Article

Can plyometric training change the pacing behavior during 10-km running?

Wiley
European Journal of Sport Science
Authors:
  • University of São Paulo - School of Medicine
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Abstract

The effects of plyometric training on middle- and long-distance running performances are well established. However, its influence on pacing behavior is still unclear. The aim of this study was to evaluate the effects of plyometric training on pacing behavior. Also, verify whether the adaptations induced by plyometric training would change ratings of perceived exertion (RPE) and/or affective feelings during the race. Twenty-eight male runners were assigned to two groups: control (C) and plyometric training (PT). PT held two weekly plyometric training sessions for eight weeks. Drop jump (DJ) performance, 10-km running performance, pacing behavior, RPE and affective feelings, VO2peak, ventilatory thresholds (VT1 and VT2), peak treadmill speed (PTS), and RE were measured. For group comparisons, a mixed model analysis for repeated measures, effect size (ES) and 90% confidence interval (CI90%) were calculated for all dependent variables. Significant differences pre to post was observed for PT group in DP (7.2%; p ≤ 0.01; ES = 0.56 (0.28 to 0.85)) and RE (4.5%; p ≤ 0.05; ES = -0.52 ((-0.73 to -0.31)) without changes in pacing behavior. While PT was effective for improving DJ and RE, there is no evidence that pacing behavior, RPE or affective feelings are directly affected by these adaptations during a 10-km time-trial run.

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... For example, ST has shown improvements in fixed blood lactate after PL [20] and blood lactate concentration at 16 km/h after a combined HL and PL intervention [21]. However, some studies have not shown any improvement in MMSS [22][23][24]. ...
... Among the studies that measured vVO 2 max, six studies applied HL [22,87,94,[105][106][107], two studies applied SubL [85,97] (not included in the meta-analysis), five studies applied PL [23,83,85,91,108], and six studies (involving seven groups) applied Combined [84,86,93,97,102,107]. Compared with the control group, no significant effects on vVO 2 max were found with HL training ( ...
... CI confidence interval, Combined high load training, plyometric training and/or submaximal load training, nES number of effect sizes resulting in lower work and energy cost than longer duration stages [128]. From a total of 15 studies included in the metaanalysis for vVO 2 max, seven studies [22,23,84,91,97,105,106] used protocols with 1.00-km/h increments every minute, or in shorter stages (i.e., 30 s), and four of these studies showed significant effects after PL [91], HL [106], SubL [97], and Combined methods [84,97]. From the seven studies that applied longer duration stages (i.e., 3 min or more), three found an effect on vVO 2 max after PL [83,108] and HL [87], whereas others found no effect after Combined [86,93,102,107] and HL [107]. ...
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Background The running performance of middle-distance and long-distance runners is determined by factors such as maximal oxygen uptake (VO2max), velocity at VO2max (vVO2max), maximum metabolic steady state (MMSS), running economy, and sprint capacity. Strength training is a proven strategy for improving running performance in endurance runners. However, the effects of different strength training methods on the determinants of running performance are unclear. Objective The aim of this systematic review with meta-analysis was to compare the effect of different strength training methods (e.g., high load, submaximal load, plyometric, combined) on performance (i.e., time trial and time until exhaustion) and its determinants (i.e., VO2max, vVO2max, MMSS, sprint capacity) in middle-distance and long-distance runners. Methods A systematic search was conducted across electronic databases (Web of Science, PubMed, SPORTDiscus, SCOPUS). The search included articles indexed up to November 2022, using various keywords combined with Boolean operators. The eligibility criteria were: (1) middle- and long-distance runners, without restriction on sex or training/competitive level; (2) application of a strength training method for ≥ 3 weeks, including high load training (≥ 80% of one repetition maximum), submaximal load training (40–79% of one repetition maximum), plyometric training, and combined training (i.e., two or more methods); (3) endurance running training control group under no strength training or under strength training with low loads (< 40% of one repetition maximum); (4) running performance, VO2max, vVO2max, MMSS and/or sprint capacity measured before and after a strength training intervention program; (5) randomized and non-randomized controlled studies. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. A random-effects meta-analysis and moderator analysis were performed using Comprehensive meta-analysis (version 3.3.0.70). Results The certainty of the evidence was very low to moderate. The studies included 324 moderately trained, 272 well trained, and 298 highly trained athletes. The strength training programs were between 6 and 40 weeks duration, with one to four intervention sessions per week. High load and combined training methods induced moderate (effect size = − 0.469, p = 0.029) and large effect (effect size = − 1.035, p = 0.036) on running performance, respectively. While plyometric training was not found to have a significant effect (effect size = − 0.210, p = 0.064). None of the training methods improved VO2max, vVO2max, MMSS, or sprint capacity (all p > 0.072). Moderators related to subject (i.e., sex, age, body mass, height, VO2max, performance level, and strength training experience) and intervention (i.e., weeks, sessions per week and total sessions) characteristics had no effect on running performance variables or its determinants (all p > 0.166). Conclusions Strength training with high loads can improve performance (i.e., time trial, time to exhaustion) in middle-distance and long-distance runners. A greater improvement may be obtained when two or more strength training methods (i.e., high load training, submaximal load training and/or plyometric training) are combined, although with trivial effects on VO2max, vVO2max, MMSS, or sprint capacity.
... (Sanchez-Sixto et al., 2021) To compare: PJT vs combined PJT on the kinetics and kinematics of the vertical jump. ...
... (do Carmo et al., 2021) To evaluate: PJT vs stimulation To verify: PJT vs perceived exertion, running pace and affective feeling. ...
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This systematic review provides critical and propositional information on criteria for determining the volume and intensity of drop jumps during plyometric training programs. Eligibility criteria were defined according to PICOS: Participants: male or female athletes, trained or recreationally active (16–40 years). Intervention duration: more than 4 weeks. Comparators: passive or active control group during a plyometric training program. Outcomes: information on improvement with Drop Jump or Depth Jump, with other jumps, acceleration, sprint, strength, and power output. Design: randomized controlled trials. We searched articles published in PubMed, SPORTDiscus, Web of Science, and Scopus. The search was conducted until 10 September 2022 for English-language articles only. The risk of bias was assessed using Grading of Recommendations, Assessment, Development and Evaluation (GRADE) for randomized controlled studies. We identified 31495 studies, of which only 22 were included. We found that six groups presented results with women, 15 presented results with men, and the remaining four presented mixed studies. Of the 686 people recruited, 329 participants aged 25.79 ± 4.76 years were involved in training. Methodological problems in training intensity, volume distribution, and individualization were noted, but methodological recommendations for their solution are also provided. It is concluded that the drop height should not be understood as the intensity determinant of plyometric training. Intensity is determined by ground reaction forces, power output, and jump height, among other factors. Furthermore, the athletes’ experience level selection should be based on the formulas recommended within this research. These results could be helpful for those who intend to conduct new plyometric training programs and research.
... Plyometric training (PT) is a well-known form of ''ballistic training,'' which refers to a wide range of jumping, bounding, and hopping exercises involving high-intensity stretching of a muscle (eccentric contraction) immediately followed by a rapid and powerful concentric contraction of the same muscle and connective tissue. 5 As PT can produce more force than can be provided by a concentric-only muscle action alone, researchers have shown that PT is an effective method for improving jumping abilities, 6,7 balance, 8 explosive performance, 8,9 strength, 8,10 speed, 11 running economy, 12 agility, 13,14 endurance performance, 8,9 and CoD ability. 15,16 Among the various types of PT, drop jump (DJ) represents one of the most frequently applied jump training aimed at improving lower limb explosive performance, speed, and jump heights. ...
... Plyometric training (PT) is a well-known form of ''ballistic training,'' which refers to a wide range of jumping, bounding, and hopping exercises involving high-intensity stretching of a muscle (eccentric contraction) immediately followed by a rapid and powerful concentric contraction of the same muscle and connective tissue. 5 As PT can produce more force than can be provided by a concentric-only muscle action alone, researchers have shown that PT is an effective method for improving jumping abilities, 6,7 balance, 8 explosive performance, 8,9 strength, 8,10 speed, 11 running economy, 12 agility, 13,14 endurance performance, 8,9 and CoD ability. 15,16 Among the various types of PT, drop jump (DJ) represents one of the most frequently applied jump training aimed at improving lower limb explosive performance, speed, and jump heights. ...
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The purpose of the present study was to examine the effects of 6 weeks of 40-, 60-, or 80-cm drop jump (DJ) training on lower limb explosive and change of direction (CoD) performance in collegiate Sanda athletes. Repeated-measure ANOVA revealed that there was a significant group × time interaction for standing long jump test (p = 0.006), counter movement jump test (p = 0.026), Illinois agility test (p = 0.003), square test (p = 0.018), Nebraska test (p = 0.027), t test (p = 0.032), and hexagon test (p = 0.012) due to the best performance observed at post-test compared with pre-test for DJ60 (effect size = 0.89–2.89), and the improvement was higher than that of the other groups. These findings suggest that 6 weeks of DJ training could improve the lower limb explosive and CoD performance in collegiate Sanda athletes and that 60 cm may be the optimal drop height.
... We considered them as a single study per one research group, and consequently, a total of 21 studies were finally adopted, in which running economy [63-68, 70-75, 78-83] and running time trial performance [65, 67, 69, 76-78, 80-82, 84] were assessed in 18 and 10 studies, respectively. The selected 22 articles were divided into the following training categories: 13 included heavy resistance training [63][64][65][66][67][68][69][70][71][72][73][74][75] and 9 included plyometric training [76][77][78][79][80][81][82][83][84]. ...
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Background As an adjunct to running training, heavy resistance and plyometric training have recently drawn attention as potential training modalities that improve running economy and running time trial performance. However, the comparative effectiveness is unknown. The present systematic review and meta-analysis aimed to determine if there are different effects of heavy resistance training versus plyometric training as an adjunct to running training on running economy and running time trial performance in long-distance runners. Methods Electronic databases of PubMed, Web of Science, and SPORTDiscus were searched. Twenty-two studies completely satisfied the selection criteria. Data on running economy and running time trial performance were extracted for the meta-analysis. Subgroup analyses were performed with selected potential moderators. Results The pooled effect size for running economy in heavy resistance training was greater ( g = − 0.32 [95% confidence intervals [CIs] − 0.55 to − 0.10]: effect size = small) than that in plyometric training ( g = -0.13 [95% CIs − 0.47 to 0.21]: trivial). The effect on running time trial performance was also larger in heavy resistance training ( g = − 0.24 [95% CIs − 1.04 to − 0.55]: small) than that in plyometric training ( g = − 0.17 [95% CIs − 0.27 to − 0.06]: trivial). Heavy resistance training with nearly maximal loads (≥ 90% of 1 repetition maximum [1RM], g = − 0.31 [95% CIs − 0.61 to − 0.02]: small) provided greater effects than those with lower loads (< 90% 1RM, g = − 0.17 [95% CIs − 1.05 to 0.70]: trivial). Greater effects were evident when training was performed for a longer period in both heavy resistance (10–14 weeks, g = − 0.45 [95% CIs − 0.83 to − 0.08]: small vs. 6–8 weeks, g = − 0.21 [95% CIs − 0.56 to 0.15]: small) and plyometric training (8–10 weeks, g = 0.26 [95% CIs − 0.67 to 0.15]: small vs. 4–6 weeks, g = − 0.06 [95% CIs 0.67 to 0.55]: trivial). Conclusions Heavy resistance training, especially with nearly maximal loads, may be superior to plyometric training in improving running economy and running time trial performance. In addition, running economy appears to be improved better when training is performed for a longer period in both heavy resistance and plyometric training.
... One such strategy is plyometric training (PT), of which the goal is to improve lower limb strength, knee function (e.g., isokinetic muscle strength test and single-legged hop tests), and movement pattern of landing (e.g., depth jump and continuous jump) (Hewett et al., 2010) by shortening muscle eccentric-concentric contraction cycle [also termed as a stretch-shortening cycle (SSC)] (Markovic and Mikulic, 2010;Ramírez-delaCruz et al., 2022). Studies have shown that PT can enhance the sport performance of athletes, such as strength (Asadi, 2012), running economy (do Carmo et al., 2022), agility (Maciejczyk et al., 2021), and sprint ability (Markovic and Mikulic, 2010), as well as reducing ACL injury risk. Alikhani et al. (2019) observed that, for example, 6week PT significantly improved dynamic balance and knee proprioception in female badminton players by enhancing their functional adaptations and neural recruitment of motor units that activate appropriate muscles before landing and the proprioceptive inputs. ...
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Objectives To investigate the effect of combined balance and plyometric training on knee function and proprioception of elite badminton athletes. Methods Sixteen elite male badminton players (age: 20.5 ± 1.1 years, height: 177.8 ± 5.1 cm, weight: 68.1 ± 7.2 kg, and training experience: 11.4 ± 1.4 years) volunteered to participate and were randomly assigned to a combined balance and plyometric training (CT) (n = 8) and plyometric (PT) group (n = 8). The CT group performed balance combined with plyometric training three times a week over 6 weeks (40 min of plyometrics and 20 min of balance training); while the PT group undertook only plyometric training for the same period (3–4 sets × 8–12 reps for each exercise). Both groups had the same technical training of badminton. Results The knee function and proprioception were assessed at baseline and after the intervention by measuring the performance of single-legged hop tests (LSIO, LSIT, LSIC, LSIS), standing postural sway (COPAP, COPML), and LSI of dominant leg and non-dominant leg. The results showed that as compared to PT, CT induced significantly greater improvements in LSIT and LSIS (p < 0.001) and significant greater percent increase in NAP (p = 0.011). The changes in LSIO, LSIC, DAP, NAP, LSIAP, DML, NML, and LSIML induced by CT did not differ from that induced by PT (p > 0.213). Conclusion In elite badminton players, intervention using CT holds great promise to augment the benefits for knee function compared to the intervention using PT only, and at the same time, with at least comparable benefits for proprioception. Future studies are needed to examine and confirm the results of this study.
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Background Running economy is defined as the energy demand at submaximal running speed, a key determinant of overall running performance. Strength training can improve running economy, although the magnitude of its effect may depend on factors such as the strength training method and the speed at which running economy is assessed. Aim To compare the effect of different strength training methods (e.g., high loads, plyometric, combined methods) on the running economy in middle- and long-distance runners, over different running speeds, through a systematic review with meta-analysis. Methods A systematic search was conducted across several electronic databases including Web of Science, PubMed, SPORTDiscus, and SCOPUS. Using different keywords and Boolean operators for the search, all articles indexed up to November 2022 were considered for inclusion. In addition, the PICOS criteria were applied: Population: middle- and long-distance runners, without restriction on sex or training/competitive level; Intervention: application of a strength training method for ≥ 3 weeks (i.e., high loads (≥ 80% of one repetition maximum); submaximal loads [40–79% of one repetition maximum); plyometric; isometric; combined methods (i.e., two or more methods); Comparator: control group that performed endurance running training but did not receive strength training or received it with low loads (< 40% of one repetition maximum); Outcome: running economy, measured before and after a strength training intervention programme; Study design: randomized and non-randomized controlled studies. Certainty of evidence was assessed with the GRADE approach. A three-level random-effects meta-analysis and moderator analysis were performed using R software (version 4.2.1). Results The certainty of the evidence was found to be moderate for high load training, submaximal load training, plyometric training and isometric training methods and low for combined methods. The studies included 195 moderately trained, 272 well trained, and 185 highly trained athletes. The strength training programmes were between 6 and 24 weeks’ duration, with one to four sessions executed per week. The high load and combined methods induced small (ES = − 0.266, p = 0.039) and moderate (ES = − 0.426, p = 0.018) improvements in running economy at speeds from 8.64 to 17.85 km/h and 10.00 to 14.45 km/h, respectively. Plyometric training improved running economy at speeds ≤ 12.00 km/h (small effect, ES = − 0.307, p = 0.028, β1 = 0.470, p = 0.017). Compared to control groups, no improvement in running economy (assessed speed: 10.00 to 15.28 and 9.75 to 16.00 km/h, respectively) was noted after either submaximal or isometric strength training (all, p > 0.131). The moderator analyses showed that running speed (β1 = − 0.117, p = 0.027) and VO2max (β1 = − 0.040, p = 0.020) modulated the effect of high load strength training on running economy (i.e., greater improvements at higher speeds and higher VO2max). Conclusions Compared to a control condition, strength training with high loads, plyometric training, and a combination of strength training methods may improve running economy in middle- and long-distance runners. Other methods such as submaximal load training and isometric strength training seem less effective to improve running economy in this population. Of note, the data derived from this systematic review suggest that although both high load training and plyometric training may improve running economy, plyometric training might be effective at lower speeds (i.e., ≤ 12.00 km/h) and high load strength training might be particularly effective in improving running economy (i) in athletes with a high VO2max, and (ii) at high running speeds. Protocol Registration The original protocol was registered (https://osf.io/gyeku) at the Open Science Framework.
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Athlete–environment interactions are crucial factors in understanding the regulation of exercise intensity in head-to-head competitions. Previously, we have proposed a framework based on the interdependence of perception and action, which allows us to explore athletic behavior in the more complex pacing situations occurring when athletes need to respond to actions of their opponents. In the present perspective we will further explore whether opponents, crucial external factors in competitive sports, could indeed be perceived as social invitations for action. Decisions regarding how to expend energy over the race are based on internal factors such as the physiological/biomechanical capacity of the athlete in relation to external factors such as those presented by opponents. For example: Is the athlete able to overtake competitors, or not? We present several experimental studies that demonstrate that athletes regulate their exercise intensity differently in head-to-head competition compared to time-trial exercises: Relational athlete-environment aspects seem to outweigh benefits of the individual optimal energy distribution. Also, the behavior of the opponents has been shown to influence pacing strategies of competing athletes, again demonstrating the importance of relational athlete–environment aspects in addition to strictly internal factors. An ecological perspective is presented in which opponents are proposed to present social affordances, and decision-making is conceptualized as a resultant of affordance-competition. This approach will provide novel insights in tactical decision-making and pacing behavior in head-to-head competitions. Future research should not only focus on the athlete's internal state, but also try to understand opponents in the context of the social affordances they provide.
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The provision of performance-related feedback during exercise is acknowledged as an influential external cue used to inform pacing decisions. The provision of this feedback in a challenging or deceptive context allows research to explore how feedback can be used to improve performance and influence perceptual responses. However, the effects of deception on both acute and residual responses have yet to be explored, despite potential application for performance enhancement. Therefore, this study investigated the effects of challenging and deceptive feedback on perceptual responses and performance in self-paced cycling time trials (TT) and explored whether changes in performance are sustained in a subsequent TT following the disclosure of the deception. Seventeen trained male cyclists were assigned to either an accurate or deceptive feedback group and performed four 16.1 km cycling TTs; (1 and 2) ride-alone baseline TTs where a fastest baseline (FBL) performance was identified, (3) a TT against a virtual avatar representing 102% of their FBL performance (PACER), and (4) a subsequent ride-alone TT (SUB). The deception group, however, were initially informed that the avatar accurately represented their FBL, but prior to SUB were correctly informed of the nature of the avatar. Affect, self-efficacy and RPE were measured every quartile. Both groups performed PACER faster than FBL and SUB (p < 0.05) and experienced lower affect (p = 0.016), lower self-efficacy (p = 0.011), and higher RPE (p < 0.001) in PACER than FBL. No significant differences were found between FBL and SUB for any variable. The presence of the pacer rather than the manipulation of performance beliefs acutely facilitates TT performance and perceptual responses. Revealing that athletes' performance beliefs were falsely negative due to deceptive feedback provision has no effect on subsequent perceptions or performance. A single experiential exposure may not be sufficient to produce meaningful changes in the performance beliefs of trained individuals beyond the acute setting.
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The purpose of this study was to perform a systematic review and meta-analysis of controlled trials to determine the effect of strength-training programs on the running economy (RE) of high-level middle- and long-distance runners. Four electronic databases were searched in September 2015 (Pubmed, SPORTDiscus, MEDLINE and CINAHL) for original research articles. After analyzing 699 resultant original articles, studies were included if the following criteria were met: (a) participants were competitive middle- and/or long-distance runners; (b) participants had a VO2max > 60mL·kg-1-·min-1; (c) studies were controlled trials published in peer-reviewed journals; (d) studies analyzed the effects of strength-training programs with a duration greater than 4 weeks; (e) RE was measured before and after the strength-training intervention. Five studies met the inclusion criteria, resulting in a total sample size of 93 competitive, high-level middle- and long-distance runners. Four out of five of the included studies used low to moderate training intensities (40-70% one-repetition maximum), and all of them used low to moderate training volume (2-4 resistance lower-body exercises plus up to 200 jumps and 5-10 short sprints) 2-3 per week for 8-12 weeks. The meta-analyzed effect of strength training programs on RE in high-level middle- and long- distance runners showed a large, beneficial effect (standardized mean difference [95%Confidence Interval] = -1.42 [-2.23, -0.60]). In conclusion, a strength-training program including low to high intensity resistance exercises and plyometric exercises performed 2-3 times per week for 8-12 weeks is an appropriate strategy to improve RE in highly training middle- and long-distance runners.
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Running economy (RE) is considered an important physiological measure for endurance athletes, especially distance runners. This review considers 1) how RE is defined and measured and 2) physiological and biomechanical factors that determine or influence RE. It is difficult to accurately ascertain what is good, average, and poor RE between athletes and studies due to variation in protocols, gas-analysis systems, and data averaging techniques. However, representative RE values for different caliber of male and female runners can be identified from existing literature with mostly clear delineations in oxygen uptake across a range of speeds in moderately and highly trained and elite runners. Despite being simple to measure and acceptably reliable, it is evident that RE is a complex, multifactorial concept that reflects the integrated composite of a variety of metabolic, cardiorespiratory, biomechanical and neuromuscular characteristics that are unique to the individual. Metabolic efficiency refers to the utilization of available energy to facilitate optimal performance, whereas cardiopulmonary efficiency refers to a reduced work output for the processes related to oxygen transport and utilization. Biomechanical and neuromuscular characteristics refer to the interaction between the neural and musculoskeletal systems and their ability to convert power output into translocation and therefore performance. Of the numerous metabolic, cardiopulmonary, biomechanical and neuromuscular characteristics contributing to RE, many of these are able to adapt through training or other interventions resulting in improved RE.
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The purpose of this study was to analyze the impact of an 8-week strength training program on the neuromuscular characteristics and pacing adopted by runners during a self-paced endurance running. Eighteen endurance runners were allocated into either strength training group (STG, n = 9) or control group (CG, n = 9) and performed the following tests before and after the training period: (a) incremental test, (b) running speed-constant test, (c) 10-km running time trial, (d) drop jump test, (e) 30-s Wingate anaerobic test, (f) maximum dynamic strength test (1RM). During 1RM, the electromyographic activity was measured. In the STG, the magnitude of improvement for 1RM (23.0 ± 4.2 %, P = 0.001), drop jump (12.7 ± 4.6 %, P = 0.039), and peak treadmill speed (2.9 ± 0.8 %, P = 0.013) was significantly higher compared to CG. This increase in the 1RM for STG was accompanied by a tendency to a higher electromyographic activity (P = 0.080). The magnitude of improvement for 10-km running performance was higher (2.5 %) for STG than for CG (-0.7 %, P = 0.039). Performance was improved mainly due to higher speeds during the last seven laps (last 2800 m) of the 10-km running trial. There were no significant differences between before and after training period for maximal oxygen uptake, respiratory compensation point, running economy, and anaerobic performance for both groups (P > 0.05). These findings suggest that a strength training program offers a potent stimulus to counteract fatigue during the last parts of a 10-km running race, resulting in an improved overall running performance.
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The psychological construct of affect is proposed to significantly contribute to pacing decisions during exercise. Borg's Ratings of Perceived Exertion (RPE) scale, another important regulator of work-rate, is criticised as an inadequate measure of the multiple perceptual responses experienced. This study aimed to examine power output distribution and associated changes in affect, self-efficacy, perceptual cues, heart rate and respiratory gases during both 16.1 km and 40 km self-paced cycling time trials (TT). Secondly, the differentiation between physical perceptions of exertion and sense of effort in self-paced exercise was investigated. METHOD: Fifteen trained male cyclists completed 16.1 km and 40 km TT using a CompuTrainer cycle ergometer. Time, power output distribution, affect, self-efficacy, physical RPE (P-RPE), task effort and awareness (TEA), heart rate and respiratory gases were measured throughout each TT. Linear mixed models explored associations of these variables with power output distribution, and the relationship between P-RPE and TEA. RESULTS: Similar pacing strategies were adopted in the 16.1 km and 40 km TT (p = 0.31) and main effects were found for affect (p = 0.001) and respiratory exchange ratio (RER) (p < 0.001). Interactions between affect (p = 0.037), and RER (p = 0.004), with condition indicated closer associations with power output distribution in 16.1 km than 40 km TT. P-RPE was not significantly different from TEA (p = 0.053). CONCLUSION: A significant association between affect and power output distribution suggests that affective responses are task-dependent even in self-paced exercise, and a greater association is demonstrated in higher-intensity, 16.1 km TT. Furthermore, physical perceptions of exertion are not clearly differentiated from sense of effort in self-paced exercise.
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The pacing strategy has been shown as an important factor for athletes' performance. During middle and long distance races, the best pacing strategy will be able to maintain a "physiological reserve" and to allow the athlete to run in his/her best time. It should be mentioned that the pacing strategy can be altered by physiological and psychological factors. These factors are frequently adjusted throughout the race and they will be used to control runner's pace. Several physiological variables have been suggested to have an important role in pacing strategy control. However, there is still controversial findings among the studies. Thus, the aim of this review was provide a better understanding about some questions such as: 1) what is the best pacing strategy for a specific race?; 2) how pacing strategy is controlled by the runner?; and 3) how physiological variables can induce changes on pacing strategy? Uniterms: Performance; Perceived exertion; Running economy.
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Running performance depends on maximal oxygen uptake (V̇O2max), the ability to sustain a high percentage of V̇O2max for an extended period of time and running economy. Running economy has been studied relatively less than the other factors. Running economy, measured as steady state oxygen uptake V̇O2) at intensities below the ventilatory threshold is the standard method. Extrapolation to a common running speed (268 m/min) or as the V̇O2 required to run a kilometer is the standard method of assessment. Individuals of East African origin may be systematically more economical, although a smaller body size and a thinner lower leg may be the primary factors. Strategies for improving running economy remain to be developed, although it appears that high intensity running may be a common element acting to improve economy.
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This article examines how pacing strategies during exercise are controlled by information processing between the brain and peripheral physiological systems. It is suggested that, although several different pacing strategies can be used by athletes for events of different distance or duration, the underlying principle of how these different overall pacing strategies are controlled is similar. Perhaps the most important factor allowing the establishment of a pacing strategy is knowledge of the endpoint of a particular event. The brain centre controlling pace incorporates knowledge of the endpoint into an algorithm, together with memory of prior events of similar distance or duration, and knowledge of external (environmental) and internal (metabolic) conditions to set a particular optimal pacing strategy for a particular exercise bout. It is proposed that an internal clock, which appears to use scalar rather than absolute time scales, is used by the brain to generate knowledge of the duration or distance still to be covered, so that power output and metabolic rate can be altered appropriately throughout an event of a particular duration or distance. Although the initial pace is set at the beginning of an event in a feedforward manner, no event or internal physiological state will be identical to what has occurred previously. Therefore, continuous adjustments to the power output in the context of the overall pacing strategy occur throughout the exercise bout using feedback information from internal and external receptors. These continuous adjustments in power output require a specific length of time for afferent information to be assessed by the brain's pace control algorithm, and for efferent neural commands to be generated, and we suggest that it is this time lag that crates the fluctuations in power output that occur during an exercise bout. These non-monotonic changes in power output during exercise, associated with information processing between the brain and peripheral physiological systems, are crucial to maintain the overall pacing strategy chosen by the brain algorithm of each athlete at the start of the exercise bout.
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Effects of deception and expected duration on the rating of perceived exertion (RPE), affect, and heart rate (HR) were examined during treadmill (n=12) and cycling (n=8) exercise. Participants completed three conditions: (1) 20 MIN-exercise for 20 min, stop after 20 min; (2) 10 MIN-exercise for 10 min, in 10th min be told to exercise for 10 min more; and (3) UNKNOWN-no information about duration. Intensities were set at 70% and 65% of peak oxygen uptake for treadmill and cycling, respectively. RPE increased (treadmill) and affect decreased (treadmill and cycling) in the absence of changes in HR and oxygen uptake in the 10 MIN conditions. These changes suggest a disruption to a feed-forward/feedback system. The lower HR in the UNKNOWN conditions suggests a subconscious attempt to conserve energy when the duration of the exercise task is unknown.
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Athletic competition has been a source of interest to the scientific community for many years, as a surrogate of the limits of human ambulatory ability. One of the remarkable things about athletic competition is the observation that some athletes suddenly reduce their pace in the mid-portion of the race and drop back from their competitors. Alternatively, other athletes will perform great accelerations in mid-race (surges) or during the closing stages of the race (the endspurt). This observation fits well with recent evidence that muscular power output is regulated in an anticipatory way, designed to prevent unreasonably large homeostatic disturbances. Here we demonstrate that a simple index, the product of the momentary Rating of Perceived Exertion (RPE) and the fraction of race distance remaining, the Hazard Score, defines the likelihood that athletes will change their velocity during simulated competitions; and may effectively represent the language used to allow anticipatory regulation of muscle power output. These data support the concept that the muscular power output during high intensity exercise performance is actively regulated in an anticipatory manner that accounts for both the momentary sensations the athlete is experiencing as well as the relative amount of a competition to be completed.
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The aim of this study was to examine the influence of the performance level of athletes on pacing strategy during a simulated 10-km running race, and the relationship between physiological variables and pacing strategy. Twenty-four male runners performed an incremental exercise test on a treadmill, three 6-min bouts of running at 9, 12 and 15 km h(-1), and a self-paced, 10-km running performance trial; at least 48 h separated each test. Based on 10-km running performance, subjects were divided into terziles, with the lower terzile designated the low-performing (LP) and the upper terzile designated the high-performing (HP) group. For the HP group, the velocity peaked at 18.8 +/- 1.4 km h(-1) in the first 400 m and was higher than the average race velocity (P < 0.05). The velocity then decreased gradually until 2,000 m (P < 0.05), remaining constant until 9,600 m, when it increased again (P < 0.05). The LP group ran the first 400 m at a significantly lower velocity than the HP group (15.6 +/- 1.6 km h(-1); P > 0.05) and this initial velocity was not different from LP average racing velocity (14.5 +/- 0.7 km h(-1)). The velocity then decreased non-significantly until 9,600 m (P > 0.05), followed by an increase at the end (P < 0.05). The peak treadmill running velocity (PV), running economy (RE), lactate threshold (LT) and net blood lactate accumulation at 15 km h(-1) were significantly correlated with the start, middle, last and average velocities during the 10-km race. These results demonstrate that high and low performance runners adopt different pacing strategies during a 10-km race. Furthermore, it appears that important determinants of the chosen pacing strategy include PV, LT and RE.
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Thepacing strategy may be defined as the process in which the total energy expenditure during exercise is regulated on a moment-to-moment basis in order to ensure that the exercise bout can be completed in a minimum time and without a catastrophic biological failure. Experienced athletes develop a stable template of the power outputs they are able to sustain for different durations of exercise, but it is not known how they originally develop this template or how that template changes with training and experience. While it is understood that the athlete's physiological state makes an important contribution to this process, there has been much less interest in the contribution that the athlete's emotional status makes. The aim of this review is to evaluate the literature of physiological, neurophysiological and perceptual responses during exercise in order to propose a complex model interpretation of this process which may be a critical factor determining success in middle- and long-duration sporting competitions. We describe unconscious/physiological and conscious/emotional mechanisms of control, the focus of which are to ensure that exercise terminates before catastrophic failure occurs in any bodily system. We suggest that training sessions teach the athlete to select optimal pacing strategies by associating a level of emotion with the ability to maintain that pace for exercise of different durations. That pacing strategy is then adopted in future events. Finally, we propose novel perspectives to maximise performance and to avoid overtraining by paying attention also to the emotional state in training process.
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During self-paced exercise, the exercise work rate is regulated by the brain based on the integration of numerous signals from various physiological systems. It has been proposed that the brain regulates the degree of muscle activation and thus exercise intensity specifically to prevent harmful physiological disturbances. It is presently proposed how the rating of perceived exertion (RPE) is generated as a result of the numerous afferent signals during exercise and serves as a mediator of any subsequent alterations in skeletal muscle activation levels and exercise intensity. A conceptual model for how the RPE mediates feedforward, anticipatory regulation of exercise performance is proposed, and this model is applied to previously described research studies of exercise in various conditions, including heat, hypoxia and reduced energy substrate availability. Finally, the application of this model to recent novel studies that altered pacing strategies and performance is described utilising an RPE clamp design, central nervous system drugs and the provision of inaccurate duration or distance feedback to exercising athletes.
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The regulation of the pacing strategy remains poorly understood, because much of classic physiology has focused on the factors that ultimately limit, rather than regulate, exercise performance. When exercise is self-paced and work rate is free to vary in response to external and internal physiological cues, then a complex system is proposed to be responsible for alterations in exercise intensity, possibly through altered activation of skeletal muscle motor units. The present review evaluates the evidence for such a complex system by investigating studies in which interventions such as elevated temperature, altered oxygen content of the air, reduced fuel availability and misinformation about distance covered have resulted in alterations to the pacing strategy. The review further investigates how such a pacing strategy might be regulated for optimal performance, while ensuring that irreversible physiological damage is not incurred.
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The pattern of energy expenditure during sustained high-intensity exercise is influenced by several variables. Data from athletic populations suggest that a pre-exercise conceptual model, or template, is a central variable relative to controlling energy expenditure. The aim of this study was to make systematic observations regarding how the performance template develops in fit individuals who have limited specific experience with sustained high-intensity exercise (eg, time trials). The study was conducted in four parts and involved measuring performance (time and power output) during: (A) six 3 km cycle time trials, (B) three 2 km rowing time trials, (C) four 2 km rowing time trials with a training period between trials 2 and 3, and (D) three 10 km cycle time trials. All time trials were self-paced with feedback to the subjects regarding previous performances and momentary pace. In all four series of time trials there was a progressive pattern of improved performance averaging 6% over the first three trials and 10% over six trials. In all studies improvement was associated with increased power output during the early and middle portions of the time trial and a progressively greater terminal rating of perceived exertion. Despite the change in the pattern of energy expenditure, the subjects did not achieve the pattern usually displayed by athletes during comparable events. This study concludes that the pattern of learning the performance template is primarily related to increased confidence that the trial can be completed without unreasonable levels of exertion or injury, but that the process takes more than six trials to be complete.
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This study assessed the relationship of the rating of perceived exertion (RPE) with heart rate and pacing strategy during competitive running races of differing distance and course elevation. Nine men and women competed in a 7-mile road race (7-MR) and the Great West Run half marathon (GWR; 13.1 miles). Heart rate, split mile time, and RPE were recorded throughout the races. The RPE was regressed against time and %time to complete the 7-MR and GWR. Although the rate of increase in RPE was greater in the 7-MR, there were no differences when expressed against %time (inferring that the brain uses a scalar timing mechanism). As the course elevation, distance, pacing strategy, and heart rate response varied between conditions, this study has provided evidence that the perceptual response may have distinct temporal characteristics during distance running. The results provide further evidence that RPE scales with the proportion of exercise time that remains.
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To investigate the effects of simultaneous explosive-strength and endurance training on physical performance characteristics, 10 experimental (E) and 8 control (C) endurance athletes trained for 9 wk. The total training volume was kept the same in both groups, but 32% of training in E and 3% in C was replaced by explosive-type strength training. A 5-km time trial (5K), running economy (RE), maximal 20-m speed (V20 m), and 5-jump (5J) tests were measured on a track. Maximal anaerobic (MART) and aerobic treadmill running tests were used to determine maximal velocity in the MART (VMART) and maximal oxygen uptake (VO2 max). The 5K time, RE, and VMART improved (P < 0.05) in E, but no changes were observed in C. V20 m and 5J increased in E (P < 0.01) and decreased in C (P < 0.05). VO2 max increased in C (P < 0.05), but no changes were observed in E. In the pooled data, the changes in the 5K velocity during 9 wk of training correlated (P < 0.05) with the changes in RE [O2 uptake (r = -0.54)] and VMART (r = 0.55). In conclusion, the present simultaneous explosive-strength and endurance training improved the 5K time in well-trained endurance athletes without changes in their VO2 max. This improvement was due to improved neuromuscular characteristics that were transferred into improved VMART and running economy.
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Running performance depends on maximal oxygen uptake (VO(2max)), the ability to sustain a high percentage of VO(2max) for an extended period of time and running economy. Running economy has been studied relatively less than the other factors. Running economy, measured as steady state oxygen uptake (VO(2)) at intensities below the ventilatory threshold is the standard method. Extrapolation to a common running speed (268 m/min) or as the VO(2) required to run a kilometer is the standard method of assessment. Individuals of East African origin may be systematically more economical, although a smaller body size and a thinner lower leg may be the primary factors. Strategies for improving running economy remain to be developed, although it appears that high intensity running may be a common element acting to improve economy.
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It is widely recognized that an athlete's 'pacing strategy', or how an athlete distributes work and energy throughout an exercise task, can have a significant impact on performance. By applying mathematical modelling (i.e. power/velocity and force/time relationships) to athletic performances, coaches and researchers have observed a variety of pacing strategies. These include the negative, all-out, positive, even, parabolic-shaped and variable pacing strategies. Research suggests that extremely short-duration events (< or =30 seconds) may benefit from an explosive 'all-out' strategy, whereas during prolonged events (>2 minutes), performance times may be improved if athletes distribute their pace more evenly. Knowledge pertaining to optimal pacing strategies during middle-distance (1.5-2 minutes) and ultra-endurance (>4 hours) events is currently lacking. However, evidence suggests that during these events well trained athletes tend to adopt a positive pacing strategy, whereby after peak speed is reached, the athlete progressively slows. The underlying mechanisms influencing the regulation of pace during exercise are currently unclear. It has been suggested, however, that self-selected exercise intensity is regulated within the brain based on a complex algorithm involving peripheral sensory feedback and the anticipated workload remaining. Furthermore, it seems that the rate and capacity limitations of anaerobic and aerobic energy supply/utilization are particularly influential in dictating the optimal pacing strategy during exercise. This article outlines the various pacing profiles that have previously been observed and discusses possible factors influencing the self-selection of such strategies.
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The hypothesis that fatigue during prolonged exercise arises from insufficient intramuscular glycogen, which limits tricarboxylic acid cycle (TCA) activity due to reduced TCA cycle intermediates (TCAI), was tested in this experiment. Seven endurance-trained men cycled at similar to70% of peak O-2 uptake ((V)over dot (O2 peak)) until exhaustion with low (LG) or high (HG) preexercise intramuscular glycogen content. Muscle glycogen content was lower (P < 0.05) at fatigue than at rest in both trials. However, the increase in the sum of four measured TCAI (>70% of the total TCAI pool) from rest to 15 min of exercise was not different between trials, and TCAI content was similar after 103 +/- 15 min of exercise (2.62 +/- 0.31 and 2.59 +/- 0.28 mmol/kg dry wt for LG and HG, respectively), which was the point of volitional fatigue during LG. Subjects cycled for an additional 52 +/- 9 min during HG, and although glycogen was markedly reduced (P < 0.05) during this period, no further change in the TCAI pool was observed, thus demonstrating a clear dissociation between exercise duration and the size of the TCAI pool. Neither the total adenine nucleotide pool (TAN = ATP + ADP + AMP) nor IMP was altered compared with rest in either trial, whereas creatine phosphate levels were not different when values measured at fatigue were compared with those measured after 15 min of exercise. These data demonstrate that altered glycogen availability neither compromises TCAI pool expansion nor affects the TAN pool or creatine phosphate or IMP content during prolonged exercise to fatigue. Therefore, our data do not support the concept that a decrease in muscle TCAI during prolonged exercise in humans compromises aerobic energy provision or is the cause of fatigue.
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Purpose: To verify the affective feelings (AFs) and rating of perceived exertion (RPE) responses during a 10-km competitive head-to-head (HTH) running race and compare them with a time-trial (TT) running race. Methods: Fourteen male runners completed 2 × 10-km runs (TT and HTH) on different days. Speed, RPE, and AF were measured every 400 m. For pacing analysis, races were divided into the following 4 stages: first 400 m (F400), 401-5000 m (M1), 5001-9600 m (M2), and the last 400 m (final sprint). Results: Improvement of performance was observed (39:32 [02:41] min:s vs 40:28 [02:55] min:s; P = .03; effect size = -0.32) in HTH compared with TT. There were no differences in either pacing strategy or RPE between conditions. AFs were higher during the HTH, being different in M2 compared with TT (2.09 [1.81] vs 0.22 [2.25]; P = .02; effect size = 0.84). Conclusions: AFs are directly influenced by the presence of opponents during an HTH race, and a more positive AF could be involved in the dissociation between RPE and running speed and, consequently, the overall race performance.
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To investigate the effects of simultaneous explosive-strength and endurance training on physical performance characteristics, 10 experimental (E) and 8 control (C) endurance athletes trained for 9 wk. The total training volume was kept the same in both groups, but 32% of training in E and 3% in C was replaced by explosive-type strength training. A 5-km time trial (5K), running economy (RE), maximal 20-m speed ( V 20 m ), and 5-jump (5J) tests were measured on a track. Maximal anaerobic (MART) and aerobic treadmill running tests were used to determine maximal velocity in the MART ( V MART ) and maximal oxygen uptake (V˙o 2 max ). The 5K time, RE, and V MART improved ( P < 0.05) in E, but no changes were observed in C. V 20 m and 5J increased in E ( P < 0.01) and decreased in C ( P < 0.05).V˙o 2 max increased in C ( P < 0.05), but no changes were observed in E. In the pooled data, the changes in the 5K velocity during 9 wk of training correlated ( P< 0.05) with the changes in RE [O 2 uptake ( r = −0.54)] and V MART ( r = 0.55). In conclusion, the present simultaneous explosive-strength and endurance training improved the 5K time in well-trained endurance athletes without changes in theirV˙o 2 max . This improvement was due to improved neuromuscular characteristics that were transferred into improved V MART and running economy.
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Objectives: Studies comparing multiple groups (i.e., experimental and control) often examine the efficacy of an intervention by calculating within group effect sizes using Cohen's d. This method is inappropriate and largely impacted by the pre-test variability as opposed to the variability in the intervention itself. Furthermore, the percentage change is often analyzed, but this is highly impacted by the baseline values and can be potentially misleading. Thus, the objective of this study was to illustrate the common misuse of the effect size and percent change measures. Design: Here we provide a realistic sample data set comparing two resistance training groups with the same pre-test to post-test change. Methods: Statistical tests that are commonly performed within the literature were computed. Results: Analyzing the within group effect size favors the control group, while the percent change favors the experimental group. The most appropriate way to present the data would be to plot the individual responses or, for larger samples, provide the mean change and 95% confidence intervals of the mean change. This details the magnitude and variability within the response to the intervention itself in units that are easily interpretable. Conclusions: This manuscript demonstrates the common misuse of the effect size and details the importance for investigators to always report raw values, even when alternative statistics are performed.
Article
The purpose of the current study was to identify the main determinants of the self-selected pacing strategy during a 10-km running time-trial. Twenty eight male long-distance runners performed the following tests: a) maximal incremental treadmill test, b) economy running test, c) maximum dynamic strength test, and d) 10-km running time-trial on an outdoor track. A stepwise multiple regression model was used to identify the contribution of rating of perceived exertion (RPE), physiological, and muscular parameters on the pacing strategy adopted by athletes. In the start phase (first 400m), RPE accounted for 72% (P=0.001) of the pacing variance. Peak treadmill speed measured during a maximal incremental test explained 52% (P=0.001) of the pacing variance during the middle phase (400 to 9600 m), while maximal oxygen uptake and maximum dynamic strength accounted for additional 23% (P=0.002) and 5% (P=0.003), respectively. In the end phase (last 400m), peak treadmill speed accounted alone for 66% (P=0.003) of the pacing variance. These data suggest that predictors of the pacing strategy during a 10-km running time-trial have a transitional behavior from perceptive (start phase) to muscular and physiological factors (middle and end phases).
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Successful participation in competitive endurance activities requires continual regulation of muscular work rate in order to maximise physiological performance capacities, meaning that individuals must make numerous decisions with regards to the muscular work rate selected at any point in time. Decisions relating to the setting of appropriate goals and the overall strategic approach to be utilised are made prior to the commencement of an event, whereas tactical decisions are made during the event itself. This review examines current theories of decision-making in an attempt to explain the manner in which regulation of muscular work is achieved during athletic activity. We describe rational and heuristic theories, and relate these to current models of regulatory processes during self-paced exercise in an attempt to explain observations made in both laboratory and competitive environments. Additionally, we use rational and heuristic theories in an attempt to explain the influence of the presence of direct competitors on the quality of the decisions made during these activities. We hypothesise that although both rational and heuristic models can plausibly explain many observed behaviours in competitive endurance activities, the complexity of the environment in which such activities occur would imply that effective rational decision-making is unlikely. However, at present, many proposed models of the regulatory process share similarities with rational models. We suggest enhanced understanding of the decision-making process during self-paced activities is crucial in order to improve the ability to understand regulation of performance and performance outcomes during athletic activity.
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232 undergraduates participated in 3 experiments that evaluated the feeling scale (FS) by W. J. Rejeski et al (1987) as a measure of affect during exercise. In Exp 1, Ss were instructed to check adjectives on the Multiple Affective Adjective Checklist—Revised that they would associate with either a "good" or a "bad" feeling during exercise. As predicted, discriminant function analysis indicated that the good/bad dimension of the FS appears to represent a core of emotional expression. In Exp 2, Ss rated how they felt during exercise at 3 rates of perceived exertion (RPE). Exp 3 involved 3 4-min bouts of exercise at 30, 60, and 90% of maximum oxygen consumption. RPE and the FS were moderately related, but only at easy and hard workloads. FS ratings evidenced greater variability as metabolic demands increased, and RPEs consistently had stronger ties to physiologic cues than responses to the FS. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
This study examined the determinants of pacing strategy and performance during self-paced maximal exercise. Eight well-trained cyclists completed two 20-km time trials. Power output, rating of perceived exertion (RPE), positive and negative affect, and iEMG activity of the active musculature were recorded every 0.5 km, confidence in achieving preexercise goals was assessed every 5 km, and blood lactate and pH were measured postexercise. Differences in all parameters were assessed between fastest (FAST) and slowest (SLOW) trials performed. Mean power output was significantly higher during the initial 90% of FAST, but not the final 10%, and blood lactate concentration was significantly higher and pH significantly lower following FAST. Mean iEMG activity was significantly higher throughout SLOW. Rating of perceived exertion was similar throughout both trials, but participants had significantly more positive affect and less negative affect throughout FAST. Participants grew less confident in their ability to achieve their goals throughout SLOW. The results suggest that affect may be the primary psychological regulator of pacing strategy and that higher levels of positivity and lower levels of negativity may have been associated with a more aggressive strategy during FAST. Although the exact mechanisms through which affect acts to influence performance are unclear, it may determine the degree of physiological disruption that can be tolerated, or be reflective of peripheral physiological status in relation to the still to be completed exercise task.
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Plyometric training improves vertical jump height (VJH). However, the effectiveness of plyometric training depends on various factors. A meta-analysis of 56 studies with a total of 225 effect sizes (ESs) was carried out to analyze the role of various factors on the effects of plyometrics on VJH performance. The inclusion criteria for the analysis were a) studies using plyometric programs for lower-limb muscles, b) studies employing true experimental designs and valid and reliable measurements, and c) studies including enough data to calculate ESs. Subjects with more experience in sport obtained greater enhancements in VJH performance (p < 0.01). Subjects in either good or bad physical condition benefit equally from plyometric work (p < 0.05), although men tend to obtain better power results than women after plyometric training (p < 0.05). With relation to the variables of performance, training volumes of more than 10 weeks and more than 20 sessions, using high-intensity programs (with more than 50 jumps per session), were the strategies that seemed to maximize the probability of obtaining significantly greater improvements in performance (p < 0.05). To optimize jumping enhancement, the combination of different types of plyometrics (squat jump + countermovement jump + drop jump) is recommended rather than using only 1 form (p < 0.05). However, no extra benefits were found to be gained from doing plyometrics with added weight. The responses identified in this analysis are essential and should be considered by strength and conditioning professionals with regard to the most appropriate dose-response trends for optimizing plyometric-induced gains.
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Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.
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To study the physiologic basis of variability of physical performance in the laboratory, ten male subjects were studied once a week, during a 9-12 month period. Previously, the reference maximal work load attained (Wref) was determined in each subject. The test protocol of the actual study was based on the individual Wref and started at 70% Wref for 5 min whereupon the work load was increased by 5% Wref every 2.5 min to exhaustion. The maximal work load attained (Wmax) was considered as the test performance. Heart rate, respiratory variables, oxygen uptake (VO2), and blood lactate concentration were determined at each work load. The rate of perceived exertion during submaximal and maximal work was also scored. In all subjects, Wmax and VO2max varied randomly, while the coefficient of variation in VO2max (4.20% - 11.35%) exceeded that in Wmax (2.95%-6.83%). No seasonal influences on VO2 max and Wmax were observed. In all subjects the physiologic variables, when plotted as a function of external work load, were shifted to the right with higher Wmax values and to the left with lower Wmax values. With lower Wmax values, the rate of perceived exertion during submaximal work tended to increase. The results suggest that the magnitude of physiologic responses to exercise is related to relative work load and that variability of physical performance is related to changes in gross mechanical efficiency.
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Field and laboratory studies were made on 16 trained distance runners to determine the relationship between selected metabolic measurements and distance running performance. Measurements were made for oxygen consumption, heart rate, and blood lactate accumulation during submaximal and maximal treadmill running. Several days after the laboratory test all of the runners competed in a 10-mile road race. The correlation between max[latin capital V with dot above]o2 (ml/kg x min) and performance in the 10-mile race (min) was -0.91 At a selected speed (268 m/min) the % max[latin capital V with dot above]o2 and % max HR were found to be highly related to distance running performance (r = -0.94 and 0.98, respectively). At all running speeds above 70% max[latin capital V with dot above]o2 the faster runners were found to accumulate less blood lactate than the slower runners at similar speeds and relative percentages of their aerobic capacities. The findings suggest that successful distance running is dependent on the economical utilization of a highly developed aerobic capacity and the ability to employ a large fraction of that capacity with minimal accumulation of lactic acid. (C)1973The American College of Sports Medicine
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There is a great demand for perceptual effort ratings in order to better understand man at work. Such ratings are important complements to behavioral and physiological measurements of physical performance and work capacity. This is true for both theoretical analysis and application in medicine, human factors, and sports. Perceptual estimates, obtained by psychophysical ratio-scaling methods, are valid when describing general perceptual variation, but category methods are more useful in several applied situations when differences between individuals are described. A presentation is made of ratio-scaling methods, category methods, especially the Borg Scale for ratings of perceived exertion, and a new method that combines the category method with ratio properties. Some of the advantages and disadvantages of the different methods are discussed in both theoretical-psychophysical and psychophysiological frames of reference.
Article
This study was carried out to investigate the importance of maximal oxygen uptake (VO2max) and so-called muscle power factors relating to neuromuscular and anaerobic characteristics as determinants of peak horizontal and uphill treadmill running velocity (Vmax). Muscle power factors were measured as peak velocity (VMART) and blood lactate concentration (BlaMART) in a maximal anaerobic running test and as maximal 30-m run velocity (V30m). Seven middle-distance runners, eight triathletes and eight cross-country skiers performed an incremental VO2max-test at horizontal (subscript max0) and 7 degrees uphill (subscript max7) and the MART at 3 degrees uphill on a treadmill and V30m-test on a track. The MART consisted of n x 20-s runs with a 100-s recovery between the runs and the velocity was increased by 0.41 m x s(-1) for each consecutive run until exhaustion. At 0 degrees Vmax was significantly higher but VO2max, ventilation and Bla were significantly lower than at 7 degrees inclination. Vmax0 correlated with VMART (r=0.85, P<0.001), Blamax0 (r=0.49, P<0.05) and V30m (r=0.78, P<0.001) but not with VO2max0. Vmax7 correlated with VO2max7 (r=0.78, P<0.001), VMART (r=0.61, P<0.01) and V30m (r=0.53, P<0.05). VMART correlated with BlaMART (r=0.71, P<0.01) and V30m (r=0.96, P<0.001) but not with VO2max0 or VO2max7. Middle-distance runners had a significantly (P<0.001) higher Vmax0, VMART BlaMART and V30m than triathletes and cross-country skiers, but no significant differences were found between the three groups in VO2max0, VO2max7 or Vmax7. We conclude that so-called muscle power factors, e.g. VMART, V30m and BlaMART, contribute to peak treadmill running performance and especially to horizontal running performance and that VO2max contributes more to uphill than horizontal running performance.
Article
Previous research has reported that plyometric training improves running economy (RE) and ultimately distance-running performance, although the exact mechanism by which this occurs remains unclear. This study examined whether changes in running performance resulting from plyometric training were related to alterations in lower leg musculotendinous stiffness (MTS). Seventeen male runners were pre- and post-tested for lower leg MTS, maximum isometric force, rate of force development, 5-bound distance test (5BT), counter movement jump (CMJ) height, RE, VO(2max), lactate threshold (Th(la)), and 3-km time. Subjects were randomly split into an experimental (E) group which completed 6 weeks of plyometric training in conjunction with their normal running training, and a control (C) group which trained as normal. Following the training period, the E group significantly improved 3-km performance (2.7%) and RE at each of the tested velocities, while no changes in VO(2max) or Th(la) were recorded. CMJ height, 5BT, and MTS also increased significantly. No significant changes were observed in any measures for the C group. The results clearly demonstrated that a 6-week plyometric programme led to improvements in 3-km running performance. It is postulated that the increase in MTS resulted in improved RE. We speculate that the improved RE led to changes in 3-km running performance, as there were no corresponding alterations in VO(2max) or Th(la).
Article
Previous studies suggest that the rating of perceived exertion (RPE) increases during steady-state, open-loop exercise in proportion to the relative time to fatigue. This suggests that RPE is scalar and integrates physiological status and homeostatic disturbances. This study assessed the relationship between the rate of change in RPE, and relative distance in time trials at distances of 2.5, 5, and 10 km. It also assessed the rate of change in RPE during 5-km time trials while breathing hypoxic air. The subjects were well-conditioned cyclists. In part 1, each subject completed habituation time trials, and then randomly ordered time trials at each distance. The category ratio RPE was measured in 10% increments throughout each trial. In part 2, each subject completed three 5-km time trials while breathing different inspired gas mixtures (FiO2 = 0.2093 throughout the trial, FiO2 = 0.15 between 2 and 4 km, and FiO2 = 0.15 between 2.5 and 4 km). RPE was measured at 10% increments. In part 1, when RPE was plotted against relative distance, there was no significant difference in the growth of RPE at proportional distances. In part 2, the decrease in power output during the hypoxic segments was sufficient that the growth of RPE was the same at each proportional distance. In both parts of the study, an RPE of 5 (hard) was achieved after 20% of the time trial distance, and an RPE of 8 was achieved after 80% distance. This study supports the hypothesis that RPE increases similarly in relation to relative distance, regardless of the distance performed, and it suggests that the perception of effort has scalar properties.
Pacing strategy in middle and long distance running: How are velocities adjusted during the race? Revista Brasileira de Educação Física e Esporte
  • E Carmo
  • D L M Barreti
  • C Ugrinowitsch
  • V Tricoli
Carmo, E., Barreti, D. L. M., Ugrinowitsch, C., & Tricoli, V. (2012). Pacing strategy in middle and long distance running: How are velocities adjusted during the race? Revista Brasileira de Educação Física e Esporte, 26(2), 351-363.
Improvements in cycling time trial performance are not sustained following the acute provision of challenging and deceptive feedback
  • W Hopkins
  • S Marshall
  • A Batterham
  • J Hanin
  • H S Jones
  • E L Williams
  • D Marchant
  • A Sparks
  • C A Bridge
  • A W Midgley
Hopkins, W., Marshall, S., Batterham, A., & Hanin, J. (2009). Progressive statistics for studies in sports medicine and exercise science. Medicine+ Science in Sports+ Exercise, 41(1), 3. Jones, H. S., Williams, E. L., Marchant, D., Sparks, A., Bridge, C. A., & Midgley, A. W. (2016). Improvements in cycling time trial performance are not sustained following the acute provision of challenging and deceptive feedback. Frontiers in Physiology, 7, 399.
Fractional utilization of the aerobic capacity during distance running
  • Costill D. L.