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A Systematic Review on Markers of Functional Overreaching in Endurance Athletes
Abstract
Purpose:
The aim of this brief review was to present an overview of noninvasive markers in trained to professional endurance athletes that can reflect a state of functional overreaching.
Methods:
A systematic literature search was conducted in the PubMed, Scopus, and PsycINFO databases. After screening 380 articles, 12 research papers were included for the systematic review.
Results:
Good consensus was found between the different papers in which noninvasive parameters were able to reflect a state of functional overreaching. Changes in power output (PO), heart rate (HR; [sub]maximal and HR recovery), rating of perceived exertion, and scores in the Daily Analysis of Life Demands for Athletes (DALDA) and/or Profile of Mood States (POMS) were shown to be able to reflect functional overreaching, whereas changes in maximal oxygen uptake and HR-variability parameters were not.
Conclusion:
Functional overreaching within a maximal performance test was characterized by a decrease in peak PO and a lower maximum HR, whereas a lower mean PO and a lower HR were observed during time trials. Changes in parameters during a standardized submaximal test when functionally overreached were characterized by a higher PO at a fixed HR or a lower HR at a fixed intensity, higher rating of perceived exertion, and a faster HR recovery. Although both the DALDA and POMS were able to reflect functional overreaching, the POMS was not able to differentiate this response from acute fatigue, which makes it unsuitable for accurately monitoring functional overreaching.
... Numerous models have been suggested for monitoring and diagnosing overreaching status amongst endurance athletes (13, 14,19,20). While sustained underperformance is required to diagnose a verifiable state of overreaching (1), performance is difficult to assess 3 due to normal day-to-day variability and can be confounded by the initial training status of the individual (17,21). ...
... While sustained underperformance is required to diagnose a verifiable state of overreaching (1), performance is difficult to assess 3 due to normal day-to-day variability and can be confounded by the initial training status of the individual (17,21). As such, other markers such as reductions in exercising HR and lactate, and elevated RPE at a submaximal exercise load (typically ≥70% of VO 2 max) (5,13,14,19) can be used to accompany a suspected reduction in performance. Mood states and subjective reports of fatigue are consistently shown to be worsened with overreaching; however, these likely cannot distinguish between acute fatigue and overreaching as stand-alone measures (19,20). ...
... As such, other markers such as reductions in exercising HR and lactate, and elevated RPE at a submaximal exercise load (typically ≥70% of VO 2 max) (5,13,14,19) can be used to accompany a suspected reduction in performance. Mood states and subjective reports of fatigue are consistently shown to be worsened with overreaching; however, these likely cannot distinguish between acute fatigue and overreaching as stand-alone measures (19,20). ...
... Though maximal endurance performance testing has been considered the gold standard for quantifying and monitoring training status (Meeusen et al., 2013), these are impractical to use daily (Halson & Jeukendrup, 2004;Roete et al., 2021), and are contraindicated for individuals at risk of developing N-FOR, since the fatigue associated will only exacerbate these condition (Bellenger, Fuller, et al., 2016;. Thus, measurements that more practically assess individual capacity to respond or adapt to training on a daily basis are preferential for identifying training-induced fatigue, facilitating training adjustments (Borresen & Lamberts, 2009). ...
... Thus, additional self-report measures of stress tolerance (e.g., Daily Analysis of Life Demands for Athletes (DALDA) questionnaire) have been suggested to facilitate appropriate interpretation of HRV (Bellenger et al., 2017;Bellenger, Karavirta, et al., 2016;. Indeed, previous systematic reviews highlighted that self-reported measures reflect both acute and chronic training load with higher sensitivity and consistency than commonly used objective measures, especially indicators of ANS activity (Roete et al., 2021;Saw et al., 2016). Surprisingly, self-report measures have been typically used in applied research to monitor the response to a training stimuli rather than an indicator to help guide decision-making (Saw et al., 2016). ...
... The DALDA is a two-part survey that reflects the general sources (Part A) and symptoms of stressors which are likely to exist (Part B). Only scores marked as "worse than normal" for part B of the questionnaire was analysed, since this has been demonstrated a sensitive measure of training status (Roete et al., 2021). ...
The aim of this study was to determine the effect of endurance training individually guided by objective (Heart Rate Variability-HRV) or self-report measure of stress (DALDA-questionnaire) in comparison to predefined endurance training prescription for improving endurance performance in recreational runners. After a 2-week preliminary baseline period to establish resting HRV and self-reported measure of stress, thirty-six male recreational runners were randomly assigned to HRV-guided (GHRV; n = 12), DALDA-guided (GD; n = 12) or predefined training (GT; n = 12) prescription groups. Before and after 5-weeks of endurance training, participants performed a track field peak velocity (Vpeak_TF), time limit (Tlim) at 100% of Vpeak_TF and 5 km time-trial (5 km TT) tests. GD lead to higher improvements in Vpeak_TF (8.4 ± 1.8%; ES = 1.41) and 5 km TT (-12.8 ± 4.2%; ES = -1.97), than GHRV (6.6 ± 1.5% and -8.3 ± 2.8%; ES = -1.20; 1.24) and GT (4.9 ± 1.5% and -6.0 ± 3.3%; ES = -0.82; 0.68), respectively, with no differences for Tlim. Self-report measures of stress may be used to individualize endurance training prescription on a daily basis leading to better performance enhancement, which may be used with HRV for a holistic understanding of daily training-induce adaptations.
... In addition to these objective load parameters, there is also the perceived internal load of the athlete. In particular, athletes' perceived training satisfaction and training load using Rating of Perceived Exertion (RPE) are relevant and frequently used subjective measures to assess the impact of training on the athlete [11][12][13]. Choosing appropriate analyses, interpretation, and decision making to adapt upcoming training programmes and sessions challenges the skills, knowledge, and time of the coach [14,15]. This complex challenge leads to the problem at hand: how can the coach be informed about training load and subjective measures to gain insights into the impact of training on the athlete and adapt their training programmes accordingly? ...
... A survey was constructed based on a narrative literature review on monitoring aspects during and around training, overreaching, and overtraining [5,7,12]. The aim of the survey was to empathise with the importance, needs, and bottlenecks experienced by coaches in collecting, analysing, and interpreting training and health data. ...
... To illustrate this, coaches can use the readiness score collected in the daily questionnaire for last-minute changes to the training session. External training load is collected based on the sport modality and used monitoring wearable sensors and systems [12,35]. Displayed data are training duration, distance, velocity (average, maximum, and load), power (average, maximum, and load), fastest lap data, and a graph displaying power and velocity over training duration. ...
Athlete development depends on many factors that need to be balanced by the coach. The amount of data collected grows with the development of sensor technology. To make data-informed decisions for training prescription of their athletes, coaches could be supported by feedback through a coach dashboard. The aim of this paper is to describe the design of a coach dashboard based on scientific knowledge, user requirements, and (sensor) data to support decision making of coaches for athlete development in cyclic sports. The design process involved collaboration with coaches, embedded scientists, researchers, and IT professionals. A classic design thinking process was used to structure the research activities in five phases: empathise, define, ideate, prototype, and test phases. To understand the user requirements of coaches, a survey (n = 38), interviews (n = 8) and focus-group sessions (n = 4) were held. Design principles were adopted into mock-ups, prototypes, and the final coach dashboard. Designing a coach dashboard using the co-operative research design helped to gain deep insights into the specific user requirements of coaches in their daily training practice. Integrating these requirements, scientific knowledge, and functionalities in the final coach dashboard allows the coach to make data-informed decisions on training prescription and optimise athlete development.
... However, the internal training load response of the athlete determines the outcome of the training [8]. The internal load (psychophysiological response) is in turn dependent on the actual external load and personal circumstances of the athletes, such as age [9], experience [10], and perceived stressors [11]. ...
... A consensus statement reads that the outcome of training stimuli is, among other factors, influenced by burdening psycho-social factors [3]. In addition, a recent review described that increased perception of stress is one of the main indicators of functional overreaching [11]. Therefore, regular measurement of perceived stress and recovery can be useful for athletes to prevent maladaptation to training. ...
The aim of this observational study was to examine the differences between training variables as intended by coaches and perceived by junior speed skaters and to explore how these relate to changes in stress and recovery. During a 4-week preparatory period, intended and perceived training intensity (RPE) and duration (min) were monitored for 2 coaches and their 23 speed skaters, respectively. The training load was calculated by multiplying RPE by duration. Changes in perceived stress and recovery were measured using RESTQ-sport questionnaires before and after 4 weeks. Results included 438 intended training sessions and 378 executed sessions of 14 speed skaters. A moderately higher intended (52:37 h) versus perceived duration (45:16 h) was found, as skaters performed fewer training sessions than anticipated (four sessions). Perceived training load was lower than intended for speed skating sessions (−532 ± 545 AU) and strength sessions (−1276 ± 530 AU) due to lower RPE scores for skating (−0.6 ± 0.7) or shorter and fewer training sessions for strength (−04:13 ± 02:06 hh:mm). All training and RESTQ-sport parameters showed large inter-individual variations. Differences between intended–perceived training variables showed large positive correlations with changes in RESTQ-sport, i.e., for the subscale’s success (r = 0.568), physical recovery (r = 0.575), self-regulation (r = 0.598), and personal accomplishment (r = 0.589). To conclude, speed skaters that approach or exceed the coach’s intended training variables demonstrated an increased perception of success, physical recovery, self-regulation, and personal accomplishment.
... Increasing the total duration of training above MMSS was found to lead to better performance outcomes [6]. However, trying to maximize the time spent above MMSS in every training session could lead to delayed fatigue, acute performance impairment, and increased risk of illness [7][8][9]. Therefore, athletes should focus on optimizing, not maximizing the time spent above MMSS both within a single exercise session and across a training cycle. ...
Background To improve sport performance, athletes use training regimens that include exercise below and above the maxi- mal metabolic steady state (MMSS).
Objective The objective of this review was to determine the additional effect of training above MMSS on VO2peak, Wpeak and time-trial (TT) performance in endurance-trained athletes.
Methods Studies were included in the review if they (i) were published in academic journals, (ii) were in English, (iii) were prospective, (iv) included trained participants, (v) had an intervention group that contained training above and below MMSS, (vi) had a comparator group that only performed training below MMSS, and (vii) reported results for VO2peak, Wpeak, or TT performance. Medline and SPORTDiscus were searched from inception until February 23, 2023.
Results Fourteen studies that ranged from 2 to 12 weeks were included in the review. There were 171 recreational and 128 competitive endurance athletes. The mean age and VO2peak of participants ranged from 15 to 43 years and 38 to 68 mL·kg−1·min−1, respectively. The inclusion of training above MMSS led to a 2.5 mL·kg−1·min−1 (95% CI 1.4–3.6; p < 0.01; I2 = 0%) greater improvement in VO2peak. A minimum of 81 participants per group would be required to obtain sufficient power to determine a significant effect (SMD 0.44) for VO2peak. No intensity-specific effect was observed for Wpeak or TT performance, in part due to a smaller sample size.
Conclusion A single training meso-cycle that includes training above MMSS can improve VO2peak in endurance-trained athletes more than training only below MMSS. However, we do not have sufficient evidence to conclude that concurrent adaptation occurs for Wpeak or TT performance.
... Another condition that determined the performance of exercise is skeletal muscle fatigue. Muscle fatigue can be monitored and evaluated using a variety of methods (Finsterer & Mahjoub, 2014;Roete et al., 2021). The lactic acid hypothesis, which is defined as the accumulation of lactate and acidosis in the working muscle, causing the inhibition of contraction in the muscles, and the decrease in exercise performance, has become controversial for the last decades, and it is thought that it is not appropriate to use it alone as an indicator of fatigue (Theofilidis et al., 2018). ...
Capsaicinoids and capsinoids are bioactive compounds mostly found in peppers. Although preclinical studies have reported that these compounds can improve exercise performance due to transient receptor potential vanilloid subtype 1 (TRPV1)-mediated thermogenesis, sympathetic modulation, and releasing calcium, it is still unclear how they affect exercise performance in humans as ergogenic supplements. Conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guide 2020, this systematic review examined the ergogenic effect of capsaicinoids and capsinoids on exercise performance in healthy adults. A total of 19 randomized placebo-controlled trials were included in the study. Studies were accessed by searching five databases (PubMed, Scopus, SPORTDiscus, Web of Science, and Cochrane Library). The quality of the studies was evaluated using the Cochrane risk-of-bias assessment tool. According to the study results, 10 studies examining the effect of capsaicinoid and capsinoid supplements on exercise performance reported positive effects. Also, the effect of capsaicinoids and capsinoids on exercise performance is more pronounced in resistance training. This difference, which varies according to the type of exercise, may be due to the correlation between capsaicin transient receptor potential vanilloid subtype 1 and insulin-like growth factor-1.
... Training load monitoring provides essential information to coaches when prescribing training sessions to their athletes, as training load parameters can be useful to evaluate injuries, illness, or overtraining. [19][20][21][22][23] Even though it is recommended to assess both internal and external training load parameters for sufficient insights into training stress, 2 few studies have investigated the direct relationship between internal and external load, and mostly in terms of their correlations 5,24 or ratio 25 using one score per (training) session. However, simplifying the time series data within sessions into one summary score may come at a cost of losing relevant information. ...
Background:
Training load is typically described in terms of internal and external load. Investigating the coupling of internal and external training load is relevant to many sports. Here, continuous kernel-density estimation (KDE) may be a valuable tool to capture and visualize this coupling.
Aim:
Using training load data in speed skating, we evaluated how well bivariate KDE plots describe the coupling of internal and external load and differentiate between specific training sessions, compared to training impulse scores or intensity distribution into training zones.
Methods:
On-ice training sessions of 18 young (sub)elite speed skaters were monitored for velocity and heart rate during 2 consecutive seasons. Training session types were obtained from the coach's training scheme, including endurance, interval, tempo, and sprint sessions. Differences in training load between session types were assessed using Kruskal-Wallis or Kolmogorov-Smirnov tests for training impulse and KDE scores, respectively.
Results:
Training impulse scores were not different between training session types, except for extensive endurance sessions. However, all training session types differed when comparing KDEs for heart rate and velocity (both P < .001). In addition, 2D KDE plots of heart rate and velocity provide detailed insights into the (subtle differences in) coupling of internal and external training load that could not be obtained by 2D plots using training zones.
Conclusion:
2D KDE plots provide a valuable tool to visualize and inform coaches on the (subtle differences in) coupling of internal and external training load for training sessions. This will help coaches design better training schemes aiming at desired training adaptations.
... Functional overreaching (FOR) is considered to be a desirable training outcome where periods of OT lead to an initial short-term reduction in performance, followed by an improvement or "rebound" above the initial baseline [7,8]. This improvement in performance is only observed after an initial reduction in performance lasting several days [9]. Interestingly, whilst symptoms of increased fatigue, hormonal disruption, and psychological disturbance (e.g., impaired mood, reduced vigor) are associated with NFOR/OTS, these symptoms may also be present in athletes classified as FOR [7]. ...
Short-term periods of increased resistance exercise training are often used by athletes to enhance performance, and can induce functional overreaching (FOR), resulting in improved physical capabilities. Non-functional overreaching (NFOR) or overtraining syndrome (OTS), occur when training demand is applied for prolonged periods without sufficient recovery. Overtraining (OT) describes the imbalance between training demand and recovery, resulting in diminished performance. While research into the effects of resistance exercise OT has gathered attention from sports scientists in recent years, the current research landscape is heterogeneous, disparate, and underrepresented in the literature. To date, no studies have determined a reliable physiological or psychological marker to assist in the early detection of NFOR or OTS following periods of resistance exercise OT. The purpose of this work is to highlight the conceptual and methodological limitations within some of the current literature, and to propose directions for future research to enhance current understanding.
... exercise intensity and volume) and proper recovery [e.g. [1][2][3][4]. Some evidence even suggests that daily directed training 14:203 decisions based on certain physiologic metrics can lead to longer term performance improvements [5][6][7]. ...
Background
The non-linear index alpha 1 of Detrended Fluctuation Analysis (DFA a1) of heart rate variability, has been shown to be a marker of fatigue during endurance exercise. This report aims to explore its ability to assess the physiological status as a surrogate metric for “readiness to train” while performing simulated warm-up sessions the day after two different exercise sessions.
Methods
11 triathletes were recruited to determine the first ventilatory threshold (VT1) during a baseline assessment and to perform 10-min of cycling at 90% of VT1 (simulating a warm-up bout) before (PRE) and within 36 h after (POST) light and heavy running exercise. RR intervals were recorded for DFA a1 analysis along with neuromuscular testing to verify the effects of the performed exercise sessions. In addition to common statistical methods, magnitude-based inferences (MBI) were applied to assess the changes in true score and thus also the practical relevance of the magnitude.
Results
Rating of perceived exertion for the heavy exercise session showed a significant higher rating as opposed to the light exercise session ( p < 0.001, d = 0.89). In regard of MBIs, PRE versus POST comparisons revealed a significant reduced DFA a1 with large effect size after the heavy exercise session ( p = 0.001, d = − 1.44) and a 99% chance that this negative change was clinically relevant.
Conclusions
Despite inter-individual differences, DFA a1 offers potential to assess physiological status and guide athletes in their training as an easy-to-apply monitoring procedure during a standardized warm-up. A regular assessment including individual data history and statistical references for identification of response is recommended. Further data are necessary to confirm the results in a larger and more homogeneous population.
... For example, an increased workload to the same level of perceived exertion represents an improvement in physical fitness-i.e., a positive training effect [17,50]. In addition, when athletes are in a state of accumulated fatigue due to an imbalance between training loads and recovery periods, a lower heart rate accompanies a higher perceived exertion for a given workload [90,91]. Heart rate reduction for the same exercise intensity most often indicates positive training adaptations [92,93]. ...
The perceived exertion construct creation is a landmark in exercise physiology and sport science. Obtaining perceived exertion is relatively easy, but practitioners often neglect some critical methodological issues in its assessment. Furthermore, the perceived exertion definition, neurophysiological basis, and practical applications have evolved since the perceived exertion construct’s inception. Therefore, we revisit the careful work devoted by Gunnar Borg with psychophysical methods to develop the perceived exertion construct, which resulted in the creation of two scales: the rating of perceived exertion (RPE) and the category-ratio 10 (CR10). We discuss a contemporary definition that considers perceived exertion as a conscious perception of how hard, heavy, and strenuous the exercise is, according to the sense of effort to command the limbs and the feeling of heavy breathing (respiratory effort). Thus, other exercise-evoked sensations would not hinder the reported perceived exertion. We then describe the neurophysiological mechanisms involved in the perceived exertion genesis during exercise, including the influence of the peripheral feedback from the skeletal muscles and the cardiorespiratory system (i.e., afferent feedback) and the influence of efferent copies from the motor command and respiratory drive (i.e., corollary discharges), as well as the interaction between them. We highlight essential details practitioners should consider when using the RPE and CR10 scales, such as the perceived exertion definition, the original scales utilization, and the descriptors anchoring process. Finally, we present how practitioners can use perceived exertion to assess cardiorespiratory fitness, individualize exercise intensity prescription, predict endurance exercise performance, and monitor athletes’ responses to physical training.
... In addition, and similar to previous research, HR measurements seem substantially different when comparing single-and multi-day events (van . One reason for the differing measurements is thus the adoption of different race tactics with another factor being the suppression of HR caused by accumulating fatigue which influences HR and HR max in male cycling (Lucia et al., 2003;Rodriguez-Marroyo et al., 2017;Roete et al., 2021;. Currently, the UCI limits women's multi-day races to a maximum of seven days with special permission needed for longer events. ...
This study is governed by two aims: firstly, expanding the meagre knowledge store regarding the demands set by professional female road cycling and, secondly, ascertaining whether these demands vary in relation to different race-levels and race duration (single- or multi-day events). A total of 1349 female professional road races was analysed and demands (intensity, load and performance) were determined. Races were classified based on race level (i.e. Women's World Tour [WWT], level.1 and level.2 according to the International Cycling Federation) and race duration (single- or multi-day events). Differences were assessed with a multilevel random intercept model whilst the strength of said differences were indicated by Cohen’s d (0–0.19 trivial; 0.20–0.59 small; 0.60–1.1.9 moderate; 1.20–1.99 large; ≥2.00 very large). In general, no moderate differences for load and intensity were noted for the different race levels. This result contrasts with data obtained from male road cycling. Moderate higher 3 and 5 min maximal mean power (MMP) values were noted in the WWT compared to Level.2 races. More substantial differences were found to exist between single- and multi-day races with single-day races presenting small to large higher load and intensity values. In addition, single-day races presented higher MMPs overall durations (5 s–60 min) although these differences can be rated trivial to small. This study contributes to the limited knowledge store describing demands in professional female cycling. The reported data provide valuable insights which may aid practitioners and/or coaches in preparing female professional cyclists for races.
• Highlights
• Within female professional cycling, some differences were noted in the demands (load, intensity and performances) set by different race levels. However, (in general), these differences were trivial to small, which contrasts with male professional cycling.
• More pronounced differences were noted in the demands set by single- and multi-day races. The load (Work done, eTRIMP and TSS) was moderate to large higher in single-day races. Differences in load are primarily caused by a combination of small higher duration and small higher intensity.
• No moderate differences in performance measures (i.e MMPs) were noted for different race levels or between single- and multi-day races.
Extended overreaching without recovery carries risks of nonfunctional overreaching and overtraining. Coaches mitigate these risks by screening for overreaching, often using jump testing; however, many are uncertain about which jump variables to measure. A systematic review was conducted to identify jumping kinetic and kinematic variables associated with heightened training stress. Manuscripts were included if they monitored overreaching in healthy, adult athletes at National Level or above using an unloaded vertical jump test; and excluded if they did not report measured kinetic/kinematic variables, did not include sufficient data to calculate effect sizes (ES) and confidence intervals (95% CI) or were not available in English. Fourteen manuscripts met inclusion/exclusion criteria. Most studies had a low (71.4%) or moderate (21.4%) risk of bias. Twenty-nine unique outcome measures were reported with 11 reported in multiple studies. The most reported measures were the ratio of flight time to contraction time (15 ES reported), jump height (JH, 12 ES), mean power (7 ES), peak power (PP, 7 ES), mean velocity (5 ES), and peak force (PF, 5 ES). PP, PF, and JH demonstrated the most consistent negative alterations. Coaches should consider metrics that include changes in jump strategy alongside JH in jump screening.
See Video 1—Video Abstract—http://links.lww.com/SCJ/A408.
Purpose:
To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists.
Method:
For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen's d.
Results:
Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men's training (d = 0.44-1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men's and women's training (d = 0.07-0.12). However, load values expressed per kilometer were moderately (d = 0.67-0.76) higher in women compared with men's training.
Conclusions:
Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists.
The use of heart rate variability (HRV) to inform daily training prescription is becoming common in endurance sport. Few studies, however, have investigated the use of pre-training HRV to predict decreased performance or altered exercising autonomic response, typical of functional overreaching (FOR). Further, a new cardiac vagal tone (ProCVT) technology purports to eliminate some of the noise associated with daily HRV, and therefore may be better at predicting same-day performance. The purpose of this investigation was to examine if changes to resting HRV and ProCVT were associated with alterations in performance, maximal heart rate (HRmax), or heart rate recovery (HRrec) in FOR athletes. Twenty-eight recreational cyclists and triathletes were assigned to experimental/control conditions and underwent: 1 week of reduced training, 3 weeks of overload (OL) or regular training (CON), and 1 week of recovery. Testing occurred following the reduced training week (T1), post-3 weeks of training (T2), and following the recovery week (T3). Measures of resting HRV/ProCVT were collected each testing session, followed by maximal incremental exercise tests with HRrec taken 60 s post-exercise. Performance decreased from T1 to T2 in the OL group vs. CON (Δ−9 ± 12 vs. Δ9 ± 11 W, P < .001), as did HRmax (Δ−8 ± 4 vs. Δ−2 ± 4 bpm, P < .001). HRrec increased from T1 to T2 in the OL group vs. CON (Δ10 ± 9 vs. Δ2 ± 5 beats/min, P < .01). HRV and ProCVT did not change in either group. Same-day resting autonomic measures are insufficient in predicting alterations to performance or exercising HR measures following overload training.
Recent research has demonstrated decreases in resting metabolic rate (RMR), body composition and performance following a period of intensified training in elite athletes, however the underlying mechanisms of change remain unclear. Therefore, the aim of the present study was to investigate how an intensified training period, designed to elicit overreaching, affects RMR, body composition, and performance in trained endurance athletes, and to elucidate underlying mechanisms.Thirteen (n = 13) trained male cyclists completed a six-week training program consisting of a "Baseline" week (100% of regular training load), a "Build" week (~120% of Baseline load), two "Loading" weeks (~140, 150% of Baseline load, respectively) and two "Recovery" weeks (~80% of Baseline load). Training comprised of a combination of laboratory based interval sessions and on-road cycling. RMR, body composition, energy intake, appetite, heart rate variability (HRV), cycling performance, biochemical markers and mood responses were assessed at multiple time points throughout the six-week period. Data were analysed using a linear mixed modeling approach.The intensified training period elicited significant decreases in RMR (F(5,123.36) = 12.0947, p
The relationship between recovery and fatigue and its impact on performance has attracted the interest of sports science for many years. An adequate balance between stress (training and competition load, other life demands) and recovery is essential for athletes to achieve continuous high-level performance. Research has focused on the examination of physiological and psychological recovery strategies to compensate external and internal training and competition loads. A systematic monitoring of recovery and the subsequent implementation of recovery routines aims at maximizing performance and preventing negative developments such as underrecovery, non-functional overreaching, the overtraining syndrome, injuries, or illnesses. Due to the inter- and intra-individual variability of responses to training, competition, and recovery strategies, a diverse set of expertise is required to address the multifaceted phenomena of recovery, performance and their interactions to transfer knowledge from sports science to sports practice. For this purpose, a symposium on Recovery and Performance was organized at the Technical University Munich Science and Study Center Raitenhaslach (Germany) in September 2016. Various international experts from many disciplines and research areas gathered to discuss and share their knowledge of recovery for performance enhancement in a variety of settings. The results of this meeting are outlined in this consensus statement that provides central definitions, theoretical frameworks, as well as practical implications as a synopsis of the current knowledge of recovery and performance. While our understanding of the complex relationship between recovery and performance has significantly increased through research, we also elaborate some important issues for future investigations.
Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best method- ologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the eld has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on “Monitoring Athlete Training Loads—The Hows and the Whys” was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary prac- tices in this rapidly growing eld and also to investigate where it may branch to in the future. This consensus statement brings together the key ndings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.
Todd M Sabato, Tanis J Walch, Dennis J Caine Department of Kinesiology and Public Health Education, University of North Dakota, Grand Forks, ND, USA Abstract: This article presents a current review of the risk of physical and psychological injury associated with participation in elite youth sport, and suggests strategies to ensure the physical and emotional health of these young athletes. Although there is lack of epidemiological data, especially with regard to psychological injury, preliminary data suggest that the risk of injury is high in this population. While there is lack of incident and follow-up data, there is also concern regarding burnout, disordered eating, and the long-term consequences of injury. Modifiable injury risk factors identified include postural control, competition anxiety, life events, previous injury, and volume of training. There are presently no studies designed to determine the effectiveness of injury prevention measures in elite youth sports. However, there is adequate evidence arising from injury prevention studies of youth sports participants – including neuromuscular training, protective equipment, mental training to enhance self-esteem, and sport rules modification – to prevent injuries in elite youth sports settings. Although not tested, psychosocial prevention strategies such as adoption of task-oriented coping mechanisms, autonomous support from parents, and a proactive organizational approach also show promise in injury prevention. Keywords: elite, young athlete, athletic injury, psychological, risk factors, injury prevention
Purpose:
Faster heart rate recovery (HRR) following high-to-maximal exercise (≥90% HRmax) 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 and results:
HRR and rate of perceived exertion (RPE) responses were compared during an incremental intermittent running protocol to exhaustion in twenty experienced male triathletes (8 control and 13 overload subjects led to f-OR) before (Pre), immediately after an overload training period (Mid) and following a 1-week taper (Post). Both groups demonstrated an increase in HRR values at Mid, but this change was very likely to almost certainly larger in the f-OR group at all running intensities (large to very large differences, e.g. +16 ±7 bpm vs. +3 ±5 bpm, in the f-OR and control groups at 11 km·h-1, respectively). The highest between-group differences in changes in HRR were reported at 11 km·h-1 (13 ±4 bpm) and 12 km·h-1 (10 ±6 bpm). 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 AU).
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 following submaximal exercise may be more discriminant than HRR measures taken following maximal exercise for monitoring f-OR. These findings may be applied in practice by regularly assessing HRR following submaximal exercise (i.e., warm-up) for monitoring endurance athletes responses to training.
Purpose:
The aim of the study was to investigate whether heart rate recovery (HRR) may represent an effective marker of functional overreaching (f-OR) in endurance athletes.
Methods and results:
Thirty-one experienced male triathletes were tested (10 control and 21 overload subjects) before (Pre), and immediately after an overload training period (Mid) and after a 2-week taper (Post). Physiological responses were assessed during an incremental cycling protocol to exhaustion, including heart rate, catecholamine release and blood lactate concentration. Ten participants from the overload group developed signs of f-OR at Mid (i.e. -2.1 ± 0.8% change in performance associated with concomitant high perceived fatigue). Additionally, only the f-OR group demonstrated a 99% chance of increase in HRR during the overload period (+8 ± 5 bpm, large effect size). Concomitantly, this group also revealed a >80% chance of decreasing blood lactate (-11 ± 14%, large), plasma norepinephrine (-12 ± 37%, small) and plasma epinephrine peak concentrations (-51 ± 22%, moderate). These blood measures returned to baseline levels at Post. HRR change was negatively correlated to changes in performance, peak HR and peak blood metabolites concentrations.
Conclusion:
These findings suggest that i) a faster HRR is not systematically associated with improved physical performance, ii) changes in HRR should be interpreted in the context of the specific training phase, the athletes perceived level of fatigue and the performance response; and, iii) the faster HRR associated with f-OR may be induced by a decreased central command and by a lower chemoreflex activity.
The aim of this paper is to review current cycling related sport science literature to formulate guidelines to classify female subject groups. We aim to compare this classification system for female subject groups with the classification system for male subject groups.
A database of 82 papers which described female subject groups contains information on pre-experimental maximal cycle-protocol designs, terminology, biometrical and physiological parameters and cycling experience. Subject groups were divided into "performance levels", according to the nomenclature. Body mass, body mass index, maximal oxygen consumption (VO2max), peak power output (PPO), and training status were compared between performance levels and between female and male performance levels.
Five female performance levels (PL) were defined, representing untrained, active, trained, well-trained and professional female subjects. VO2max and PPO significantly increased with the level of performance, except for PL3 and PL4 (p< 0.01). For each performance level significant differences were observed in absolute and relative VO2max and PPO between male and female subject groups. Relative VO2max is the most cited parameter for female subject groups and is proposed as the principal parameter to classify the female subject groups.
This systematic review shows the large variety in the description of female subject groups in the existing literature. We propose a standardized pre-experimental testing protocol and guidelines to classify female subject groups into 5 performance levels, based on (1) relative VO2max, (2) relative PPO and (3) training status, absolute VO2max and absolute PPO.
Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
Background: Functional overreaching (F-OR) induced by heavy load endurance training programs has been associated with reduced heart rate values both at rest and during exercise. Because this phenomenon may reflect an impairment of cardiac response, this research was conducted to test this hypothesis. Methods and Results: Thirty-five experienced male triathletes were tested (11 control and 24 overload subjects) before overloading (Pre), immediately after overloading (Mid) and after a 2-week taper period (Post). Physiological responses were assessed during an incremental cycling protocol to volitional exhaustion, including catecholamine release, oxygen uptake (VO2), arteriovenous O2 difference, cardiac output (Q), systolic (SBP) and diastolic blood pressure (DBP). Twelve subjects of the overload group developed signs of F-OR at Mid (decreased performance with concomitant high perceived fatigue), while 12 others did not (acute fatigue group, AF). VO2max was reduced only in F-OR subjects at Mid. Lower Q and SBP values with greater arteriovenous O2 difference were reported in F-OR subjects at all exercising intensities, while no significant change was observed in the control and AF groups. A concomitant decrease in epinephrine excretion was reported only in the F-OR group. All values returned to baseline at Post. Conclusion: Following an overload endurance training program leading to F-OR, the cardiac response to exhaustive exercise is transiently impaired, possibly due to reduced epinephrine excretion. This finding is likely to explain the complex process of underperformance syndrome experienced by F-OR endurance athletes during heavy load programs.
We analyzed HR variability (HRV) to detect alterations in autonomic function that may be associated with functional overreaching (F-OR) in endurance athletes.
Twenty-one trained male triathletes were randomly assigned to either intensified training (n = 13) or normal training (n = 8) groups during 5 wk. HRV measures were taken daily during a 1-wk moderate training (baseline), a 3-wk overload training, and a 1-wk taper.
All the subjects of the intensified training group demonstrated a decrease in maximal incremental running test performance at the end of the overload period (-9.0% ± 2.1% of baseline value) followed by a performance supercompensation after the taper and were therefore diagnosed as F-OR. According to a qualitative statistical analysis method, a likely to very likely negative effect of F-OR on HR was observed at rest in supine and standing positions, using isolated seventh-day values and weekly average values, respectively. When considering the values obtained once per week, no clear effect of F-OR on HRV parameters was found. In contrast, the weekly mean of each HRV parameter showed a larger change in indices of parasympathetic tone in the F-OR group than the control group in supine position (with a 96%/4%/0% chance to demonstrate a positive/trivial/negative effect on Ln RMSSD after the overload period; 77%/22%/1% on LnHF) and standing position [98%/1%/1% on Ln RMSSD; 99%/0%/1% on LnHF; 95%/1%/4% on Ln(LF + HF)]. During the taper, theses responses were reversed.
Using daily HRV recordings averaged over each week, this study detected a progressive increase in the parasympathetic modulation of HR in endurance athletes led to F-OR. It also revealed that due to a wide day-to-day variability, isolated, once per week HRV recordings may not detect training-induced autonomic modulations in F-OR athletes.
Purpose:
The aim of this systematic literature review was to outline the various preexperimental maximal cycle-test protocols, terminology, and performance indicators currently used to classify subject groups in sport-science research and to construct a classification system for cycling-related research.
Methods:
A database of 130 subject-group descriptions contains information on preexperimental maximal cycle-protocol designs, terminology of the subject groups, biometrical and physiological data, cycling experience, and parameters. Kolmogorov-Smirnov test, 1-way ANOVA, post hoc Bonferroni (P < .05), and trend lines were calculated on height, body mass, relative and absolute maximal oxygen consumption (VO(2max)), and peak power output (PPO).
Results:
During preexperimental testing, an initial workload of 100 W and a workload increase of 25 W are most frequently used. Three-minute stages provide the most reliable and valid measures of endurance performance. After obtaining data on a subject group, researchers apply various terms to define the group. To solve this complexity, the authors introduced the neutral term performance levels 1 to 5, representing untrained, recreationally trained, trained, well-trained, and professional subject groups, respectively. The most cited parameter in literature to define subject groups is relative VO(2max), and therefore no overlap between different performance levels may occur for this principal parameter. Another significant cycling parameter is the absolute PPO. The description of additional physiological information and current and past cycling data is advised.
Conclusion:
This review clearly shows the need to standardize the procedure for classifying subject groups. Recommendations are formulated concerning preexperimental testing, terminology, and performance indicators.
Small changes in performance, as low as 1%, are regarded as meaningful in well-trained cyclists. Being able to detect these changes is necessary to fine tune training and optimise performance. The typical error of measurement (TEM) in common performance cycle tests is about 2-3%. It is not known whether this TEM is lower in well-trained cyclists and therefore whether small changes in performance parameters are detectable. In this research, after familiarisation, 17 well-trained cyclists each completed three Peak Power Output (PPO) tests (including VO2max) and three 40km time trials (40km TT). All tests were performed after a standardised warm-up at the same relative intensity and under a strict testing-protocol. TEM within the PPO-test was 2.2% for VO2max and 0.9% for PPO, while TEM for the 40km TT was 0.9%. In conclusion, measurement of PPO and 40km TT time, after a standardised warm-up, has sufficient precision in well-trained cyclists to detect small meaningful changes.
The aim of the present study was to compare the maximal isometric torque and cardio-respiratory parameters in well-trained young and master triathletes prior to and following an Olympic distance triathlon. One day before and 24 h following the event, participants performed three maximum voluntary isometric knee extensions and flexions and an incremental running test on a treadmill to determine the maximal isometric torque, maximal oxygen uptake VO(2max), speed at VO(2max) (vVO(2)max), speed at ventilatory thresholds (VT1 and VT2) and submaximal running economy. Prior to the event VO(2max), vVO(2)max, speed at ventilatory thresholds and running economy were significantly lower in master athletes, but maximal voluntary torque was similar between the groups. 24 h following the race, a similar significant decrease in VO(2max) (-3.1% in masters, and -6.2% in young, p < 0.05), and vVO(2)max (-9.5% in masters, and -5.6% in young, p < 0.05) was observed in both the groups. The speed at VT2 significantly decreased only in master athletes (-8.3%, p < 0.05), while no change was recorded in maximal voluntary torque or submaximal running economy following the event. The results indicate that for well-trained subjects, the overall relative exercise intensity during an Olympic distance triathlon and the fatigue 24 h following the event seem to be independent of age.
Recently a novel submaximal test, known as the Lamberts and Lambert submaximal cycle test (LSCT), has been developed with the purpose of monitoring and predicting changes in cycling performance. Although this test has been shown to be reliable and able to predict cycling performance, it is not known whether it can measure changes in training status. Therefore, the aim of this study was to determine whether the LSCT is able to track changes in performance parameters, and objective and subjective markers of well-being. A world class cyclo-cross athlete (31 years) volunteered to participate in a 10-week observational study. Before and after the study, a peak power output (PPO) test with respiratory gas analysis (VO(2max)) and a 40-km time trial (40-km TT) test were performed. Training data were recorded in a training logbook with a daily assessment of well-being, while a weekly LSCT was performed. After the training period all performance parameters had improved by a meaningful amount (PPO +5.2%; 40-km TT time -2.5%; VO(2max) +1.4%). Increased training loads during weeks 2 and 6 and the subsequent training-induced fatigue was reflected in the increased well-being scores. Changes during the LSCT were most clearly notable in (1) increased power during the first minute of third stage, (2) increased rating of perceived exertion during second and third stages, and (3) a faster heart rate recovery after the third stage. In conclusion, these data suggest that the LSCT is able to track changes in training status and detect the consequences of sharp increases in training loads which seem to be associated with accumulating fatigue.
Tapering and Peaking for Optimal Performance offers in-depth discussion of the science, strategy, and program design of the tapering phase of training. This first-ever book devoted to the subject presents current scientific data on tapering, its physiological and psychological effects, and how these effects relate to athletic performance. Featuring various training models and experiential knowledge, this book allows readers to design optimal tapering programs for each athlete. Though most coaches and sport scientists are aware of the key role of tapering in preparation for competition, many tapering programs are developed by a trial-and-error process, often leading athletes to fall short of their optimal performance. In Tapering and Peaking for Optimal Performance, author Iñigo Mujika, one of the foremost researchers on tapering in sport, presents various models and explains current scientific data on tapering and its effects on physiological and psychological factors that support or hinder performance. Using this information, coaches, athletes, and sport scientists will be able to do the following: design optimal tapering plans specific to athletes and the competition; set realistic performance goals for competition; avoid negative outcomes associated with a deficient tapering program.
The regular monitoring of athletes is important to fine-tune training and detect early symptoms of overreaching. Therefore the aim of this study was to determine if a noninvasive submaximal running test could reflect a state of overreaching. 14 trained runners completed a noninvasive Lamberts Submaximal Running Test, one week before and 2 days after finishing an ultramarathon, and delayed onset of muscle soreness and the daily analysis of life demands for athletes questionnaire were also captured. After the ultramarathon, submaximal heart rate was lower at 70% (−3 beats) and 85% of peak treadmill running speed (P<0.01). Ratings of perceived exertion were higher at 60% (2 units) and 85% (one unit) of peak treadmill running speed, while 60-second heart rate recovery was significantly faster (7 beats, P<0.001). Delayed Onset of Muscle Soreness scores and the number of symptoms of stress (Daily Analysis of Life Demands for Athletes) were also higher after the ultramarathon (P<0.01). The current study shows that the Lamberts Submaximal Running Test is able to reflect early symptoms of overreaching. Responses to acute fatigue and overreaching were characterized by counterintuitive responses, such as lower submaximal heart rates and faster heart rate recovery, while ratings of perceived exertion were higher.
Purpose:
The Lamberts and Lambert Submaximal Cycle Test (LSCT) consists of 3 stages during which cyclist's cycle for 6 minutes at 60%, 6 minutes at 80% and 3 minutes at 90% of their maximal heart rate, followed by one-minute recovery. It was the aim of this study to determine if the LSCT is able to reflect a state of functional overreaching in professional female cyclists during an 8-day training camp and the following recovery days.
Methods:
Six professional female cyclists performed an LSCT on day 1, day 5 and day 8 of the training camp and 3 days after the training camp. During each stage of the LSCT, power output and rating of perceived exertion (RPE) were determined. Training diaries and profile of mood status (POMS) were also completed.
Results:
At the middle and the end of the training camp, increased power output during the 2(nd) and 3(rd) stage of the LSCT were accompanied with increased RPE during these stages and/or the inability to reach 90% of their maximal heart rate. All athletes reported increased feelings of fatigue and muscle soreness, while changes in energy-balance, calculated from the POMS, were less indicative of a state of overreaching. After 3 days of recovery, all parameters of the LSCT returned to baseline, indicating a state of functional overreaching during the training camp.
Conclusion:
The LSCT is able to reflect a state of overreaching in elite professional female cyclists during an 8-day training camp and the following recovery days.
Purpose:
High training loads combined with other stressors can lead to performance decrements. The time needed to recover determines the diagnosis of (non)-functional overreaching or the overtraining syndrome. The aim of this study was to describe the effects of an 8-day (intensified) training camp of professional female cyclists on physical and cognitive performance.
Methods:
Nine subjects performed a 30-min time trial (TT), cognitive test and profile of mood state questionnaire before, during and after a training camp (49% increased training volume). Upon data collection, cyclists were classified as "overreached" (OR) or "adapted" (A) based on TT performance. Two-way repeated measures ANOVA was used to detect changes in physical and cognitive parameters.
Results:
Five cyclists were OR, based on decreased mean power output (MPO) (-7.03 %) on day 8. Four cyclists were A (increased MPO: +1.72 %). MPO and HRmax were significantly different between A and OR. A significant slower reaction time (RT) (+3.35 %) was found in OR, whereas RT decreased (-4.59 %) in A. The change in MPO was negatively correlated with change in RT in the cognitive test (R2 = 0.52).
Conclusion:
This study showed that the use of objective, inexpensive and easy-to-interpret physical and cognitive tests can facilitate the monitoring of training adaptations in professional female athletes.
The Lamberts and Lambert Submaximal Cycle Test (LSCT) is a novel test designed to monitor performance, and fatigue/recovery in cyclists. Studies have shown the ability to predict performance; however, there is a lack of studies concerning monitoring of fatigue/recovery. 23 trained male cyclists (31±9y, VO2max: 59.4±7.4 ml/min/kg) completed a training camp. The LSCT was conducted at day 1, day 8, and day 11. After day 1, an intensive 6-day training period was performed. Between day 8 and day 11, recovery period was realized. The LSCT consists of three stages with fixed heart rates of 6min at 60% and 80% and 3min at 90% of maximum heart rate. During the stages, power output and rating of perceived exertion (RPE) were determined. Heart rate recovery (HRR) was measured after stage 3. Power output almost certainly (standardized mean difference: 1.0) and RPE very likely (1.7) increased from day 1 to day 8 at stage 2. Power output likely (0.4) and RPE almost certainly (2.6) increased at stage 3. From day 8 to day 11, power output possibly (-0.4) and RPE likely (-1.5) decreased at stage 2 and possibly (-0.1) and almost certainly (-1.9) at stage 3. HRR was likely (0.7) accelerated from day 1 to day 8. Changes from day 8 to day 11 were unclear (-0.1). The LSCT can be used for monitoring fatigue and recovery, since parameters were responsive to a fatiguing training and a following recovery period. However, consideration of multiple LSCT variables is required to interpret the results correctly.
A self-report inventory of sources of life-stress and symptoms of stress is described. The tool can be used to determine the nature of an athlete's response to training, particularly his/her capacity to tolerate training loads. Data are used to demonstrate the use of the inventory to determine i) training responses which are either too stressed or under-stressed, ii) the ideal amount of stress to promote the optimum level of training effort, iii) the influence of outside-of-sport stresses that interfere with the training response, iv) preliminary features of overtraining, v) reactions to jet-lag and travel fatigue, and vi) peaking responses.
Fatigue is commonly reported in many neurologic illnesses, including multiple sclerosis, Parkinson disease, myasthenia gravis, traumatic brain injury, and stroke. Fatigue contributes substantially to decrements in quality of life and disability in these illnesses. Despite the clear impact of fatigue as a disabling symptom, our understanding of fatigue pathophysiology is limited and current treatment options rarely lead to meaningful improvements in fatigue. Progress continues to be hampered by issues related to terminology and assessment. In this article, we propose a unified taxonomy and a novel assessment approach to addressing distinct aspects of fatigue and fatigability in clinical and research settings. This taxonomy is based on our current knowledge of the pathophysiology and phenomenology of fatigue and fatigability. Application of our approach indicates that the assessment and reporting of fatigue can be clarified and improved by utilizing this taxonomy and creating measures to address distinct aspects of fatigue and fatigability. We review the strengths and weaknesses of several common measures of fatigue and suggest, based on our model, that many research questions may be better addressed by using multiple measures. We also provide examples of how to apply and validate the taxonomy and suggest directions for future research.
The purpose of this study was to characterize the effect of a 2-week overload period immediately followed by a 1-week taper period on different cognitive processes including executive and nonexecutive functions, and related heart rate variability. Eleven male endurance athletes increased their usual training volume by 100% for 2 weeks, and decreased it by 50% for 1 week. A maximal graded test, a constant speed test at 85% of peak treadmill speed, and a Stroop task with the measurement of heart rate variability were performed at each period. All participants were considered as overreached. We found a moderate increase in the overall reaction time to the three conditions of the Stroop task after the overload period (816 ± 83 vs 892 ± 117 ms, P = 0.03) followed by a return to baseline after the taper period (820 ± 119 ms, P = 0.013). We found no association between cognitive performance and cardiac parasympathetic control at baseline, and no association between changes in these measures. Our findings clearly underscore the relevance of cognitive performance in the monitoring of overreaching in endurance athletes. However, contrary to our hypothesis, we did not find any relationship between executive performance and cardiac parasympathetic control.
In sports, the importance of optimizing the recovery-stress state is critical. Effective recovery from intense training loads often faced by elite athletes can often determine sporting success or failure. In recent decades, athletes, coaches, and sport scientists have been keen to find creative, new methods for improving the quality and quantity of training for athletes. These efforts have consistently faced barriers, including overtraining, fatigue, injury, illness, and burnout. Physiological and psychological limits dictate a need for research that addresses the avoidance of overtraining, maximizes recovery, and successfully negotiates the fine line between high and excessive training loads. Monitoring instruments like the Recovery-Stress Questionnaire for Athletes can assist with this research by providing a tool to assess their perceived state of recovery. This article will highlight the importance of recovery for elite athletes and provide an overview of monitoring instruments.
The control of heart rate by the autonomic nervous system was investigated in conscious human subjects by observing the effects of β-adrenergic blockade with propranolol, of parasympathetic blockade with atropine, and of combined sympathetic and parasympathetic blockade. The increase in heart rate with mild exercise in supine men was mediated predominantly by a decrease in parasympathetic activity; at higher levels of work, however, sympathetic stimulation also contributed to cardiac acceleration. When the response to 80° head-up tilt was compared with the response to exercise in the same subject supine, it appeared that the attainment of an equivalent heart rate was associated with a significantly greater degree of sympathetic activity during tilting than during exercise. Although heart rate was always higher at any given pressure during exercise than it had been at rest, the changes in heart rate that followed alterations in arterial pressure were found to be of similar magnitudes at rest and during exercise; it was therefore concluded that the sensitivity of the baroreceptor system was not altered during exercise. Investigation of the efferent pathways concerned in mediating the baroreceptor-induced changes in heart rate suggested that the relative roles of the sympathetic and parasympathetic systems were nearly equal in the resting state. During exercise, on the other hand, changes in sympathetic activity appeared to be the predominant mechanism by which speeding and slowing of the heart was achieved. It thus appears that baroreceptor-induced alterations in heart rate may be mediated by increased or decreased activity of either efferent system; the ultimate balance, however, is critically dependent on the preexisting level of background autonomic activity.
The parasympathetic, Addison type, overtraining syndrome represents the dominant modern type of this syndrome. Beside additional mechanisms, an autonomic or neuroendocrine imbalance is hypothesized as underlying.
Several findings support this thesis. During heavy endurance training or overreaching periods, the majority of findings give evidence of a reduced adrenal responsiveness to ACTH. This is compensated by an increased pituitary ACTH release. In an early stage of the overtraining syndrome, despite increased pituitary ACTH release, the decreased adrenal responsiveness is no longer compensated. The cortisol response decreases. In an advanced stage of overtraining syndrome, the pituitary ACTH release also decreases. In this stage, there is additionally evidence for decreased intrinsic sympathetic activity and sensitivity of target organs to catecholamines. This is indicated by decreased catecholamine excretion during night rest, decreased beta-adrenoreceptor density, decreased beta-adrenoreceptor-mediated responses, and increased resting plasma norepinephrine levels and responses to exercise. However, this complete pattern is only observed subsequent to high-volume endurance overtraining at high caloric demands.
The described functional alterations of pituitary-adrenal axis and sympathetic system can explain persistent performance incompetence in affected athletes.
In the exercising human, maximal oxygen uptake (VO2max) is limited by the ability of the cardiorespiratory system to deliver oxygen to the exercising muscles. This is shown by three major lines of evidence: 1) when oxygen delivery is altered (by blood doping, hypoxia, or beta-blockade), VO2max changes accordingly; 2) the increase in VO2max with training results primarily from an increase in maximal cardiac output (not an increase in the a-v O2 difference); and 3) when a small muscle mass is overperfused during exercise, it has an extremely high capacity for consuming oxygen. Thus, O2 delivery, not skeletal muscle O2 extraction, is viewed as the primary limiting factor for VO2max in exercising humans. Metabolic adaptations in skeletal muscle are, however, critical for improving submaximal endurance performance. Endurance training causes an increase in mitochondrial enzyme activities, which improves performance by enhancing fat oxidation and decreasing lactic acid accumulation at a given VO2. VO2max is an important variable that sets the upper limit for endurance performance (an athlete cannot operate above 100% VO2max, for extended periods). Running economy and fractional utilization of VO2max also affect endurance performance. The speed at lactate threshold (LT) integrates all three of these variables and is the best physiological predictor of distance running performance.
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