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Purpose: To investigate the effect of measurement timing and concurrent validity of session (sRPE) and differential (dRPE) ratings of perceived exertion as measures of internal training load (ITL) in adolescent distance runners. Methods: Fifteen adolescent distance runners (15.2 ± 1.6 y) performed a two-step incremental treadmill test for the assessment of maximal oxygen uptake, heart rate and the blood lactate responses. Participants were familiarised with RPE and dRPE during the treadmill test using Foster's modified CR-10 Borg scale. Subsequently, each participant completed a regular two-week mesocycle of training. Participants wore a heart rate monitor for each exercise session and recorded their training in a logbook, including sRPE, dRPE leg exertion (dRPE-L) and breathlessness (dRPE-B) following session completion (0 min), 15 min post-session and 30 min post-session. Results: sRPE, dRPE-L and dRPE-B scores were all most likely lower when reported 30 min post-session, compared to scores 0 min post-session (% change ±90% confidence limits; sRPE, -26.5% ±5.5%; dRPE-L, -20.5% ±5.6%, dRPE-B, -38.9% ±7.4%). sRPE, dRPE-L and dRPE-B all maintained their largest correlations (r = 0.74 to 0.89) when reported at session completion (0 min), in comparison to each of the HR-based criteria measures. Conclusion: sRPE, whether reported 0 min, 15 min or 30 min post-session, provides a valid measure of ITL in adolescent distance runners. Also, dRPE-L and dRPE-B can be used in conjunction with sRPE, across all time-points (0, 15 and 30 min), in order to discriminate between central and peripheral exertion.

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... Many GPS watches have the capacity to monitor wrist-based HR, which was found to be within 3.3% to 6.2% of the goldstandard chest-based HR during running. 21 Strong relationships were reported between sRPE and training impulse, a measure of continuous HR, in adolescent long-distance runners 22 and between sRPE summation of time spent in different HR zones in youth atheltes. 23 However, it is unknown if a single measure of intensity, such as average or maximal HR, is related to sRPE among adolescent long-distance runners. ...
... Therefore, the primary purpose of this study was to compare the validity of self-reported external and internal loads to GPS watch-derived measures in high school cross-country runners. We hypothesized that (1) similar to prior studies in adult runners, 15,16 there would be strong positive relationships among selfreported and GPS watch-derived measures of external and (2) similar to a prior study in adolescents runners using continuous HR, 22 there would be strong positive relationships among self-reported and GPS watch-derived discrete measures of internal loads. A secondary aim was to investigate if there was agreement in intensity zone classification according to sRPE and average and maximal HR. ...
... Previously, training impulse (derived from cumulative time spent in different HR zones) was found to have a strong relationship with sRPE in adolescent longdistance runners. 22 Training impulse is likely a more comprehensive analysis of objective intensity compared with average and maximal HR. However, continuous HR data are needed to calculate training impulse and extracting the data may be challenging, and impractical for coaches. ...
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Purpose: Running programs are designed to progress training loads by manipulating the duration, frequency, and/or intensity of running sessions. While some studies use journals to monitor training load, others have used wearable technology. The purpose of this study was to compare the validity of self-reported and global positioning system (GPS)-watch-derived measures of external and internal loads in high school cross-country runners. Methods: Twenty-two high school cross-country runners participated in the study during fall 2020. Participants recorded running sessions using a GPS watch and self-reported the running session using an electronic journal. External (distance and duration) and internal loads (session rating of perceived exertion [sRPE], average, and maximum heart rate) were retrieved from the GPS watch and electronic journal. Correlations compared relationships, and Bland-Altman plots compared agreements between GPS-watch-derived and self-reported measures of training loads. Results: We found moderate relationships between self-reported and GPS-watch-derived measures of external loads (distance: r = .76, moving duration: r = .74, and elapsed duration: r = .70) and poor relationships between internal loads (sRPE vs average heart rate: ρ = .11, sRPE vs maximal heart rate: ρ = .13). We found mean differences of -0.8 km (95% = -6.3 to +4.8 km) for distance, -4.5 minutes (95% = -27.8 to +33.2 min) for moving duration, and 2.7 minutes (95% = -27.8 min to +33.2 min) for elapsed duration. Conclusions: High school runners overreported running distance and duration using self-reports, and self-reported and GPS-watch-derived measures of internal loads demonstrated poor agreement. Coaches and clinicians should use caution when comparing results from studies using different methods of monitoring training loads.
... Eight studies applied the session-RPE [5] method to quantify and monitor internal training loads in youth athletes across soccer [25][26][27], taekwondo [28,29], basketball [30], long distance running [31] and water polo [32] (Table 1). Overall, low (r = 0.17) to high (r = 0.88) correlations (p < 0.05) were found between the session-RPE method and the criterion; Edward's HR-method (n = 8) and Banister's Training Impulse (TRIMP) (n = 3). ...
... Eight studies exploring the validity of the session-RPE method [5] to quantify internal training load in youth athletes across various sports were identified [25][26][27][28][29][30][31][32]. The findings of these studies suggest that the session-RPE method may be a useful and inexpensive tool for quantifying internal training load for very high-intensity (e.g. ...
... While most studies [27,29,30,32] collected session-RPE at 30 min, two [25,26] have collected at 20 min post session. Additionally, two studies [28,31] found in this scoping review explored the timing effects of when the session-RPE was requested. Lupo et al. [28] found in a group of young taekwondo athletes, session-RPE collected at 30 min correlated higher compared to immediately post-training. ...
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In adults, ratings of perceived exertion (RPE) can be used to predict maximal oxygen uptake, estimate time to exhaustion, assess internal training load and regulate exercise intensity. However, the utility of RPE in children is less researched and therefore, warrants investigation. The purpose of this scoping review is to map out the literature around the application of RPE specifically during aerobic exercise in paediatric populations. Seven bibliographic databases were systematically searched. Grey literature searching and pearling of references were also conducted. To be included for the review, studies were required to comply with the following: (1) participants aged ≤ 18 years asymptomatic of any injuries, disabilities or illnesses; (2) applied RPE in aerobic exercise, testing and/or training; (3) included at least one measure of exercise intensity; and (4) be available in English. The search identified 22 eligible studies that examined the application of RPE in children. These studies involved a total of 718 participants across ten different countries. Nine different types of RPE scales were employed. Overall, the application of RPE in paediatric populations can be classified into three distinct themes: prediction of cardiorespiratory fitness/performance, monitoring internal training loads, and regulation of exercise intensity. The utility of RPE in paediatric populations remains unclear due to the small body of available research and inconsistencies between studies. However, findings from the included studies in this scoping review may show promise. Further research focussing on child-specific RPE scales across various sports, subgroups, and in field-based settings is needed.
... To calculate internal training load (ITL), each participant self-reported their most recent training week, including the duration (minutes), distance (km), session type, and rating of perceived exertion (RPE) for each of their training sessions. Weekly session RPE (sRPE) was subsequently calculated, having been validated as a measure of ITL in adolescent distance runners (Mann et al., 2019). Use of a coach, inclusion of a warm-up/cool-down, and inclusion of a strength and conditioning programme were categorised via binary (i.e., yes/no) self-reported responses. ...
... It is also important to recognise that self-reported intensity was based on perceived exertion. Although this approach has been validated for use within this population (Mann et al., 2019), this does not mean that other physiological or biomechanical measures of intensity did not vary between participants and the different age-groups. ...
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Background: Distance running is one of the most popular sports around the world. The epidemiology of running-related injury (RRI) has been investigated in adults, but few studies have focused on adolescent distance runners. Objectives: (1) To provide descriptive epidemiology of RRI (risks, rates, body regions/areas, and severity) and examine the training practices (frequency, volume, and intensity) of competitive adolescent distance runners (13–18 years) in England, and (2) to describe potential risk factors of RRI. Methods: A cross-sectional study design was used. Adolescent distance runners ( n = 113) were recruited from England Athletics affiliated clubs. Participants voluntarily completed an online questionnaire between April and December 2018. At the time of completion, responses were based on the participant's previous 12-months of distance running participation. Incidence proportions (IP) and incidence rates (IR) were calculated. Results: The IP for “all RRI” was 68% (95% CI: 60–77), while the IR was 6.3/1,000 participation hours (95% CI: 5.3–7.4). The most commonly injured body areas were the knee, foot/toes, and lower leg; primarily caused by overuse. The number of training sessions per week (i.e., frequency) significantly increased with chronological age, while a large proportion of participants (58%) self-reported a high level of specialisation. Conclusions: RRI is common in competitive adolescent distance runners. These descriptive data provide guidance for the development of RRI prevention measures. However, analytical epidemiology is required to provide better insight into potential RRI risk factors in this specific population.
... Based on the idea that differentiated central and peripheral on-task RPE might be associated with specific physiological changes during exercise (Pandolf, 1982;Robertson & Noble, 1997), studies differentiating sRPE into breathing and muscular components of an exercise bout have been proliferating in the scientific literature (Green et al., 2009;Green et al., 2011;Mann et al., 2019;McLaren et al., 2016;Ribeiro et al., 2013). The rationale for this approach is to go beyond procuring only an overall sRPE (sRPE-O) and gain more detailed information on perceptual signal dominance for a whole exercise session (Ribeiro et al., 2013). ...
... It should be noted that knowledge of differentiated sRPE after running exercise is still in its infancy, with studies scarce and available results equivocal (Green et al., 2011;Mann et al., 2019;McLaren et al., 2016). In this context, the modest dominance of sRPE-L over sRPE-B, as well as its amplification in the more demanding exercise bout, add interesting data to this relatively unexplored topic. ...
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Session ratings of perceived exertion (sRPE) are considered a practical marker of whole session exercise intensity, but its relationship to exercise volume has remained unclear. We analyzed the effects of exercise duration at different intensities on overall and differentiated sRPE. Sixteen males (Mage = 22.6, SD = 2.2 years; Mheight = 176.4, SD = 5.8 cm; Mweight = 74.0, SD = 5.9 kg; and Mbody fat = 9.4, SD = 2.2%) performed 15 and 30 minute runs at speeds associated with RPE levels of two (weak), three (moderate) and five (strong) on Borg's CR-10 scale during a previous graded exercise test. We used Foster's scale to access sRPE 30 minutes after each trial. Significant increases in sRPE were found with increases in running speed (p < 0.01, η G 2 = 0.48) and duration (p < 0.01, η G 2 = 0.16), with a significant speed X duration interaction (p < 0.01, η G 2 = 0.10). In addition, there was a significant effect for sRPE type (p = 0.01, η G 2 = 0.05) in that overall sRPE was slightly lower than sRPE differentiated to legs and higher than sRPE differentiated to breathing through the trials. Changes in sRPE from 15 to 30-minute trials were minimal for the slow speed and weak sRPE (Cohen´s dz = 0.04 - 0.25) but got higher at the moderate (Cohen´s dz = 0.88 - 1.06) and strong (Cohen´s dz = 1.94 - 2.50) speeds and sRPEs. Thus, exercise duration affects sRPE in an intensity dependent manner. This finding has practical relevance for prescribing exercise, suggesting a need to target specific training loads or aims to optimize trainees' retrospective perceptions of the exercise experience.
... This result is consistent with the level of validity of CR10-based sRPE encountered in youth athletes of other sports. 4,18 Second, moderate to large differences were found in the slopes of the relationships between the sRPE and Edwards load when assessed only in training sessions or games, in all age groups. Figure 1 highlight how the games slopes are typically shallower than the training ones, signifying that, for a given change in HR load, the change in sRPE is not the same if a player rates the effort originating from a game or a training session. ...
Article
Purpose: To assess the convergent validity of internal load measured with the CR100 scale in youth football players of 3 age groups. Methods: A total of 59 players, age 12-17 years, from the youth academy of a professional football club were involved in this study. Convergent validity was examined by calculating the correlation between session ratings of perceived exertion (sRPE) and Edwards load, a commonly used load index derived from the heart rate, with the data originating from 1 competitive season. The magnitude of the relationship between sRPE and Edwards load was obtained with weighted mean correlations and by assessing the effect of the change of the Edwards load on sRPE. Differences between the individuals' intercepts and slopes were assessed by interpreting the SD representing the random effects (player identity and the interaction of player identity and scaled Edwards load). Probabilistic decisions about true (infinite sample) magnitudes accounting for sampling uncertainty were based on 1-sided hypothesis tests of substantial magnitudes, followed by reference Bayesian analysis. Results: Very high relationships exist between the sRPE and Edwards load across all age groups, with no meaningful differences in the magnitudes of the relationships between groups. Moderate to large differences between training sessions and games were found in the slopes of the relationships between the sRPE and Edwards load in all age groups. Finally, mostly small to moderate differences were observed between individuals for the intercepts and slopes of the relationships between the sRPE and Edwards load. Conclusion: Practitioners working in youth team sports can safely use the CR100 scale to track internal load.
... interval session), and rating of perceived exertion (RPE) for each of their training sessions. Weekly session RPE (sRPE) was subsequently calculated, having been validated as a measure of ITL in adolescent distance runners [40]. Use of a coach, inclusion of a warm-up/cool-down, and inclusion of a strength and conditioning programme were categorised via binary (yes/no) self-report responses. ...
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Background: Distance running is one of the most popular sports around the world. The epidemiology of running-related injuries (RRI) has been examined in adults, but only a few studies have focused on adolescent distance runners. Therefore, the purpose of this study was 1) to examine the training practices (frequency, volume, and intensity) and descriptive epidemiology of RRI (risks, rates, sites, and severity) in competitive adolescent distance runners (13-18 years) in England, and 2) to explore potential correlates (risk factors) of RRI. Methods: A cross-sectional study design was used. Adolescent distance runners (n = 113) were recruited from England Athletics affiliated athletics clubs. Participants voluntarily completed an online questionnaire between April and December 2018. At the point of completion, responses were based on the participant’s previous 12-months of distance running participation. Injury incidence proportions (IP) and incidence rates (IR) were calculated. Potential correlates of RRI were estimated using an odds ratio (OR) and 95% confidence intervals (CI). Results: The injury IP was 122/100 participants/year (95% CI: 113 to 138). The injury IR was 6.3/1000 participation hours (95% CI: 5.3 to 7.4). The most common injury sites were the knee, foot/toes, and lower leg; primarily caused by overuse. Exploratory univariate analyses showed a larger number of training sessions per week (volume) is associated with a lower risk of RRI (OR = 0.71, 95% CI: 0.53 to 0.94), and that a higher level of specialisation is associated with a lower risk of time loss injury (OR = 0.26, 95% CI: 0.11 to 0.63). Conclusions: Injury is common in adolescent distance runners, aligned with adult-based research. These data provide guidance for the development of appropriate injury prevention interventions.
... It is somewhat surprising that the MDMQ data quoted higher reliabilities compared to Borg scale (BS) values. RPE is regularly used in sports science research and a valid parameter of internal training load 33 . However, not much is known about its reliability in the context of endurance exercise. ...
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There is currently insufficient evidence about the reliable quantification of exercise load and athlete’s recovery management for monitoring training processes. Therefore, this test-retest study investigated the reliability of various subjective, muscle force, and blood-based parameters in order to evaluate their suitability for monitoring exercise and recovery cycles. 62 subjects completed two identical 60-minute continuous endurance exercise bouts intermitted by a four-week recovery period. Before, immediately after, three, and 24 hours after each exercise bout, analysis of parameters were performed. Significant changes over time were found for rating of perceived exertion (RPE), multidimensional mood state questionnaire (MDMQ), maximum voluntary contraction parameters (MVCs), and blood-based biomarkers (p<0.05). Excellent reliability was calculated for MVCs, mean corpuscular volume and 5-bound distance (ICC>0.90). A good reliability was found for thiobarbituric acid reactive substances (TBARS) (ICC=0.79) and haematological markers (ICC=0.75–0.86). For RPE, MDMQ, interleukin (IL-) 1RA, IL-6, IL-8, IL-15, cortisol, lactate dehydrogenase (LDH), creatine kinase (CK) only moderate reliability was found (ICC<0.75). Significant associations for IL1-RA and CK to MVC were found. The excellent to moderate reliability of TBARS, LDH, IL-1RA, six measured haematological markers, MVCs and MDMQ implicate their suitability as physiological exercise response and recovery markers for monitoring athletes’ load management.
Article
Context: Running programs traditionally monitor external loads (e.g., time, distance). There has been a recent movement to encompass a more comprehensive approach to also monitor training loads that account for internal loads (e.g., intensity, measured as session rating of perceived exertion [sRPE]). The combination of an external and internal load accounts for the potential interaction between these loads. While differences in weekly change in training loads have been reported between external loads and the combination of an external and internal load during 2- and 4-week training cycles, there are no reports whether these differences are apparent during an entire cross-country season in high school runners. Objective: To compare change in training loads, as measured by external loads and combinations of an external and internal load, in high school runners during an interscholastic cross-country season. Design: Case-series. Setting: Community-based with daily online surveys. Participants: Twenty-four high school cross-country runners (female=14, male=10, age=15.9±1.1 years, running experience=9.9±3.2 years). Main Outcome Measure(s): Week-to-week percent change in training load when measured by external loads (time, distance) and the combination of an external and internal load (timeRPE, distanceRPE). Results: Overall, the average weekly change was 7.1% greater for distanceRPE compared to distance (p=.04, d=0.18). When decreasing weekly running duration, the average weekly change was 5.2% greater for distanceRPE compared to timeRPE (p=.03, d=0.24). When maintaining or increasing weekly running duration, the average weekly change was 10–15% greater when an external load was combined with an internal load compared to external loads alone, but these differences were non- significant (p=.11–.22, d=0.19–0.34). Conclusions: Our results demonstrate that progression in training load may be underestimated when relying solely on external loads. The interaction between internal loads (sRPE) and external loads (distance or time) appears to provide a different measure of training stresses experienced by runners than external loads alone.
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Purpose: The aim of this review is to (1) retrieve all data validating the Session-rating of perceived exertion (RPE)-method using various criteria, (2) highlight the rationale of this method and its ecological usefulness, and (3) describe factors that can alter RPE and users of this method should take into consideration. Method: Search engines such as SPORTDiscus, PubMed, and Google Scholar databases in the English language between 2001 and 2016 were consulted for the validity and usefulness of the session-RPE method. Studies were considered for further analysis when they used the session-RPE method proposed by Foster et al. in 2001. Participants were athletes of any gender, age, or level of competition. Studies using languages other than English were excluded in the analysis of the validity and reliability of the session-RPE method. Other studies were examined to explain the rationale of the session-RPE method and the origin of RPE. Results: A total of 950 studies cited the Foster et al. study that proposed the session RPE-method. 36 studies have examined the validity and reliability of this proposed method using the modified CR-10. Conclusion: These studies confirmed the validity and good reliability and internal consistency of session-RPE method in several sports and physical activities with men and women of different age categories (children, adolescents, and adults) among various expertise levels. This method could be used as “standing alone” method for training load (TL) monitoring purposes though some recommend to combine it with other physiological parameters as heart rate.
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While historically adolescents were removed from their parents to prepare to become warriors, this process repeats itself in modern times but with the outcome being athletic performance. This review considers the process of developing athletes and managing load against the backdrop of differing approaches of conserving and maximizing the talent available. It acknowledges the typical training ‘dose’ that adolescent athletes receive across a number of sports and the typical ‘response’ when it is excessive or not managed appropriately. It also examines the best approaches to quantifying load and injury risk acknowledging the relative strengths and weaknesses of subjective and objective approaches. Making evidence based decisions is emphasized, while choosing the appropriate monitoring techniques is determined by both the sporting context and individual situation. Ultimately a systematic approach to training load monitoring is recommended for adolescent athletes to both maximize their athletic development and to allow an opportunity for learning, reflection and the enhancement of performance knowledge of coaches and practitioners.
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Injury aetiology models that have evolved over the previous two decades highlight a number of factors which contribute to the causal mechanisms for athletic injuries. These models highlight the pathway to injury, including (1) internal risk factors (eg, age, neuromuscular control) which predispose athletes to injury, (2) exposure to external risk factors (eg, playing surface, equipment), and finally (3) an inciting event, wherein biomechanical breakdown and injury occurs. The most recent aetiological model proposed in 2007 was the first to detail the dynamic nature of injury risk, whereby participation may or may not result in injury, and participation itself alters injury risk through adaptation. However, although training and competition workloads are strongly associated with injury, existing aetiology models neither include them nor provide an explanation for how workloads alter injury risk. Therefore, we propose an updated injury aetiology model which includes the effects of workloads. Within this model, internal risk factors are differentiated into modifiable and non-modifiable factors, and workloads contribute to injury in three ways: (1) exposure to external risk factors and potential inciting events, (2) fatigue, or negative physiological effects, and (3) fitness, or positive physiological adaptations. Exposure is determined solely by total load, while positive and negative adaptations are controlled both by total workloads, as well as changes in load (eg, the acute:chronic workload ratio). Finally, we describe how this model explains the load—injury relationships for total workloads, acute:chronic workload ratios and the training load—injury paradox.
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Purpose: The session RPE (sRPE) has gained popularity as a "user friendly" method for evaluating internal training load. sRPE has historically been obtained 30-min following exercise. This study evaluated the effect of post-exercise measurement time on sRPE following steady-state and interval cycle exercise. Methods: Well-trained subjects (N=15) (VO2max=51+4 & 36+4 ml.kg-1 (cycle ergometer) for men & women, respectively) completed counterbalanced 30-min steady-state and interval training bouts. The steady-state ride was at 90% of ventilatory threshold (VT). The work-to-rest ratio of the interval rides was 1:1 and the interval segment durations were 1-, 2- & 3-min. The high-intensity component of each interval bout was 75% peak power output (PPO), which was accepted as a surrogate of the respiratory compensation threshold, critical power or maximal lactate steady state. Heart rate (HR), blood lactate [BLa], and Rating of Perceived Exertion (RPE) were measured. The sRPE (Category Ratio Scale) was measured at 5-, 10-, 15-, 20-, 2-, 30-, 60-min and 24-hr following each ride, using a Visual Analog Scale (VAS) to prevent bias associated with specific RPE verbal anchors. Results: sRPE, at 30-min post exercise, followed a similar trend: steady state=3.7, 1-min=3.9, 2-min=4.7, 3-min=6.2. No significant differences (p > 0.05) in sRPE were found based on post-exercise sampling times, from 5-min to 24-hr post-exercise. Conclusion: Post-exercise time does not appear to have a significant effect on sRPE after either steady-state or interval exercise. Thus, sRPE appears to be temporally robust and is not necessarily limited to the 30-min post exercise window historically used with this technique, although the presence/absence of a cool-down period after the exercise bout may be of importance.
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Background: The session rating of perceived exertion (session-RPE) proved to be a valuable method to quantify the internal training load (ITL) in taekwondo. However, no study validated this method in youth taekwondo athletes performing different training sessions. Thus this study aimed at evaluating the reliability of the session-RPE to monitor the ITL of prepubescent taekwondo athletes during pre-competitive (PC) and competitive (C) training sessions. Methods: Five female (age: 12.0 ± 0.7 y; height: 1.54 ± 0.08 m; body mass: 48.8 ± 7.3 kg) and four male (age: 12.0 ± 0.8 yrs; height: 1.55 ± 0.07 m; body mass: 47.3 ± 5.3 kg) taekwondo athletes were monitored during 100 individual sessions (PC: n = 33; C: n = 67). The Edwards' HR method was used as reference measure of ITL; the CR-10 RPE scale was administered at 1- and 30-minutes from the end of each session. Results: No difference for gender emerged. The ITLs of C (Edwards: 228 ± 40 arbitrary units, AU) resulted higher than that of PC (192 ± 26 AU; P = .04). Although all training typologies and data collections achieved significant correlations between Edwards' and session-RPE methods, a large relationship (r = .71, P < .001) emerged only for PC sessions evaluated at 30 minutes of the recovery phases. Conclusion: Findings support coaches of prepubescent taekwondo athletes to successfully use session-RPE to monitor the ITL of different training typologies. However, PC training evaluated at 30 minutes of the recovery phase represents the best condition for a highly reliable ITL perception.
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Assessing biological maturity in studies of children is challenging. Sex-specific regression equations developed using anthropometric measures are widely used to predict somatic maturity. However, prediction accuracy was not established in external samples. Thus, we aimed to evaluate the fit of these equations, assess for over-fitting (adjusting as necessary), and calibrate using external samples. We evaluated potential over-fitting using the original Pediatric Bone Mineral Accrual Study (PBMAS; 79 boys, 72 girls; 7.5-17.5 years). We assessed change in R and standard error of the estimate (SEE) with the addition of predictor variables. We determined the effect of within-subject correlation using cluster-robust variance and 5-fold random-splitting followed by forward-stepwise regression. We used dominant predictors from these splits to assess predictive abilities of various models. We calibrated using participants from the Healthy Bones Study-III (HBS-III; 42 boys, 39 girls; 8.9-18.9 years) and Harpenden Growth Study (HGS; 38 boys, 32 girls; 6.5-19.1years). Change in R and SEE was negligible when later predictors were added during step-by-step refitting of the original equations, suggesting over-fitting. After redevelopment, new models included age*sitting height for boys (R=0.91; SEE=0.51) and age*height for girls (R=0.90; SEE=0.52). These models calibrated well in external samples; HBS boys: b0=0.04(0.05); b1=0.98(0.03); RMSE=0.89, HBS girls: b0=0.35(0.04); b1=1.01(0.02); RMSE=0.65, HGS boys: b0=-0.20(0.02); b1=1.02(0.01); RMSE=0.85, HGS girls: b0=-0.02(0.03); b1=0.97(0.02); RMSE=0.70; where b0=calibration intercept (standard error; SE) and b1=calibration slope (SE), and RMSE=root mean squared error (of prediction). We subsequently developed an age*height alternate for boys; allowing for predictions without sitting height. Our equations provided good fits in external samples and provide an alternative to commonly used models. Original prediction equations were simplified with no meaningful increase in estimation error.
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Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
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Objective To investigate the application of differential ratings of perceived exertion for the examination of internal load during Australian Football League (AFL) matches. Design Single cohort, observational study. Methods Using the centiMax rating of perceived exertion (RPE) scale, 26 professional AFL players provided ratings for match exertion (RPE-M), along with differential ratings for breathlessness (RPE-B), leg exertion (RPE-L), and technical demand (RPE-T) following 129 matches (5.0 ± 1.6 matches per player). Global positioning satellite (GPS) and accelerometer measures were also collected. Data were analysed using magnitude-based inferences. Results RPE scores were 93.0 ± 8.2 AU (RPE-M), 89.0 ± 11.0 AU (RPE-B), 91.5 ± 9.8 AU (RPE-L), and 87.0 ± 10.0 AU (RPE-T). There was a most likely small difference between RPE-L and RPE-T (5.5%; ±90% confidence limits 1.9%), a likely small difference between RPE-L and RPE-B (3.5%; ±1.5%) and a possibly small difference between RPE-B and RPE-T (1.9%; ±1.9%). Within-player correlations between RPE and GPS measures were small for RPE-M (r = 0.14-0.28), unclear to small for RPE-B (r = 0.06-0.24) and unclear to moderate for RPE-L (r = 0.06-0.37). Differential RPE's combined to explain 76% of the variance in RPE-M. For all RPE scores, within-player variability was moderate-high (typical error: 7.9-12.4%), and the thresholds for a likely between-match change were 8.8-13.7%. Conclusions As differential RPE's represent distinct sensory inputs, the collection of these scores facilitate the interpretation of internal match loads and therefore represent a valuable addition to match data collection procedures. Moderate to high within-player variability should be considered when interpreting between-match changes in all RPE scores.
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Measures of resting, exercise, and recovery heart rate are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load (1) daily during specific training blocks and (2) throughout the competitive season. However, these measures are still not widely implemented to monitor athletes' responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in heart rate, reflecting cardiac parasympathetic activity) and submaximal exercise (30- to 60-s average) heart rate are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load, and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker's sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of heart rate cannot inform on all aspects of wellness, fatigue, and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training status in athletes participating in aerobic-oriented sports.
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The assessment of internal training load (ITL) using the session rate of perceived exertion (session-RPE) has been demonstrated to provide valuable information, also in team sports. Nevertheless, no studies investigated the use of this method during youth water polo training. Thus, the aim of this study was to evaluate youth water polo training, showing the correspondent level of reliability of the session-RPE method. Thirteen male youth water polo players (age, 15.6 ± 0.5 y; stature, 1.80 ± 0.06 m; body mass, 72.7 ± 7.8 kg) were monitored during 8 training sessions (80 individual training sessions) within 10-days. The Edwards summated heart rate zone method was used as a reference measure of internal training load; the session-RPE rating was obtained using CR-10 scale modified by Foster. The Pearson product-moment was applied to regress the Edwards' heart rate zone method against CR-10 session-RPE for each training session and individual data. Analyses reported overall high (r=0.88; R2=0.78) and significant (P<0.001) correlations between Edwards's heart rate and session-RPE methods. Significant correlations were also shown for each training session (r range: 0.69-0.92; R2 range: 0.48-0.85, P<0.05) and individual data (r range: 0.76-0.98; R2 range: 0.58-0.97, P<0.05). The present results confirmed the session-RPE method as an easy and reliable tool to evaluate ITL in youth water polo, allowing coaches to efficiently monitor their training plans.
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The ability to accurately control and monitor internal training load is an important aspect of effective coaching. The aim of this study was to apply in soccer the RPE-based method proposed by Foster et al. to quantify internal training load (session-RPE) and to assess its correlations with various methods used to determine internal training load based on the HR response to exercise. Nineteen young soccer players (mean +/- SD: age 17.6 +/- 0.7 yr, weight 70.2 +/- 4.7 kg, height 178.5 +/- 4.8 cm, body fat 7.5 +/- 2.2%, VO2max, 57.1 +/- 4.0 mL x kg x min) were involved in the study. All subjects performed an incremental treadmill test before and after the training period during which lactate threshold (1.5 mmol x L above baseline) and OBLA (4.0 mmol x L) were determined. The training loads completed during the seven training weeks were determined multiplying the session RPE (CR10-scale) by session duration in minutes. These session-RPE values were correlated with training load measures obtained from three different HR-based methods suggested by Edwards, Banister, and Lucia, respectively. Individual internal loads of 479 training sessions were collected. All individual correlations between various HR-based training load and session-RPE were statistically significant (from r = 0.50 to r = 0.85, P < 0.01). The results of this study show that the session-RPE can be considered a good indicator of global internal load of soccer training. This method does not require particular expensive equipment and can be very useful and practical for coaches and athletic trainer to monitor and control internal load, and to design periodization strategies.
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Because little is known about the effects of aging on perceived exertion, the aim of this article is to review the key findings from the published literature concerning rating of perceived exertion (RPE) in relation to the developmental level of a subject. The use of RPE in the exercise setting has included both an estimation paradigm, which is the quantification of the effort sense at a given level of exercise, and a production paradigm, which involves producing a given physiological effort based on an RPE value. The results of the review show that the cognitive developmental level of children aged 0-3 years does not allow them to rate their perceived exertion during a handgrip task. From 4 to 7 years of age, there is a critical period where children are able to progressively rate at first their peripheral sensory cues during handgrip tests, and then their cardiorespiratory cues during outdoor running in an accurate manner. Between 8 and 12 years of age, children are able to estimate and produce 2-4 cycling intensities guided by their effort sense and distinguish sensory cues from different parts of their body. However, most of the studies report that the exercise mode and the rating scale used could influence their perceptual responsiveness. During adolescence, it seems that the RPE-heart rate (HR) relationship is less pronounced than in adults. Similar to observations made in younger children, RPE values are influenced by the exercise mode, test protocol and rating scale. Limited research has examined the ability of adolescents to produce a given exercise intensity based on perceived exertion. Little else is known about RPE in this age group. In healthy middle-aged and elderly individuals, age-related differences in perceptual responsiveness may not be present as long as variations in cardiorespiratory fitness are taken into account. For this reason, RPE could be associated with HR as a useful tool for monitoring and prescribing exercise. In physically deconditioned elderly persons, a rehabilitation training programme may increase the subject's ability to detect muscular sensations and the ability to utilise these sensory cues in the perception of effort. RPE appears to be a cognitive function that involves a long and progressive developmental process from 4 years of age to adulthood. In healthy middle-aged and elderly individuals, RPE is not impaired by aging and can be associated with HR as a useful tool to control exercise intensity. While much is known about RPE responses in 8- to 12-year-old children, more research is needed to fully understand the influence of cognitive development on perceived exertion in children, adolescents and elderly individuals.
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Training quantification is basic to evaluate an endurance athlete's responses to the training loads, ensure adequate stress/recovery balance and determine the relationship between training and performance. Quantifying both external and internal workload is important, because the external workload does not measure the biological stress imposed by the exercise sessions. Generally used quantification methods include retrospective questionnaires, diaries, direct observation and physiological monitoring, often based on the measurement of oxygen uptake, heart rate and blood lactate concentration. Other methods in use in endurance sports include speed measurement and the measurement of power output, made possible by recent technological advances, such as power meters in cycling and triathlon. Among subjective methods of quantification the RPE stands out because of its wide use. Concurrent assessments of the various quantification methods allow researchers and practitioners to evaluate stress/recovery balance, adjust individual training programmes and determine the relationships between external load, internal load and athletes' performance. This brief review summarizes the most relevant external and internal workload quantification methods in endurance sports, and provides practical examples of their implementation to adjust the training programmes of elite athletes in accordance to their individualized stress/recovery balance.
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Sports specialization is becoming the norm in youth sports for a variety of reasons. When sports specialization occurs too early, detrimental effects may occur, both physically and psychologically. If the timing is correct and sports specialization is performed under the correct conditions, the athlete may be successful in reaching specific goals. Young athletes who train intensively, whether specialized or not, can also be at risk of adverse effects on the mind and body. The purpose of this clinical report is to assist pediatricians in counseling their young athlete patients and their parents regarding sports specialization and intensive training. This report supports the American Academy of Pediatrics clinical report "Overuse Injuries, Overtraining, and Burnout in Child and Adolescent Athletes."
To investigate the sensitivity of differential ratings of perceived exertion (dRPE) as measures of internal load. Twenty-two, male, university soccer players performed two maximal incremental exercise protocols (Cycle, Treadmill) on separate days. Maximal oxygen uptake (VO2max), maximal heart rate (HRmax), peak blood lactate concentration (B[La]peak) and the post-pre protocol change in countermovement jump height (ΔCMJH) were measured for each protocol. Players provided dRPE (CR100®) for breathlessness (RPE-B) and leg exertion (RPE-L) immediately upon exercise termination (RPE-B0, RPE-L0) and 30-minutes post-exercise (RPE-B30, RPE-L30). Data were analysed using magnitude-based inferences. There were clear between-protocol differences for VO2max (Cycle 46.5 ± 6.3 vs Treadmill 51.0 ± 5.1 ml·kg-1·min-1, mean difference -9.2%; ±90% confidence limits 3.7%), HRmax (185 ± 13 vs 197 ± 8 b·min-1, -6.0%; ±1.7%), B[La]peak (9.7 ± 2.1 vs 8.5 ± 2.0 mmol·L-1, 15%; ±10%) and ΔCMJH (-7.1 ± 4.2 vs 0.6 ± 3.6 cm, -23.2%; ±5.4%). Clear between-protocol differences were recorded for RPE-B0 (78 ± 12 vs 94.7 ± 9.5 AU, -18.1%; ±4.5%), RPE-L0 (92.6 ± 9.7 vs 81 ± 14 AU, 15.3%; ±7.6%), RPE-B30 (70 ± 11 vs 82 ± 13 AU, -13.8%; ±7.3%) and RPE-L30 (86 ± 12 vs 65 ± 19 AU, 37%; ±17%). A substantial timing effect was observed for dRPE, with moderate to large reductions in all scores 30-minutes post-exercise when compared to scores collected upon exercise termination. dRPE enhance the precision of internal load measurement and therefore represent a worthwhile addition to training load monitoring procedures.
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Historically, the ability of coaches to prescribe training to achieve optimal athletic performance can be attributed to many years of personal experience. A more modern approach is to adopt scientific methods in the development of optimal training programmes. However, there is not much research in this area, particularly into the quantification of training programmes and their effects on physiological adaptation and subsequent performance. Several methods have been used to quantify training load, including questionnaires, diaries, physiological monitoring and direct observation. More recently, indices of training stress have been proposed, including the training impulse, which uses heart rate measurements and training load, and session rating of perceived exertion measurements, which utilizes subjective perception of effort scores and duration of exercise. Although physiological adaptations to training are well documented, their influence on performance has not been accurately quantified. To date, no single physiological marker has been identified that can measure the fitness and fatigue responses to exercise or accurately predict performance. Models attempting to quantify the relationship between training and performance have been proposed, many of which consider the athlete as a system in which the training load is the input and performance the system output. Although attractive in concept, the accuracy of these theoretical models has proven poor. A possible reason may be the absence of a measure of individuality in each athlete's response to training. Thus, in the future more attention should be directed towards measurements that reflect individual capacity to respond or adapt to exercise training rather than an absolute measure of changes in physiological variables that occur with training.
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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.
Middle-and long-distance running Sport and exercise physiology testing
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Jones A. Middle-and long-distance running Sport and exercise physiology testing., 2007:147-154.
Volume ${article.issue.volume}, Article Number ${article.issue.issue} "The Validation of Session Rating of Perceived Exertion for Quantifying Internal Training Load in Adolescent Distance Runners
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Borg's percieved exertion and pain scales United States: Human Kinetics
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Borg G. Borg's percieved exertion and pain scales United States: Human Kinetics, 1998.
Relation between individualized training impulses and performance in distance runners
  • V Manzi
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Manzi V, Iellamo F, Impellizzeri F, D'Ottavio S, Castagna C. Relation between individualized training impulses and performance in distance runners. Med Sci Sports Exerc, 2009; 41:2090-2096.
summated heart rate zone method; TRIMPL, Lucia's training impulse; sRPE, session rating of perceived exertion; dRPE-L, differential rating of perceived exertion for leg exertion; dRPE-B, differential rating of perceived exertion for breathlessness; 0, time-point 0 min; 15, time-point 15 min
  • Edwards Trimpe
TRIMPE, Edwards' summated heart rate zone method; TRIMPL, Lucia's training impulse; sRPE, session rating of perceived exertion; dRPE-L, differential rating of perceived exertion for leg exertion; dRPE-B, differential rating of perceived exertion for breathlessness; 0, time-point 0 min; 15, time-point 15 min; 30, time-point 30 min.