The impact of a 40‐min nap on neuromuscular fatigue profile and recovery following the 5‐m shuttle run test

This study aims to investigate the impact of a 40‐min nap opportunity on perceived recovery, exertion, and maximal voluntary isometric contraction (MVIC) following the 5‐m shuttle run test (5SRT), after 1 night of normal sleep. In a randomised, counterbalanced, cross‐over design, 17 trained men (mean [SD] age 20 [3] years, height 173 [6] cm, body mass 68 [6] kg) performed a 5SRT under two conditions: a 40‐min nap opportunity and no‐nap condition. After both conditions, electromyography signals during a 5‐s isometric knee extension were recorded before and immediately after the 5SRT. Two electrical nerve stimulations at the femoral nerve were measured during and after the MVIC. Force, voluntary activation level, M‐wave amplitudes, potentiated twitch, and electromyography signals (root mean square) were measured during each MVIC. Perceived exertion was recorded after each repetition of the test and perceived recovery was determined after the end of the MVIC. Compared to the no‐nap condition, the 40‐min nap resulted in significant enhancements in both the highest distance (p < 0.01, Δ = +7.6%) and total distance (p < 0.01, Δ = +7.5%). Before and after exercise, values for MVIC, root mean square, M‐wave amplitudes, and voluntary activation level were improved after the 40‐min nap opportunity compared to no‐nap condition (all p ≤ 0.01). Values for perceived exertion and recovery were improved after the 40‐min nap opportunity in comparison with no‐nap condition (p ≤ 0.01). A 40‐min nap opportunity improved repeated high‐intensity short‐term maximal performance, perceived recovery, associated neuromuscular responses, and reduced perceived fatigue. Therefore, our findings suggest that central and peripheral processes are involved in the improvements of 5SRT performance after napping.

Before and after exercise, values for MVIC, root mean square, M-wave amplitudes, and voluntary activation level were improved after the 40-min nap opportunity compared to no-nap condition (all p ≤ 0.01).Values for perceived exertion and recovery were improved after the 40-min nap opportunity in comparison with no-nap condition (p ≤ 0.01).A 40-min nap opportunity improved repeated high-intensity short-term maximal performance, perceived recovery, associated neuromuscular responses, and reduced perceived fatigue.Therefore, our findings suggest that central and peripheral processes are involved in the improvements of 5SRT performance after napping.

| INTRODUCTION
Daytime napping is defined as a 'short sleep', which is <50% of a person's normal sleep at night (Lastella et al., 2021).Napping is commonplace in many cultures, and this period of sleep is usually connected with the post-lunch dip (Monk, 2005).The post-lunch dip is commonly characterised by a slight decrease in body temperature that leads to a desire to sleep (Monk, 2005).Athletes frequently employ napping as a strategy to supplement their nocturnal sleep, to enhance their overall recovery from exercise.Indeed, sleep is essential for restoration process and regeneration (Driller et al., 2023).
According to previous reviews and meta-analyses, the nocturnal period of rest could be disrupted or shortened in athletes due to many factors such as increases in training load, early morning training sessions, jet lag, travel, and night time competition (Roberts et al., 2019;Walsh et al., 2021).For these reasons, napping could be a useful strategy as a supplement to an athletes' night-time sleep (Romyn et al., 2018), allowing them to reach peak athletic performance (Boukhris, Trabelsi, Ammar, et al., 2020).In this context, two systematic reviews have concluded that naps of 20-90 min are beneficial for attaining better physical performance results, independent of the previous night's sleep (Lastella et al., 2021;Souabni et al., 2021).However, according to a narrative review (Botonis et al., 2021), firm conclusions cannot be drawn with regard to the mechanisms responsible for the influence of diurnal napping on athletic performance.
Recently, it has been demonstrated that increased parasympathetic activity during napping could be a contributing factor to enhanced physical performance during the 5-m shuttle run test (5SRT; Boukhris, Trabelsi, et al., 2022).Additionally, it has been revealed that athletic performance enhancement after diurnal napping could be explained by a reduction of muscle damage and inflammation, along with a reduction of muscle soreness and perceived exertion, and an amelioration in perceived recovery (Boukhris et al., 2021).Nevertheless, as far as we know, no prior study has examined the impacts of napping on neuromuscular responses to high-intensity repeated maximal efforts.In order to explore neuromuscular fatigue, surface electromyography (EMG) can be used to evaluate the level of activation of the muscles, by the collection of myoelectric activity during voluntary maximal muscular contractions (Hägg et al., 2000).This experimental technique may provide information on peripheral and/or central fatigue following napping.As athletes are frequently exposed to exercises that involve both peripheral and central fatigue, it is important to see if napping could minimise these peripheral and central factors.Central fatigue is associated with a decrease in muscle force production due to a decrease in voluntary muscle activation, as well as a decrease in the EMG signal during contractions because the central nervous system becomes exhausted and is unable to adequately activate the muscle fibres (Taylor et al., 2016).Peripheral fatigue, on the other hand, is associated with a decrease in muscle force production due to changes at the neuromuscular junction, which can be reflected in the EMG signal because the muscle fibres themselves become exhausted and are unable to contract fully (Taylor et al., 2016).The neuromuscular fatigue experienced during the 5SRT has been shown to involve both peripheral and central factors (Boukhris, Zghal, et al., 2022).Therefore, 5SRT is regarded as an appropriate exercise to evaluate the effect of napping on neuromuscular fatigue.While previous research has indeed demonstrated improved performance in the 5SRT following daytime napping (Boukhris et al., 2019;Boukhris et al., 2021;Boukhris, Trabelsi, et al., 2022;Boukhris, Trabelsi, Ammar, et al., 2020), a critical aspect that remains to be explored is the underlying mechanism driving this enhancement.Specifically, the extent to which this performance improvement can be attributed to a significant reduction in neuromuscular fatigue, including both peripheral and central fatigue, remains an interesting area of investigation.Understanding the relationship between napping and its potential impact on neuromuscular fatigue could reveal valuable insights into the physiological foundations of improved athletic performance offered by daytime napping.Thus, the objective of the present study was to assess the impact of a 40-min nap opportunity on perceived recovery (perceived recovery status scale [PRS]), perceived exertion (rating of perceived exertion [RPE]), maximal voluntary isometric contraction (MVIC), and EMG in response to the 5SRT after 1 night of normal sleep ($8 h).The choice of a 40-min nap duration in our study is based on the findings of a recent meta-analysis (Mesas et al., 2023), which suggests that naps lasting between 30 and <60 min have been associated with improved physical performance.We presume that an enhancement in short-term maximal performance and a reduction in neuromuscular fatigue will be observed following a 40-min nap compared to the no-nap condition (CON).

| Participants
A total of 17 male athletes trained in team sport (soccer [eight], rugby

| Experimental design
Following a familiarisation session conducted 1 week before the study, during which participants were introduced to all testing measures, participants completed two experimental trials in a randomised, counterbalanced, cross-over design: CON and a 40-min nap.All testing was performed at 5:00 p.m. with at least 72 h and a maximum of 96 h between experimental trials.In each testing session, participants were provided with a standardised lunch at 12:30 p.m.After 12:30 p.m., participants were permitted only to drink water.In the nap condition, participants went to bed in a dark, quiet sleep laboratory at 1:45 p.m.The 40-min nap opportunity was from 2:00 p.m. to 2:40 p.m.The period between 1:45 p.m. and 2:00 p.m. was allocated to participants to be acclimated to the napping environment.For CON, participants spent the same amount of time watching television or playing sports video games in a comfortable armchair.Before and after each experimental condition daytime sleepiness was recorded using the Stanford Sleepiness Scale (SSS; Hoddes et al., 1973).Additionally, sleep during the 40-min nap trial was assessed upon awakening using a 0-10 scale, with '0' being 'no sleep', '5' being 'some sleep with some interruptions', and '10' being 'uninterrupted, deep sleep throughout' (Waterhouse et al., 2007).
From 2:40 p.m. to 5:00 p.m., participants engaged in their usual activities such as watching television or playing sport video games, but they refrained from participating in any physical activity.This time was allowed to minimise the risk of sleep inertia.At 5:00 p.m., participants executed a 5-min warm-up (5-min jog at a self-chosen adequate pace, then some series of dynamic stretching over 5 min such as hip abduction/adduction, hip flexion/extension, butt kicks, and five progressive accelerations carried out over a 10-m distance).Participants then completed the following tests in the same order: MVIC with EMG and electrical nerve stimulation, the 5SRT, and a second MVIC/ EMG.Perceived exertion (RPE) was recorded after every repetition of the 5SRT.The PRS was determined immediately after the MVIC/EMG was concluded.The experimental design is summarised in Figure 1.

| Actigraphy
Participants were wearing GT3X activity monitors on the non-dominant wrist (Actigraph, Pensacola, FL, USA) to record sleep patterns during the night before each test session (i.e., to ensure compliance with a similar sleep-wake schedule before each experimental trial) and during the diurnal napping opportunity.The Actilife 6 (Version 6.13.1, ActiGraph) software was used for analysing sleep patterns and wake behaviours.The Sadeh algorithm was utilised for calculating sleep metrics owing to its overall high accuracy in comparison to that of polysomnography (PSG; Slater et al., 2015).The sleep parameters obtained were sleep efficiency, sleep latency, bedtime, wake time, total sleep time, and total time in bed.The GT3X is considered a reliable and valid device for sleep and wake behaviours (Cellini et al., 2013).

| The 5SRT
During the test, volunteers were required to realise six repetitions of maximal sprints separated by 35 s of recovery.Each repetition lasted 30 s and consisted of a maximal shuttle to 5, 10, 15, 20, 25, and 30 m (Boukhris, Trabelsi, Abdessalem, et al., 2020).In each sprint, the objective was to cover the maximum distance within the 30-s time frame.
At the signal 'Ready!', the participant positioned themselves at the • Total distance (TD, m) = the total distance achieved during the six 30-s shuttles.
• Fatigue index (FI, %) = determined as follows  which is a measure that indicates the physiological activity in the motor unit during contraction (Fukuda et al., 2010), were calculated over a 0.5-s period of the MVIC plateau, before the superimposed stimulation.intensity has been specified from M-wave and twitch torque measurements before the tests.In brief, the stimulation intensity was raised by 5 mA until there was no additional rise in either the peak twitch force (i.e., plateau in knee extensor twitch force) or in concomitant VL, VM and RF peak-to-peak M-wave amplitudes (M max ).In subsequent procedures for testing, the intensity was defined at 150% of the peak stimulation intensity to prevail over the potential confounding effect of axonal hyperpolarisation (Burke, 2002).During every MVIC, two instances of electrical stimulation were administered via the femoral nerve.The initial stimulation, applied during the MVIC, was termed the superimposed twitch, while the subsequent stimulation occurring after a 3-s interval from the MVIC was referred to as the potentiated resting twitch (Ptw).This 3-s delay was implemented to acquire an intensified mechanical response, aiming to minimise measurement variability as compared to an unpotentiated twitch (Kufel et al., 2002).
To explain possible changes in physical measures, correlations between variables were investigated using Pearson correlation coefficient for data normally distributed or Spearman correlation coefficient for data not normally distributed.
Statistical significance was set at p < 0.05 for all analyses.Precise p values are being offered; however, results reported as '0.000' in the statistics output have been described as '<0.0005'.

| Actigraphy
Sleep parameters (i.e., bedtime, wake time, sleep latency, sleep efficiency, total time in bed, and total sleep time) were similar during the night preceding the CON and the 40-min nap trials (p > 0.05; Table S1).
Additionally, the SSS recorded after the 40-min nap was 47% lower than after CON ( p < 0.0005).

| The EMG responses
The RMS, M max , Ptw, and VAL values are presented in Table 2.

| The VAL
There were significant main effects of Time (F = 96.09,p < 0.0005, The RPE scores at the end of the 5SRT were 14.2% lower after the 40-min nap in comparison with CON (Z = 3.17, p = 0.001, d = 1.69;Table 1).T A B L E 1 Highest distance, total distance, fatigue index, rating of perceived exertion (RPE) and perceived recovery status (PRS) scores recorded after the no-nap condition (CON) and the 40-min nap opportunity condition (NAP) for the 5-m shuttle run test (5SRT).

| The PRS
Statistical analysis showed that the PRS was 24.8% higher after the 40-min nap in comparison with CON (Z = 3.18, p = 0.001, d = 1.83;Table 1).

| Correlations
Spearman test showed that changes in TD were significantly correlated to changes in VAL recorded before (r = 0.55, p = 0.01) and after (r = 0.52, p = 0.03) 5SRT.In addition, Spearman test showed that changes in MVIC were significantly correlated to changes in PRS (r = 0.54, p = 0.02).However, no significant correlations were found between the remaining variables.

| DISCUSSION
This is the first study to the impacts of daytime napping opportunity on repeated high-intensity short-duration maximal performance and associated neuromuscular responses following a normal night of sleep ($8 h).The main findings are that a nap opportunity enhanced 5SRT performance and MVIC.Additionally, a 40-min nap opportunity positively affected neuromuscular responses to the 5SRT, except Ptw.
Furthermore, the RPE and PRS scores were associated with positive findings for the napping condition.
In the present study, the sleepiness score was reduced after the nap opportunity, which may explain improvements in MVIC, HD, and TD.In fact, after a diurnal nap, interleukin 6 levels are reduced (Vgontzas et al., 2007).An increase in interleukin 6 is related to heightened muscle damage (Bruunsgaard et al., 1997) and fatigue sensation (Robson-Ansley et al., 2004).Therefore, participants in the present study were perhaps able to better perform after a nap opportunity because it was perceived as less difficult.This is supported by the fact that the RPE scores during the 5SRT decreased after the 40-min nap opportunity compared to CON.These observations are in agreement with previous studies (Boukhris et al., 2019;Boukhris, Trabelsi, Ammar, et al., 2020;Boukhris et al., 2021;Boukhris, Trabelsi, et al., 2022) which also reported significant reductions in RPE scores during the 5SRT following nap opportunities.In addition, the results of the present study demonstrated that napping was associated with higher perceived recovery after the 5SRT compared to CON.To support this finding, a significant correlation was observed between changes in the PRS and changes in MVIC recorded after the 5SRT.This correlation could support the idea that napping could lead to an improved recovery status for the participants.It has been reported that a 1-h nap positively affected subjective mood and ratings of tiredness (Brotherton et al., 2019).Thus, the improvement of performance during the 5SRT after the 40-min nap may be related to the reduction of the perceived exertion and an enhancement in perceived recovery.
Daytime napping also seems to have a positive influence on the central mechanisms responsible for fatigue engendered by 5SRT.
The central factors of fatigue include decreases in the voluntary activation of the muscle, typically due to reductions in the number of recruited motor units and their discharge rate (Boukhris, Zghal, et al., 2022).In this context, VAL recorded during CON was lower in comparison to the 40-min nap, as well as the VAL's decrement before to after 5SRT was significantly less in the 40-min nap than CON (13.1% in CON versus 5.6% in NAP).To further support these findings, changes in TD were significantly correlated with changes in VAL recorded at before and after 5SRT.This correlation supports the idea that central mechanisms might indeed contribute to the improvement in performance during the 5SRT.
Additionally, surface EMG activity level, that is, RMS, recorded during the MVIC measured before and after the 5SRT, was used as an  index of the level of the physiological activities in the motor unit during a muscular contraction (Fukuda et al., 2010).The fact that RMS values were higher during the 40-min nap in comparison with CON could suggest that neural drive was positively affected by the nap.
The decrease in M max values of the EMG signal indicates a neuromuscular transmission failure, suggesting a partially peripheral origin of the fatigue (Boukhris, Zghal, et al., 2022).MVIC was measured before and after the 5SRT in order to quantify the neuromuscular responses.MVIC decreased before to after 5SRT, and this decrement was significantly less in the 40-min nap than CON (11.1% in CON versus 8.1% in NAP), indicating less fatigue occurred after napping.
Taking into account the positive results of the M max during the 40-min nap in comparison with CON, it appears napping may reduce the magnitude of the alterations (i.e., neuromuscular transmission) caused by peripheral fatigue.However, the present study revealed that the contractile properties of the muscle were not influenced by the napping opportunity.The Ptw, which provides information on the contractile properties of the muscle (Boukhris, Zghal, et al., 2022), were not significantly different between conditions.One possible explanation for the absence of significant enhancement of Ptw is the duration of the nap.It has been reported that muscle contraction efficiency is improved when rapid eye movement (REM) sleep is included (Cai, 2015).However, it is expected that our participants did not reach the REM stage of sleep with only a 40-min napping window.Indeed, it is shown that a mean (SD) of 0.19 (0.75) min of REM sleep are observed in a 60-min napping opportunity (Petit et al., 2014).
The positive effect of the nap opportunity on the EMG parameters (i.e., RMS, M max , and VAL) in the present study could be explained by the amount of time spent in non-REM (NREM) sleep during the nap.In fact, NREM sleep is known for restoring and repairing the body, which might explain the beneficial impact of a diurnal nap on physiological measures (Souabni et al., 2023).In this context, it has been shown that the increase of muscle damage and inflammation during the 5SRT was minimised due to the impact of napping (Boukhris et al., 2021), confirming that daytime napping decreases peripheral fatigue.Moreover, due to the higher parasympathetic activation observed during napping (Boukhris, Trabelsi, et al., 2022), the NREM sleep period during a diurnal nap could facilitate neural and peripheral cellular restoration and improve energy conservation (Botonis et al., 2021).Therefore, the decrease of central fatigue observed after napping could be most apparent due to higher parasympathetic activation during the afternoon nap.
A limitation of the present study is the absence of a measurement

| CONCLUSION
A 40-min napping opportunity following a normal night sleep time was associated with improvements in physical performance and reduced fatigue during a MVIC and a 5SRT.This enhancement of performance associated with napping may be explained by a decrease in central and peripheral fatigue and lower perceived exertion, sleepiness, and higher perceived recovery status.Therefore, napping could be a good strategy to ameliorate muscle force and improve performance in exercises that solicit peripheral and/or central fatigue.
From a practical point of view, napping could be implemented to decrease neuromuscular fatigue and enhance athletic performance in competitions or high-intensity training.

[
four], handball [five]) volunteered for the presnt study (mean [SD] age 20 [3] years, height 173 [6] cm, body mass 68 [6] kg).After obtaining an explanation of the protocol, possible risks, and advantages of this study, every volunteer provided written informed consent.The study was done under the declaration of Helsinki and the protocol was fully endorsed by the Institutions' Ethics Committee before the beginning of any data collection (CPP: 0098/2018).The criteria for participants' inclusion in the present study were as follows: they had no major sleep issues (i.e., each scored <5 on the Pittsburgh Sleep Quality Index), did not drink alcohol 24 h before the day of each experimental trial, and were non-smokers.Participants were regularly involved in training for $2 h/day for 4 days/week.Participants were recruited by advertising in university classes and posting notices on bulletin boards in local team sport clubs and gyms.
starting line.Upon the 'Go!' command, the 30-s timer commenced, and the participant sprinted towards the 5-m mark.After reaching the 5-m point, they swiftly changed direction and sprinted back to the starting line.Upon crossing the start line, they again changed direction abruptly, sprinting this time to the 10-m mark before returning to the start line.The pattern continued, with the participant aiming to shuttle back and forth to the 15-m mark.If time allowed, they would proceed to the 20-m mark, then potentially the 25-m mark, and finally, if time permitted, to the 30-m mark.The distance achieved in each repetition was recorded and the following indices were used for analysis • Highest distance (HD, m) = the longest distance achieved during a single 30-s shuttle.
The MVIC An isometric dynamometer (Good Strength, Metitur, Finland) fitted out with a cuff connected to a strain gauge was utilised to measure MVIC.The cuff was attached to the anterior aspect of the lower limb using a Velcro strap placed $2 cm above the lateral malleolus to minimise uncontrolled movements.The knee and hip angles were posed at 90 (knee full extension = 0 ) and participants were seated during testing.To stay away from vertical, lateral, or frontal movements, seat belts were tied around the chest, hips, and thighs.All tests were performed on the right side of the body.Participants were required to perform three $3 s maximal voluntary knee extensions against the lever arm with 2-min recovery between each.Strong verbal encouragement was given to all participants during each MVIC.The highest MVIC value was used for the final analysis.

2. 5
| Neuromuscular fatigue 2.5.1 | Surface EMG recordings During MVIC and nerve stimulations, bipolar silver chloride surface electrodes (Blue Sensor N-00-S, Ambu, Denmark) were utilised to record the EMG signals of the rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL) muscles.The recording electrodes were attached to the skin in a direction parallel with the muscle belly following SENIAM (Surface Electromyography for the Non-Invasive Assessment of Muscles) recommendations (Hermens et al., 2000), with an inter-electrode distance of 20 mm.A reference electrode was affixed to the patella.Low impedance (Z < 5 kΩ) at the skin-electrode surface was acquired by shaving, abrading the skin with thin sandpaper, and cleaning with alcohol.A bandwidth frequency that ranges from 10 to 1 kHz (common mode rejection ratio >96 dB, gain = 1000) was used to amplify EMG signals (Octal Bio Amp ML 138, ADInstruments, Australia).An acquisition card (Powerlab 16SP, ADInstruments) and LabChart 7.0 software (ADInstruments) were used to digitise both EMG and force signals.The sampling frequency was 2 kHz.The root mean square (RMS) values of the VM, VL, and RF EMG recordings, Using a constant current stimulator (Digitimer DS7A, Hertfordshire, UK), a single square-wave stimulus of 1-ms duration, with a maximal voltage of 400 V, was used to stimulate the femoral nerve.In the femoral triangle, a cathode (self-adhesive electrode: Ag-AgCl, 10-mm diameter, type 0601000402; Contrôle Graphique Medical, Brie-Comte-Robert, France) was placed and pressed securely into place by the researcher.The anode, a 10 Â 5 cm self-adhesive stimulation electrode (Medicompex SA, Ecublens, Switzerland), was positioned midway between the iliac crest and the greater trochanter.Optimal stimulation F I G U R E 1 Schematic depiction of the experimental protocol.#, rating of perceived exertion; EMG, electromyography; MVIC, maximal voluntary isometric contractions; PRS, perceived recovery status; SSS, Stanford Sleepiness Scale.
were analysed: Ptw and M max of the VM, VL, and RF muscles, which are measures indicating peripheral fatigue.Voluntary activation level (VAL), which is a measure indicating central fatigue, was calculated using both superimposed and potentiated twitches amplitude as follows:VAL (%) = [1superimposed twitch/Ptw] Â 100.2.6 | Subjective measures2.6.1 | Rating of perceived exertion (RPE)Immediately after every repetition of the 5SRT, participants reported their subjective RPE(Haddad et al., 2013) from a scale of 0 (no exertion) to 10 (maximal exertion).The RPE mean score during the 5SRT was determined applying the subsequent formula: RPE AU ð Þ¼ Sum of RPE scores after all repetitions Number of repetitions 2.6.2 | Perceived recovery status scale (PRS) Data are shown as means ± standard deviation (SD) and were tested utilising the Statistica software (StatSoft, France; version 10).The normality of the distributions was proved applying the Shapiro-Wilk test.Data of bedtime, HD, TD, FI, RPE (mean values), MVIC, RMS, M max , Ptw, and VAL were normally distributed.Therefore, parametric tests were conducted.However, data of wake time, sleep latency, sleep efficiency, total sleep time, total time in bed, SSS, PRS, and RPE (at the end of the 5SRT) were not normally distributed.Therefore, non-parametric tests were conducted.A Student's t test was used for the HD, TD, FI, RPE (mean values), bedtime, between the two experimental trials.A two-way ANOVA (Condition Â Time) was used for MVIC, RMS, M max , Ptw, and VAL.When appropriate, post hoc comparisons were realised with the Bonferroni test.A Friedman nonparametric analysis of variance (Friedman's Test) was applied only on SSS.Pairwise comparisons were conducted on SSS, PRS, RPE (at the end of the 5SRT), sleep efficiency, sleep latency, wake time, total sleep time, and total time in bed, utilising a Wilcoxon test.

F
I G U R E 3 Maximal voluntary isometric contractions (MVIC) from pre to post 5-m shuttle run test in the no-nap condition (CON) and the 40-min nap opportunity condition (NAP).#: significant pre-post difference; *significant difference compared to CON.Bars represent mean values and error bars represent SD.

T A B L E 2
Maximal voluntary isometric contractions (MVIC), root mean square (RMS), peak-to-peak M-wave amplitudes (M max ), potentiated twitch (Ptw), and voluntary activation level (VAL) were measured before and after the 5-m shuttle run test (5SRT) in the no-nap condition (CON) and the 40-min nap opportunity condition (NAP).
of sleep staging during napping using techniques such as PSG.In fact, the assessment of sleep stages could contribute to a more comprehension understanding of the underlying mechanisms and a more effective exploitation of the benefits offered by napping.Therefore, in order to enhance the explanation of the present findings, future studies should determine the specific sleep phases participants experienced during their naps and linking these phases to the observed post-nap changes.Further, understanding the phase of sleep (e.g., N1, N2, N3, REM) that participants wake up in, may give insight into sleep inertia and subsequent performance metrics.Moreover, the sleep monitors used in the present study probably overestimated sleep time(Cellini et al., 2013).Therefore, the use of PSG or other technological advancements similar to PSG is recommended for future studies.Additionally, the present findings cannot be generalised to all populations, as the present study examined the impact of napping on healthy athletes with normal sleep.Moreover, it is important to note that the present study did not investigate potential variations in outcomes based on the specific choice of activities performed during the control condition or between the end of napping and testing measures.It is worth noting that all of the athletes in the study were able to nap (for $35 min on average), with no correlation between length of nap and outcome measures.This indicates the effectiveness of the napping opportunity window regardless of total sleep duration when compared to CON.Future studies should consider recording and standardising control activities across participants to further enhance the comprehensiveness of the findings.