Impact of resistance training status on trunk muscle activation in a fatiguing set of heavy back squats.

PURPOSE: In this study we measured neural activation (EMG) in four trunk stabilizer muscles and vastus lateralis (VL) in trained and novice participants during a set of squat repetitions to volitional fatigue at 85% 1RM. METHODS: Forty males were recruited into two groups, novice (NG: n = 21) and experienced (EG: n = 19), according to relative squat 1RM. Participants were tested twice to: (1) determine squat 1RM, and (2) complete a single set of repetitions to volitional fatigue at 85% 1RM. Relative squat 1RM; NG < 140% body mass, EG > 160% body mass. Neuromuscular activation was measured by EMG for the following: rectus abdominus (RA), external oblique (EO), lumbar sacral erector spinae (LSES), upper lumbar erector spinae (ULES) and VL in eccentric and concentric phase. Completed repetitions, RPE and EMG in repetition 1 and at 20, 40, 60, 80 and 100% of completed repetitions were analysed. RESULTS: No group differences were found between number repetitions completed and RPE in repetitions to volitional fatigue at 85% 1RM. Neuromuscular activation increased significantly in all muscle groups in eccentric and concentric phase apart from RA in the eccentric phase. Trunk neuromuscular activation was higher in NG compared to EG and this was significant in EO, LSES and ULES in eccentric phase and LSES in the concentric phase. VL activation increased in both phases with no group differences. CONCLUSION: Trunk neuromuscular activation increases in a fatiguing set of heavy squats regardless of training status. Increased back squat strength through training results in lower neuromuscular activation despite greater absolute external squat loads.

Analysis of a Submaximal Cycle Test to Monitor Adaptations to Training: Implications for Optimizing Training Prescription.

ABSTRACT: Capostagno, B, Lambert, MI, and Lamberts, RP. Analysis of a submaximal cycle test to monitor adaptations to training: Implications for optimizing training prescription. J Strength Cond Res 35(4): 924-930, 2021-The Lamberts and Lambert Submaximal Cycle Test (LSCT) was developed to monitor training adaptation to optimize the training prescription of cyclists. However, it is not known which of the variables within the LSCT are most closely associated with changes in training status. The aim of this study was to retrospectively analyze the LSCT data of cyclists (n = 15) who completed a 2-week high-intensity interval training intervention. The cyclists were retrospectively allocated to 1 of 2 groups based on the change in their 40-km time trial (40-km TT) performance. The "adapters" (n = 7) improved their 40-km TT performance, while the "nonadapters" (n = 8) failed to improve their 40-km TT performance. The variables measured in the LSCT were analyzed to determine which measures tracked the improvements in 40-km TT performance the best. Heart rate recovery increased significantly during the training period in the "adapters" group, but decreased in the "nonadapters" group. Mean power output in stage 2 of the LSCT tended to increase during the high-intensity interval training period in the "adapters" group and was unchanged in the "nonadapters" group. The findings of this study suggest that heart rate recovery and mean power output during stage 2 are the most sensitive markers to track changes in training status within the LSCT.

Trunk Muscle Activation in the Back and Hack Squat at the Same Relative Loads.

Clark, DR, Lambert, MI, and Hunter, AM. Trunk muscle activation in the back and hack squat at the same relative loads. J Strength Cond Res 33(7S): S60-S69, 2019-The hack squat (HS) is likely to produce a greater 1 repetition maximum (1RM) compared with the back squat (BS). This can be attributed to the support of the trunk during the HS compared with no support during BS. This support, however, may compromise trunk muscle activation (TMA), therefore producing different training adaptations. Accordingly, the purpose of this study was to compare 1RM in BS and HS and TMA at 4 relative loads, 65, 75, 85, and 95% of maximal system mass. Ten males completed 3 test sessions: (a) BS and HS 1RM, (b) HS and BS neuromuscular test familiarization, and (c) neuromuscular test for 3 reps at 4 loads for BS and HS. Back squat TMA was significantly greater (p ≤ 0.05) than HS for all muscles and phases except rectus abdominus in concentric phase. Trunk muscle activation increased (p ≤ 0.05) with load in all muscles for both exercises and phases apart from lumbar sacral erector spinae in HS eccentric phase. Mean HS 1RM and submaximal loads were significantly (p < 0.0001) higher than the equivalent BS loads. Duration of the eccentric phase was higher (p < 0.01) in HS than BS but not different in concentric phase. Duration increased significantly (p < 0.01) with load in both exercises and both phases. Despite higher absolute tests loads in HS, TMA was higher in BS. Trunk muscle activation is sensitive to load in both exercises. Back squat is more effective than HS in activating the muscles of the trunk and therefore, arguably more effective in developing trunk strength and stability for dynamic athletic performance.

Tackle technique and tackle-related injuries in high-level South African Rugby Union under-18 players: real-match video analysis.

BACKGROUND: The high injury rate associated with rugby union is primarily due to the tackle, and poor contact technique has been identified as a risk factor for injury. We aimed to determine whether the tackle technique proficiency scores were different in injurious tackles versus tackles that did not result in injury using real-match scenarios in high-level youth rugby union. METHODS: Injury surveillance was conducted at the under-18 Craven Week tournaments (2011-2013). Tackle-related injury information was used to identify injury events in the match video footage and non-injury events were identified for the injured player cohort. Injury and non-injury events were scored for technique proficiency and Cohen's effect sizes were calculated and the Student t test (p<0.05) was performed to compare injury versus non-injury scores. RESULTS: The overall mean score for front-on ball-carrier proficiency was 7.17±1.90 and 9.02±2.15 for injury and non-injury tackle events, respectively (effect size=moderate; p<0.05). The overall mean score for side/behind ball-carrier proficiency was 4.09±2.12 and 7.68±1.72 for injury and non-injury tackle events, respectively (effect size=large; p<0.01). The overall mean score for front-on tackler proficiency was 7.00±1.95 and 9.35±2.56 for injury and non-injury tackle events, respectively (effect size=moderate; p<0.05). The overall mean score for side/behind tackler proficiency was 5.47±1.60 and 8.14±1.75 for injury and non-injury tackle events, respectively (effect size=large; p<0.01). SUMMARY: Higher overall mean and criterion-specific tackle-related technique scores were associated with a non-injury outcome. The ability to perform well during tackle events may decrease the risk of injury and may manifest in superior performance.

Changes in body size and physical characteristics of South African under-20 rugby union players over a 13-year period.

This study compared changes in the body size and physical characteristics of South African under-20 rugby union players over a 13-year period. A total of 453 South African under-20 players (forwards: n = 256 and backs: n = 197) underwent measurements of body mass, stature, muscular strength, endurance, and 10- and 40-m sprint times. A 2-way analysis of variance was used to determine significant differences for the main effects of position (forwards vs. backs) and time (1998-2010). The pooled data showed that forwards were significantly heavier (22%), taller (5%), and stronger (18%) than the backs. However, when 1 repetition maximum strength scores were adjusted for body mass, backs were stronger per kg body mass. Stature did not change over the 13-year period for both groups. There were, however, significant increases in muscular strength (50%), body mass (20%), and muscular endurance (50%). Furthermore, an improvement in sprint times over 40 (4%) and 10 m (7%) was evident over the period of the study. In conclusion, the players became heavier, stronger, taller, and improved their upper-body muscular endurance over the 13 years of the study. Furthermore, sprint times over 10 and 40 m improved over the same time period despite the increase in body mass. It can be speculated that the changes in physical characteristics of the players over time are possibly a consequence of (a) adaptations to the changing demands of the game and (b) advancements in training methods.

Faster Heart Rate Recovery With Increased RPE: Paradoxical Responses After an 87-km Ultramarathon.

The aim of this study was to determine the relationship between heart rate recovery (HRR) and an acute training "overload" by comparing HRR responses before and after an ultramarathon road race. Ten runners completed a standardized laboratory protocol ∼7 days before and between 2 and 4 days after participating in the 87-km Comrades Marathon. The protocol included muscle pain ratings, a 5-bound test, and 20 minutes of treadmill exercise at 70% of maximal oxygen uptake followed by 15 minutes of recovery. Respiratory gases and heart rate measurements were used to calculate steady-state exercise responses, HRR, and excess postexercise oxygen consumption (EPOC), and participants also provided a rating of perceived exertion (RPE) during exercise. The RPE was significantly increased (13 ± 2 vs. 11 ± 1) (p < 0.01), and HRR was significantly faster (35 ± 5 beats vs. 29 ± 4 beats) (p < 0.01) following the postrace vs. prerace submaximal exercise bout, with no significant changes in respiratory or heart rate parameters during exercise or in EPOC. Although previous studies have shown that faster HRR reflected an "adapted" state with enhanced training status, the current findings suggest that this may not always be the case. It follows that changes in HRR should be considered in the context of other factors, such as recent training load and RPE during submaximal exercise.

Effect of exercise intensity on post-exercise oxygen consumption and heart rate recovery.

PURPOSE: There is some evidence that measures of acute post-exercise recovery are sensitive to the homeostatic stress of the preceding exercise and these measurements warrant further investigation as possible markers of training load. The current study investigated which of four different measures of metabolic and autonomic recovery was most sensitive to changes in exercise intensity. METHODS: Thirty-eight moderately trained runners completed 20-min bouts of treadmill exercise at 60, 70 and 80% of maximal oxygen uptake (VO2max) and four different recovery measurements were determined: the magnitude of excess post-exercise oxygen consumption (EPOCMAG), the time constant of the oxygen consumption recovery curve (EPOCτ), heart rate recovery within 1 min (HRR60s) and the time constant of the heart rate recovery curve (HRRτ) . RESULTS: Despite significant differences in exercise parameters at each exercise intensity, only EPOCMAG showed significantly slower recovery with each increase in exercise intensity at the group level and in the majority of individuals. EPOCτ was significantly slower at 70 and 80% of VO2max vs. 60% VO2max and HRRτ was only significantly slower when comparing the 80 vs. 60% VO2max exercise bouts. In contrast, HRR60s reflected faster recovery at 70 and 80% of VO2max than at 60% VO2max. CONCLUSION: Of the four recovery measurements investigated, EPOCMAG was the most sensitive to changes in exercise intensity and shows potential to reflect changes in the homeostatic stress of exercise at the group and individual level. Determining EPOCMAG may help to interpret the homeostatic stress of laboratory-based research trials or training sessions.

Physical fitness metrics and their relationship to locomotor activity profiles among female international field hockey players across an Olympic cycle.

OBJECTIVES: The study explored the correlations between physical fitness metrics and match locomotor activity profiles. Furthermore exploring the transformations of both fitness tests as well as match locomotor activities over an Olympic cycle. DESIGN: Observational descriptive study. METHODS: Fitness testing (n = 24) and match locomotor activity (n = 102) profiles were collected. A Pearson's product-moment correlation and 95 % confidence intervals were calculated to determine relationships between metrics for each year. A mixed-effects model was used for repeated measures to identify differences in the physical fitness tests and match locomotor activity profiles between years. RESULTS: The YoYo intermittent reocvery testest level 1 changed significantly (p < 0.0001) and accounted for 29 % of the variance in average speed (p < 0.001, rrm (59) = 0.54) Upper and lower body muscular strength, also improved, evidenced by the 3RM bench press (p < 0.0001), and a 28 % (2017-2019) increase in 3RM squat (p < 0.0001). Also pull-ups increased from 4.2 ± 2.8 pull-ups (2017) to 10.0 ± 3.1 pull-ups (2020) (p < 0.0001) and. countermovement jump height increased over the study duration (p < 0.0001). Match total distances remained unchanged, while average speed increased significantly (p < 0.0001). High-speed running distance (p < 0.0003) and sprint counts (p < 0.0001), showed significant improvements over the study period. CONCLUSIONS: The study underscores noteworthy improvements in physical attributes and performance metrics over an Olympic cycle. Contributing valuable insights for enhancing athletic performance in hockey players competing in the Olympics.

The effect of a single session of short duration biofeedback-induced deep breathing on measures of heart rate variability during laboratory-induced cognitive stress: a pilot study.

This study examines the acute effect of heart rate variability (HRV) biofeedback on HRV measures during and immediately after biofeedback and during the following laboratory-induced stress. Eighteen healthy males exposed to work-related stress were randomised into an HRV biofeedback group (BIO) or a comparative group (COM). Subjects completed a modified Stroop task before (Stroop 1) and after (Stroop 2) the intervention. Both groups had similar physiological responses to stress in Stroop 1. In Stroop 2, the COM group responded similarly to the way they did to Stroop 1: respiratory frequency (RF) and heart rate (HR) increased, RMSSD and high frequency (HF) power decreased or had a tendency to decrease, while low frequency (LF) power showed no change. The BIO group responded differently in Stroop 2: while RF increased and LF power decreased, HR, RMSSD and HF power showed no change. In the BIO group, RMSSD was higher in Stroop 2 compared to Stroop 1. In conclusion, HRV biofeedback induced a short term carry-over effect during both the following rest period and laboratory-induced stress suggesting maintained HF vagal modulation in the BIO group after the intervention, and maintained LF vagal modulation in the COM group.

Allometric scaling of peak power output accurately predicts time trial performance and maximal oxygen consumption in trained cyclists.

OBJECTIVE: The purpose of this study was to determine if peak power output (PPO) adjusted for body mass(0.32) is able to accurately predict 40-km time trial (40-km TT) performance. METHODS: 45 trained male cyclists completed after familiarisation, a PPO test including respiratory gas analysis, and a 40-km TT. PPO, maximal oxygen consumption (VO(2max)) and 40-km TT time were measured. Relationships between 40-km TT performance and (I) absolute PPO (W) and VO(2max) (l/min), (II) relative PPO (W/kg) and VO(2max) (ml/min/kg) and (III) PPO and VO(2max) adjusted for body mass (W/kg(0.32) and ml/min/kg(0.32), respectively) were studied. RESULTS: The continuous ramp protocol resulted in a similar relationship between PPO and VO(2max) (r=0.96, p<0.0001) compared with a stepwise testing protocol but was associated with a lower standard error of the estimated when predicting VO(2max). PPO adjusted for body mass (W/kg(0.32)) had the strongest relationship with 40-km TT performance (s) (r=-0.96, p<0.0001). Although significant relationships were also found between absolute (W) and/or relative PPO (W/kg) and 40-km TT performance (s), these relationships were significantly weaker than the relationship between 40-km TT performance and PPO adjusted for body mass (W/kg(0.32)) (p<0.0001). CONCLUSIONS: VO(2max) can be accurately predicted from PPO when using a continuous ramp protocol, possibly even more accurately than when using a stepwise testing protocol. 40-km TT performance (s) in trained cyclists can be predicted most accurately by PPO adjusted for body mass (W/kg(0.32)). As both VO(2max) and 40-km TT performance can be accurately predicted from a PPO test, this suggests that (well)-trained cyclists can possibly be monitored more frequently and with fewer tests.

Physical fitness of South African primary school children, 6 to 13 years of age: discovery vitality health of the nation study.

Basic physical fitness was measured using 8 different measures for 10,295 South African children and youths (5,611 boys, 4,684 girls) ages 6 to 13 years. These measurements included height, weight, Body Mass Index, standing long jump, shuttle run, sit-and-reach, sit-up (EUROFIT testing battery), and cricket ball throw scores. Due to the effects of earlier apartheid laws on separating communities, it was hypothesized that scores for different ethnic groups may differ. Therefore, in addition to the calculation of basic norms and sex differences, ethnic differences were also tested. Height and weight, relative to age, were different between the various ethnic groups (Black, White, and Mixed ancestry) for boys, with Black boys being shorter and lighter than White boys. There were no differences in sit-and-reach flexibility scores between the groups. With the exception of the cricket ball throw for girls, White children had higher scores in most tests. Although not significantly different from the White children, in the majority of cases, the children of mixed ancestral origin had scores that ranged between the other two ethnic groups. These results suggest a need for encouraging fitness in school children, and the reintroduction of formal physical education into the South African school curriculum, especially into schools in which Black children predominate.

The sensitivity of the Fatigue and Fitness Test for Teams (FFITT) to measure the demands of a rugby match.

Regular monitoring of players in a team can be a challenge because it is time consuming, expensive and impractical. The Fatigue and Fitness Test for Teams (FFITT) was developed to satisfy the demands of a practical monitoring protocol for frequent use in team sports. This study aimed to quantify the sensitivity of the FFITT and assess the practicality of implementing the FFITT in a rugby team. The FFITT was completed before and after three university 1st XV rugby union matches. The FFITT was sensitive to the demands of a rugby match in some individuals. Grouped results (n = 22 players) revealed a significant reduction in HRR60s of 7 beats post-match 3 (P = 0.002; ES = 0.52), which is greater than the 5 beats which constitute a meaningful change in fatigue and fitness. A significant reduction in SLJ of 11 cm was also observed post-match 3 (P = 0.04; ES = 0.69), which is less than the meaningful change (13 cm). On an individual level, meaningful changes occurred in SLJ distance in nine players, in HRR60s in 14 players and in both HRR60s and SLJ in three players. Descriptive analysis of the RTT-Q revealed that players experienced increased muscle soreness and reduced readiness-to-train post-match 1 and post-match 2. The FFITT could be successfully completed by the squad in 8 min during their warm-up. The FFITT satisfies both scientific principles and the coach's demands of a practical monitoring protocol for frequent use in the team sports setting.

Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist.

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.

The Fatigue and Fitness Test for Teams (FFITT): A practical option for monitoring athletes in a team as individuals.

We developed the Fatigue and Fitness Test for Teams (FFITT) to address the challenges of monitoring players in a team simultaneously. The test, which takes 8 min for the entire team, incorporates subjective measures of well-being (RTT-Q), and objective measures of the autonomic system (HRR60s) and neuromuscular function (SLJ). The aim of this study was to present the rationale for the FFITT as a novel athlete monitoring protocol and to measure the reliability of each component of the test. The internal consistency of the RTT-Q questions ranged from α = 0.69-0.92. All questions had an α > 0.83, with one exception of question 'Rate the well-being/stress your school/university/work is causing you to feel' which had an α = 0.69. The reliability of the HRR60s and SLJ was high (R = 0.92, and 0.91 respectively). The absolute typical error of measurement (TEM) of the SLJ was 8 cm and HRR60s was 3 beats. When expressed relatively the CVTEM of HRR60s was 8.4% and SLJ was 3.0%. Based on the TEM the HRR60s and SLJ could detect medium and large changes in fatigue and fitness. In absolute terms this equates to more than 5 bpm (HRR60s) and more than 13 cm (SLJ). The FFITT has the potential to satisfy both scientific principles and the coach's demands of a practical monitoring protocol for frequent use in a team.

Changes in heart rate recovery after high-intensity training in well-trained cyclists.

Heart rate recovery (HRR) after submaximal exercise improves after training. However, it is unknown if this also occurs in already well-trained cyclists. Therefore, 14 well-trained cyclists (VO(2max) 60.3 +/- 7.2 ml kg(-1) min(-1); relative peak power output 5.2 +/- 0.6 W kg(-1)) participated in a high-intensity training programme (eight sessions in 4 weeks). Before and after high-intensity training, performance was assessed with a peak power output test including respiratory gas analysis (VO(2max)) and a 40-km time trial. HRR was measured after every high-intensity training session and 40-km time trial. After the training period peak power output, expressed as W kg(-1), improved by 4.7% (P = 0.000010) and 40-km time trial improved by 2.2% (P = 0.000007), whereas there was no change in VO(2max) (P = 0.066571). Both HRR after the high intensity training sessions (7 +/- 6 beats; P = 0.001302) and HRR after the 40-km time trials (6 +/- 3 beats; P = 0.023101) improved significantly after the training period. Good relationships were found between improvements in HRR(40-km) and improvements in peak power output (r = 0.73; P < 0.0001) and 40-km time trial time (r = 0.96; P < 0.0001). In conclusion, HRR is a sensitive marker which tracks changes in training status in already well-trained cyclists and has the potential to have an important role in monitoring and prescribing training.

Day-to-day variation in heart rate at different levels of submaximal exertion: implications for monitoring training.

The HIMS test, which consists of controlled exercise at increasing workloads, has been developed to monitor changes in training status and accumulative fatigue in athletes. As the workload can influence the day-to-day variation in heart rate, the exercise intensity, which is associated with the highest sensitivity, needs to be established with the goal of refining the interpretability of these heart rate measurements. The aim of the study was to determine the within-subject day-to-day variation of submaximal and recovery heart rate in subjects who reached different exercise intensities. Thirty-eight subjects participated in this study and after familiarization were allocated to 1 of 4 groups based on the percentage of predicted heart rate maximum that was elicited during the first test (i.e., groups: <85, 85-90, 90-95, and >95% maximum heart rate). Variation in heart rate was determined for the following 4 days at a range of intensities (61-98% of maximum heart rate) and recovery periods. Variation in heart rate decreased with increasing exercise intensity in all groups. The lowest variation in heart rate was found at the end of the last stage of the test in the 85-90% group (3 +/- 1 bxmin) and >95% group (3 +/- 2 bxmin). The lowest variation during the recovery periods occurred at the first minute after the last stage. Although there were no significant differences between the groups, the 85-90% group showed a tendency to have the lowest variation in heart rate. If changes in heart rate and heart rate recovery are to be monitored in athletes, a submaximal protocol should elicit heart rate between 85 and 90% of maximum heart rate, because this intensity is associated with the least day-to-day variation.

Effects of high-intensity training by heart rate or power in well-trained cyclists.

The aim of this study was to determine whether the performance of cyclists after 4 weeks of high-intensity training improved similarly using either heart rate or power to prescribe training. Twenty-one well-trained men cyclists (age, 32 +/- 6 years; peak power output, 371 +/- 46 W) were randomly assigned to a power-based (GPOWER) or heart rate-based (GHEART) high-intensity training (HIT) group or a control group (GCONTROL). Training consisted of 8 repetitions of 4 minutes at either 80% of peak power output (GPOWER) or at the heart rate coinciding with 80% of peak power output (GHEART), with rest periods of 90 seconds. A 40-km time trial and VO2max test were performed before and after 8 training sessions. There were significant improvements (p < 0.05) in peak power output (GPOWER = 3.5%; GHEART = 5.0%) and 40-km time trial performance (GPOWER = 2.3%; GHEART = 2.1%) for both of the high-intensity groups. Although there were no significant differences between groups for these variables, when the data were analyzed using magnitude-based effects, the GHEART group showed greater probability of a "beneficial" effect for peak power output. The current general perception that prescribing training based only on power is more effective than prescribing training based on heart rate was not supported by the data from this study. Coaches who are unable to monitor progress frequently should prescribe training based on heart rate, when intervals are performed under stable conditions, because this may provide an additional advantage over prescribing training using power.

Autonomic control of heart rate during and after exercise : measurements and implications for monitoring training status.

Endurance training decreases resting and submaximal heart rate, while maximum heart rate may decrease slightly or remain unchanged after training. The effect of endurance training on various indices of heart rate variability remains inconclusive. This may be due to the use of inconsistent analysis methodologies and different training programmes that make it difficult to compare the results of various studies and thus reach a consensus on the specific training effects on heart rate variability. Heart rate recovery after exercise involves a coordinated interaction of parasympathetic re-activation and sympathetic withdrawal. It has been shown that a delayed heart rate recovery is a strong predictor of mortality. Conversely, endurance-trained athletes have an accelerated heart rate recovery after exercise. Since the autonomic nervous system is interlinked with many other physiological systems, the responsiveness of the autonomic nervous system in maintaining homeostasis may provide useful information about the functional adaptations of the body. This review investigates the potential of using heart rate recovery as a measure of training-induced disturbances in autonomic control, which may provide useful information for training prescription.

Monitoring Rugby Players for Fitness and Fatigue: What Do Coaches Want?

PURPOSE: The advantages of monitoring players in a team are well documented. However, barriers associated with lack of resources and time prevent teams from implementing systematic monitoring programs. This study aimed to identify (1) the methods rugby teams use to monitor the training load and associated response to the training load and (2) prerequisites of a monitoring protocol that are scientifically suitable and practically applicable for monitoring fitness and fatigue of rugby players. METHODS: Coaches and support staff working with varying levels of rugby union were invited to complete an online questionnaire. RESULTS: Of the 55 respondents, 96% indicated that although they regarded monitoring the training load and training-load response as important, there is no monitoring protocol that is cost-effective, time efficient, and nonaversive to the players. Respondents measured several variables when monitoring and incorporated more subjective than objective measures. Respondents (41%) indicated that they would like a protocol that is time efficient (5-10 min) and provides immediate feedback on players who identify as fatigued (50%). For coaches to have confidence in the information provided by the protocol, it needs to meet basic clinimetric principles of reliability and validity. The technical and biological error in the measurement needs to be known so that meaningful changes in fatigue and fitness can be distinguished from natural variations in the measurements. CONCLUSIONS: Prerequisites of an ideal monitoring protocol for rugby players were identified. It follows that a monitoring protocol that fulfills these prerequisites should satisfy both scientific principles and the coach's demands.

Contemporary perspectives of core stability training for dynamic athletic performance: a survey of athletes, coaches, sports science and sports medicine practitioners.

BACKGROUND: Core stability training has grown in popularity over 25 years, initially for back pain prevention or therapy. Subsequently, it developed as a mode of exercise training for health, fitness and sport. The scientific basis for traditional core stability exercise has recently been questioned and challenged, especially in relation to dynamic athletic performance. Reviews have called for clarity on what constitutes anatomy and function of the core, especially in healthy and uninjured people. Clinical research suggests that traditional core stability training is inappropriate for development of fitness for heath and sports performance. However, commonly used methods of measuring core stability in research do not reflect functional nature of core stability in uninjured, healthy and athletic populations. Recent reviews have proposed a more dynamic, whole body approach to training core stabilization, and research has begun to measure and report efficacy of these modes training. The purpose of this study was to assess extent to which these developments have informed people currently working and participating in sport. METHODS: An online survey questionnaire was developed around common themes on core stability training as defined in the current scientific literature and circulated to a sample population of people working and participating in sport. Survey results were assessed against key elements of the current scientific debate. RESULTS: Perceptions on anatomy and function of the core were gathered from a representative cohort of athletes, coaches, sports science and sports medicine practitioners (n = 241), along with their views on effectiveness of various current and traditional exercise training modes. Most popular method of testing and measuring core function was subjective assessment through observation (43%), while a quarter (22%) believed there was no effective method of measurement. Perceptions of people in sport reflect the scientific debate, and practitioners have adopted a more functional approach to core stability training. There was strong support for loaded, compound exercises performed upright, compared to moderate support for traditional core stability exercises. Half of the participants (50%) in the survey, however, still support a traditional isolation core stability training. CONCLUSION: Perceptions in applied practice on core stability training for dynamic athletic performance are aligned to a large extent to the scientific literature.