The Importance of Monitoring Sleep within Adolescent Athletes: Athletic, Academic, and Health Considerations

Association between Low Energy Availability (LEA) and Impaired Sleep Quality in Young Rugby Players

Low energy availability (LEA) has been associated with several physiological consequences, but its impact on sleep has not been sufficiently investigated, especially in the context of young athletes. This study examined the potential association between energy availability (EA) status and objective sleep quality in 42 male rugby players (mean age: 16.2 ± 0.8 years) during a 7-day follow-up with fixed sleep schedules in the midst of an intensive training phase. Participants' energy intake was weighed and recorded. Exercise expenditure was estimated using accelerometry. Portable polysomnography devices captured sleep on the last night of the follow-up. Mean EA was 29.3 ± 9.14 kcal·kg FFM-1·day-1, with 47.6% of athletes presenting LEA, 35.7% Reduced Energy Availability (REA), and 16.7% Optimal Energy Availability (OEA). Lower sleep efficiency (SE) and N3 stage proportion, along with higher wake after sleep onset (WASO), were found in participants with LEA compared to those with OEA (p = 0.04, p = 0.03 and p = 0.005, respectively, with large effect sizes). Segmented regression models of the EA-sleep outcomes (SE, sleep onset latency [SOL]), WASO and N3) relationships displayed two separate linear regions and produced a best fit with a breakpoint between 21-33 kcal·kg FFM-1·day-1. Below these thresholds, sleep quality declines considerably. It is imperative for athletic administrators, nutritionists, and coaches to conscientiously consider the potential impact of LEA on young athletes' sleep, especially during periods of heavy training.

Sleep and the Young Athlete

CONTEXT

Sleep plays a vital role in cognitive and physical performance. Teenage athletes (ages 13-19 years) are considered especially at risk for disordered sleep and associated negative cognitive, physical, and psychosomatic effects. However, there is a paucity of evidence-based recommendations to promote sleep quality and quantity in athletes who fall within this age range. We performed a review of the literature to reveal evidence-based findings and recommendations to help sports instructors, athletic trainers, physical therapists, physicians, and other team members caring for young athletes provide guidance on sleep optimization for peak sports performance and injury risk reduction.

METHODS

PubMed, Scopus, and Cochrane CENTRAL were searched on May 11, 2016, and then again on September 1, 2020, for relevant articles published to date.

STUDY DESIGN

Narrative review.

LEVEL OF EVIDENCE

Level 4.

RESULTS

Few studies exist on the effects disordered sleep may have on teenage athletes. By optimizing sleep patterns in young athletes during training and competitions, physical and mental performance, and overall well-being, may be optimized. Adequate sleep has been shown to improve the performance of athletes, although further studies are needed.

CONCLUSION

Twenty-five percent of total sleep time should be deep sleep, with a recommended sleep time of 8 to 9 hours for most young athletes. Screen and television use during athletes' bedtime should be minimized to improve sleep quality and quantity. For young athletes who travel, jet lag can be minimized by allowing 1 day per time zone crossed for adjustment, limiting caffeine intake, planning meals and onboard sleeping to coincide with destination schedules, timing arrivals in the morning whenever possible, and using noise-canceling headphones and eyeshades.

STRENGTH-OF-RECOMMENDATION TAXONOMY (SORT)

B.

Sleep Quality and Well-Being in Junior Elite Athletes

Abstract. Little cross-sectional and even less longitudinal research has been conducted on sleep quality and well-being in junior elite athletes. This study analyzed the relationship between subjective sleep quality and both psychological and physiological well-being in junior elite athletes using both a cross-sectional ( N = 625 athletes; 49.9 % = female; M = 16.4 years, SD = 3.5 years) and a longitudinal approach ( n = 79; 44.3 % = female; M = 16.4 years, SD = 3.5 years) over a period of M = 1.66 years ( SD = 0.87 years). The results demonstrated that both samples showed that subjective sleep quality is correlated with well-being in junior elite athletes. In addition, the results showed that athletes of prepuberty age reported significantly better sleep quality than athletes during and after puberty, and that the relationship between sleep quality and psychological well-being is stronger in female junior athletes than in male athletes. This study emphasizes the need to ensure quality sleep in junior elite athletes.

Examining the trajectory and predictors of post-concussion sleep quality in children and adolescents

OBJECTIVES

This study aimed to 1) determine if post-concussion sleep quality of children and adolescents differed from healthy sleep estimates; 2) describe the trajectory of parameters of sleep quality; 3) determine factors that predict sleep quality outcomes; and 4) compare sleep parameter outcomes between asymptomatic and symptomatic participants at 4 weeks post-concussion.

METHODS

Nightly actigraphy estimates of sleep in 79 children and adolescents were measured throughout 4 weeks post-concussion. Total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), number of arousals (NOA), and average arousal length (AAL) were measured.

RESULTS

Child and adolescent participants experienced significantly poorer SE and longer WASO duration throughout 4 weeks of recovery and adolescents experienced significantly longer TST. SE significantly improved with time post-injury (p = .047). Older age was associated with longer TST (p = .003) and female sex was associated with longer WASO (p = .025) and AAL duration (p = .044). Week 4 sleep parameter outcomes were not significantly different between asymptomatic and symptomatic participants.

CONCLUSIONS

The sleep quality of youth is adversely affected by concussion, particularly in females. Sleep quality appears to improve with time but may require more than 4 weeks to return to normal.

"The Competitive Season and Off-Season": Preliminary Research concerning the Sport-Specific Performance, Stress, and Sleep in Elite Male Adolescent Basketball Athletes

BACKGROUND

Through scholastic sports programs, adolescent athletes compete to represent their communities. However, few studies investigate the changes in physiological and mental profiles during varied sport periodization among this population. Therefore, the purpose of this study was to compare the changes in sports performance and stress-related biomarkers between the competitive season (CS) and off-season (OS) in elite adolescent basketball players.

METHOD

Nine elite Division I male basketball players (age: 15-18 years. old) participated in this study. Basketball-specific performance, salivary dehydroepiandrosterone sulfate (DHEA-S)/cortisol levels, mood state, and sleep quality were all accessed during the CS and OS periods.

RESULTS

The training load during OS was 26.0% lower than CS (p = 0.001). Muscle mass, aerobic capacity, 10 m sprint, and Abalakov jump (AJ) power during OS were greater than that during CS (+2.2-9.8%, p < 0.05), but planned agility was greater during CS (p = 0.003). The salivary DHEA-S/cortisol was greater during CS than during OS (p = 0.039). The overall mood state and sleep quality did not differ between periods, but the POMS-tension was higher during CS (p = 0.005).

CONCLUSION

The present study demonstrates that muscle mass, aerobic capacity, peak AJ power, and 10 m sprint performance, but not planned agility, were greater during OS compared to CS among elite adolescent basketball players. Furthermore, the stress-related responses reflected by the D/C ratio and mood tension were relatively lower during the OS in these athletes. Thus, this study suggests that coaches and sport science professionals should closely monitor athletes' training states across varied training/competition periods to better react to modifying training or recovery plans.

COVID-19 Lockdowns: A Worldwide Survey of Circadian Rhythms and Sleep Quality in 3911 Athletes from 49 Countries, with Data-Driven Recommendations

Objective

In a convenience sample of athletes, we conducted a survey of COVID-19-mediated lockdown (termed ‘lockdown’ from this point forward) effects on: (i) circadian rhythms; (ii) sleep; (iii) eating; and (iv) training behaviors.

Methods

In total, 3911 athletes [mean age: 25.1 (range 18–61) years, 1764 female (45%), 2427 team-sport (63%) and 1442 elite (37%) athletes] from 49 countries completed a multilingual cross-sectional survey including the Pittsburgh Sleep Quality Index and Insomnia Severity Index questionnaires, alongside bespoke questions about napping, training, and nutrition behaviors.

Results

Pittsburgh Sleep Quality Index (4.3 ± 2.4 to 5.8 ± 3.1) and Insomnia Severity Index (4.8 ± 4.7 to 7.2 ± 6.4) scores increased from pre- to during lockdown (p < 0.001). Pittsburgh Sleep Quality Index was predominantly influenced by sleep-onset latency (p < 0.001; + 29.8%), sleep efficiency (p < 0.001; − 21.1%), and total sleep time (p < 0.001; − 20.1%), whilst Insomnia Severity Index was affected by sleep-onset latency (p < 0.001; + 21.4%), bedtime (p < 0.001; + 9.4%), and eating after midnight (p < 0.001; + 9.1%). During lockdown, athletes reported fewer training sessions per week (− 29.1%; d = 0.99). Athletes went to bed (+ 75 min; 5.4%; d = 1.14) and woke up (+ 150 min; 34.5%; d = 1.71) later during lockdown with an increased total sleep time (+ 48 min; 10.6%; d = 0.83). Lockdown-mediated circadian disruption had more deleterious effects on the sleep quality of individual-sport athletes compared with team-sport athletes (p < 0.001; d = 0.41), elite compared with non-elite athletes (p = 0.028; d = 0.44) and older compared with younger (p = 0.008; d = 0.46) athletes.

Conclusions

These lockdown-induced behavioral changes reduced sleep quality and increased insomnia in athletes. Data-driven and evidence-based recommendations to counter these include, but are not limited to: (i) early outdoor training; (ii) regular meal scheduling (whilst avoiding meals prior to bedtime and caffeine in the evening) with appropriate composition; (iii) regular bedtimes and wake-up times; and (iv) avoidance of long and/or late naps.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40279-021-01601-y.

Subjective Sleep Patterns and Jet Lag Symptoms of Junior Netball Players Prior to and During an International Tournament: A Case Study

PURPOSE

To assess the impact of long-haul transmeridian travel on subjective sleep patterns and jet lag symptoms in youth athletes around an international tournament.

METHODS

An observational descriptive design was used. Subjective sleep diaries and perceived responses to jet lag were collected and analyzed for a national junior netball team competing in an international tournament. Sleep diaries and questionnaires were completed daily prior to and during travel, and throughout the tournament. Results were categorized into pretravel, travel, training, and match nights. Means were compared performing a paired Student t test with significance set at P < .05. Data are presented as mean (SD) and median (minimum, maximum).

RESULTS

Athletes reported significantly greater time in bed on match days compared with training (P < .001) and travel (P = .002) days, and on pretravel days compared with travel (P < .001) and training (P = .028) days. Sleep ratings were significantly better on pretravel days compared with match (P = .013) days. Perceived jet lag was worse on match (P = .043) days compared with pretravel days. Significant differences were also observed between a number of conditions for meals, mood, bowel activity, and fatigue.

CONCLUSION

Youth athletes experience significantly less opportunity for sleep during long-haul transmeridian travel and face disruptions to daily routines during travel which impact food intake. Young athletes also experience disturbed sleep prior to and during competition. These results highlight the need for practices to alleviate jet lag symptoms and improve the sleep of young athletes traveling for tournaments in an effort to optimize recovery and performance.

The Use of Recovery Strategies in Professional Soccer: A Worldwide Survey

PURPOSE

To survey soccer practitioners' recovery strategy: (1) use, (2) perceived effectiveness, and (3) factors influencing their implementation in professional soccer.

METHODS

A cross-sectional convenience sample of professional soccer club/confederation practitioners completed a web-based survey (April to July 2020). Pearson chi-square and Fisher exact tests with Cramer V (φ - c) assessed relationships and their strength, respectively, between the perceived effectiveness and frequency of strategy use.

RESULTS

A total of 80 soccer practitioners (13 countries) completed the survey. The 3 most important recovery objectives were "alleviating muscle damage/fatigue," "minimizing injury risk," and "performance optimization." The most frequently used strategies were active recovery, structured recovery day, extra rest day, massage, cold-water therapy, and carbohydrate provision (predominantly on match day and match day + 1). Relationships were identified between perceived effectiveness and frequency of strategy use for sleep medication (P < .001, φ - c = 0.48), carbohydrate provision (P = .007, φ - c = 0.60), protein provision (P = .007, φ - c = 0.63), an extra rest day (P < .001, φ - c = 0.56), and a structured recovery day (P = .049, φ - c = 0.50).

CONCLUSIONS

The study demonstrates that professional soccer practitioners have a range of objectives geared toward enhancing player recovery. A disconnect is apparent between the perceived effectiveness of many recovery strategies and their frequency of use in an applied setting. Novel data indicate that strategies are most frequently employed around match day. Challenges to strategy adoption are mainly competing disciplinary interests and resource limitations. Researchers and practitioners should liaise to ensure that the complexities involved with operating in an applied environment are elucidated and apposite study designs are adopted, in turn, facilitating the use of practically effective and compatible recovery modalities.

Evidence That Sleep Is an Indicator of Overtraining during the Competition Phase of Adolescent Sprinters

Although sleep disturbance is a common complaint in overtrained athletes, the role of sleep in the overtraining process is not clear. This study aimed (i) to compare sleep efficiency/quantity at the start of a competition phase in elite adolescent sprinters who adapted to prior training with that in those who maladapt and (ii) to examine the influence of prior training, fatigue, and sleep on performance through a moderated mediation model. Fatigue (via Profile of Mood State) and internal training load (via session rating of perceived exertion and duration of training as volume) were measured in 20 sprinters (mean age: 15.9 ± 1.7 years) across 4 mesocycles (baseline (T1); preparatory (T2); precompetitive (T3); and competitive (T4) phases), over 26 weeks. Performances were assessed during the competitive period (T3, T4), while sleep was monitored (via actigraphy) for a week during T4. It was inferred that sprinters who had increasingly greater fatigue and concomitant decrements in performance (35%) were maladapted to training and the remaining sprinters who improved fatigue and performance (65%) were adapted to training. Sleep efficiency (91 ± 3% vs. 82 ± 3%, p < 0.001) and quantity (425 ± 33 min vs. 394 ± 20 min, p < 0.001) at the start of T4 were significantly greater in sprinters who adapted. Moreover, higher prior training volume (mean of T1 to T3 training volume) was associated with lower sleep efficiency at the start of T4 (R² = 0.55, p < 0.001) which was associated with poorer performance (R² = 0.82, p < 0.001). Fatigue moderated the indirect effect of prior training volume on performance through its moderation of the effect of sleep efficiency on performance (R² = 0.89, p < 0.001). Impaired sleep as a result of greater prior training volume may be related to performance decrements through fatigue. Athletes should improve sleep during periods of higher training volume to reduce fatigue for better adaptation to training.

Influence of Perceptions of Sleep on Well-Being in Youth Athletes

ABSTRACT

Sawczuk, T, Jones, B, Scantlebury, S, and Till, K. Influence of perceptions of sleep on well-being in youth athletes. J Strength Cond Res 35(4): 1066-1073, 2021-To date, most research considering well-being questionnaires has only considered the training stress imposed on the athlete, without evaluating the questionnaire's relationship with a measure of recovery (e.g., sleep). This study aimed to assess the influence of sleep duration (Sduration), sleep quality (Squality), and sleep index (Sindex; Sduration × Squality) on well-being in youth athletes, while accounting for the known training stressors of training load and exposure to match play. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily questionnaire including well-being (DWBno-sleep; fatigue, muscle soreness, stress, and mood) measures, Perceived Recovery Status Scale (PRS), the previous day's training loads, Sduration, and Squality every day for 13 weeks. Linear mixed models assessed the impact of Sduration, Squality, and Sindex on DWBno-sleep, its individual subscales, and PRS. Sduration had a small effect on DWBno-sleep (d = 0.31; ±0.09), fatigue (d = 0.42; ±0.11), and PRS (d = 0.25; ±0.09). Squality had a small effect on DWBno-sleep (d = 0.47; ±0.08), fatigue (d = 0.53; ±0.11), stress (d = 0.35; ±0.07), mood (d = 0.41; ±0.09), and PRS (d = 0.37; ±0.08). Sindex had a small effect on DWBno-sleep (d = 0.44; ±0.08), fatigue (d = 0.55; ±0.11), stress (d = 0.29; ±0.07), mood (d = 0.37; ±0.09), and PRS (d = 0.36; ±0.09). The results indicate that an athlete's perceptions of sleep are associated with deviations in well-being measures and should be used as an input to the monitoring process rather than as part of the outcome well-being score. The sleep index is suggested as a potential input because it provides information on both the duration and quality of the sleep experienced.

Sleep pattern and staging in elite adolescent rugby players during the in-season competitive phase compared to an age matched non-athlete population

Young athletes must contend with the constraints of elite sports on top of school commitments and the physiological processes associated with adolescence. This study assessed week and weekend sleep and schedule of activities in elite adolescent rugby players during the in-season competitive phase compared with age-matched non-athlete controls. 32 adolescents (GR: 16 elite rugby players, GC: 16 controls) from the same boarding school filled out a daily schedule of activities and a sleep diary, and wore a multichannel electroencephalogram for 14 days. They later filled out questionnaires on their sleep quality, sleepiness, and perceived stress. Both groups showed insufficient sleep duration during the week (<7 h). Only GC caught up on their sleep debt during the weekend (increased TIB, TST and time spent in REM sleep, all p < 0.001). Weekend TIB, TST and, N3 sleep remained similar to that for weekdays in GR. However, GR experienced lower sleep quality (decreased SE, increased WASO, all p < 0.01) and a decrease in REM sleep (p < 0.01). Schedules of activities showed an increase in time spent on overall activities during the weekend, mainly due to competition and sport-specific travel, which resulted in a decrease in sleep opportunity time compared with GC (p < 0.001). Δ sleep opportunity time (weekend-week) was associated with Δ TST (weekend-week), and Δ TST (weekend-week) was associated with sleepiness and perceived stress. Busy schedules during the competitive season decreased sleep opportunity time and prevented elite adolescent rugby players from catching up on their sleep at weekends.HIGHLIGHTS Adolescent rugby players have insufficient sleep during both week and weekend of the in-season competitive phaseCongested schedule prevented elite adolescent rugby players from catching up on their sleep at weekends.Sleep considerations are necessary when planning the weekend sporting schedules.

A Combined Sleep Hygiene and Mindfulness Intervention to Improve Sleep and Well-Being During High-Performance Youth Tennis Tournaments

PURPOSE

To investigate the effects of combined sleep hygiene recommendations and mindfulness on actigraphy-based sleep parameters, perceptual well-being, anxiety, and match outcomes during high-performance junior tennis tournaments.

METHODS

In a randomized crossover design, 17 high-performance junior tennis players completed the baseline, control, and intervention (INT) conditions across 3 separate weeks. The baseline consisted of unassisted, habitual sleep during a regular training week, and the control was unassisted sleep during a tournament week. The players attended a sleep education workshop and completed a nightly sleep hygiene protocol during a tournament week for the INT. Analysis was performed on the weekly means and on the night prior to the first match of the tournament (T-1).

RESULTS

Significant differences were observed for increased time in bed, total sleep time, and an earlier bedtime (P < .05) across the INT week. These parameters also significantly improved on T-1 of the INT. A moderate effect size (P > .05, d > 1.00) was evident for decreased worry on T-1 of the INT. Small effect sizes were also evident for improved mood, cognitive anxiety, and sleep rating across the INT week. The match performance outcomes remained unchanged (P > .05).

CONCLUSIONS

Sleep hygiene INTs increase the sleep duration of high-performance junior tennis players in tournament settings, including the night prior to the tournament's first match. The effects on perceptual well-being and anxiety are unclear, although small trends suggest improved mood, despite no effect on generic match performance outcomes.

Assessing the effects of sleep on neurocognitive performance and injury rate in adolescent athletes using actigraphy

The National Sleep Foundation recommends that adolescents (age 14-17 years) sleep 8 to 10 hours per night. Sleep loss is associated with cognitive dysfunction, decreased reaction time, and poorer athletic performance. This study evaluated the effects of sleep on sports injury rate and academic and cognitive performance. Seventeen high school track and field athletes (7 males, 10 females, mean age 15.9 years) wore an actigraph device for 10 weeks and performed a computerized neurocognitive assessment. Overall, 900 nights of nocturnal sleep data were analysed. Total minutes in bed averaged 501 minutes (8 hours and 21 minutes) and total sleep time averaged 378 minutes (6 hours and 18 minutes). Statistically significant correlations were observed between mean total sleep time and age-adjusted scores for the neurocognitive domains of episodic memory (p = .03) and fluid cognition (p = .03). Sleep loss in student-athletes may result in greater cognitive difficulties and impair academic abilities in the classroom.

Subjective and Objective Responses to Two Rugby Sevens World Series Competitions

Fowler, PM, Murray, A, Farooq, A, Lumley, N, and Taylor, L. Subjective and objective responses to two rugby sevens world series competitions. J Strength Cond Res 33(4): 1043-1055, 2019-The purpose was to examine the utility of subjective and objective measures of player preparedness, interpreted at both group level and individual level, during 2 consecutive competitions of the World Rugby Sevens Series (WRSS). Subjective (sleep, energy, and muscle soreness ratings) and objective (heart rate [HR] at rest [HRREST] and in response to submaximal exercise [HREX]) measures were obtained from 16 male rugby 7s players from 1 team for 3 consecutive days (D1-3) at home (HOME) and on arrival at 4 tournament (T1-4) locations (T1-New Zealand; T2-USA; T3-Hong Kong; and T4-Tokyo) across 2 WRSS competitions (2 tournaments per competition) separated by 1 month. At a group level, energy ratings were significantly lower in T2 and T4 compared with HOME, and on D1 T2 compared with D1 T1 (p ≤ 0.05). Greatest variability in subjective ratings was observed during T1 and T3 at an individual level, particularly for sleep quality. Although at a group level HRREST and HREX significantly decreased in T1-4 compared with HOME (p ≤ 0.05), there was only a ∼50% agreement between the direction of change in HR indices at an individual level. Results from this study suggest that relocation between tournaments within WRSS competitions disrupts player preparedness measures to the largest degree. Hence, this period could be targeted by practitioners with appropriate recovery and/or sleep-promoting interventions or modulation of match-/training-load. Moreover, subjective rather than objective measures seem to be of greater use to inform player preparedness decision making, particularly at an individual level compared with a group level.

Inter-relationship between sleep quality, insomnia and sleep disorders in professional soccer players

Objective

Insufficient sleep duration and quality has negative effects on athletic performance, injury susceptibility and athlete development. This study aimed to assess the sleep characteristics of professional Qatar Stars League (QSL) soccer players.

Methods

In a cross-sectional study, QSL players (n=111; 23.7±4.8 years) completed three questionnaires to screen sleep disorders: (1) Pittsburgh Sleep Quality Index (PSQI), (2) Insomnia Severity Index (ISI) and (3) Epworth Sleepiness Scale (ESS). Poor sleep quality was defined as PSQI≥5, excessive daytime sleepiness was defined by ESS>8 and insomnia was defined as ISI≥11.

Results

The prevalence of poor sleep quality (PSQI≥5) was 68.5%, with subthreshold insomnia (ISI≥11) 27.0% and daytime sleepiness 22.5% (ESS>8). Sleep quality was positively associated with insomnia (r=0.42, p<0.001) and daytime sleepiness (r=0.23, p=0.018). Age, anthropometry, body composition and ethnicity were not associated with any of the reported sleep quality parameters.

Conclusion

The prevalence of poor sleep quality (68.5%) reported should concern practitioners. Increasing awareness of the importance of sleep relative to athletic performance, recovery, injury and illness appears prudent. Further, regular qualitative/quantitative sleep monitoring may help target subsequent evidence-informed interventions to improve sleep in those demonstrating undesirable sleep traits.

Sleep characteristics, sources of perceived stress and coping strategies in adolescent athletes

The aim of the study was to examine sleep characteristics, scheduling of activities, perceived stress and coping strategies between periods of perceived high and low scheduling commitments in adolescent athletes. Twenty adolescents (10 male and 10 female) wore an Actiwatch during two 14-day testing periods, one in in January (JAN), which was deemed to be a period of low school and sport commitments, and one in March (MAR), during which there was a high volume of school and sport commitments. Actiwatches and sleep diaries assessed sleep quantity and quality, a daily schedule of all activities in 30-min increments was recorded and questionnaires related to perceived stress and coping strategies were administered. Time in bed and asleep, latency, efficiency and number of awakenings were not different between JAN and MAR (p > 0.05). Sleep durations were lower than their age-related recommendations (JAN 449 ± 47 min versus MAR 437 ± 31 min). Examination of differences between sexes showed shorter latency and higher sleep efficiency in female participants compared with male participants. Participants spent more time at school, completing homework, and travelling to and competing in sport, with reduced time spent on resting, social activities, physical activity and meal times during MAR compared with JAN (p < 0.05). Finally, stress levels were significantly increased during MAR compared with JAN, with no difference between sexes (p < 0.05). Adolescent athletes not attaining sufficient sleep quantity or quality during periods of low and high school and sport commitments, are experiencing increased perceived stress during these busy times but are using a wider range of coping strategies during this time.

Melatonin ingestion after exhaustive late-evening exercise improves sleep quality and quantity, and short-term performances in teenage athletes

The present study aimed to explore the effects of a single 10-mg dose of melatonin (MEL) administration after exhaustive late-evening exercise on sleep quality and quantity, and short-term physical and cognitive performances in healthy teenagers. Ten male adolescent athletes (mean ± SD, age = 15.4 ± 0.3 years, body-mass = 60.68 ± 5.7 kg, height = 167.9 ± 6.9 cm and BMI = 21.21 ± 2.5) performed two test sessions separated by at least one week. During each session, participants completed the Yo-Yo intermittent-recovery-test level-1 (YYIRT-1) at ~20:00 h. Then, sleep polysomnography was recorded from 22:15 min to 07:00 h, after a double blind randomized order administration of a single 10-mg tablet of MEL (MEL-10 mg) or Placebo (PLA). The following morning, Hooper wellness index was administered and the participants performed the Choice Reaction Time (CRT) test, the Zazzo test and some short-term physical exercises (YYIRT-1, vertical and horizontal Jumps (VJ; HJ), Hand grip strength (HG), and five-jump test (5-JT)). Evening total distance covered in the YYIRT-1 did not change during the two conditions (p > 0.05). Total sleep time (Δ = 24.55 mn; p < 0.001), sleep efficiency (Δ = 4.47%; p < 0.001), stage-3 sleep (N3 sleep) (Δ = 1.73%; p < 0.05) and rapid-eye-movement sleep (Δ = 2.15%; p < 0.001) were significantly higher with MEL in comparison with PLA. Moreover, sleep-onset-latency (Δ = -8.45mn; p < 0.001), total time of nocturnal awakenings after sleep-onset (NA) (Δ = -11 mn; p < 0.001), stage-1 sleep (N1 sleep) (Δ = -1.7%; p < 0.001) and stage-2 sleep (N2 sleep) (Δ = -1.9%; p < 0.05) durations were lower with MEL. The Hooper index showed a better subjective sleep quality, a decrease of the subjective perception of fatigue and a reduced level of muscle soreness with MEL. Moreover, MEL improved speed and performance but not inaccuracy during the Zazzo test. CRT was faster with MEL. Morning YYIRT-1 (Δ = 82 m; p < 0.001) and 5-JT (Δ = 0.08 m; p < 0.05) performances were significantly higher with MEL in comparison with PLA. In contrast, HG, VJ and HJ performances did not change during the two conditions (p > 0.05). The administration of a single dose of MEL-10 mg after strenuous late-evening exercise improved sleep quality and quantity, selective attention, subjective assessment of the general wellness state, and some short-term physical performances the following morning in healthy teenagers.

Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living

Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual's physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise prescription. Here, we outline 24-h monitoring of selected parameters by these technologies that (i) allows responsive adjustments of exercise programs, (ii) enhances performance and/or (iii) reduces the risk for overuse, injury and/or illness.

Impaired Sleep Mediates the Negative Effects of Training Load on Subjective Well-Being in Female Youth Athletes

Background:

Although increased training load (TL) and impaired sleep are associated with decreases in subjective well-being in adult athletes, these relationships among female youth athletes are unclear. It is unknown whether the effects of sleep and TL on well-being are independent or whether alterations in sleep mediate the effects of TL on subjective well-being.

Hypothesis:

Sleep and TL exert independent effects on subjective well-being among youth athletes, although alterations in sleep mediate a significant portion of the effect of TL on well-being in female youth athletes.

Study Design:

Prospective cohort study.

Level of Evidence:

Level 4.

Methods:

A total of 65 female soccer athletes (age range, 13-18 years) were monitored for 1 year. Daily TL was determined by session rating of perceived exertion and converted to z-scores. Every morning, participants recorded sleep duration in hours and rated stress, mood, fatigue, and soreness on a scale from −3 to +3 (worst to best). Linear mixed-effects models and mediation analysis were used to evaluate the independent effects of TL and sleep on well-being.

Results:

Average sleep duration was 7.9 ± 1.4 hours during the study period. In the multivariable model, TL and sleep duration were independently associated with fatigue (TL: β = −0.19, P < 0.001; sleep: β = 0.15, P < 0.001), mood (TL: β = −0.030, P = 0.014; sleep: β = 0.13, P < 0.001), stress (TL: β = −0.055, P = 0.001; sleep: β = 0.13, P < 0.001), and soreness (TL: β = −0.31, P < 0.001; sleep: β = 0.022, P = 0.042). Sleep duration mediated a significant portion of the effect of TL on mood (26.8%, P < 0.001), fatigue (12.6%, P < 0.001), and stress (24.5%, P < 0.001).

Conclusion:

Among female youth athletes, decreased sleep duration and increased TL are independently associated with impairments of subjective well-being. In addition, decreased sleep mediates a significant portion of the negative effect of increases in TL on subjective well-being.

Clinical Relevance:

Monitoring and promoting sleep among female adolescent athletes may significantly improve subjective well-being, particularly during periods of increased TL.