European Journal of Sport Science

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Influence of exercise intensity and duration on perceived exertion in adolescent Taekwondo athletes Monoem Haddad , Anis Chaouachi , Del P. Wong , Carlo Castagna , Olivie Hue , Franco M. Impellizzeri & Karim Chamari To cite this article: Monoem Haddad , Anis Chaouachi , Del P. Wong , Carlo Castagna , Olivie Hue , Franco M. Impellizzeri & Karim Chamari (2014) Influence of exercise intensity and duration on perceived exertion in adolescent Taekwondo athletes, European Journal of Sport Science, 14:sup1, S275-S281, DOI: 10.1080/17461391.2012.691115 To link to this article: https://doi.org/10.1080/17461391.2012.691115

Published online: 31 May 2012.

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European Journal of Sport Science, 2014 Vol. 14, No. S1, S275
S281, http://dx.doi.org/10.1080/17461391.2012.691115

ORIGINAL ARTICLE

Influence of exercise intensity and duration on perceived exertion in adolescent Taekwondo athletes

MONOEM HADDAD1, ANIS CHAOUACHI1, DEL P. WONG2, CARLO CASTAGNA3, OLIVIE HUE4, FRANCO M. IMPELLIZZERI5, & KARIM CHAMARI1,6 1

Tunisian Research Laboratory ‘Sports Performance Optimisation’, National Center of Medicine and Science in Sports (CNMSS), Tunis, Tunisia, 2Faculty of Management and Hospitality, Technological and Higher Education Institute of Hong Kong (THEi), 3Football Training and Biomechanics Laboratory, Italian Football Federation (FIGC), Technical Department, Coverciano (Florence), Italy, 4Laboratory ACTES, Department of Physiology, University of the French West Indies, Guadeloup, *CAREST (CAribbean network of REsearchers on Sickle cell disease and Thalassemia), 5Research Centre for Sport, Mountain and Health, University of Verona, Rovereto, Italy, and 6University of Manouba, ISSEP Ksar Said

Abstract The aim of this study was to examine the influence of exercise intensity and session duration on rating of perceived exertion (RPE) in adolescent Taekwondo (TKD) athletes. Twelve male youth competitive TKD athletes, aged between 13 and 18 years took part in this study. Training data (368 individual sessions) were collected during the 12 weeks of the precompetitive TKD season. Daily training load was calculated using the heart rate and the session-RPE. Exercise intensity was also classified in five zones [i.e. 50
60%, 61
70%, 71
80%, 81
90% and 91
100% of maximal heart rate (HRmax)] and the time spent in each zone was expressed as percentage of total session time. The analysis of variance showed a significant main effect for zone (pB0.001) with most of the time (69%) spent at intensities between 61 and 90% of HRmax, and only 10% spent above 91% (mean differences compared to the other zones ranging from
6.6% versus zone 1 to
14.8% versus zone 3; pB0.0001). The individual correlation between session-RPE and HR-based methods were moderate to large. The stepwise multiple regression showed that RPE was influenced mainly by the time spent in the high intensity zone that explained 22.1% of the variance in RPE. Session duration accounted for only an additional 3.2%. The results suggest the time spent at high-intensity (i.e. between 91 and 100% HRmax) and only marginally the session duration influences the RPE referred to the whole training session. This seems to confirm that the determination of the TL multiplying the RPE and session duration is acceptable.

Keywords: Martial art, youth, RPE, heart rate, training load, high intensity

Introduction Taekwondo (TKD) has evolved from a traditional martial art into a modern competitive combat sport. The transition to Olympic sport has increased the physical demands on athletes during competition (Chiodo et al., 2011; Heller et al., 1998). Previous studies have used the heart rate (HR) and lactate for quantifying the exercise intensity during TKD training and competition (Bouhlel et al., 2006; Bridge, Jones, Hitchen, & Sanchez, 2007). Besides, it has

been recently shown that a method based on the rating of perceived exertion (RPE) is a valid approach in order to quantify the exercise intensity during whole TKD training sessions (Haddad et al., 2011). The session-RPE method has been developed by Foster et al. (2001) and is calculated by multiplying the RPE by session duration. The RPE is referred to the whole training session. Thus allow obtaining a single training load value taking into account both

Correspondence: Monoem Haddad, Tunisian Research Laboratory ‘‘Sports Performance Optimisation’’, National Center of Medicine and Science in Sports (CNMSS) Ave Med Ali Akid, 1004 El Menzah, Tunis, Tunisia. E-mail: [email protected] # 2013 European College of Sport Science

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exercise duration and intensity (Foster et al., 2001). This method has been proven by correlating the session-RPE with the training load determined using HR-based methods, which are commonly considered valid indicators of exercise intensity (Foster et al., 2001; Haddad et al., 2011). Moderate to large correlations have been found for both steady-state (Foster et al., 2001; Foster et al., 1995) and intermittent exercises (Foster et al., 2001; Impellizzeri, Rampinini, Coutts, Sassi, & Marcora, 2004) in different types of sports and athletes in various age categories (Foster et al., 2001; Haddad et al., 2011; Impellizzeri et al., 2004). Although the use of the session-RPE method and the studies examining its validity is growing, only few investigations have examined the effect of exercise duration and exercise intensity distribution on RPE (Green et al., 2009). This information is important given the session-RPE is obtained multiplying the RPE with the session duration. This calculation implies that the RPE referred to the whole session is not influenced by its duration. Green et al. (2009) compared RPE among treadmill trials (TM) at a clamped workload with various durations (i.e. 20, 30 and 40 min). They showed that no significant differences among TM20, TM30 and TM40 for mean HR or [La] which isolated effects of duration on RPE. Primary results of that study indicate that the effects of the exercise duration on RPE are minimal. Green et al. (2009) concluded that ‘duration’ as a mediator of RPE is either weak or nonexistent with intensity serving as a stronger mediator. Therefore, RPE is influenced more by intensity than duration (Green et al., 2009). The previous studies involving intermittent or constant-load exercises used average measures as intensity criterion (Foster et al., 2001; Green et al., 2009). Consequently, a definitive inference on the selective effect of intensity and duration on training RPE is yet to be drawn. Information in this regard would be of great interest for those sport activities that involve variations in exercise intensity during the training session. Therefore, the aim of this study was to examine the influence of exercise intensity distribution (i.e. time spent in selected training HR zones) and session duration on RPE referred to the whole session in adolescents TKD athletes.

Methods Participants Twelve male young competitive TKD athletes, aged between 13 and 18 years, took part in this study. The athletes’ physical characteristics are presented in Table 1. The sample included five 2nd Poom grades, four 1st Dan grades and three 2st Dan grades. All athletes had four to seven years of experience with participation in national and international competitions. Prior to the study, athletes received a letter with written information about the study design, the experimental risks and a request for consent from the parents to allow their children to participate in the study. The study was conducted according to the Declaration of Helsinki and the approved by the Clinical Research Ethics Committee of the National Centre of Medicine and Science of Sports of Tunis (CNMSS). All athletes were fully accustomed with the procedures used in this research.

Procedures Field data collection. Training data were collected during the 12 weeks of the pre-competitive season (from November to January). All participants were actively involved in the same training programme. During the 12 weeks of the study, athletes trained 4 days per week, 90 min in each session. The amount of training sessions completed by each participant within the 12 weeks of training was differed between athletes due to the participation of some athletes to the national team training camp without competition. It is important to note that the convened international athletes were not the same in each national camp, hence the difference of number of sessions performed by each athletes. Athlete had to have at least 20 monitored training sessions in order to be included in the study. The training programme was planned by the coach of the team. The researchers did not alter the original training programme. Training intensity during each TKD training session was recorded using the Polar Team System HR monitors (Polar Electro Oy, Kempele, Finland), with HR recorded every 5 seconds. After each training session, HR data were downloaded into a portable PC using Polar Advantage Software (Polar Electro Oy, Finland) and subsequently exported and

Table 1. Characteristics of the athletes (mean  12) Age (Years) 15.291.5 a

Body mass (Km) Height (m) 55913

Maximal aerobic speed.

BMI

Vmaxa

1.6090.11 21.192.6 18.691.1 Km/h

Estimated VO2max (ml min 1 kg 1)

HRmax (bmin 1)

Resting HR (b min 1)

60,3392.42

20095

5698

Influence of exercise intensity and duration on perceived exertion analyzed using the Excel software program (Microsoft Corporation, USA). Training programme. During the typical training, the beginning of Tuesday and Wednesday sessions were designed to focus on conditioning. The heaviest cardiovascular training was usually completed during the Tuesday sessions. During the Wednesday sessions, the first 30 min of training sessions were generally dedicated to speed development consisting mainly of sprint and plyometric training exercises. The following remaining part of sessions were devoted to technical and tactical TKD-training that included a combination of the following typical activities: basic techniques, technical combinations, predetermined sequence of movements (forms), breaking techniques, self-defence techniques, step sparring, sparring (skill) drills and free sparring. Before commencement and at the end of preseason training, all athletes were tested using the YoYo Intermittent Recovery test Level 1 (Krustrup et al., 2003). During this test, the highest average value from three consecutively recorded HRs (15 seconds) was considered as maximal HR (HRmax). The resting HR was assessed with athletes laying down on a bed for 10 minutes at 5:30 am. The resting HR value corresponded to the minimal HR observed during this 10-min period. Training load indices determination. Daily training load was calculated using an RPE-based (i.e. session-RPE) (Foster et al., 2001) and two HR-based methods (i.e. Banister’s TRIMP and Edwards’ TL) (Banister, 1991; Edwards, 1993). The session-RPE method training load is calculated by multiplying the training duration in minutes by the mean training intensity. The training intensity is measured quantifying the RPE using a modification of the Category-Ratio scale (Foster et al., 2001). The RPE was collected approximately 30 min after each TKD session. All athletes had been well familiarised to this scale before starting the study (2 years using session-RPE). For quantifying the training load using the HR, Banister’s TRIMP and Edwards’ TL were used. The Banister’s TRIMP is calculated using training duration, HRmax, resting HR and average HR during the exercise session. This method tries to weight the duration using an exponential factor with the following formula: TD  HR  ð0:64e1:92HRreserve Þ In which TD is the effective training session duration expressed in min and HRreserve is determined with the following equation: ½ðHR average  HR rest Þ=ðHR max  HR rest Þ:

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The Edwards’ TL method is a modification to the calculation of training impulses that facilitates the quantification of interval training (Edwards, 1993). This HR-based method was also used as a criterion measure of TL in various studies (Foster et al., 2001; Haddad et al., 2011). The accumulated duration (minutes) spent in each of five HR zones was calculated (i.e. 50
60%, 61
70%, 71
80%, 81
90% and 91
100% of HRmax) and then multiplied by a multiplier factor for each zone (50
60% 1, 61
70%  2, 71
80% 3, 81
90% 4 and 91
100% 5). The results were then summated (Edwards, 1993). Training intensity distribution and duration session. The exercise intensity distribution was calculated as the time spent in five zones: 50
60%, 61
70%, 71
80%, 81
90% and 91
100% of HRmax). The time spent in each zone was expressed in percent of total session duration. The duration in minutes of each session included the intra-session recovery periods. This intensity classification was proposed by Edwards (1993) to monitor training intensity where arbitrary intensity measures (i.e. 1, 2, 3, 4 and 5) were referred to the five zones, respectively. This method was demonstrated convergent with Banister’ TRIMP (Haddad, Chaouachi, Castagna, Wong del, & Chamari, 2012). Statistical analyses The results are presented as mean9SD. The normal distribution of the data was checked using the Kolmogorov-Smirnov test. After confirming normal distribution, Pearson product moment correlation coefficient ‘r’ was calculated to examine the relationships between session-RPE and Banister’ TRIMP. Pearson’s r was also calculated between the% of time spent in each intensity zone and each of the two methods motioned above (i.e. session-RPE and Banister’ TRIMP). The magnitude of the correlations was interpreted using the modified scale by Hopkins (2000): r B0.1, trivial; 0.1
0.3, small; 0.3
0.5, moderate; 0.5
0.7, large; 0.7
0.9, very large; 0.9, nearly perfect; and one perfect. To examine the predictors of RPE referred to the TKD training session (dependent variable) we used a stepwise multiple regression entering the time spent in the 5 HR zones and the session duration as independent variables. Collinearity tolerance statistics were calculated to determine the correlation between the predictor variables. The collinearity tolerance statistics were used to determine when a predictor is highly correlated with one or more of the other predictors. If the predictor variables are highly correlated with each other, the influence of one

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M. Haddad et al. 10% spent above 91% with mean differences compared to the other zones ranging from
6.6% (95%CI from
8.3 to
4.9%) compared to zone one and
14.8% (95%CI from
16.4 to
18.2%) versus zone three (p B0.0001). All the differences between the time spent in the five zones were significant (pB0.0001) with only the difference between zone two and four close to significance (1.4%, 95%CI from
3.0 to 0.3%; p 0.10). Small correlations were observed between percentage of time spent in zone five and the two methods for quantifying TL, respectively, used in the present study (pooled n 369; Session-RPE, r 0.24, p B0.05; 95%CI 0.14
0.36 and Banister’ TRIMP, r 0.30 pB0.05; 95%CI 0.21
0.39). The model generated using the stepwise multiple regression only included two variables (time spent in zone five and duration) and explained 24.9% (adjusted) of the variance in TKD session-RPE. The first variable entered in the model was the time spent in the zone 5 (high intensity) explaining 21.9% (adjusted) of variance in session-RPE. The second variable was session duration, explaining additional 3.2% of the variance. Significant difference was observed in YYIRTL1 performed before and after the experimental period (t 
6.66; p B0.001). The corresponding HRmax did not change during the study period (p0.05).

variable on the response variable could not be separated from the other predictor variable. Therefore any variable that had a tolerance level of less than 0.10 was not included in the model. One-way repeated measures analysis of variance (ANOVA) was used to examine differences in time spent in the five intensity zones determined in relation to HRmax. Sphericity was examined with the Mauchly’s Test and violation taken into account using Huynh-Feldt correction of degrees of freedom. When a significant F-value was found, post-hoc Bonferroni’s test was applied. The differences between the two Yo-Yo Intermittent Recovery tests Level 1 (YYIRTL1) performed before and after the experimental period and corresponding HRmax were analyzed using paired t-test. Statistical significance was set at p B0.05. Calculations were performed with SPSS statistical software package (Version 13 for Windows; SPSS, Inc., Chicago, USA).

Results The session-RPE, Banister’s TRIMP and Edwards’ TL were calculated from 368 individual training sessions. Significant relationships were found between individual session-RPE and HR-based methods (Banister’s TRIMP, r values from 0.53 to 0.86; Edwards’ TL, r values from 0.58 to 0.79, moderate to large effect; p B0.001, Table 2). Figure 1 shows the intensity distribution of TKD training session. The mean RPE and session duration from all individual training sessions were 3.591.28 and 73.44920.36 min, respectively. A moderate correlation was observed between RPE measures and time spent in zone 5 (r 0.50; 95% CI 0.42
0.57). The ANOVA (after Huynh-Feldt correction) showed a significant main effect for zone (pB0.001). Most of the time (69%) was spent at intensities between 61 and 90% of HRmax, and only

Discussion To our knowledge for the first time, the present study investigated the influence of different intensity ranges and session duration on training RPE and session-RPE in adolescents TKD athletes. Specifically, we determined the correlations between RPE, session-RPE, session duration, Banister’ TRIMP and a common classification of intensities (i.e. 50
60%, 61
70%, 71
80%, 81
90% and 91
100% of HRmax). Results showed the main

Table 2. Individual correlations between session-RPE and HR-based methods (i.e. Banister’s TRIMP and Edwards’ TL CI (95%)

CI (95%)

Subjects

n

Banister’s TRIMP

Lower limit

Upper limit

Edwards’ TL

Lower limit

Upper limit

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12

40 31 16 42 41 39 32 23 29 22 19 34

0.64** 0.71** 0.86** 0.78** 0.70** 0.79** 0.73** 0.72** 0.53** 0.76** 0.57** 0.79**

0.41 0.50 0.64 0.62 0.49 0.64 0.52 0.44 0.20 0.50 0.154 0.624

0.64** 0.855 0.95 0.873 0.83 0.88 0.86 0.87 0.75 0.89 0.81 0.89

0.69** 0.72** 0.77** 0.58** 0.79** 0.67** 0.75** 0.73** 0.69** 0.76** 0.59** 0.78**

0.49 0.50 0.36 0.34 0.64 0.45 0.55 0.46 0.44 0.50 0.18 0.59

0.83 0.86 0.90 0.75 0.88 0.81 0.87 0.88 0.84 0.90 0.82 0.88

**p B0.001.

Influence of exercise intensity and duration on perceived exertion

Figure 1. Percent of HR intensity distribution during TKD training.

effect of intensity and duration on training RPE in TKD athletes.

Validity of session-RPE with the variance influences on RPE In the present investigation, moderate to large individual correlations were found between sessionRPE and HR-based methods (Banister’s TRIMP, r values from 0.53 to 0.86; Edwards’ TL, r values from 0.58 to 0.79). The magnitude of correlations of the current study are similar to those found between session-RPE method and the HR-based methods in steady-state and more aerobic conditions such as endurance athletes (r 0.75
0.90) (Foster, 1998) and swimmers (r values from 0.55 to 0.92) (Wallace, Slattery, & Coutts, 2009), and also in intermittent activities such as soccer (r values from 0.50 to 0.85) (Impellizzeri et al., 2004). The individual correlations observed in the present study between sessionRPE and Banister’ TRIMP confirmed the construct validity of session-RPE found in our previous study in young TKD athletes (r values from 0.56 to 0.90) (Haddad et al., 2011). The present study shown a new contribute on RPE (i.e. high intensity zone) that can influence the self rating and then session-RPE.

RPE and high intensity zone Significant individual correlations were reported between RPE and time spent in zone five, demonstrating the influence of the high intensity zone on perceived exertion. Moreover, the pooled correlation confirmed the previous result and proved that the relationship between RPE and all predicting variables (i.e. each intensity zone and session duration) was stronger when considering the percentage of time spent in high intensity zone (91
100% HRmax). This result demonstrates that adolescent TKD athlete is influenced by the high intensity zone in rating his perceived exertion.

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However, correlation analysis showed that this intensity zone explained approximately 22.1% of the variance in RPE following TKD training with adolescent athletes and 74.7% of the RPE could not be explained by intensity and duration. This result strengthened the concept of creating a training load score based on RPE (a reflection of intensity) and duration (another factor influencing training load, yet independent of RPE). The present study confirms that factors other than session-duration and intensity may contribute to adolescent athlete’ RPE during TKD training. Psycho-biological factors such as metabolic acidosis, ventilatory drive, respiratory gases, catecholamines, endorphins and body temperature are also related to perception of effort, however, the relationship of these factors to RPE during high-intensity, intermittent exercise is yet to be determined (Robertson & Noble, 1997). Although these factors were not measured in the present study, it is likely that these could also account for some of the additional variance in RPE not explained by duration and intensity given that these variables significantly changed during TKD training also. Effect of session-duration on RPE The introduction of session duration in the multiple regression model accounted for only an additional 3.2% of the explained variance for RPE. This finding clearly demonstrated that training intensity had an effect on RPE in young athletes performing TKD while session duration (B90 min) had a marginal role. These results are similar to previous studies examining the relationship between session duration and RPE measures (Foster et al., 2001; Green et al., 2009; Green et al., 2007). In their studies, they indicated that duration does not provide a strong affect on session-RPE. Green et al. (2009) concluded that duration as a mediator of RPE was either weak or non-existent with intensity serving as a stronger mediator. In addition, no significant differences were found for RPE among trials differing in duration (20 min, 30 min and 40 min) but at a clamped individualised workload approximating 70% VO2max (Green et al., 2009). While a mild, yet noticeable drift occurred for acute markers of intensity, analyses showed that HR and [La] were not significantly different among trials verifying a similar metabolic load and overall similar disruption in internal environment. Similar physiological responses consequent to workload permitted isolation of exercise duration as a factor potentially mediating Session-RPE (Robertson & Noble, 1997). According to the results of the present and previous studies, RPE is coupled with high intensity more than duration or other intensity zones (Foster et al.,

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M. Haddad et al.

2001; Green et al., 2009; Green et al., 2007). Nevertheless, session duration may be a stronger mediator in situations involving inadequate recovery from a competition or a series of training bouts, or under conditions of sub-optimal glycogen restoration (Green et al., 2009). In addition, it is possible that duration can play a major role when the exercise session is long enough (at the least 90 min) for either muscle or liver glycogen depletion to exert an indirect effect (increasing central motor command activity and hence perception of effort). However, these possibilities have not been examined and need further studies. A limitation of the present study is that blood lactate concentration was not taken into account during TKD training to determine the correlation of RPE and blood lactate concentration. Coutts, Rampinini, Marcora, Castagna, and Impellizzeri (2009) have shown that the combination of HR and blood lactate concentration predicts RPE more accurately than either measure taken alone. This might better explain higher correlation coefficients between zone five and RPE. Summary In summary, results suggest that exercise duration does not significantly impact RPE during TKD session. RPE appears more responsive to high intensity (91
100% HRmax) zone than other intensity zones. With minimal roles of session duration on RPE and high intensity zone on Session RPE, the concept of creating a training load score based on RPE (a reflection of intensity) and duration (another factor influencing training load, yet independent of RPE) is strengthened. An appealing aspect of this approach is the convenience afforded by RPE and the lack of need for extensive monitoring of objective and physiological variables [HR, (La)] which can be tedious (due to hygiene and equipment issues) and unlikely in applied settings such as daily training sessions. Additional work is warranted to definitively identify factors associated with session RPE in various exercise paradigms. Coaches and scientists should be aware of the influence of high intensity exercise (i.e. zone five) on the RPE of a given training session. This should be further investigated to allow coaches to better schedule their training sessions with respect to their training goals. Acknowledgements The authors acknowledge the young TKD athletes involved in this investigation. Regard to Mme Souhir Fhal for her collaboration in this paper. This study was financially supported by the Tunisian Ministry of Scientific Research.

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