Validation of the Acute Recovery and Stress Scale (ARSS) and the Short Recovery and Stress Scale (SRSS) in three English-speaking regions.

The Acute Recovery and Stress Scale (ARSS) and the Short Recovery and Stress Scale (SRSS) are well-established monitoring tools in German-speaking countries. This study aimed at validating them for English-speaking populations. Overall, 996 athletes (536 males, 24.9 ± 9.1 years) of Australia/New Zealand (n = 380), the United Kingdom (n = 316), and North America (n = 300) participated. The 32-item ARSS consists of eight scales. These scales constitute the eight items of the SRSS with the corresponding ARSS items as descriptors. Confirmatory factor analysis (CFA), internal consistency (α), and discriminatory power of the items (rit) were calculated for the total and subsamples separately. Satisfactory discriminatory power (rit > .30) for all ARSS and SRSS items and acceptable internal consistency (α > .70) was achieved. CFA indicated good fit indices for the total sample and subsamples, and strong measurement invariance was found across subsamples and gender. Correlations between corresponding scales and items (rs = .68 - .78) support theoretical congruency as well as independent usage of both questionnaires. Construct validity of both tools is shown through hypothesis-conforming correlations with the Recovery-Stress Questionnaire for Athletes. Future studies may apply the ARSS and SRSS as monitoring tools in English-speaking regions worldwide.

The effect of westward travel across five time zones on sleep and subjective jet-lag ratings in athletes before and during the 2015's World Rowing Junior Championships.

This study examined sleep-wake habits and subjective jet-lag ratings of 55 German junior rowers (n = 30 male, 17.8 ± 0.5 years) before and during the World Rowing Junior Championships 2015 in Rio de Janeiro, Brazil. Athletes answered sleep logs every morning, and Liverpool John Moore's University Jet-Lag Questionnaires each evening and morning. Following an 11-h westward flight with 5-h time shift, advanced bedtimes (-1 h, P < .001, ηp2 = 0.68), reduced sleep onset latency (P = .002, ηp2 = 0.53) and increased sleep duration (P < .001, ηp2 = 0.60) were reported for the first two nights. Jet-lag symptoms peaked upon arrival but were still present after 6 days. Sleep quality improved (P < .001, ηp2 = 0.31) as well as some scales of the Recovery-Stress Questionnaire for Athletes. Participation was successful as indicated by 11 of 13 top 3 placings. Overall, the initial desynchronisation did not indicate negative impacts on competition performance. As travel fatigue probably had a major effect on perceptual decrements, sleep during travel and time to recover upon arrival should be emphasised. Coaches and practitioners should consider higher sleep propensity in the early evening by scheduling training sessions and meetings until the late afternoon.

Comparing Subjective With Objective Sleep Parameters Via Multisensory Actigraphy in German Physical Education Students.

This study compared subjective with objective sleep parameters among 72 physical education students. Furthermore, the study determined whether 24-hr recording differs from nighttime recording only. Participants wore the SenseWear Armband™ for three consecutive nights and kept a sleep log. Agreement rates ranged from moderate to low for sleep onset latency (ICC = 0.39 to 0.70) and wake after sleep onset (ICC = 0.22 to 0.59), while time in bed (ICC = 0.93 to 0.95) and total sleep time (ICC = 0.90 to 0.92) revealed strong agreement during this period. Comparing deviations between 24-hr wearing time (n = 24) and night-only application (n = 20) revealed no statistical difference (p > 0.05). As athletic populations have yet to be investigated for these purposes, this study provides useful indicators and practical implications for future studies.

Portable PSG for sleep stage monitoring in sports: Assessment of SOMNOwatch plus EEG.

Current sport-scientific studies mostly neglect the assessment of sleep architecture, although the distribution of different sleep stages is considered an essential component influencing an athlete's recovery and performance capabilities. A mobile, self-applied tool like the SOMNOwatch plus EEG might serve as an economical and time-friendly alternative to activity-based devices. However, self-application of SOMNOwatch plus EEG has not been validated against conventional polysomnography (PSG) yet. For evaluation purposes, 25 participants (15 female, 10 male; M age = 22.92 ± 2.03 years) slept in a sleep laboratory on two consecutive nights wearing both, conventional PSG and SOMNOwatch plus EEG electrodes. Sleep parameters and sleep stages were compared using paired t-tests and Bland-Altman plots. No significant differences were found between the recordings for Sleep Onset Latency, stages N1 to N3 as well as Rapid Eye Movement stage. Significant differences (Bias [95%-confidence interval]) were present between Total Sleep Time (9.95 min [-29.18, 49.08], d = 0.14), Total Wake Time (-13.12 min [-47.25, 23.85], d = -0.28), Wake after Sleep Onset (-11.70 min [-47.25, 23.85], d = -0.34) and Sleep Efficiency (2.18% [-7.98, 12.34], d = 0.02) with small effect sizes. Overall, SOMNOwatch plus EEG can be considered a valid and practical self-applied method for the examination of sleep. In sport-scientific research, it is a promising tool to assess sleep architecture in athletes; nonetheless, it cannot replace in-lab PSG for all clinical or scientific purposes.

Modification and Applicability of Questionnaires to Assess the Recovery-Stress State Among Adolescent and Child Athletes.

Despite the general consensus regarding the implementation of self-report measures in the training monitoring, there is a lack of research about their applicability and comprehensibility among developing athletes. However, this target group needs special considerations to manage the increasing training demands while maintaining health and performance. This study deals with challenges of applying recovery-stress questionnaires which were validated with adult populations among developing athletes and presents a possible approach to enhance their applicability. In two phases, the Acute Recovery and Stress Scale (ARSS), a 32-adjective list covering eight scales, and the 8-item derived version, the Short Recovery and Stress Scale (SRSS) were answered by 1052 athletes between 10 and 16 years. Phase 1 included 302 14- to 16-year-old athletes who used the original questionnaires with the additional option to mark "I don't understand," while modified versions with additional explanations (phase 2) were applied to 438 adolescents (14.7 ± 0.6 years) and 312 child athletes (11.8 ± 1.1 years). Data of the original validation sample (n = 442) were reanalyzed to examine measurement invariance between adults and adolescents. The results showed comparable psychometric properties to the validation sample (e.g., r it > 0.30) and acceptable fit indices via confirmatory factor analyses (CFA), although more difficulties and limitations were present within the younger groups (e.g., Cronbach's α between 0.50 and 0.87), especially among 10- and 11-year-olds. The original as well as the modified SRSS, on the other hand, indicated good applicability (Cronbach's α between 0.72 and 0.80). Multigroup CFA revealed measurement invariance of the original ARSS among adults and adolescents and of the modified ARSS among adolescents and children. Overall, the present study confirmed the assumption that questionnaires designed by and for adults cannot be directly transferred to younger athletes. The peculiarities and differences in the cognitive and affective development of each age group need to be considered. Future research needs to identify a cut-off age to start the proper use of psychometric tools, especially for state-oriented assessments for routine application in training monitoring. Further modifications and long-term investigations are necessary to implement psychometric monitoring in high-performance environments within youth sport.

Verbal Encouragement and Between-Day Reliability During High-Intensity Functional Strength and Endurance Performance Testing.

As verbal encouragement (VE) is used in high intensity functional exercise testing, this randomized controlled crossover study aimed at investigating whether VE affects high intensity functional strength and endurance performance testing. We further examined between-day variability of high intensity functional strength and endurance performance testing with and without VE. Nineteen experienced athletes (seven females and 12 males, age: 23.7 ± 4.3 years) performed a standardized one repetition maximum (1 RM) squat test and a 12-min high-intensity functional training (HIFT) workout [as many repetitions as possible (AMRAP)] on four different days over a 2-week period. Athletes randomly performed each test twice, either with VE or without (CON), with a minimum of 72 h rest between tests. Very good to excellent relative between-day reliability with slightly better values for strength testing (ICC: 0.99; CV: 3.5-4.1%) compared to endurance testing (ICC 0.87-0.95; CV: 3.9-7.3%) were observed. Interestingly, VE led to higher reliability during endurance testing. Mean squat strength depicted higher strength values with VE (107 ± 33 kg) compared to CON (105 ± 33 kg; p = 0.009, Cohen's d: 0.06). AMRAP in the endurance test showed negligible differences between VE (182 ± 33 AMRAP) and CON (181 ± 35 AMRAP; p = 0.71, Cohen's d: 0.03). In conclusion, the effects of VE do not notably exceed day-to-day variability during high intensity functional strength (CV: 3.5-4.1%) and endurance (CV: 3.9-7.3%) testing. However, high intensity functional strength and endurance testing with VE seems to be slightly more reliable, particularly during endurance testing.

Sleep-Related Issues for Recovery and Performance in Athletes.

The body of research that reports the relevance of sleep in high-performance sports is growing steadily. While the identification of sleep cycles and diagnosis of sleep disorders are limited to lab-based assessment via polysomnography, the development of activity-based devices estimating sleep patterns provides greater insight into the sleep behavior of athletes in ecological settings. Generally, small sleep quantity and/or poor quality appears to exist in many athletic populations, although this may be related to training and competition context. Typical sleep-affecting factors are the scheduling of training sessions and competitions, as well as impaired sleep onset as a result of increased arousal prior to competition or due to the use of electronic devices before bedtime. Further challenges are travel demands, which may be accompanied by jet-lag symptoms and disruption of sleep habits. Promotion of sleep may be approached via behavioral strategies such as sleep hygiene, extending nighttime sleep, or daytime napping. Pharmacological interventions should be limited to clinically induced treatments, as evidence among healthy and athletic populations is lacking. To optimize and manage sleep in athletes, it is recommended to implement routine sleep monitoring on an individual basis.

Sleep monitoring of a six-day microcycle in strength and high-intensity training.

This study examined the effect of microcycles in eccentric strength and high-intensity interval training (HIT) on sleep parameters and subjective ratings. Forty-two well-trained athletes (mean age 23.2 ± 2.4 years) were either assigned to the strength (n = 21; mean age 23.6 ± 2.1 years) or HIT (n = 21; mean age 22.8 ± 2.6 years) protocol. Sleep monitoring was conducted with multi-sensor actigraphy (SenseWear Armband™, Bodymedia, Pittsburg, PA, USA) and sleep log for 14 days. After a five-day baseline phase, participants completed either eccentric accented strength or high-intensity interval training for six days, with two training sessions per day. This training phase was divided into two halves (part 1 and 2) for statistical analyses. A three-day post phase concluded the monitoring. The Recovery-Stress Questionnaire for Athletes was applied at baseline, end of part 2, and at the last post-day. Mood ratings were decreased during training, but returned to baseline values afterwards in both groups. Sleep parameters in the strength group remained constant over the entire process. The HIT group showed trends of unfavourable sleep during the training phase (e.g., objective sleep efficiency at part 2: mean = 83.6 ± 7.8%, F3,60 = 2.57, P = 0.06, [Formula: see text] = 0.114) and subjective improvements during the post phase for awakenings (F3,60 = 2.96, P = 0.04, [Formula: see text] = 0.129) and restfulness of sleep (F3,60 = 9.21, P < 0.001, [Formula: see text] = 0.315). Thus, the HIT protocol seems to increase higher recovery demands than strength training, and sufficient sleep time should be emphasised and monitored.

The longer the better: Sleep-wake patterns during preparation of the World Rowing Junior Championships.

Recovery is essential for high athletic performance, and therefore especially sleep has been identified as a crucial source for physical and psychological well-being. However, due to early-morning trainings, which are general practice in many sports, athletes are likely to experience sleep restrictions. Therefore, this study investigated the sleep-wake patterns of 55 junior national rowers (17.7 ± 0.6 years) via sleep logs and actigraphy during a four-week training camp. Recovery and stress ratings were obtained every morning with the Short Recovery and Stress Scale on a 7-point Likert-type scale ranging from 0 (does not apply at all) to 6 (fully applies). The first training session was scheduled for 6:30 h every day. With two to four training sessions per day, the training load was considerably increased from athletes' home training. Objective sleep measures (n = 14) revealed less total sleep time (TST) in the first two weeks (409.6 ± 19.1 and 416.0 ± 16.3 min), while training volume and intensity were higher. In the second half of the camp, less training sessions were implemented, more afternoons were training free and TSTs were longer (436.3 ± 15.8 and 456.9 ± 25.7 min). A single occasion of 1.5-h delayed bedtime and usual early morning training (6:30 h) resulted in reduced ratings of Overall Recovery (OR) (M = 3.3 ± 1.3) and greater Negative Emotional State (NES) (M = 1.3 ± 1.2, p < .05), which returned to baseline on the next day. Following an extended night due to the only training-free day, sleep-offset times were shifted from ~5:30 to ~8:00 h, and each recovery and stress score improved (p < .01). Moreover, subjective ratings of the first six days were summarised as a baseline score to generate reference data as well as to explore the association between sleep and recovery. Intercorrelations of these sleep parameters emphasised the relationship between restful sleep and falling asleep quickly (r = .34, p < .05) as well as few awakenings (r = .35, p < .05). Overall, the findings highlight the impact of sleep on subjective recovery measures in the setting of a training camp. Providing the opportunity of extended sleep (and a day off) seems the most simple and effective strategy to enhance recovery and stress-related ratings.

Sleep, Travel, and Recovery Responses of National Footballers During and After Long-Haul International Air Travel.

PURPOSE: The current study examined the sleep, travel, and recovery responses of elite footballers during and after long-haul international air travel, with a further description of these responses over the ensuing competitive tour (including 2 matches). METHODS: In an observational design, 15 elite male football players undertook 18 h of predominantly westward international air travel from the United Kingdom to South America (-4-h time-zone shift) for a 10-d tour. Objective sleep parameters, external and internal training loads, subjective player match performance, technical match data, and perceptual jet-lag and recovery measures were collected. RESULTS: Significant differences were evident between outbound travel and recovery night 1 (night of arrival; P < .001) for sleep duration. Sleep efficiency was also significantly reduced during outbound travel compared with recovery nights 1 (P = .001) and 2 (P = .004). Furthermore, both match nights (5 and 10), showed significantly less sleep than nonmatch nights 2 to 4 and 7 to 9 (all P < .001). No significant differences were evident between baseline and any time point for all perceptual measures of jet-lag and recovery (P > .05), although large effects were evident for jet-lag on d 2 (2 d after arrival). CONCLUSIONS: Sleep duration is truncated during long-haul international travel with a 4-h time-zone delay and after night matches in elite footballers. However, this lost sleep appeared to have a limited effect on perceptual recovery, which may be explained by a westbound flight and a relatively small change in time zones, in addition to the significant increase in sleep duration on the night of arrival after the long-haul flight.