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Clint R. Bellenger, Laura Karavirta, Rebecca L. Thomson, Eileen Y. Robertson, Kade Davison and Jonathan D. Buckley

Purpose:

Heart-rate variability (HRV) as a measure of autonomic function may increase in response to training interventions leading to increases or decreases in performance, making HRV interpretation difficult in isolation. This study aimed to contextualize changes in HRV with subjective measures of training tolerance.

Methods:

Supine and standing measures of vagally mediated HRV (root-mean-square difference of successive normal RR intervals [RMSSD]) and measures of training tolerance (Daily Analysis of Life Demands for Athletes questionnaire, perception of energy levels, fatigue, and muscle soreness) were recorded daily during 1 wk of light training (LT), 2 wk of heavy training (HT), and 10 d of tapering (T) in 15 male runners/triathletes. HRV and training tolerance were analyzed as rolling 7-d averages at LT, HT, and T. Performance was assessed after LT, HT, and T with a 5-km treadmill time trial (5TTT).

Results:

Time to complete the 5TTT likely increased after HT (effect size [ES] ± 90% confidence interval = 0.16 ± 0.06) and then almost certainly decreased after T (ES = −0.34 ± 0.08). Training tolerance worsened after HT (ES ≥ 1.30 ± 0.41) and improved after T (ES ≥ 1.27 ± 0.49). Standing RMSSD very likely increased after HT (ES = 0.62 ± 0.26) and likely remained higher than LT at the completion of T (ES = 0.38 ± 0.21). Changes in supine RMSSD were possible or likely trivial.

Conclusion:

Vagally mediated HRV during standing increased in response to functional overreaching (indicating potential parasympathetic hyperactivity) and also to improvements in performance. Thus, additional measures such as training tolerance are required to interpret changes in vagally mediated HRV.

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Yann Le Meur, Martin Buchheit, Anaël Aubry, Aaron J Coutts and Christophe Hausswirth

Purpose:

Faster heart-rate recovery (HRR) after high to maximal exercise (≥90% of maximal heart rate) has been reported in athletes suspected of functional overreaching (f-OR). This study investigated whether this response would also occur at lower exercise intensity.

Methods:

Responses of HRR and rating of perceived exertion (RPE) were compared during an incremental intermittent running protocol to exhaustion in 20 experienced male triathletes (8 control subjects and 13 overload subjects led to f-OR) before and immediately after an overload training period and after a 1-wk taper.

Results:

Both groups demonstrated an increase in HRR values immediately after the training period, but this change was very likely to almost certainly larger in the f-OR group at all running intensities (large to very large differences, eg, +16 ± 7 vs +3 ± 5 beats/min, in the f-OR and control groups at 11 km/h, respectively). The highest between-groups differences in changes in HRR were reported at 11 km/h (13 ± 4 beats/min) and 12 km/h (10 ± 6 beats/min). A concomitant increase in RPE at all intensities was reported only in the f-OR group (large to extremely large differences, +2.1 ± 1.5 to +0.7 ± 1.5 arbitrary units).

Conclusion:

These findings confirm that faster HRR does not systematically predict better physical performance. However, when interpreted in the context of the athletes’ fatigue state and training phase, HRR after submaximal exercise may be more discriminant than HRR measures taken after maximal exercise for monitoring f-OR. These findings may be applied in practice by regularly assessing HRR after submaximal exercise (ie, warm-up) for monitoring endurance athletes’ responses to training.

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Ben T. Stephenson, Christof A. Leicht, Keith Tolfrey and Victoria L. Goosey-Tolfrey

the possibility athletes may be at risk of acute fatigue. 1 Meeusen et al 2 define acute fatigue as the first state experienced as a result of IT and its associated stressors. If the accumulation of physical and/or nonphysical stress were to continue, the development of overreaching (OR) may ensue

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Twan ten Haaf, Selma van Staveren, Erik Oudenhoven, Maria F. Piacentini, Romain Meeusen, Bart Roelands, Leo Koenderman, Hein A.M. Daanen, Carl Foster and Jos J. de Koning

Purpose:

To investigate whether monitoring of easily measurable stressors and symptoms can be used to distinguish early between acute fatigue (AF) and functional overreaching (FOR).

Methods:

The study included 30 subjects (11 female, 19 male; age 40.8 ± 10.8 y, VO2max 51.8 ± 6.3 mL · kg–1 · min–1) who participated in an 8-d cycling event over 1300 km with 18,500 climbing meters. Performance was measured before and after the event using a maximal incremental test. Subjects with decreased performance after the event were classified as FOR, others as AF. Mental and physical well-being, internal training load, resting heart rate, temperature, and mood were measured daily during the event. Differences between AF and FOR were analyzed using mixed-model ANOVAs. Logistic regression was used to determine the best predictors of FOR after 3 and 6 d of cycling.

Results:

Fifteen subjects were classified as FOR and 14 as AF (1 excluded). Although total group changes were observed during the event, no differences between AF and FOR were found for individual monitoring parameters. The combination of questionnaire-based changes in fatigue and readiness to train after 3 d cycling correctly predicted 78% of the subjects as AF or FOR (sensitivity = 79%, specificity = 77%).

Conclusions:

Monitoring changes in fatigue and readiness to train, using simple visual analog scales, can be used to identify subjects likely to become FOR after only 3 d of cycling. Hence, we encourage athlete support staff to monitor not only fatigue but also the subjective integrated mental and physical readiness to perform.

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Selenia di Fronso, Fabio Y. Nakamura, Laura Bortoli, Claudio Robazza and Maurizio Bertollo

The aim of the study was to examine differences in stress and recovery across gender and time (preseason and play-offs) in a sample of amateur basketball players of the Italian league (C division). Fifty amateur basketball players (33 men and 17 women) age 17–30 y (23.5 ± 9.19 y) participated in the study. Twenty-eight athletes (16 men and 12 women) completed the Recovery-Stress Questionnaire for Sport (RESTQ-Sport) in the preseason phase, after a training period of 21 days, and in the competition phase during the play-off period. Repeated-measures MANOVA showed significant differences by gender and preparation phase. Univariate follow-up ANOVA highlighted differences by gender on physical recovery, sleep quality, and self-efficacy, with higher scores in men. Moreover, differences between preseason and competition phases were shown on emotional stress and fatigue, with higher scores on emotional stress and lower scores on fatigue in the competition phase. These findings suggest that RESTQ-Sport could be a useful tool for coaches to monitor stress/recovery balance in male and female team-sport athletes during different periods of the season.

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Kristie-Lee Taylor, Will G. Hopkins, Dale W. Chapman and John B. Cronin

The purpose of this study was to calculate the coefficients of variation in jump performance for individual participants in multiple trials over time to determine the extent to which there are real differences in the error of measurement between participants. The effect of training phase on measurement error was also investigated. Six subjects participated in a resistance-training intervention for 12 wk with mean power from a countermovement jump measured 6 d/wk. Using a mixed-model meta-analysis, differences between subjects, within-subject changes between training phases, and the mean error values during different phases of training were examined. Small, substantial factor differences of 1.11 were observed between subjects; however, the finding was unclear based on the width of the confidence limits. The mean error was clearly higher during overload training than baseline training, by a factor of ×/÷ 1.3 (confidence limits 1.0–1.6). The random factor representing the interaction between subjects and training phases revealed further substantial differences of ×/÷ 1.2 (1.1–1.3), indicating that on average, the error of measurement in some subjects changes more than in others when overload training is introduced. The results from this study provide the first indication that within-subject variability in performance is substantially different between training phases and, possibly, different between individuals. The implications of these findings for monitoring individuals and estimating sample size are discussed.

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Iñigo Mujika, Trent Stellingwerff and Kevin Tipton

The adaptive response to training is determined by the combination of the intensity, volume, and frequency of the training. Various periodized approaches to training are used by aquatic sports athletes to achieve performance peaks. Nutritional support to optimize training adaptations should take periodization into consideration; that is, nutrition should also be periodized to optimally support training and facilitate adaptations. Moreover, other aspects of training (e.g., overload training, tapering and detraining) should be considered when making nutrition recommendations for aquatic athletes. There is evidence, albeit not in aquatic sports, that restricting carbohydrate availability may enhance some training adaptations. More research needs to be performed, particularly in aquatic sports, to determine the optimal strategy for periodizing carbohydrate intake to optimize adaptations. Protein nutrition is an important consideration for optimal training adaptations. Factors other than the total amount of daily protein intake should be considered. For instance, the type of protein, timing and pattern of protein intake and the amount of protein ingested at any one time influence the metabolic response to protein ingestion. Body mass and composition are important for aquatic sport athletes in relation to power-to-mass and for aesthetic reasons. Protein may be particularly important for athletes desiring to maintain muscle while losing body mass. Nutritional supplements, such as b-alanine and sodium bicarbonate, may have particular usefulness for aquatic athletes’ training adaptation.

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Susan Vrijkotte, Romain Meeusen, Cloe Vandervaeren, Luk Buyse, Jeroen van Cutsem, Nathalie Pattyn and Bart Roelands

The margin between optimal training load and excessive stress varies on a daily basis. When training stress is experienced for too long, nonfunctional overreaching (NFO) and the “overtraining syndrome” (OTS) can be developed, with impaired performance for weeks up to months and sometimes even

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Alice M. Wallett, Amy L. Woods, Nathan Versey, Laura A. Garvican-Lewis, Marijke Welvaert and Kevin G. Thompson

intensified training loads in order to elicit fatigue, which may result in short-term “overreaching.” 13 During this phase, studies have identified that disturbances in mood state, impaired race times, and decreased power output can occur in athletes. 14 – 16 Consequently, a training mesocycle will