without listening to music (No-MUS) during warming-up. TOD 8:00h 11:00h 15:00h 18:00h Oral temperature (°C) No-MUS 35.66 ± 0.67 bbb, ccc 36.08 ± 0.12 aaa, ccc 36.57 ± 0.18 aaa, bbb 36.81 ± 0.13 aaa, bbb, ccc Yes-MUS 35.63 ± 0.72 bbb, ccc 36.05 ± 0.14 aaa, ccc 36.56 ± 0.19 aaa, bbb 36.78 ± 0.12 aaa, bbb , ccc CMJ (cm) No-MUS 21.86 ± 1.94 22.77 ± 1.75 22.19 ± 1.65 22.88 ± 1.70 aaa , bb , c Yes-MUS 22.31 ± 1.69 *** 22.97 ± 1.79 ** 22.89 ± 1.74 ** 23.45 ± 1.66 aa , b , * MDBT (m) No-MUS 3.81 ± 0.88 bb , ccc 4.06 ± 0.75 a 4.11 ± 0.70 aa 4.3 ± 0.72 aaa , b Yes-MUS 4.14 ± 0.73 *** 4.32 ± 0.73 ** 4.36 ± 0.72 * 4.42 ± 0.81 aa (20m-ST) (s) No-MUS 5.27 ± 0.31 bbb, ccc 5.12 ± 0.23 aaa , 5.08 ± 0.25 aaa 4.96 ± 0.21 aaa, bbb, ccc Yes-MUS 5.03 ± 0.43 cc , *** 4.96 ± 0.33 *** 4.91 ± 0.32 aa , *** 4.86 ± 0.19 aaa, b , * IAT (s) No-MUS 19.21 ± 0.50 ccc 18.47 ± 0.57 ccc 19.06 ± 0.57 aaa, bbb , 18.37 ± 0.64 aaa, bbb, ccc Yes-MUS 18.70 ± 0.41 ccc , *** 18.11 ± 0.62 cc , *** 17.84 ± 0.46 aaa, bb , *** 17.61 ± 0.51 aaa, bbb,, ccc , ** a (p < 0.05), aa (p < 0.01), aaa (p < 0.001): Significant difference compared to 8:00h (in the same condition); b (p < 0.05), bb (p < 0.01), bbb (p < 0.001): Significant difference compared to 11:00h (in the same condition); c (p < 0.05), cc (p < 0.01), ccc (p < 0.001): Significant difference compared to 15:00h (in the same condition) ; *:(p < 0.001), **(p < 0.05) : Significant difference compared to without music condition (at the same TOD). CMJ Test A moderate significant effect of MUS [F (1,17) = 70.58, p < 0.001, ηp² = 0.80] was observed, along with a small significant effect of TOD [F (3,51) = 13.85, p < 0.001, ηp² = 0.44] on CMJ height. No significant effects were observed on the interaction of MUS and TOD [F (3,51) = 0.92, p = 0.43, ηp² = 0.05]. Post hoc analysis revealed an improvement on CMJ performance from 08:00h to 18:00h (p < 0.001, 5.7%) under No-MUS condition. The morning-afternoon performance differences were blunted under Yes-MUS condition (p < 0.001, 2.3%) (Table 1 ). Regarding Music effects, CMJ performance increased significantly during 08:00h (p < 0.001, 4.2%), 11:00h (p < 0.01, 3.1%), 15:00h. (p < 0.01, 3%) and 18:00h. (p < 0.05, 2.4%) compared to No-MUS condition (Table 1 ). 2.2. The 2 kg Medicine Ball Throw Test Statistical analysis of MDBT performance indicated a moderate significant effect for MUS [F (1,17) = 36.31, p < 0.001, ηp² = 0.68], along with a small significant effect of TOD [F (3,51) = 19.97, p < 0.001, ηp² = 0.54]. Likewise, no significant effects were revealed for the interation of MUS and TOD [F (3,51) = 1.77, p = 0.16, ηp² = 0.09]. MDBT performance was observed to improve in the afternoon compared to the morning (p < 0.001, 13%) under No-MUS condition. However, this daily diurnal variation was blunted under Yes-MUS condition (p < 0.001, 6.6%). Regarding Music effects, a significant improvement in MDBT performance were observed during 08:00h (p < 0.001, 8.9%), 11:00h (p < 0.01, 6.4%), 15:00h. (p < 0.05, 5.9%) compared to No-MUS condition (Table 1 ). 2.2. 20m Sprint performance The results of the two-way ANOVA showed a moderate significant main effect of MUS [F (1,17) = 69.50, p < 0.001, ηp² = 0.80] on 20m ST. A small significant main effect of TOD [F (3,51) = 9.01, p < 0.001, ηp² = 0.34], as well as the interaction of MUS and TOD [F (3,51) = 4.56, p < 0.01, ηp² = 0.21] were revealed. According to the post hoc test, 20m ST were greater in the afternoon compared to the morning for conditions (p < 0.001, − 5.9%) during No-MUS condition. Further investigations showed that these daily morning to afternoon variation were diminished during Yes-MUS condition (p < 0.001, − 3.3%), as presented in Table 1 . Regarding the impact of Music, 20m ST time significantly decreased during 08:00h (p < 0.001, − 4.8%), 11:00h (p < 0.001, − 3.3%), 15:00h. (p < 0.001, − 3.7%), and 18:00h (p < 0.05, − 1.9%) compared to No-MUS condition (Table 1 ). 2.2. Illinois Agility test (IAT) A moderate significant effect on IAT were observed for both MUS [F (1,17) = 62.63, p < 0.001, ηp² = 0.78] and TOD [F (3,51) = 82.47, p < 0.001, ηp² = 0.82] on agility performance. Additionally, a small significant effect on interaction between MUS and TOD [F (3,51) = 15.04, p < 0.001, ηp² = 0.46] was recorded. Post hoc analysis revealed that IAT performance were lower in the morning compared to the afternoon (p < 0.001, − 7.1%) under No-MUS condition. Interestingly, these morning-afternoon differences were blunted under Yes-MUS condition (p < 0.001, − 4.7%) (Table 1 ). Compared to No-MUS condition, IAT time significantly decreased during 08:00h (p < 0.001, − 3.9%), 11:00h (p < 0.001, − 3.6%), 15:00h. (p < 0.001, − 3.2%), and 18:00h (p < 0.01, − 1.3%) (Table 1 ). Discussion This study aimed to assess the effects of listening to self-selected motivational music during warm-up at various times of day (08:00h, 11:00h, 15:00h, and 18:00h) on several maximal exercise performances among young female handball players. The main findings revealed that (1) high-intensity short-term physical exercises such as CMJ ; MDBT; 20m-ST; and IAT significantly improved throughout the day, peaking in the late afternoon (18:00h); (2) listening to motivational music during warm-up enhanced physical performance across all time points especially during the morning hours; and (3) the amplitude of diurnal variation was attenuated under the music conditiond. These findings provide valuable insights into the interaction between chronobiological rhythms and ergogenic aids such as music in female athletes. Regarding the TOD effects on short term high intensity performances and in line with the current findings, a number of investigations have demonstrated that the peak anaerobic performances were observed in the afternoon between 16:00h and 18:00h 79 – 81 compared to morning among female team sports athletes. In addition, the current outcomes align with a recent meta-analysis 82 that revealed that late afternoon (between 16:00h and 19:30h) is most favorable TOD for short-term maximal physical performance. An afternoon improvement of repeated sprints performance 79 , 83 , 84 , and agility 79 , 84 , was observed on female team ball players. A recent systematic review revealed that singular sprints tended to perform much better in the afternoon than in the morning with 5m and 20m overground running sprint timings decreasing by 10.9% and 10.8% respectively 85 . Mhenni et al. 86 revealed that the handgrip strength, the ball-throwing velocity, the modified T-test, and the repeated sprint performances were better in the evening than in the morning. Performances of total distance and peak distance of 5m shuttle run test, increased at 17h00 compared to 07h00, 09h00, 11h00, 13h00 and 15h00 62 . Consistent with our findings, numerous studies report peak maximal exercise performances occurring in the late afternoon (16:00–18:00h) compared to morning sessions among female team-sport athletes 79 – 81 . This observation is supported by a recent meta-analysis 82 which identified the late afternoon (16:00–19:30) as the most favorable TOD for short-term maximal physical performance. Specifically, enhanced afternoon performance has been consistently reported in repeated sprint ability performance 79 , 83 , 84 and agility 79 , 84 among female team-sport athletes. Likewise, a recent systematic review reported that sprint performances significantly improved in the afternoon compared to the morning, with overground sprint times for 5 m and 20 m decreasing by 10.9% and 10.8%, respectively 85 . Diurnal performance variation is further evidenced by superior evening results in handgrip strength, ball-throwing velocity, and shuttle run performance 62 , 86 , 87 . However, some studies report no significant TOD effects 88 – 90 . potentially due to methodological differences in chronotype inclusion, training schedules, or testing protocols. In our study, we controlled for these factors by exclusively including intermediate chronotypes and standardizing testing procedures. These discrepancies may be partly attributed to individual differences in chronotype, biological clock alignment, and motivation throughout the day. Differences in sleep–wake patterns, the time people typically wake up, and personal circadian preferences can all affect performance and help explain why studies sometimes produce inconsistent results. These findings highlight the importance of considering circadian typology in both research and training contexts 91 . Since optimal performance timing varies between individuals 92 , our study specifically recruited intermediate chronotypes and excluded extreme chronotypes to mitigate these effects. Aligning daily physical activity with an individual's circadian rhythm is essential, as it impacts cognitive and neuromuscular functions such as attention, reaction time, and psychomotor vigilance 93 , 94 . Additionally, external factors such as academic schedules, sex, seasonal daylight exposure 60 , 83 , 95 , age, sport-specific demands, training status, and habitual training times 61 may also influence performance at different TODs. In the current study, all athletes habitually trained in the afternoon (between 17:00 and 19:00), which may have enhanced afternoon performance and partly explains the performance differences between morning and evening sessions. Although the exact mechanism behind the superior performance in the evening is not fully understood, the prevailing hypothesis suggests that factors such as body temperature as well as related physiological, psychological, and metabolic cycles reach their peak levels in the afternoon 96 – 99 . In line with previous research on female team ball athletes 83 , 100 , 101 , our findings also revealed higher oral temperatures at 18:00, which coincide with the expected increase in core temperature observed between 15:00 and 18:00. Recently, Ayala et al. 102 revealed that body temperature follow a circadian rhythm, peaking in the latter afternoon (16:30–18:30 h), when physical performance (i.e., agility, speed, power, and distance covered) reaches its maximum and indicated that this slot is the most appropriate TOD for several aspects of physical activity. Higher afternoon temperatures appear to facilitate key metabolic processes. For example, increased body heat is associated with enhanced muscle glycogenolysis, glycolysis, and the breakdown of high-energy phosphates 103 , as well as quicker action potential conduction 104 . An estimated 0.9% increase in body temperature during the afternoon 97 promotes more efficient glycogen utilization and leads to stronger muscle contractions 96 . Additionally, improvements in muscle function, elevated hormone levels 99 , and faster reaction times 93 all contribute to the better anaerobic performance observed later in the day. By contrast, lower performance during morning sessions (08:00 and 11:00) and in the early afternoon (15:00) may be due to a core temperature that has not yet fully risen from its nocturnal low, thereby impairing both muscle and metabolic functions 97 , 98 , 105 . Moreover, higher and more fluctuating melatonin levels in the morning can contribute to fatigue and reduced attentiveness 106 , while sleep inertia—characterized by reduced alertness and slower reaction times right after waking—further diminishes performance 56 , 83 , 91 , 97 , 101 . Interestingly, the common "post-lunch dip" appears to cause a temporary drop in performance at 15:00, likely because energy is redirected toward digestion, leading to a brief reduction in arousal and cognitive function 107 , 108 . Together, these physiological and cognitive factors contribute to the diurnal variations in performance observed throughout the day. Regarding the music effects on short term high intensity performances, the findings of this study are consistent with previous research, indicating that listening to motivational music during warm-up can help female collegiate athletes boost their power output and total work during repeated sprint exercises 109 . Research has shown that motivational music not only enhances overall performance but also increases the distance achieved during repeated sprints effects that are particularly notable in morning sessions 110 . In addition, even neutral music during warm-up has been demonstrated to improve muscle power throughout the day, which helps counteract the common drop in anaerobic performance seen in the morning 111 . While some studies have found no significant effects of motivational music on short-term, high-intensity performance 112 , other investigations reveal that music-enhanced warm-ups can lead to increased peak power and better performance outcomes in various tests, especially among highly trained athletes and sprinters 44 , 110 , 113 . Moreover, a recent systematic review and meta-analysis suggest that listening to music during the Wingate Anaerobic Test may have a positive physiological impact on relative anaerobic exercise performance, although the exact mechanisms remain to be fully clarified 114 . However, the effect of music appears to be less significant for long-distance runners or highly trained individuals, with its ergogenic impact tending to diminish as overall fitness levels increase 113 , 115 . Since our athletes are young players with only about 4.66 ± 0.48 years of experience in a regional club, this may partly explain the pronounced effectiveness of motivational music within our sample. Variations in study findings could be attributed to differences in participants’ fitness levels, the type of music used, and whether the music was played during exercise or specifically during warm-up periods 110 , 116 . Additionally, recent research suggests that the timing of music exposure is critical when music is integrated with exercise routines, it appears to enhance both emotional well-being and anaerobic performance, particularly when played during workouts 117 . Furthermore, studies have demonstrated that synchronizing the tempo of the music with an individual’s movement patterns not only optimizes energy expenditure but also improves motor efficiency, leading to significant enhancements in kinetic and physiological outcomes 118 . Although some recent meta-analyses suggest that preferred music does not significantly alter mean heart rate or perceived exertion (RPE), thereby questioning its direct influence on exercise performance 119 , other studies highlight the powerful impact of fast-paced, loud music. In particular, such music can enhance performance by diverting athletes’ attention away from feelings of fatigue 120 and by modulating psychomotor arousal acting either as a sedative or a stimulant depending on the specific context and the demands placed on the athlete 121 , 122 . Regarding the combined effects of music and TOD effects on short term high intensity performances, the current findings indicate that listening to music before physical activities can reduce the differences in anaerobic performance observed between morning and evening sessions among handball players. However, because there is limited research examining the interaction between music effects and performance at various times of the day, it remains challenging to directly compare these results with previous studies. To the best of our knowledge, no prior study has assessed these parameters in young female athletes or evaluated performance at more than two distinct time points throughout the day. This highlights the need for further research to explore how music and time of day together influence athletic performance across a broader range of populations and conditions. Our results are consistent with earlier findings that suggest listening to music during warm-up can help minimize diurnal fluctuations in physiological performance, as observed in studies with male athletes 123 . For instance, Belkhir et al. 124 reported that warm-ups accompanied by high-tempo music (120–140 bpm) were more effective at enhancing performance on the 30-second continuous jump test especially in the morning (07:00) compared to the afternoon (17:00)—among semi-professional male soccer players. Other studies have indicated that both total and maximal distance covered during a 5-meter shuttle run test, as well as athletes’ subjective responses, are influenced by the time of day and the type of music used during warm-ups. Specifically, warm-ups featuring self-selected motivational music were found to boost maximal performance and positively affect mood at both 07:00 and 17:00, with stronger effects in the morning, whereas neutral music improved these parameters only in the morning 110 . Similarly, Bentouati et al. 125 demonstrated that warm-ups using self-selected motivational music improved muscle power during the Wingate test and reduced perceived exertion at both time points, showing greater benefits in the morning. These findings suggest that incorporating music during warm-up not only enhances performance across different times of day but also helps reduce the performance gap between morning and afternoon sessions among trained individuals. Moreover, research indicates that a warm-up with motivational music is more beneficial than one with synchronous music for improving short-term maximal performance, regardless of whether it is performed in the morning or afternoon 126 . In addition, Khemila et al. 127 found that including music in warm-ups can improve cognitive function and short-term maximal performance following both normal sleep and partial sleep deprivation among male physical education students. Since lower morning motivation may partly explain the diurnal variation of anaerobic performances, listening to music before exercise could play a critical role in altering this pattern. Music has been shown to boost motivation, reduce discomfort, and enhance perceived effort 110 , 128 , which might explain its heightened effectiveness during the morning compared to other TOD. We hypothesize that music, as an external stimulus, has a more significant impact when maximal physical performance levels are at their lowest, such as during the morning timepoints. During these times, physiological and psychological factors like reduced energy levels, lower body temperature, and diminished alertness combine to create a challenging environment for peak physical performance. Thus, by providing an external boost to motivation and focus, music may counteract these natural performance dips, effectively narrowing the gap between morning and afternoon/evening anaerobic outputs. Further research is warranted to explore this hypothesis and determine the exact mechanisms underlying this interaction. The observed diurnal variation in anaerobic performance may be partially attributable to reduced morning motivation levels. In this context, pre-exercise music exposure appears to modulate this circadian performance pattern through several psychophysiological mechanisms. Empirical evidence demonstrates that music enhances motivational state, reduces perceived exertion, and improves effort perception 110 , 128 , potentially explaining its greater efficacy during morning sessions compared to other time points. We hypothesize that music, as an external stimulus, has a more significant impact when maximal physical performance levels are at their lowest, particularly in morning hours. During these chronobiological troughs, concurrent factors including depressed energy metabolism, reduced core temperature, and diminished CNS arousal collectively impair physical performance capacity. Music may serve as a countermeasure by enhancing psychomotor arousal and attentional focus, thereby attenuating the typical morning-to-evening performance differential in anaerobic output. These findings suggest several important directions for future research to elucidate: to elucidate: (1) the specific neurophysiological mechanisms underlying music-induced performance enhancement, particularly their modulation of motor cortex excitability and autonomic nervous system responses; and (2) the nature of cross-modal interactions between auditory stimulation and circadian regulatory processes, including potential synchronization effects on central pacemaker activity. Study limitations While this study provides novel insights into chronobiological and musical influences on athletic performance, several limitations must be acknowledged. Primarily, the absence of melatonin assays and hematological markers represents a significant constraint, as these biomarkers could have offered more direct evidence of circadian modulation and physiological responses. Furthermore, the exclusive focus on young female handball players constrains extrapolation to other demographic groups, including male athletes, older athletes, or sedentary populations. Additionally, the specific protocols applied in this study may limit the generalizability of the results, necessitating caution when applying these findings to other contexts or sports. The study was also conducted exclusively on young female athletes, which restricts the applicability of the conclusions to other populations, such as adult male athletes or inactive individuals. Future research should aim to replicate these findings across a broader range of athletic disciplines and demographics to better solidify and contextualize the role of self-selected motivational music in enhancing anaerobic performance. Exploring the effects of different music types, tempos, and chronotypes across diverse sports contexts could further deepen our understanding of these variables. Additionally, examining a wider array of physiological and psychological factors under conditions of both rest and fatigue would provide valuable insights. Conclusion The primary findings of the current study indicate that several maximal short-term physical exercises are influenced by the TOD. Specifically, measures such as oral temperature and performance outcomes in the CMJ, MDBT, 20m sprint, and IAT tests showed a gradual improvement throughout the day, peaking in the late afternoon around 18:00h. From a practical viewpoint, adolescent female handball players with an intermediate chronotype are likely to achieve their best short-term maximal physical performance during this time. Nonetheless, there is a support to schedule training sessions and or competitions in the late afternoon, rather than in the morning or early afternoon, as the current study highlights the lower performance levels observed at those times. The findings of this study suggest that incorporating self-selected music during warm-up can be an effective strategy to enhance acute anaerobic performance. This improvement is evident through increased results in the CMJ, MDB, 20m ST, and IAT tests conducted throughout the day at 08:00h, 11:00h, 15:00h, and 18:00h. Notably, the positive effects of music were more pronounced during the morning sessions. Furthermore, music appears to minimize diurnal variations in performance, effectively elevating results during the earlier time points. Ultimately, these insights carry practical relevance, as they suggest that team ball coaches may benefit from encouraging players to listen to their preferred motivational music acting as a motivating stimulant both in the morning and afternoon before engaging in short-term high-intensity activities. In conclusion, music serves as a powerful external stimulant capable of offsetting the diurnal fluctuations in physical performance throughout the day. While its influence appears particularly impactful during mornings or energy-dip periods, individual responses and preferences should guide its application. Further research is essential to refine these recommendations and uncover the precise mechanisms linking music to enhanced physical output. For now, the strategic integration of music in athletic routines can contribute to more improved performances across varying TOD. Declarations Author Contributions: Conceptualization: H.B., T.P., and N.S.; methodology: H.B., T.P., and I.D.; investigation: H.B.,I.G., and I.D.; data curation: H.B.; formal analysis: H.B. and J.M.; writing-original draft: H.B.; writing—review and editing: T.P., N.S., I.G., J.M., A.A.A., O.A., and I.D.; supervision: T.P., H.B., and N.S.; validation: O.A., I.D., and ., A.A.A.; resources: A.A.A. and O.A.; software: J.M.; visualization: I.G.; project administration: I.D., T.P., and N.S.; funding acquisition: A.A.A. and O.A. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Informed Consent Statement: This study complied with the ethical and procedural requirements for conducting sports medicine and exercise science research. As the participants were minors, written informed consent for publication was obtained from their parents or legal guardians before participation. Acknowledgments : We thank all the participants in this study. The authors would like to acknowledge the Researchers Supporting Project (Number RSP2025R342), King Saud University, Riyadh, Saudi Arabia. Conflicts of Interest: The authors declare no conflicts of interest. Data Availability Statement: The raw data supporting the conclusions of this article will be made available by the first author on request. Institutional Review Board Statement: The study protocol adhered to the ethical principles of the Declaration of Helsinki for research involving human subjects and received approval from the local research ethics committee of the High Institute of Sport and Physical Education of El Kef, University of Jendouba, Jednouba, Tunisia (reference (ISSEPK-0033/2024). It also complied with the ethical and procedural requirements for the conduct of sports medicine and exercise science research 129 . Since participants were minors, written informed consent was obtained from their parents or legal guardians before participation, along with verbal assent from the participants. This consent process followed a thorough explanation of the study’s methodology and a discussion of its potential risks and benefits. Declaration: In preparing this paper, the authors used the ChatGPT model 4 on 15 March 2024, to revise some manuscript passages, double-check for grammar mistakes, and improve academic English only. After using this tool, the authors reviewed and edited the content as necessary and took take full responsibility for the publication’s content 130,131 . References Atkinson, G. & Reilly, T. Circadian Variation in Sports Performance. Sports Med. 21 , 292–312 (1996). Douglas, C. M., Hesketh, S. J. & Esser, K. A. Time of Day and Muscle Strength: A Circadian Output? Physiology 36 , 44–51 (2021). Reilly, T. & Waterhouse, J. Sports performance: is there evidence that the body clock plays a role? Eur. J. Appl. Physiol. 106 , 321–332 (2009). Vitale, J. A., Weydahl, A. & Chronotype Physical Activity, and Sport Performance: A Systematic Review. Sports Med. 47 , 1859–1868 (2017). Golombek, D. A. & Rosenstein, R. E. Physiology of circadian entrainment. Physiol. Rev. 90 , 1063–1102 (2010). 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Valdez, P., Reilly, T. & Waterhouse, J. Rhythms of Mental Performance. Mind Brain Educ. 2 , 7–16 (2008). Meglic, C. E., Orman, C. M., Rogers, R. R., Williams, T. D. & Ballmann, C. G. Influence of Warm-Up Music Preference on Anaerobic Exercise Performance in Division I NCAA Female Athletes. JFMK 6, 64 (2021). Belkhir, Y., Rekik, G., Chtourou, H. & Souissi, N. Listening to neutral or self-selected motivational music during warm-up to improve short-term maximal performance in soccer players: Effect of time of day. Physiology Behavior . 204 , 168–173 (2019). Chtourou, H., Chaouachi, A., Hammouda, O., Chamari, K. & Souissi, N. Listening to Music Affects Diurnal Variation in Muscle Power Output. Int. J. Sports Med. 33 , 43–47 (2012). Pujol, T. J. & Langenfeld, M. E. Influence of Music on Wingate Anaerobic Test Performance. Percept. Mot Skills . 88 , 292–296 (1999). Eliakim, M., Meckel, Y., Nemet, D. & Eliakim, A. The Effect of Music during Warm-Up on Consecutive Anaerobic Performance in Elite Adolescent Volleyball Players. Int. J. Sports Med. 28 , 321–325 (2006). Castañeda-Babarro, A. et al. Effect of Listening to Music on Wingate Anaerobic Test Performance. A Systematic Review and Meta-Analysis. IJERPH 17 , 4564 (2020). Terry, P. C., Karageorghis, C. I., Saha, A. M. & D’Auria, S. Effects of synchronous music on treadmill running among elite triathletes. J. Sci. Med. Sport . 15 , 52–57 (2012). Simpson, S. D. & Karageorghis, C. I. The effects of synchronous music on 400-m sprint performance. J. Sports Sci. 24 , 1095–1102 (2006). Lu, L. et al. The difference of affect improvement effect of music intervention in aerobic exercise at different time periods. Front. Physiol. 15 , 1341351 (2024). Terry, P. C., Karageorghis, C. I., Curran, M. L., Martin, O. V. & Parsons-Smith, R. L. Effects of music in exercise and sport: A meta-analytic review. Psychol. Bull. 146 , 91–117 (2020). Herodek, R. T. et al. Effects of preferred music on internal load in adult recreational athletes: a systematic review and meta-analysis. J. Sports Med. Phys. Fit. 10.23736/S0022-4707.24.16178-6 (2025). Hutchinson, J. C. & Karageorghis, C. I. Moderating Influence of Dominant Attentional Style and Exercise Intensity on Responses to Asynchronous Music. J. Sport Exerc. Psychol. 35 , 625–643 (2013). Cotellessa, F. et al. Improvement of Motor Task Performance: Effects of Verbal Encouragement and Music—Key Results from a Randomized Crossover Study with Electromyographic Data. Sports 12 , 210 (2024). Van Dyck, E. Musical Intensity Applied in the Sports and Exercise Domain: An Effective Strategy to Boost Performance? Front. Psychol. 10 , 1145 (2019). Chtourou, H., Chaouachi, A., Hammouda, O., Chamari, K. & Souissi, N. Listening to Music Affects Diurnal Variation in Muscle Power Output. Int. J. Sports Med. 33 , 43–47 (2012). Belkhir, Y., Rekik, G., Chtourou, H. & Souissi, N. Does warming up with different music tempos affect physical and psychological responses? The evidence from a chronobiological study. J Sports Med. Phys. Fitness 62 , (2022). Bentouati, E., Romdhani, M., Khemila, S., Chtourou, H. & Souissi, N. The Effects of Listening to Non-preferred or Self-Selected Music during Short-Term Maximal Exercise at Varied Times of Day. Percept. Mot Skills . 130 , 539–554 (2023). Belkhir, Y., Rekik, G., Chtourou, H. & Souissi, N. Effect of listening to synchronous versus motivational music during warm-up on the diurnal variation of short-term maximal performance and subjective experiences. Chronobiol. Int. 37 , 1611–1620 (2020). Khemila, S. et al. Listening to motivational music during warming-up attenuates the negative effects of partial sleep deprivation on cognitive and short-term maximal performance: Effect of time of day. Chronobiol. Int. 38 , 1052–1063 (2021). Chtourou, H., Jarraya, M., Aloui, A., Hammouda, O. & Souissi, N. The effects of music during warm-up on anaerobic performances of young sprinters. Science Sports . 27 , e85–e88 (2012). Guelmami, N. et al. The Ethical Compass: Establishing ethical guidelines for research practices in sports medicine and exercise science. Int. J. Sport Stud. Health . 7 , 31–46 (2024). Dergaa, I. et al. Moving Beyond the Stigma: Understanding and Overcoming the Resistance to the Acceptance and Adoption of Artificial Intelligence Chatbots. NAJM 29–36 (2023). 10.61838/kman.najm.1.2.4 Dergaa, I. et al. A thorough examination of ChatGPT-3.5 potential applications in medical writing: A preliminary study. Medicine 103 , e39757 (2024). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6617578","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":462568205,"identity":"87abaabe-dce3-457b-a221-6ccc5a455971","order_by":0,"name":"Houda Bougrine","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACAyCWYGwAMUFkhQUPiPmBBC1nJEBaGGcQqQWktk2CgaAWc/Yewxs/d9gkzo8+3Pbg4zwJGYPjDYzNFXi0WPacMbbsPZOWuPFcYrvhzG0SPAZnDjA2nsHnsBs5ZhK8bYcTN/YwtknzArVIzkhgf9hAQIvkX5iWv3OAWuY/YGwkpEUaZMt8HqAWxgYJHn4JBgJazhwrtpY9k2a8AahFsucYUAtPYiN+LcebN958u8NGdn4P+zOJHzU29mzshw/i1YLQewDOhEcTASBPpLpRMApGwSgYgQAA3gVO6zrjKMoAAAAASUVORK5CYII=","orcid":"","institution":"University of Pau et des Pays de l’Adour","correspondingAuthor":true,"prefix":"","firstName":"Houda","middleName":"","lastName":"Bougrine","suffix":""},{"id":462568206,"identity":"3ca99611-39b2-47af-be77-005baf498950","order_by":1,"name":"Imed Gandouzi","email":"","orcid":"","institution":"University of Gafsa","correspondingAuthor":false,"prefix":"","firstName":"Imed","middleName":"","lastName":"Gandouzi","suffix":""},{"id":462568207,"identity":"8d5019cc-2ea5-423c-bf8b-fbc63456c4e8","order_by":2,"name":"Ismail Dergaa","email":"","orcid":"","institution":"National Observatory of Sports","correspondingAuthor":false,"prefix":"","firstName":"Ismail","middleName":"","lastName":"Dergaa","suffix":""},{"id":462568208,"identity":"8c5a7e1e-234a-4b19-9bb9-eee0378d5d79","order_by":3,"name":"Julien Maitre","email":"","orcid":"","institution":"University of Pau et des Pays de l’Adour","correspondingAuthor":false,"prefix":"","firstName":"Julien","middleName":"","lastName":"Maitre","suffix":""},{"id":462568209,"identity":"8604272f-160c-42ce-a555-9abeede10f98","order_by":4,"name":"Abdulwahed Ahmed Alaizari","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Abdulwahed","middleName":"Ahmed","lastName":"Alaizari","suffix":""},{"id":462568210,"identity":"210d1756-3882-47c5-9d6b-5d7e5cd0175d","order_by":5,"name":"Osama Aljuhani","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Osama","middleName":"","lastName":"Aljuhani","suffix":""},{"id":462568211,"identity":"573582e6-3d65-4bf4-8a76-3a6aae9e7a59","order_by":6,"name":"Thierry Paillard","email":"","orcid":"","institution":"University of Pau et des Pays de l’Adour","correspondingAuthor":false,"prefix":"","firstName":"Thierry","middleName":"","lastName":"Paillard","suffix":""},{"id":462568212,"identity":"4f4cd8a4-26e1-4c53-83fe-afca0065b127","order_by":7,"name":"Nizar Souissi","email":"","orcid":"","institution":"National Observatory of Sports","correspondingAuthor":false,"prefix":"","firstName":"Nizar","middleName":"","lastName":"Souissi","suffix":""}],"badges":[],"createdAt":"2025-05-08 07:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6617578/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6617578/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-21414-7","type":"published","date":"2025-11-05T15:56:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83555925,"identity":"e2c1dafa-a270-4fa3-b4f4-86874f50751b","added_by":"auto","created_at":"2025-05-28 11:43:53","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":137184,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYes-MUS, with listening to music during warming-up; No-MUS, without listening to music; OT, Oral temperature; CMJ, Countermouvement jump test; MDBT, medecine bell throw test; 20m-ST, 20m sprint test; IAT, Illinois agility test; all times given are expressed in local time (GMT + 1 h).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6617578/v1/e019629910bfcbfe5a7c7140.jpg"},{"id":95563880,"identity":"f152e85a-fd5f-42f7-9986-d4588f6e2d48","added_by":"auto","created_at":"2025-11-10 15:59:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1365438,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6617578/v1/a63e1876-dfb0-48be-b45c-1c1045267864.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of Self-Selected Motivational Music During Warm-Up on Time- of-Day Variations in Anaerobic Performance Among Female Handball Players","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCircadian rhythms, endogenous biological oscillations regulated by the central biological clock, regulate numerous physiological processes \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. These rhythms are modulated by external, psychobiological, internal, and chronobiological factors \u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, influencing body temperature \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, and hormonal regulation (e.g., cortisol, melatonin) \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Such fluctuations extend to skeletal muscle, altering molecular clock mechanisms \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. These variations have been shown to influence maximal strength output \u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and the ability to perform repeated sprints \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, thereby contributing to time-of-day-dependent variations in neuromuscular performance \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIndeed, athletic performance whether endurance or strength-based fluctuate with the TOD\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Maximal short-duration efforts, heavily reliant on anaerobic metabolism, demonstrate pronounced performance differences between morning and evening \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, with peak performance typically occurring in the late afternoon or early evening (16:00\u0026ndash;20:00) \u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e compared to morning performance (06:00\u0026ndash;10:00) \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. These fluctuations are primarily driven by peripheral (muscular) rather than neural adaptations \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. While factors such as such as active warm-up, fasting, controlled environmental conditions, and consistent morning training can mitigate these diurnal variations \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, research on female athletes remains limited, particularly in team-sport contexts \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Thus, optimizing training and competition timing is especially relevant for female athletes.\u003c/p\u003e \u003cp\u003eIn parallel, music has emerged as a potential modulator of athletic performance. Listening to music during exercise has been shown to reduce perceived exertion, improve motivation and arousal, and support better motor coordination \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Music acts as a cognitive distractor \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, helping to reduce effort perception, while also stimulating neural activity \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, improving running economy and overall physical output \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Its ergogenic effects span endurance exercise \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, sprint performance \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, and resistance training \u003csup\u003e\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Music has also been reported to influence mental states, helping athletes to energize, relax, or increase confidence and self-esteem \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eImportantly, music may also attenuate time-of-day-related performance declines, particularly during suboptimal morning periods \u003csup\u003e\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. While some studies report enhanced power output during anaerobic tasks when music is used during warm-up \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, others report inconsistent results \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. These discrepancies may be attributed to differences in exercise type, individual music preferences, or psychological factors such as self-confidence and arousal \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. For instance, results on anaerobic threshold performance show, for example, that there is no increase in the threshold, although performance is improved in women \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, whereas its impact on supramaximal efforts remains contested \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The impact of rhythm and tempo on physical performance remains an area of uncertainty, with mixed findings in the literature \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Thus, while music clearly interacts with multiple physiological and psychological domains, the precise mechanisms remain insufficiently understood, justifying continued investigation \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTaken together, the existing literature confirms that TOD significantly influences short-term maximal performance, and that music offers promising benefits. However, studies integrating both variables remain scarce, especially among female populations. To the best of the authors\u0026rsquo; knowledge, no study has yet examined the combined effects of TOD and self-selected motivational music during warm-up on short-term anaerobic performance in female athletes. This study therefore aims to evaluate the effects of self-selected motivational music during warm-up at four TODs (08:00, 11:00, 15:00, and 18:00) on short-term maximal performance in female athletes. The study specifically investigates whether motivational music can attenuate the typical diurnal decline in performance, particularly in the morning, and offers practical insights into how female athletes can use chronobiological and psychological strategies to optimize physical performance throughout the day. We hypothesize that music will blunt diurnal performance fluctuations, with the most pronounced effects during morning sessions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eThe study protocol adhered to the principles outlined in the Declaration of Helsinki regarding human experimentation and the ethical guidelines and procedural standards for Human Chronobiology research \u003csup\u003e52\u003c/sup\u003e. The study protocol adhered to the ethical principles of the Declaration of Helsinki for research involving human subjects and received approval from the local research ethics committee of the High Institute of Sport and Physical Education of El Kef, University of Jendouba, Jendouba, Tunisia, under the reference (ISSEPK-0033/2024). It also complied with the ethical and procedural requirements for the conduct of sports medicine and exercise science research \u003csup\u003e53\u003c/sup\u003e. Written informed consent was secured from parents/guardians of minor participants, with additional verbal assent from the athletes following a detailed explanation of the study's objectives, methodology, potential risks, and benefits.\u003c/p\u003e\n \u003cp\u003eThe sample size estimation for the study was performed using G*Power software \u003csup\u003e54\u003c/sup\u003e, following the recommendations of Beck \u003csup\u003e55\u003c/sup\u003e. An alpha level of 0.05 and a target statistical power of 0.80 were chosen. The anticipated effect size, set at 0.3, was based on a prior similar study \u003csup\u003e56\u003c/sup\u003e and the consensus among the authors. The calculations indicated that a minimum of 16 athletes was necessary to reduce the likelihood of a Type II error. To minimize the impact of potential dropouts, 37 subjects were initially assessed, of which 26 met the inclusion criteria. However, two participants later withdrew, and six athletes were excluded due their menstural cycles, resulting in a final study sample of 18 athletes.\u003c/p\u003e\n \u003cp\u003eThe sample consisted of 18 female handball players (age: 16.16 ± 0.38 years, height: 1.67 ± 0.9 m, weight: 57.68 ± 13.1 kg, BMI: 20.28 ± 3.2 kg/m²) from the same regional team, each with over three years of experience in handball (4.66 ± 0.48 years). On average, these athletes participated in 3.77 ± 0.42 training sessions per week.\u003c/p\u003e\n \u003cp\u003eTo qualify for participation in the study, female athletes were required to meet several inclusion criteria. These included being aged between 16 and 18 years, having a minimum of three years of prior handball training experience, and regularly attending at least two training sessions per week. Additionally, participants were expected to have no history of menstrual irregularities within the past six months, and to be free from injury within the preceding four months. Further, they must not have been using hormonal contraceptives such as pills, patches, injections, implants, or intrauterine devices within the past six months. Exclusion criteria were rigorously applied to ensure the integrity of the study. Athletes were excluded if they had any medical condition or illness that could impair test performance or if they were under medication for a chronic medical issue. Other exclusions included, the use of medications (such as stimulants, narcotics, or psychotropic drugs), dietary supplements, or restrictive diets potentially affecting hormonal balance within the last three months. Athletes with sleep disorders characterized by Pittsburgh Sleep Quality Index (PSQI) scores exceeding 5, those consuming alcohol or tobacco, or those displaying extreme morning or evening chronotypes were also omitted. Athletes who had any diseases and abnormalities of the ear or hearing were exclude from the study.\u003c/p\u003e\n \u003cp\u003eAll participants menstrual cycle lengths (28,16 ± 1,65 days) and phases were assessed using the My calendar® Period Tracker \u003csup\u003e57\u003c/sup\u003e. In order to further mitigate the impact of menstrual cyle phases and in line with outlined studies \u003csup\u003e58,59\u003c/sup\u003e, the experimental sessions were performed throughout only follicular and luteal phases.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eExperimental procedure\u003c/h3\u003e\n\u003cp\u003eTo comprehensively examine the effects of self-selected motivational music and TOD on anaerobic athletic performance among female athletes, 18 female handball athletes participated in this research. The testing occurred over eight separate sessions, spaced at least 48 hours apart, to reduce the risk of fatigue-related carryover effects. These sessions were randomized across four different times of day (08 :00h, 11:00h, 15:00h, and 18:00h) and carried out under two distinct conditions either with motivational music integrated during the warm-up (Yes-MUS) or without it (No-MUS). A recovery period of at least 48h was taken between sessions. Prior to the main experiment, two familiarization sessions were conducted to minimize learning effects and to ensure accurate data collection (Fig.\u0026nbsp;1). These sessions were evenly distributed between the two extreme times of day, aligning approximately with the circadian rhythm peaks and troughs of short-term performance and oral temperature \u003csup\u003e60,61\u003c/sup\u003e. The intermediate times (11:00h, 15:00h) were incorporated to ensure evenly spaced intervals throughout the study \u003csup\u003e62\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eEach session followed a strict protocol, beginning with oral temperature measurements to account for physiological and circadian states. Participants then completed a 10-minute low-intensity warm-up. Two minutes after the testing lineup included a counter mouvement jump test (CMJ), a medecine ball throw test (MDBT), 20-meter sprint test (20m-ST), and the Illinois agility test (IAT). A 5-minute recovery period was provided between tests to mitigate fatigue. The study was conducted from January to March 2024 at the athletes' standard indoor training court under consistent environmental conditions, with an average temperature of 22°C and approximately 47% relative humidity. Athletes meeting the inclusion criteria provided informed parental consent and adhered to strict guidelines. They avoided energy drinks, anti-inflammatory, and antioxidant substances during the study period, followed regular training schedules while avoiding intense exercise, and maintained consistent dietary habits. Prior to morning sessions, body mass was recorded using a Tanita electronic scale (Tokyo, Japan).\u003c/p\u003e\n\u003cp\u003eRegarding the warm-up protocol, athletes completed two different warm-up protocols. The routine started with 3 minutes of jogging at a moderate speed (8–10 km/h), followed by 3 minutes of dynamic stretches targeting the main muscle groups. This was succeeded by a 2-minute session of sprinting drills, such as ankling, high knees, back kicks, and skipping, and another 2 minutes of sprinting. Participants then engaged in a 10-minute warm-up, either in silence (No-MUS) or while listening to their favorite motivational music (Yes-MUS). After each warm-up session, a 2-minute rest break was provided.\u003c/p\u003e\n\u003cp\u003eRegarding Music Protocol, participants selected their preferred music based on established guidelines from prior studies on music preference and exercise performance before the familiarization and testing phases \u003csup\u003e63–66\u003c/sup\u003e. During the familiarization phase, each participant choosen their favorite track, which were labeled for use during experimental sessions. The selected music was self-chosen and rated for motivational qualities using the Brunel Music Rating Inventory-2 \u003csup\u003e67\u003c/sup\u003e. To maximize stimulation, tracks had a minimum tempo of 120 beats per minute (bpm) \u003csup\u003e68\u003c/sup\u003e, with an average tempo of 136.5 ± 12.78 bpm. During testing, participants listened to their chosen playlists through headphones connected to their personal mobile devices, with the volume standardized at 80 dB using the Decibel sound level meter app. For No-Music (NoM) conditions, participants wore headphones with no music to ensure consistent testing conditions across sessions. For music conditions, tracks played continuously throughout the warm-up, with looping enabled for shorter songs to cover the full 10-minute duration.\u003c/p\u003e\n\u003ch3\u003eCircadian typology and sleep quality questionnaires\u003c/h3\u003e\n\u003cp\u003eCircadian typology was determined through the Horne and Östberg self-assessment questionnaire, which evaluates sleep and activity patterns on a 19-item scale \u003csup\u003e69\u003c/sup\u003e. To further mitigate the influence of circadian typology, only participants identified with an intermediate chronotype were included in this study and extreme chronotypes (morning or evening) were excluded. Eligible participants scored between 42 and 58 (49,5 ± 4,56), indicating an intermediate chronotype. Moreover to assess the sleep quality, all athletes demonstrated normal sleep patterns, averaging 7.22 ± 0.54 hours of nightly sleep, and achieved an average PSQI score of 2.08 ± 0.83 in the month preceding the experimental procedures, based on the validated Arabic version of the PSQI \u003csup\u003e70\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003e2.1. Oral temperature (OT)\u003c/h3\u003e\n\u003cp\u003eThe resting oral temperatures were taken with a calibrated digital clinical thermometer (Omron, Paris, France; accuracy ± 0.05°C) inserted sublingually for at least 3 min after a 10-min period of resting while seated.\u003c/p\u003e\n\u003ch3\u003e2.2. The 2 kg Medicine Ball Throw Test (MDBT)\u003c/h3\u003e\n\u003cp\u003eMedicine ball throw is the most widely known and indirect test used to evaluate the power of the upper limbs in team sports \u003csup\u003e71,72\u003c/sup\u003e. The players throw the medicine ball as vigorously, far and straight forward as they can, while keeping their back flush against the wall, and their elbows in towards their sides during the push maneuver. Three maximal throws for distance were performed using a measuring tape and measurements were recorded in meters from the wall to where the medicine ball landed \u003csup\u003e73\u003c/sup\u003e. The best throw was retained for our anlaysis. With a recovery period of ten seconds between three repetiotions the best performance was retained for our statistical analysis.\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e2.3. 20 m Sprint performance (20m-ST)\u003c/h2\u003e\n \u003cp\u003eThe 20-m sprint test was administered as a test of acceleration and sprint ability. Linear speed was measured by a 20m sprint with timing gates (Witty, Microgate®, Bolzano, Italy) setup at 0, 5 and 20m to measure the 0–5 m and 0–20 m intervals. Timing gates were placed at the approximate hip height for all players as previously recommended \u003csup\u003e74\u003c/sup\u003e. Players were instructed to initiate the sprint when ready and cover the set distance as fast as possible. The subjects completed three trials of sprint, with a minimum of 3-min rest between each trial. The best performance from each of the 3 trials was used for analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e2.4. Illinois Agility test (IAT)\u003c/h3\u003e\n\u003cp\u003eThe Illinois Agility Test incorporates acceleration, deceleration, change of direction, and sprinting. The change of direction Illinois Agility Test was reported to have high reliability and validity for team sports \u003csup\u003e75,76\u003c/sup\u003e. The length of the course is 10m and the width is 5m where four cones are used to mark the start, finish, and the two turning points. Four more cones are placed down the center an equal distance apart (spaced 3.3m apart). The duration of their performance was quantified using timing gates (Witty, Microgate®, Bolzano, Italy) positioned at the beginning and end points, and the superior outcome from the two trials was documented. Players were given instructions to maximize their running speed while following the designated course in the specified direction to reach the endpoint.\u003c/p\u003e\n\u003ch3\u003e3. Statistical analysis\u003c/h3\u003e\n\u003cp\u003eSTATISTICA software (StatSoft, France) was used to evaluate the data that were collected for this investigation. The means ± SD (standard deviation) values were calculated for each variable. A normal distribution of all the data was verified by the Shapiro-Wilk test. To examine the impact of TOD, a two-way repeated measures ANOVA (2 Music and 4 TOD) was used. Tukey's HSD (Honestly Significant Difference) Post hoc test was used to assess for significant differences between means when appropriate. The effect size statistic (ηp2) was used to determine the magnitude of the difference between age-groups. The criteria as follows were applied, according to \u003csup\u003e77\u003c/sup\u003e, to determine the effect sizes: a minor effect size was 0.01, a moderate effect size was 0.06, and a large effect size was 0.14. The study used Cohen's d analysis, a standardized effect size, to analyze the magnitude of differences between variables. The variables were categorized as follows by \u003csup\u003e78\u003c/sup\u003e: trivial (d ≤ 0.20), small (0.20 \u0026lt; d ≤ 0.60), moderate (0.60 \u0026lt; d ≤ 1.20), large (1.20 \u0026lt; d ≤ 2.0), very large (2.0 \u0026lt; d ≤ 4.0), and extremely large (d \u0026gt; 4.0). A significant level was considered as a p ≤ 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eOral temperature\u003c/h2\u003e\n \u003cp\u003eTwo-way Anova revealed a moderate significant main effect for TOD [F (3,51)\u0026thinsp;=\u0026thinsp;35.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.67], However, there were no significant effects observed for MUS [F (1,17)\u0026thinsp;=\u0026thinsp;1.7, p\u0026thinsp;=\u0026thinsp;0.2, \u0026eta;p\u0026sup2; = 0.09] or for the interaction between MUS and TOD [F (3,51)\u0026thinsp;=\u0026thinsp;0.2, p\u0026thinsp;=\u0026thinsp;0.91, \u0026eta;p\u0026sup2; = 0.009]. Bonferroni test indicated that core temperature was considerably higher at 18:00h compared to 8:00 h across No-MUS and Yes-MUS (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The morning-to-afternoon differences in core temperature showed amplitudes of 3.2% under both testing conditions (No-MUS and Yes-MUS) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eValues (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) of Oral temperature, Countermouvement jump (CMJ), Medecine ball throw Test (MSBT), 20 m sprint test (20m-ST), and Illinois Agility test (IAT) scores registered during the four times of the day (8:00 h, 11:00h, 15:00h, and 18:00h.) across two testing conditions: with listening to music (Yes-MUS), and without listening to music (No-MUS) during warming-up.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTOD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8:00h\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e11:00h\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e15:00h\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e18:00h\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eOral temperature\u003c/strong\u003e (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ebbb, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ebbb, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb\u003c/strong\u003e, \u003cstrong\u003eccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMJ\u003c/strong\u003e (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa\u003c/strong\u003e, \u003cstrong\u003ebb\u003c/strong\u003e, \u003cstrong\u003ec\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74\u003c/p\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaa\u003c/strong\u003e, \u003cstrong\u003eb\u003c/strong\u003e,\u003c/sup\u003e *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMDBT\u003c/strong\u003e (m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ebb\u003c/strong\u003e, \u003cstrong\u003eccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaa\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa\u003c/strong\u003e, \u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaa\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e(20m-ST)\u003c/strong\u003e (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ebbb, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa\u003c/strong\u003e,\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ecc\u003c/strong\u003e,\u003c/sup\u003e ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaa\u003c/strong\u003e,\u003c/sup\u003e ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, b\u003c/strong\u003e,\u003c/sup\u003e *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eIAT\u003c/strong\u003e (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb\u003c/strong\u003e,\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb, ccc\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes-MUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eccc\u003c/strong\u003e,\u003c/sup\u003e ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ecc\u003c/strong\u003e,\u003c/sup\u003e ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bb\u003c/strong\u003e,\u003c/sup\u003e ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003eaaa, bbb,, ccc\u003c/strong\u003e,\u003c/sup\u003e **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003cstrong\u003ea\u003c/strong\u003e\u0026nbsp;\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), \u003csup\u003e\u003cstrong\u003eaa\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), \u003csup\u003e\u003cstrong\u003eaaa\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001): Significant difference compared to 8:00h (in the same condition); \u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), \u003csup\u003e\u003cstrong\u003ebb\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), \u003csup\u003e\u003cstrong\u003ebbb\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001): Significant difference compared to 11:00h (in the same condition); \u003csup\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), \u003csup\u003e\u003cstrong\u003ecc\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), \u003csup\u003e\u003cstrong\u003eccc\u003c/strong\u003e\u003c/sup\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001): Significant difference compared to 15:00h (in the same condition) ; *:(p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), **(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) : Significant difference compared to without music condition (at the same TOD).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eCMJ Test\u003c/h2\u003e\n \u003cp\u003eA moderate significant effect of MUS [F (1,17)\u0026thinsp;=\u0026thinsp;70.58, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.80] was observed, along with a small significant effect of TOD [F (3,51)\u0026thinsp;=\u0026thinsp;13.85, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.44] on CMJ height. No significant effects were observed on the interaction of MUS and TOD [F (3,51)\u0026thinsp;=\u0026thinsp;0.92, p\u0026thinsp;=\u0026thinsp;0.43, \u0026eta;p\u0026sup2; = 0.05].\u003c/p\u003e\n \u003cp\u003ePost hoc analysis revealed an improvement on CMJ performance from 08:00h to 18:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 5.7%) under No-MUS condition. The morning-afternoon performance differences were blunted under Yes-MUS condition (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 2.3%) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Regarding Music effects, CMJ performance increased significantly during 08:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 4.2%), 11:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 3.1%), 15:00h. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 3%) and 18:00h. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 2.4%) compared to No-MUS condition (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. The 2 kg Medicine Ball Throw Test\u003c/h2\u003e\n \u003cp\u003eStatistical analysis of MDBT performance indicated a moderate significant effect for MUS [F (1,17)\u0026thinsp;=\u0026thinsp;36.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.68], along with a small significant effect of TOD [F (3,51)\u0026thinsp;=\u0026thinsp;19.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.54]. Likewise, no significant effects were revealed for the interation of MUS and TOD [F (3,51)\u0026thinsp;=\u0026thinsp;1.77, p\u0026thinsp;=\u0026thinsp;0.16, \u0026eta;p\u0026sup2; = 0.09].\u003c/p\u003e\n \u003cp\u003eMDBT performance was observed to improve in the afternoon compared to the morning (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 13%) under No-MUS condition. However, this daily diurnal variation was blunted under Yes-MUS condition (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 6.6%). Regarding Music effects, a significant improvement in MDBT performance were observed during 08:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 8.9%), 11:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, 6.4%), 15:00h. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 5.9%) compared to No-MUS condition (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. 20m Sprint performance\u003c/h2\u003e\n \u003cp\u003eThe results of the two-way ANOVA showed a moderate significant main effect of MUS [F (1,17)\u0026thinsp;=\u0026thinsp;69.50, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.80] on 20m ST. A small significant main effect of TOD [F (3,51)\u0026thinsp;=\u0026thinsp;9.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.34], as well as the interaction of MUS and TOD [F (3,51)\u0026thinsp;=\u0026thinsp;4.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u0026eta;p\u0026sup2; = 0.21] were revealed. According to the post hoc test, 20m ST were greater in the afternoon compared to the morning for conditions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus; 5.9%) during No-MUS condition. Further investigations showed that these daily morning to afternoon variation were diminished during Yes-MUS condition (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus; 3.3%), as presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Regarding the impact of Music, 20m ST time significantly decreased during 08:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus;\u0026thinsp;4.8%), 11:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus;\u0026thinsp;3.3%), 15:00h. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus;\u0026thinsp;3.7%), and 18:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u0026minus;\u0026thinsp;1.9%) compared to No-MUS condition (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Illinois Agility test (IAT)\u003c/h2\u003e\n \u003cp\u003eA moderate significant effect on IAT were observed for both MUS [F (1,17)\u0026thinsp;=\u0026thinsp;62.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.78] and TOD [F (3,51)\u0026thinsp;=\u0026thinsp;82.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.82] on agility performance. Additionally, a small significant effect on interaction between MUS and TOD [F (3,51)\u0026thinsp;=\u0026thinsp;15.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026eta;p\u0026sup2; = 0.46] was recorded. Post hoc analysis revealed that IAT performance were lower in the morning compared to the afternoon (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus; 7.1%) under No-MUS condition. Interestingly, these morning-afternoon differences were blunted under Yes-MUS condition (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus; 4.7%) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared to No-MUS condition, IAT time significantly decreased during 08:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus;\u0026thinsp;3.9%), 11:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus;\u0026thinsp;3.6%), 15:00h. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u0026minus;\u0026thinsp;3.2%), and 18:00h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u0026minus;\u0026thinsp;1.3%) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to assess the effects of listening to self-selected motivational music during warm-up at various times of day (08:00h, 11:00h, 15:00h, and 18:00h) on several maximal exercise performances among young female handball players. The main findings revealed that (1) high-intensity short-term physical exercises such as CMJ ; MDBT; 20m-ST; and IAT significantly improved throughout the day, peaking in the late afternoon (18:00h); (2) listening to motivational music during warm-up enhanced physical performance across all time points especially during the morning hours; and (3) the amplitude of diurnal variation was attenuated under the music conditiond. These findings provide valuable insights into the interaction between chronobiological rhythms and ergogenic aids such as music in female athletes.\u003c/p\u003e \u003cp\u003eRegarding the TOD effects on short term high intensity performances and in line with the current findings, a number of investigations have demonstrated that the peak anaerobic performances were observed in the afternoon between 16:00h and 18:00h \u003csup\u003e\u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e compared to morning among female team sports athletes. In addition, the current outcomes align with a recent meta-analysis \u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e that revealed that late afternoon (between 16:00h and 19:30h) is most favorable TOD for short-term maximal physical performance. An afternoon improvement of repeated sprints performance \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e, and agility \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e, was observed on female team ball players. A recent systematic review revealed that singular sprints tended to perform much better in the afternoon than in the morning with 5m and 20m overground running sprint timings decreasing by 10.9% and 10.8% respectively \u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e. Mhenni et al. \u003csup\u003e\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e revealed that the handgrip strength, the ball-throwing velocity, the modified T-test, and the repeated sprint performances were better in the evening than in the morning. Performances of total distance and peak distance of 5m shuttle run test, increased at 17h00 compared to 07h00, 09h00, 11h00, 13h00 and 15h00 \u003csup\u003e62\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsistent with our findings, numerous studies report peak maximal exercise performances occurring in the late afternoon (16:00\u0026ndash;18:00h) compared to morning sessions among female team-sport athletes \u003csup\u003e\u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. This observation is supported by a recent meta-analysis \u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e which identified the late afternoon (16:00\u0026ndash;19:30) as the most favorable TOD for short-term maximal physical performance. Specifically, enhanced afternoon performance has been consistently reported in repeated sprint ability performance \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e and agility \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e among female team-sport athletes. Likewise, a recent systematic review reported that sprint performances significantly improved in the afternoon compared to the morning, with overground sprint times for 5 m and 20 m decreasing by 10.9% and 10.8%, respectively \u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e. Diurnal performance variation is further evidenced by superior evening results in handgrip strength, ball-throwing velocity, and shuttle run performance \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e,\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e,\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, some studies report no significant TOD effects \u003csup\u003e\u003cspan additionalcitationids=\"CR89\" citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e. potentially due to methodological differences in chronotype inclusion, training schedules, or testing protocols. In our study, we controlled for these factors by exclusively including intermediate chronotypes and standardizing testing procedures.\u003c/p\u003e \u003cp\u003eThese discrepancies may be partly attributed to individual differences in chronotype, biological clock alignment, and motivation throughout the day. Differences in sleep\u0026ndash;wake patterns, the time people typically wake up, and personal circadian preferences can all affect performance and help explain why studies sometimes produce inconsistent results. These findings highlight the importance of considering circadian typology in both research and training contexts \u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e. Since optimal performance timing varies between individuals \u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e, our study specifically recruited intermediate chronotypes and excluded extreme chronotypes to mitigate these effects. Aligning daily physical activity with an individual's circadian rhythm is essential, as it impacts cognitive and neuromuscular functions such as attention, reaction time, and psychomotor vigilance \u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e,\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e. Additionally, external factors such as academic schedules, sex, seasonal daylight exposure \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e, age, sport-specific demands, training status, and habitual training times \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e may also influence performance at different TODs. In the current study, all athletes habitually trained in the afternoon (between 17:00 and 19:00), which may have enhanced afternoon performance and partly explains the performance differences between morning and evening sessions.\u003c/p\u003e \u003cp\u003eAlthough the exact mechanism behind the superior performance in the evening is not fully understood, the prevailing hypothesis suggests that factors such as body temperature as well as related physiological, psychological, and metabolic cycles reach their peak levels in the afternoon \u003csup\u003e\u003cspan additionalcitationids=\"CR97 CR98\" citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. In line with previous research on female team ball athletes \u003csup\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e,\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e, our findings also revealed higher oral temperatures at 18:00, which coincide with the expected increase in core temperature observed between 15:00 and 18:00. Recently, Ayala et al. \u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e revealed that body temperature follow a circadian rhythm, peaking in the latter afternoon (16:30\u0026ndash;18:30 h), when physical performance (i.e., agility, speed, power, and distance covered) reaches its maximum and indicated that this slot is the most appropriate TOD for several aspects of physical activity.\u003c/p\u003e \u003cp\u003eHigher afternoon temperatures appear to facilitate key metabolic processes. For example, increased body heat is associated with enhanced muscle glycogenolysis, glycolysis, and the breakdown of high-energy phosphates \u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e, as well as quicker action potential conduction \u003csup\u003e\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e. An estimated 0.9% increase in body temperature during the afternoon \u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e promotes more efficient glycogen utilization and leads to stronger muscle contractions \u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u003c/sup\u003e. Additionally, improvements in muscle function, elevated hormone levels \u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e, and faster reaction times \u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e all contribute to the better anaerobic performance observed later in the day.\u003c/p\u003e \u003cp\u003eBy contrast, lower performance during morning sessions (08:00 and 11:00) and in the early afternoon (15:00) may be due to a core temperature that has not yet fully risen from its nocturnal low, thereby impairing both muscle and metabolic functions \u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e,\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e,\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e. Moreover, higher and more fluctuating melatonin levels in the morning can contribute to fatigue and reduced attentiveness \u003csup\u003e\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e, while sleep inertia\u0026mdash;characterized by reduced alertness and slower reaction times right after waking\u0026mdash;further diminishes performance \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e,\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e,\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e,\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e. Interestingly, the common \"post-lunch dip\" appears to cause a temporary drop in performance at 15:00, likely because energy is redirected toward digestion, leading to a brief reduction in arousal and cognitive function \u003csup\u003e\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e,\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e\u003c/sup\u003e. Together, these physiological and cognitive factors contribute to the diurnal variations in performance observed throughout the day.\u003c/p\u003e \u003cp\u003eRegarding the music effects on short term high intensity performances, the findings of this study are consistent with previous research, indicating that listening to motivational music during warm-up can help female collegiate athletes boost their power output and total work during repeated sprint exercises \u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e. Research has shown that motivational music not only enhances overall performance but also increases the distance achieved during repeated sprints effects that are particularly notable in morning sessions \u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e. In addition, even neutral music during warm-up has been demonstrated to improve muscle power throughout the day, which helps counteract the common drop in anaerobic performance seen in the morning \u003csup\u003e\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u003c/sup\u003e. While some studies have found no significant effects of motivational music on short-term, high-intensity performance \u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e, other investigations reveal that music-enhanced warm-ups can lead to increased peak power and better performance outcomes in various tests, especially among highly trained athletes and sprinters \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e,\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e\u003c/sup\u003e. Moreover, a recent systematic review and meta-analysis suggest that listening to music during the Wingate Anaerobic Test may have a positive physiological impact on relative anaerobic exercise performance, although the exact mechanisms remain to be fully clarified \u003csup\u003e\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, the effect of music appears to be less significant for long-distance runners or highly trained individuals, with its ergogenic impact tending to diminish as overall fitness levels increase \u003csup\u003e\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e,\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e\u003c/sup\u003e. Since our athletes are young players with only about 4.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48 years of experience in a regional club, this may partly explain the pronounced effectiveness of motivational music within our sample. Variations in study findings could be attributed to differences in participants\u0026rsquo; fitness levels, the type of music used, and whether the music was played during exercise or specifically during warm-up periods \u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e,\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e\u003c/sup\u003e. Additionally, recent research suggests that the timing of music exposure is critical when music is integrated with exercise routines, it appears to enhance both emotional well-being and anaerobic performance, particularly when played during workouts \u003csup\u003e\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e\u003c/sup\u003e. Furthermore, studies have demonstrated that synchronizing the tempo of the music with an individual\u0026rsquo;s movement patterns not only optimizes energy expenditure but also improves motor efficiency, leading to significant enhancements in kinetic and physiological outcomes \u003csup\u003e\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough some recent meta-analyses suggest that preferred music does not significantly alter mean heart rate or perceived exertion (RPE), thereby questioning its direct influence on exercise performance \u003csup\u003e\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e\u003c/sup\u003e, other studies highlight the powerful impact of fast-paced, loud music. In particular, such music can enhance performance by diverting athletes\u0026rsquo; attention away from feelings of fatigue\u003csup\u003e\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e\u003c/sup\u003e and by modulating psychomotor arousal acting either as a sedative or a stimulant depending on the specific context and the demands placed on the athlete \u003csup\u003e\u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e,\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding the combined effects of music and TOD effects on short term high intensity performances, the current findings indicate that listening to music before physical activities can reduce the differences in anaerobic performance observed between morning and evening sessions among handball players. However, because there is limited research examining the interaction between music effects and performance at various times of the day, it remains challenging to directly compare these results with previous studies. To the best of our knowledge, no prior study has assessed these parameters in young female athletes or evaluated performance at more than two distinct time points throughout the day. This highlights the need for further research to explore how music and time of day together influence athletic performance across a broader range of populations and conditions.\u003c/p\u003e \u003cp\u003eOur results are consistent with earlier findings that suggest listening to music during warm-up can help minimize diurnal fluctuations in physiological performance, as observed in studies with male athletes \u003csup\u003e\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e\u003c/sup\u003e. For instance, Belkhir et al. \u003csup\u003e\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e\u003c/sup\u003e reported that warm-ups accompanied by high-tempo music (120\u0026ndash;140 bpm) were more effective at enhancing performance on the 30-second continuous jump test especially in the morning (07:00) compared to the afternoon (17:00)\u0026mdash;among semi-professional male soccer players. Other studies have indicated that both total and maximal distance covered during a 5-meter shuttle run test, as well as athletes\u0026rsquo; subjective responses, are influenced by the time of day and the type of music used during warm-ups. Specifically, warm-ups featuring self-selected motivational music were found to boost maximal performance and positively affect mood at both 07:00 and 17:00, with stronger effects in the morning, whereas neutral music improved these parameters only in the morning \u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e. Similarly, Bentouati et al. \u003csup\u003e\u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e\u003c/sup\u003e demonstrated that warm-ups using self-selected motivational music improved muscle power during the Wingate test and reduced perceived exertion at both time points, showing greater benefits in the morning. These findings suggest that incorporating music during warm-up not only enhances performance across different times of day but also helps reduce the performance gap between morning and afternoon sessions among trained individuals. Moreover, research indicates that a warm-up with motivational music is more beneficial than one with synchronous music for improving short-term maximal performance, regardless of whether it is performed in the morning or afternoon \u003csup\u003e\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e\u003c/sup\u003e. In addition, Khemila et al. \u003csup\u003e\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e\u003c/sup\u003e found that including music in warm-ups can improve cognitive function and short-term maximal performance following both normal sleep and partial sleep deprivation among male physical education students.\u003c/p\u003e \u003cp\u003eSince lower morning motivation may partly explain the diurnal variation of anaerobic performances, listening to music before exercise could play a critical role in altering this pattern. Music has been shown to boost motivation, reduce discomfort, and enhance perceived effort \u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e,\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e\u003c/sup\u003e, which might explain its heightened effectiveness during the morning compared to other TOD. We hypothesize that music, as an external stimulus, has a more significant impact when maximal physical performance levels are at their lowest, such as during the morning timepoints. During these times, physiological and psychological factors like reduced energy levels, lower body temperature, and diminished alertness combine to create a challenging environment for peak physical performance. Thus, by providing an external boost to motivation and focus, music may counteract these natural performance dips, effectively narrowing the gap between morning and afternoon/evening anaerobic outputs. Further research is warranted to explore this hypothesis and determine the exact mechanisms underlying this interaction.\u003c/p\u003e \u003cp\u003eThe observed diurnal variation in anaerobic performance may be partially attributable to reduced morning motivation levels. In this context, pre-exercise music exposure appears to modulate this circadian performance pattern through several psychophysiological mechanisms. Empirical evidence demonstrates that music enhances motivational state, reduces perceived exertion, and improves effort perception \u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e,\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e\u003c/sup\u003e, potentially explaining its greater efficacy during morning sessions compared to other time points. We hypothesize that music, as an external stimulus, has a more significant impact when maximal physical performance levels are at their lowest, particularly in morning hours. During these chronobiological troughs, concurrent factors including depressed energy metabolism, reduced core temperature, and diminished CNS arousal collectively impair physical performance capacity. Music may serve as a countermeasure by enhancing psychomotor arousal and attentional focus, thereby attenuating the typical morning-to-evening performance differential in anaerobic output.\u003c/p\u003e \u003cp\u003eThese findings suggest several important directions for future research to elucidate: to elucidate: (1) the specific neurophysiological mechanisms underlying music-induced performance enhancement, particularly their modulation of motor cortex excitability and autonomic nervous system responses; and (2) the nature of cross-modal interactions between auditory stimulation and circadian regulatory processes, including potential synchronization effects on central pacemaker activity.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStudy limitations\u003c/h2\u003e \u003cp\u003eWhile this study provides novel insights into chronobiological and musical influences on athletic performance, several limitations must be acknowledged. Primarily, the absence of melatonin assays and hematological markers represents a significant constraint, as these biomarkers could have offered more direct evidence of circadian modulation and physiological responses. Furthermore, the exclusive focus on young female handball players constrains extrapolation to other demographic groups, including male athletes, older athletes, or sedentary populations. Additionally, the specific protocols applied in this study may limit the generalizability of the results, necessitating caution when applying these findings to other contexts or sports. The study was also conducted exclusively on young female athletes, which restricts the applicability of the conclusions to other populations, such as adult male athletes or inactive individuals. Future research should aim to replicate these findings across a broader range of athletic disciplines and demographics to better solidify and contextualize the role of self-selected motivational music in enhancing anaerobic performance. Exploring the effects of different music types, tempos, and chronotypes across diverse sports contexts could further deepen our understanding of these variables. Additionally, examining a wider array of physiological and psychological factors under conditions of both rest and fatigue would provide valuable insights.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe primary findings of the current study indicate that several maximal short-term physical exercises are influenced by the TOD. Specifically, measures such as oral temperature and performance outcomes in the CMJ, MDBT, 20m sprint, and IAT tests showed a gradual improvement throughout the day, peaking in the late afternoon around 18:00h. From a practical viewpoint, adolescent female handball players with an intermediate chronotype are likely to achieve their best short-term maximal physical performance during this time. Nonetheless, there is a support to schedule training sessions and or competitions in the late afternoon, rather than in the morning or early afternoon, as the current study highlights the lower performance levels observed at those times.\u003c/p\u003e \u003cp\u003eThe findings of this study suggest that incorporating self-selected music during warm-up can be an effective strategy to enhance acute anaerobic performance. This improvement is evident through increased results in the CMJ, MDB, 20m ST, and IAT tests conducted throughout the day at 08:00h, 11:00h, 15:00h, and 18:00h. Notably, the positive effects of music were more pronounced during the morning sessions. Furthermore, music appears to minimize diurnal variations in performance, effectively elevating results during the earlier time points.\u003c/p\u003e \u003cp\u003eUltimately, these insights carry practical relevance, as they suggest that team ball coaches may benefit from encouraging players to listen to their preferred motivational music acting as a motivating stimulant both in the morning and afternoon before engaging in short-term high-intensity activities.\u003c/p\u003e \u003cp\u003eIn conclusion, music serves as a powerful external stimulant capable of offsetting the diurnal fluctuations in physical performance throughout the day. While its influence appears particularly impactful during mornings or energy-dip periods, individual responses and preferences should guide its application. Further research is essential to refine these recommendations and uncover the precise mechanisms linking music to enhanced physical output. For now, the strategic integration of music in athletic routines can contribute to more improved performances across varying TOD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization: H.B., T.P., and N.S.; methodology: H.B., T.P., and I.D.; investigation: H.B.,I.G., and I.D.; data curation: H.B.; formal analysis: H.B. and J.M.; writing-original draft: H.B.; writing—review and editing: T.P., N.S., I.G., J.M., A.A.A., O.A., and I.D.; supervision: T.P., H.B., and N.S.; validation: O.A., I.D., and ., A.A.A.; resources: A.A.A. and \u0026nbsp;O.A.; software: J.M.; visualization: I.G.; project administration: I.D., T.P., and N.S.; funding acquisition: A.A.A. and O.A. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e This study complied with the ethical and procedural requirements for conducting sports medicine and exercise science research. As the participants were minors, written informed consent for publication was obtained from their parents or legal guardians before participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e : We thank all the participants in this study.\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the Researchers Supporting Project (Number RSP2025R342), King Saud University, Riyadh, Saudi Arabia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The raw data supporting the conclusions of this article will be made available by the first author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e The study protocol adhered to the ethical principles of the Declaration of Helsinki for research involving human subjects and received approval from the local research ethics committee of the High Institute of Sport and Physical Education of El Kef, University of Jendouba, Jednouba, Tunisia (reference (ISSEPK-0033/2024). It also complied with the ethical and procedural requirements for the conduct of sports medicine and exercise science research \u003csup\u003e129\u003c/sup\u003e. Since participants were minors, written informed consent was obtained from their parents or legal guardians before participation, along with verbal assent from the participants. This consent process followed a thorough explanation of the study’s methodology and a discussion of its potential risks and benefits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration:\u0026nbsp;\u003c/strong\u003eIn preparing this paper, the authors used the ChatGPT model 4 on 15 March 2024, to revise some manuscript passages, double-check for grammar mistakes, and improve academic English only. After using this tool, the authors reviewed and edited the content as necessary and took take full responsibility for the publication’s content\u0026nbsp;\u003csup\u003e130,131\u003c/sup\u003e.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAtkinson, G. \u0026amp; Reilly, T. Circadian Variation in Sports Performance. \u003cem\u003eSports Med.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e, 292\u0026ndash;312 (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDouglas, C. M., Hesketh, S. J. \u0026amp; Esser, K. A. Time of Day and Muscle Strength: A Circadian Output? \u003cem\u003ePhysiology\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e, 44\u0026ndash;51 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReilly, T. \u0026amp; Waterhouse, J. Sports performance: is there evidence that the body clock plays a role? \u003cem\u003eEur. J. Appl. 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A thorough examination of ChatGPT-3.5 potential applications in medical writing: A preliminary study. \u003cem\u003eMedicine\u003c/em\u003e \u003cb\u003e103\u003c/b\u003e, e39757 (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adolescent, Athletics, Chronobiology, Circadian Rhythms, Exercise Performance, Motor Skills, Psychometrics, Psychophysiology, Team Sports","lastPublishedDoi":"10.21203/rs.3.rs-6617578/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6617578/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examined how self-selected music during warm-up influences time-of-day (TOD) effects on short-term maximal performance in female handball players. Eighteen female athletes (age: 16.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38 years, height: 1.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 m, BMI: 20.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 kg/m\u0026sup2;) completed eight randomized sessions under two warm up conditions: with (Yes-MUS) or without (No-MUS) listening to self-selected motivational music, at four distinct times of day (08:00, 11:00, 15:00, and 18:00). A minimum recovery period of 48 hours was provided between sessions. During each session, oral temperature (OT), countermovement jump (CMJ), medicine ball throw (MBT), 20-meter sprint (20m-ST), and Illinois agility test (IAT) were recorded. The findings indicated that OT and all physical performances improved from 08 :00h to 18:00h (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The amplitude of diurnal variation was attenuated in the Yes-MUS condition for CMJ (5.7% vs. 2.3%), MBT (13% vs. 6.6%), 20m-ST (5.9% vs. 3.3%), and IAT (7.1% vs. 4.7%) compared to No-MUS. Likewise, OT variation remained unchanged across conditions (both 3.2%). Compared to No-MUS condition, performance improvements under the Yes-MUS were significant at all times : 08:00 (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 11:00 (CMJ, MBT: p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; 20m-ST, IAT: p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 15:00 (CMJ : p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, MBT : p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 20m-ST : p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, IAT : p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and 18:00 (CMJ : p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, MBT : ns, 20m-ST : p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, IAT : p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These findings suggest that self-selected motivational music during warm-up blunts diurnal performance variations and enhances anaerobic capacity in female athletes, particularly during suboptimal morning hours. Listening to music during warm-up may be an effective strategy to counteract diurnal declines in performance and optimize training outcomes among female athletes.\u003c/p\u003e","manuscriptTitle":"Effects of Self-Selected Motivational Music During Warm-Up on Time- of-Day Variations in Anaerobic Performance Among Female Handball Players","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-28 11:43:49","doi":"10.21203/rs.3.rs-6617578/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-03T14:18:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-25T15:11:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-15T21:00:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"153785778371943682847538441451316934381","date":"2025-06-15T01:39:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44097830628416479514035098726625252346","date":"2025-06-01T21:27:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-26T23:34:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-26T15:19:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-22T02:38:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-21T07:05:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-05-08T06:52:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bdf8ff71-e2b0-4f05-92af-16e0fc3ccc7e","owner":[],"postedDate":"May 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49115772,"name":"Biological sciences/Physiology"},{"id":49115773,"name":"Biological sciences/Psychology"},{"id":49115774,"name":"Health sciences/Health care"}],"tags":[],"updatedAt":"2025-11-10T15:58:29+00:00","versionOfRecord":{"articleIdentity":"rs-6617578","link":"https://doi.org/10.1038/s41598-025-21414-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-05 15:56:51","publishedOnDateReadable":"November 5th, 2025"},"versionCreatedAt":"2025-05-28 11:43:49","video":"","vorDoi":"10.1038/s41598-025-21414-7","vorDoiUrl":"https://doi.org/10.1038/s41598-025-21414-7","workflowStages":[]},"version":"v1","identity":"rs-6617578","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6617578","identity":"rs-6617578","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}