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Pattern of developing the performance template

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Carl Foster at University of Wisconsin - La Crosse
Carl Foster
K J Hendrickson
K J Hendrickson
K J Hendrickson
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Karissa L Peyer at University of Tennessee at Chattanooga
Karissa L Peyer
B Reiner
B Reiner
B Reiner
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Abstract and Figures

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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Pattern of developing the performance template
C Foster,
1
K J Hendrickson,
1
K Peyer,
1
B Reiner,
1
J J deKoning,
2
A Lucia,
3
R A Battista,
1
F J Hettinga,
2
J P Porcari,
1
G Wright
1
1
Department of Exercise and
Sport Science, University of
Wisconsin-La Crosse, La Crosse,
Wisconsin, USA;
2
Research
Institute MOVE, VU University-
Amsterdam, Amsterdam, The
Netherlands;
3
Department of
Exercise Physiology, European
University of Madrid, Madrid,
Spain
Correspondence to:
Professor C Foster, Department
of Exercise and Sports Science,
University of Wisconsin-La
Crosse, La Crosse, WI 54601,
USA; foster.carl@uwlax.edu
Accepted 7 December 2008
Published Online First
5 January 2009
ABSTRACT
Background: 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.
Aims: 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).
Methods: 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.
Results: 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.
Conclusions: 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.
The pattern of power output during self-paced
exercise has been suggested to be regulated in an
anticipatory manner, the ‘‘anticipatory feedback-
RPE model.’’
1
This pattern has been observed in
our previous results
2–5
and elsewhere,
6–10
is resistant
to change
11
and, when forced to change, is
associated with performance decrements.
12 13
During repeated sprint exercise, this anticipated
regulation is less evident
14
Other studies have
shown that humans adjust muscle power output
during prolonged exercise based on sensory feed-
back derived from progressively fatiguing muscles,
irrespective of previous competitive experience.
15–18
Given the importance of the apparently prepro-
grammed performance template to the anticipa-
tory feedback RPE model,
1
there are surprisingly
limited systematically collected data regarding how
this template develops, how it relates to practice
patterns and the number of trials required for a
stable template to develop. Accordingly, the
purpose of this study was to observe the pattern
of power output and performance with successive
exercise bouts in different groups of well-trained
individuals, during different types of exercise, and
with reference to the effects of training.
METHODS
All subjects provided written informed consent,
and the individual protocols were approved by the
university human subjects committee. In all
studies the subjects were very fit via other
elements of their lifestyle (.5 h/week of aerobic
exercise) but uniformly had little experience with
cycling or rowing time trials. Data on the subjects
are provided in table 1.
The study was conducted in four parts. In Part
A, the response to six 3 km cycle time trials was
observed with reference to the pattern of power
output. In Part B, the responses to three 2 km
rowing ergometer trials was observed. In Part C,
the effect of rowing practice on the power output
pattern during four 2 km rowing ergometer trials
was observed. In Part D, the response of recrea-
tional level cycle competitors was observed during
three 10 km cycling time trials.
In Part A, subjects performed incremental cycle
ergometer exercise to document fitness, habituate
the subjects and determine whether fitness
improved as a result of the repeated time trials.
The exercise protocol involved 3 min at a power
output of 25 W +25 W per minute until the subject
could not maintain a pedalling rate within 60–
90 rpm. Respiratory gas exchange data were
measured using open-circuit spirometry (AEI,
Pittsburgh, Pennsylvania). Ventilatory (VT) and
respiratory compensation (RCT) thresholds were
determined according to standard methods.
19
Heart
rate (HR) was measured using radio telemetry.
Between incremental tests, the subjects performed
six 3 km cycle time trials on an electronically
braked racing cycle ergometer (Racer Mate, Seattle,
Washington) with 48–96 h of light exercise
between ttials. Prior to each time trial (in this
and all other parts of the study), the subject
performed a standard 10 min warm-up, with the
first 2 min at 25 W, the next 3 min at a power
output calculated to require ,75% of the VO
2
at
VT and the last 5 min at a power output calculated
to require ,90% of the VO
2
at VT. Following the
warm-up, the subject rested for 2 min before
beginning the time trial. To prevent excessive
starting forces on the ergometer frame, 30 s before
the beginning of the time trial the subject began
pedalling at 25 W. At the beginning of the time
trial, the subject was instructed to ‘‘begin racing’’
with the only instruction being to complete the
3 km as quickly as possible. During the trial, the
subject had feedback from the ergometer display,
Original article
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including velocity, power output, HR and distance completed.
During the trial, the subject rated their level of exertion using
the category ratio (0–10) Rating of Perceived Exertion scale
20
after each 300 m. After the trials, the data were averaged based
on the time required to complete each 300 m (eg, 10% of total
distance).
In Part B, the subjects performed an incremental test on a
wind-braked rowing ergometer (Concept II, Morrisville,
Vermont) for characterisation. The initial power output was
0.5 W 6body weight in kg, and was incremented by this
amount each minute until fatigue. Respiratory gas exchange
was performed using open-circuit spirometry as described
above. Subsequently, each subject performed three 2 km time
trials on the rowing ergometer, with 48–96 h between trials.
Other than to finish as quickly as possible, the subjects were
given no instructions. Each subject was informed of their
preceding best performance and had full access to information
about distance completed and momentary pace (eg, 500 m split)
from the ergometer display. The data were averaged and
analysed every 200 m (eg, 10% distance).
In Part C, the subjects performed incremental testing for
habituation and characterisation, as in Part B. Subsequently,
each subject performed two 2 km time trials on the rowing
ergometer, with no instructions other than to finish in the
shortest possible time. During the next month, the subjects
performed two rowing training sessions per week (total = 8),
with one training session being continuous and one interval,
with a total distance of 4–6 km. Specific instructions about
rowing technique were not provided. However, the subjects
were informed that the goal of the training was to allow them
to improve their performance for subsequent time trials.
Following this training, they performed two additional 2 km
rowing time trials. The subjects had access to their previous
performances, momentary distance completed and momentary
pace from the ergometer display. Data were averaged every
200 m.
In Part D, the subjects performed a preliminary incremental
exercise as in Part A. Subsequently, they performed three 10 km
time trials on an electrically braked cycle ergometer (Racer
Mate, Seattle, Washington). Other than the instruction to
finish as rapidly as possible, no instructions were provided,
although the subject knew their maximal power output from
the preliminary test and had access to distance, velocity, power
output and HR, just as they would during competition. Blood
lactate concentration was measured in fingertip capillary blood
Table 1 Characteristics (mean (SD)) of the subjects
Series Gender Age (years) Height (cm) Mass (kg) VO
2max
(l/min)
A Male 26.8 (3.8) 187 (8) 83.3 (3.3) 4.77 (0.26)
Female 21.3 (0.5) 159 (2) 52.3 (1.71) 2.15 (0.29)
B Male 23.5 (4.1) 180 (11) 79.5 (4.4) 4.00 (0.54)
Female 21.8 (2.0) 162 (5) 62.3 (6.8) 2.40 (0.40)
C Male 24.6 (3.8) 183 (5) 82.5 (3.6) 4.08 (0.60)
Female 23.9 (3.2) 168 (3) 54.0 (2.4) 2.54 (0.34)
D Male 39.2 (10.7) 179 (6) 81.1 (5.0) 4.30 (0.68)
Female 35.0 (11.3) 167 (11) 76.2 (21.2) 3.34 (0.75)
Figure 1 Changes in performance time, normalised to the first
performance in the four series of experiments. In Part C, only the first
two rowing time trials were included, as there was an intervening period
of training between trials 2 and 3.
Figure 2 Serial pattern of power output (top) and RPE (bottom) during
the six trails of Part A. Note the progressively higher power output during
the first 600 m of the ride during the successive trails and the
progressively higher RPE at the same point in the ride during successive
trials.
Original article
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(YSI Sport, Yellow Springs, Ohio) before the beginning of the
time trial (after the warm-up) and at the completion of each
2 km of the time trial. Other data were averaged for every 1 km
of the ride (eg, 10% of the total distance).
Statistical analyses were performed for all studies using
repeated-measures ANOVA. Post-hoc analyses were performed
when indicated by ANOVA using the Tukey procedure.
Statistical significance was accepted when p,0.05.
RESULTS
In Part A, the six 3000 m cycle trials were completed in 337 (SD
63), 321 (61). 317 (63), 310 (58), 306 (57) and 303 (56) s,
respectively. Except for T5 vs T6, each trial was significantly
faster than the preceding one. Together with the time results of
the other parts of the study, performance time normalised to
the first performance is presented in fig 1. The sequential
pattern of total power output and RPE in Part A is presented in
fig 2. There was a significant trials6distance interaction for
power output. This was characterised by a progressively greater
power output during the first half of successive trials, with non-
significant differences during the last half of each trial. During
the first 1 km, there was a perfect sequential pattern with each
subsequent trial having a higher power output than during the
preceding trial. In concert with this, there were no significant
differences in total power output during the last 300 m of any
trial. There was a significant distance6trials interaction for RPE.
Although less clear than for power output, the differences can
be characterised as a lower RPE during the beginning and middle
parts of the early trials, with small but still statistically
significant differences in the terminal RPE (8.4 (0.4), 8.6 (0.5),
8.8 (0.6), 8.8 (0.9), 9.1 (0.6) and 9.3 (0.6), respectively).
In Part B, the three 2 km rowing trials were completed in 583
(84), 543 (68) and 532 (68) s, respectively. Each sequential
performance was significantly faster than the preceding one.
The sequential pattern of power output per 200 m is presented
in fig 3 and was characterised by a higher power output in the
first half of successive trials, with minimal differences during
the last portion of the trial. The RPE at the conclusion of
successive trials was 5.8 (1.3), 6.8 (1.6) and 6.9 (1.4),
respectively, with the terminal RPE of T1 significantly less
than of T2 and T3.
In Part C, the four 2 km rowing ergometer trials were
completed in 606 (144), 583 (118), 546 (88) and 540 (83) s,
respectively. The time difference between all trials except T3
and T4 was significant. The pattern of power output integrated
every 200 m over successive trials is presented in fig 4 and was
characterised by progressively higher power output during the
early part of successive trials. The RPE at the conclusion of
successive trials was 6.0 (1.2), 6.6 (1.7), 7.5 (1.4) and 7.7 (1.3),
respectively, with the RPE in T1 significantly less than T2, and
T1 and T2 significantly less than T3 and T4. There was a
significant effect across the training period, but with minimal
differences in pacing strategy between T3 and T4.
In Part D, the three 10 km cycle time trials were completed in
1059 (96), 1022 (89) and 1006 (84) s, respectively. Each trial was
significant faster than the preceding one. The pattern of power
output, HR, RPE and blood lactate is presented in fig 5 and is
characterised by a higher power output earlier in sucessive trials,
with no differences in terminal power output. From the
midpoint of T1 until the finish, the RPE was lower than in
T2 and T3. The terminal RPE was lower in T1 (8.5 (1.4)) than in
T2 (9.3 (0.8)) and T3 (9.7 (0.7)).
DISCUSSION
The main finding of this study is the similarity of pattern of
acquiring a consistent pacing pattern in four groups of well-
trained non-athletes, using two different ergometric modes. In
the early trials, the initial power output was reduced during the
first portion of the trial, with the power output during the
terminal portions of the trial being remarkably consistent.
Subsequent trials were marked by a progressively more
aggressive early pace, with evidence that an essentially stable
performance template was achieved by the third or fourth trial.
The pattern of power output during all studies normalised to
the mean power output evolved from a low early power and
high power output in the terminal portion of the time trials, in
the combined results of the first trial, to a higher power during
the early portion with more moderate terminal power output
(fig 6). While not identical to the very high early power output
pattern observed in high level competitive cyclists and speed
skaters
2–4
during events of comparable duration, it was clear that
the pattern was evolving in that direction.
Supporting the observation of reductions in power output
during beginning portions of the first trials was evidence that
the RPE increased more slowly during the first part of the first
Figure 3 Serial pattern of power output during the three rowing time
trials in Part B. Note the higher power output during the early portion of
the trial during successive trials, with comparatively small differencesin
power output during the terminal portion of the trial.
Figure 4 Serial pattern of power output during the four rowing time
trails in Part C. Note the higher early power output in successive trails
with minimal differences in power output during the terminal portion of
the trail.
Original article
Br J Sports Med 2009;43:765–769. doi:10.1136/bjsm.2008.054841 767
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time trials and that the RPE at the end of the time trials was
systematically lower. This trend was further reflected by the
pattern of blood lactate accumulation in Part D. Collectively, it
can be argued that the subjects were ‘‘holding back’’ during the
early trials, and then progressively increased their effort as they
became convinced that the time trial could be completed with a
particular strategy without negative consequences. This is not
unlike the slower speed of completion, designed to reduce errors,
typically observed in motor learning tasks.
21
Although the subjects were well trained generally, there was
no evidence of any training effect during cycling (peak power
output in part A was 281 (108) W before T1 and 288 (116) W
after T6), and there was a significant improvement in
performance across a period of training during the rowing
ergometer study (Part C). However, this was reasonably
attributable to the effects of practice on this specific ergometric
mode and seemed to be associated with the same trend toward a
modified pacing strategy (eg, higher early power output) in
successive trials.
In summary, the data from the current series of four studies
suggest that there is a learning effect during the performance of
successive high-intensity time trials. Although the largest effect
is during the first three trials, even after several trials these well-
trained subjects do not achieve the pattern of power output
typically displayed by athletes. This suggests that the pre-
exercise template that is a central feature of the ‘‘anticipatory
feedback-RPE model’’ is a non-constant feature and may require
some time to fully develop. In this regard, it would be of interest
to observe the way in which athletes spontaneously improve
their performance, and to determine whether performance
improvements are more attributable to increases in total power
output or to better optimisation of the pattern of power
distribution.
Figure 5 Serial pattern of power output, heart rate, REP and blood lactate concentration in Part D. Note the progressively higher values, particularly of
power output and blood lactate concentration during the early portion of the ride during successive trails.
Figure 6 Serial pattern of power output, normalised to the mean power
output of the entire time trial in the first and last trials of all studies
combined, in comparison with the pattern of power output in athletes
studied in our laboratory.
2–4
What this study adds
The pattern of developing the performance template appears to
follow a predictable pattern during several repetitions of time trial
exercise, characterised by a higher rate of energy expenditure
earlier in the event.
What is known on this topic
The pattern of energy expenditure during time trail exercise
appears to follow a predetermined template, which is modified by
a variety of sensory feedback mechanisms.
Original article
768 Br J Sports Med 2009;43:765–769. doi:10.1136/bjsm.2008.054841
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Funding: KJH and KP were recipients of Dean’s Summer Research Fellowships at the
University of Wisconsin-La Crosse. BR received a research grant from the Graduate
Council of the University of Wisconsin-La Crosse.
Competing interests: None.
Ethics approval: Ethics approval was provided by University of Wisconsin-La Crosse.
Patient consent: Obtained.
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Original article
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doi: 10.1136/bjsm.2008.054841
5, 2009 2009 43: 765-769 originally published online JanuaryBr J Sports Med
C Foster, K J Hendrickson, K Peyer, et al.
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... Evidence suggests that the overall pacing strategy is adjusted during prolonged exercise to prevent early exhaustion brought on by a malfunction of one or more physiological systems. Therefore, it is asserted that pacing strategies are indicators of the physiological regulation that underlies them and that pacing strategies are influenced by adjustments in muscle activation that are anticipatory in nature, based on afferent data from a variety of physiological systems [15][16][17]. Due to the low mechanical efficiency of swimming, the correct administration of the available energy is also highly dependent on technical abilities [18]. However, in competition, the athlete's surroundings constantly and simultaneously present various external stimuli, requiring decision-making regarding where and when to allocate their accessible energy resources. ...
... The ability to effectively allocate energy develops in relation to an individual's cognitive and physical characteristics and is dependent on the amount of prior specific experience [54][55][56][57]. The ideal pacing technique can thus be acquired by a wealth of training and competition experience [16,18,58,59]. Since an ideal ratio between stroke rate and stroke length is necessary to maintain the pace throughout the race, key variables like stroke rate, stroke count, split times, and rating of perceived exertion are probably crucial training tools to optimise the development of pacing skills [50,[60][61][62][63][64][65][66][67]. ...
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Pacing strategy refers to the distribution of effort and speed throughout the race to achieve optimal performance. This study aims to understand whether the choice of pacing strategy in swimming depends on the length of competitions and how sex, age, and performance level influence this strategy. Participants were the finalists of the 800 m and 1500 m freestyle events at the elite and junior world championships in 2022–2023. Race outcomes and pacing parameters were compared between the two distances and across different groups of swimmers. Swimmers in both distances did not break world records. Pacing strategy generally followed a U-shape with significant differences in the frequency and duration of speed changes between the two distances. The 800 m exhibited more frequent changes in acceleration, while the 1500 m events generally followed a more consistent time-series pattern. There were differences in pacing strategies between males and females and between junior and elite swimmers. Swimmers closer to world records showed more consistent pacing patterns compared to those farther from records. This study suggests that pacing strategies are influenced by race distance, sex, age, and performance level. The research highlights the complex interplay between physiological and psychological factors that shape a swimmer’s decision-making during a race.
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... Evidence suggests that the overall pacing strategy is adjusted during prolonged exercise to prevent early exhaustion brought on by a malfunction of one or more physiological systems. Therefore, it is asserted that pacing strategies are indicators of the physiological regulation that underlies them and that pacing strategies are influenced by adjustments in muscle activation that are anticipatory in nature, based on afferent data from a variety of physiological systems [13][14][15]. Due to the low mechanical efficiency of swimming the correct administration of the available energy is also highly dependent on technical abilities. However, in competition the athlete's surroundings constantly and simultaneously present various external stimuli, requiring decision-making regarding where and when to allocate their accessible energy resources. ...
... The ability to effectively allocate energy develops in relation to an individual's cognitive and physical characteristics and is dependent on the amount of prior specific experience [40][41][42]. The ideal pacing technique can thus be acquired by a wealth of training and 12 competition experience [14,20,43,44]. Since an ideal ratio between stroke rate and stroke length is necessary to maintain the pace throughout the race, key variables like stroke rate, stroke count, split times, and rating of perceived exertion are probably crucial training tools to optimise the development of pacing skills [45][46][47][48][49][50][51][52][53]. ...
Pacing Strategy of 800-Meter and 1500-Meter Freestyle Swimming Finals in the World Championships According to the Performance in Males and Females of Different Age Groups
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Full-text available
  • Sep 2023
Pacing strategy refers to the distribution of effort and speed throughout the race to achieve optimal performance. The study aims to understand whether the choice of pacing strategy in swimming depends on the length of competitions and how sex, age, and performance level influence this strategy. Participants were the finalists of the 800-meter and 1500-meter freestyle events at the elite and junior world championships in 2022-2023. Race outcomes and pacing parameters were compared between the two distances and across different groups of swimmers. Swimmers in both distances did not break world records. Pacing strategy generally followed a U-shape with significant differences in the frequency and duration of speed changes between the two distances. The 800-meter exhibited more frequent changes in acceleration while the 1500-meter events generally followed a more consistent time series pattern. There were differences in pacing strategies between males and females and between junior and elite swimmers. Swimmers closer to world records showed more consistent pacing patterns compared to those farther from records. The study suggests that pacing strategies are influenced by race distance, sex, age, and performance level. The research highlights the complex interplay between physiological and psychological factors that shape a swimmer's decision-making during a race.
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... Moreover, a pacing strategy is a learned behaviour and it is dependent on feedback from internal receptors (Corbett et al., 2009;Micklewright et al., 2010). In this context, competitive pacing can be developed employing different preplanned strategies to optimise performance during the race (Foster et al., 2009). ...
... Indeed, athletes' experience has been highlighted as a fundamental factor in developing the ability to maintain an adequate pacing (Elferink-Gemser & Hettinga, 2017). Based on greater experience and according to the specific characteristics of the event, athletes create an ideal performance strategy (Foster et al., 2009). ...
Analysis of pacing and kinematics in 3000 m freestyle in elite level swimmers
Article
This study aimed to determine elite swimmers' pacing strategy in the 3000 m event and to analyse the associated performance variability and pacing factors. Forty-seven races were performed by 17 male and 13 female elite swimmers in a 25 m pool (20.7 ± 2.9 years; 807 ± 54 FINA points). Lap performance, clean swim velocity (CSV), water break time (WBT), water break distance (WBD), stroke rate (SR), stroke length (SL) and stroke index (SI) were analysed including and excluding the first (0-50 m) and last lap (2950-3000 m). The most common pacing strategy adopted was parabolic. Lap performance and CSV were faster in the first half of the race compared to the second half (p < 0.001). WBT, WBD, SL and SI were reduced (p < 0.05) in the second half compared to the first half of the 3000 m when including and excluding the first and last laps for both sexes. SR increased in the second half of the men's race when the first and last laps were excluded. All studied variables showed significant variation between the two halves of the 3000 m, the highest variation being obtained in WBT and WBD, suggesting that fatigue negatively affected swimming kinematics.
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... It is remarkable that our understanding of exercise goals has evolved, as previous theories suggested that the ability to effectively allocate energy towards these goals was solely innate. However, new research suggests that this ability actually develops in connection with an individual's cognitive and physical attributes, as well as their experience with exercise [15]- [17]. ...
Coach Motivational Approaches for Youth Athletes Exercise Training and Racing Pace
Conference Paper
Full-text available
  • Jul 2024
Becoming a top-level athlete requires a substantial investment of time and effort in training and competing. While it's a well-known fact that pacing behavior plays a significant role in achieving peak performance, it remains an elusive skill among athletes. This crucial aspect involves making strategic decisions about effort regulation over an extended period of time, whether it's for a single event or an entire competitive season. Without proper management, the consequences can be severe, including injury, overtraining, and even quitting altogether. However, there is still much to be explored in how young athletes learn and refine their pacing abilities. As an athlete matures from infancy to adolescence, their pacing behavior undergoes a transformation. This change is thought to be closely connected to their physical growth, the development of pre-frontal cortex-linked cognitive processes, and the acquisition of exercise task experience. Furthermore, an athlete's motivation plays a crucial role in determining their pacing strategy for a single race and their distribution of effort over a prolonged period of time. Coaches should closely monitor the development of pacing behavior in adolescents, by tracking split times and physiological data during training and competition. They should also consider key factors like motivation, cognitive and physical maturity, and the use of targeted training to effectively shape pacing behavior. Providing training that replicates the environment and challenges of upcoming competitions can give young athletes valuable experience and preparation.
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... Een belangrijk deel van de veran deringen in het pacinggedrag van kinderen en adolescenten is dus gerelateerd aan de ontwikkeling van cognitieve vaardigheden en aan de fysieke rijping. 2 Hoewel het soms lijkt alsof deze processen 'automatisch' verlopen, is dit niet zo. Het opdoen van ervaring is essentieel voor het ontplooien van cognitieve vaardig heden en daarmee ook het pacing gedrag. 2 Hoewel in de jaren 2000 nog werd gesteld dat pacinggedrag rigide was en lastig te beïnvloeden 18 , heeft recent onderzoek aangetoond dat ook volwassenen dit nog altijd kunnen verbeteren. 2 Hoewel sporters de basis van hun pacing skills dus ontwikkelen tijdens de kindertijd en adolescentie, kunnen ze deze door middel van ervaring en specifieke oefeningen een heel leven lang blijven verbeteren en optimaliseren. 2 Een eerste stap in het oefenen van pacing is het opdoen van ervaring met de taak. Sporters moeten immers eerst een idee hebben wat ze gaan doen. 2 Bij jonge sporters is het hierbij belangrijk om de fysieke rijping en de groeispurt in gedachten te houden. ...
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... Additionally, Jeffries and Waldron [2] included all published studies on MEN, inclusive of sedentary and active participants, whereas the present review included active participants only. Given that work by Foster et al. [29] and Hibbert et al. [30] suggests that current fitness levels and experience can impact the reliability of outcomes, one may conclude that the study inclusion criteria and participant population had influence over the strength of the results, possibly explaining the difference between the two reviews. Our findings demonstrate that there was no relationship between MEN concentration, swilling duration, or mean environmental temperature during the tests. ...
How Cool is That? The Effects of Menthol Mouth Rinsing on Exercise Capacity and Performance: A Systematic Review and Meta-analysis
Article
Full-text available
  • Feb 2024
Background Menthol (MEN) mouth rinsing (MR) has gained considerable interest in the athletic population for exercise performance; however, the overall magnitude of effect is unknown. Objective The aim of this systematic review and meta-analysis was to determine the efficacy of menthol MEN MR and the impact it has on exercise capacity and performance. Methods Three databases were searched with articles screened according to the inclusion/exclusion criteria. Three-level meta-analyses were used to investigate the overall efficacy of MEN MR and the impact it has on exercise capacity and performance. Meta-regressions were then performed with 1) mean VO2peak, 2) MEN swilling duration; 3) the MEN concentration of MR solution, 4) the number of executed swills throughout a single experiment, 5) the use of flavoured sweetened, non-caloric, or non-flavoured neutral solutions as controls, 6) mean environmental temperature at the time of exercise tests, and 7) exercise type as fixed factors to evaluate their influence on the effects of MEN MR. Results Ten MEN MR studies included sufficient information pertaining to MEN MR and exercise performance and capacity. MR with MEN resulted in no significant change in capacity and performance (SMD = 0.12; 95% CI − 0.08, 0.31; p = 0.23, n = 1, tau²1 < 0.0001, tau²2 = < 0.0001, I² = 0%). No significant influence was detected in meta-regressions for VO2peak, (estimate: 0.03; df = 8; 95% CI − 0.03, 0.09; p = 0.27), swilling duration (5 vs. 10 s: 0.00; df = 16; 95% CI − 0.41, 0.41; p = 1.0), MEN concentration (low [0.01%] vs. high [0.1%]: − 0.08; df = 15; 95% CI − 0.49, 0.32; p = 0.67), number of swills (estimate: 0.02; df = 13; 95% CI − 0.05, 0.09; p = 0.56), the use of flavoured sweetener or non-caloric as control (non-flavoured vs. flavoured: 0.12; df = 16; 95% CI − 0.30, 0.55; p = 0.55) or mean room temperature during exercise tests (estimate: 0.01; df = 16; 95% CI − 0.02, 0.04; p = 0.62). Conclusion MEN MR did not significantly improve overall exercise capacity and performance, though those involved in endurance exercise may see benefits.
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... Additionally, Jeffries and Waldron(2)included all published studies on MEN, inclusive of sedentary and active participants, whereas the present review used active participants only. Given that work by Foster et al.(29) and ...
How cool is that? The effects of menthol mouth rinsing on exercise capacity and performance: a systematic review and meta-analysis
Preprint
Full-text available
  • Nov 2022
Background: Menthol (MEN) mouth rinsing (MR) has gained considerable interest in the athletic population for exercise performance; however, the overall magnitude of effect is unknown. Objective: The aim of this systematic review and meta-analysis was to determine the efficacy of menthol MEN MR and the impact it has on exercise capacity and performance. Methods: Three databases were searched with articles screened according to the inclusion/exclusion criteria. Three-level meta-analyses were used to investigate the overall efficacy of MEN MR and the impact it has on exercise capacity and performance. Meta-regressions were then performed with 1) mean VO2peak, 2) MEN swilling duration; 3) the MEN concentration of MR solution, 4) the number of executed swills throughout a single experiment, 5) the use of flavoured sweetened, non-caloric, or non-flavoured neutral solutions as controls, 6) mean environmental temperature at the time of exercise tests, and 7) exercise type as fixed factors to evaluate their influence on the effects of MEN MR. Results: Ten MEN MR studies included sufficient information pertaining to MEN MR and exercise performance and capacity. MR with MEN resulted in no significant change in capacity and performance (SMD = 0.12; 95% CI: -0.08, 0.31; p = 0.23, n = 1, tau²1 < 0.0001, tau²2 = < 0.0001, I² = 0%). No significant influence was detected in meta-regressions for VO2peak, (estimate: 0.03; df = 8; 95% CI: -0.03, 0.09; p = 0.27), swilling duration (5 vs. 10s: 0.00; df = 16; 95% CI: -0.41, 0.41; p = 1.0), MEN concentration (low [0.01%] vs. high [0.1%]: -0.08; df = 15; 95% CI: -0.49, 0.32; p = 0.67), number of swills (estimate: 0.02; df = 13; 95% CI: -0.05, 0.09; p = 0.56), the use of flavoured sweetener or non-caloric as control (non-flavoured vs. flavoured: 0.12; df = 16; 95% CI: -0.30, 0.55; p = 0.55) or mean room temperature during exercise tests (estimate: 0.01; df = 16; 95% CI: -0.02, 0.04; p = 0.62). Conclusion: MEN MR did not significantly improve overall exercise capacity and performance, though those involved in endurance exercise may see benefits.
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... There is evidence that, throughout prolonged exercise, the overall pacing strategy is modulated to avoid early exhaustion brought on by a malfunction of one or more physiological systems. It is argued, therefore, that pacing strategies are markers of the physiological regulation that underlie them, and that pacing strategies are influenced by changes in muscle activation that are anticipatory in nature [6][7][8]. Moreover, in competition, athletes are constantly and simultaneously presented with various external stimuli. ...
Pacing of Human Locomotion on Land and in Water: 1500 m Swimming vs. 5000 m Running
Article
Full-text available
  • May 2023
The study of pace strategy in different environments could help to understand its dependence on athletes’ energetic limits or on sport-specific factors. The aim of this study was to analyse the pacing strategy of finalists during seven swimming and running world events held in 2021–2022. The speed of 32 swimmers every 50 m in 1500 m freestyle competitions, and the speed of 55 runners every 100 m in 5000 m track competitions, were analysed. Differences between swimming and running were statistically significant for Total Time (p = 0.00, ES = 1.9), Average Time of splits (p = 0.00, ES = 2.0), Median Time of splits (p = 0.00, ES = 2.0), and Maximal length of split sequences (p = 0.00, ES = 1.3), and non-significantly different for number of Sequences of splits (p = 0.12, ES = 0.5), Percentage of total splits faster than the median speed (p = 0.08, ES = 0.2), Percentage of splits faster than the median speed in the first half (p = 0.16, ES = 0.4) and Percentage of splits faster than the median speed in the second half (p = 0.21, ES = 0.3). In conclusion, despite similar metabolic requirements of 1500 m swimming and 5000 m running, the influence of specific environment and sport type on the pacing strategy of world level competitions seems to be supported.
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Evolution of 1500-m Olympic Running Performance
Article
  • Jan 2024
Purpose : This study determined the evolution of performance and pacing for each winner of the men’s Olympic 1500-m running track final from 1924 to 2020. Methods : Data were obtained from publicly available sources. When official splits were unavailable, times from sources such as YouTube were included and interpolated from video records. Final times, lap splits, and position in the peloton were included. The data are presented relative to 0 to 400 m, 400 to 800 m, 800 to 1200 m, and 1200 to 1500 m. Critical speed and D′ were calculated using athletes’ season’s best times. Results : Performance improved ∼25 seconds from 1924 to 2020, with most improvement (∼19 s) occurring in the first 10 finals. However, only 2 performances were world records, and only one runner won the event twice. Pacing evolved from a fast start–slow middle–fast finish pattern (reverse J-shaped) to a slower start with steady acceleration in the second half (J-shaped). The coefficient of variation for lap speeds ranged from 1.4% to 15.3%, consistent with a highly tactical pacing pattern. With few exceptions, the eventual winners were near the front throughout, although rarely in the leading position. There is evidence of a general increase in both critical speed and D′ that parallels performance. Conclusions : An evolution in the pacing pattern occurred across several “eras” in the history of Olympic 1500-m racing, consistent with better trained athletes and improved technology. There has been a consistent tactical approach of following opponents until the latter stages, and athletes should develop tactical flexibility, related to their critical speed and D′, in planning prerace strategy.
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Unraveling the Role of (Meta-) Cognitive Functions in Pacing Behavior Development during Adolescence: Planning, Monitoring and Adaptation
Article
Full-text available
  • May 2023
  • MED SCI SPORT EXER
Purpose: To investigate whether (meta-) cognitive functions underpin the development of the self-regulated distribution of effort during exercise (i.e. pacing) throughout adolescence. Methods: Participants included 18 adolescents (9 females, 15.6 ± 2.5 years old) and 26 adults (13 females, 26.8 ± 3.1 years old), all recreationally active but unfamiliar with time trial cycling. The (meta-) cognitive functions involved in pre-exercise planning were quantified by calculating the difference between estimated and actual finish time during a 4-km cycling time trial. The capability to monitor and adapt one's effort distribution during exercise was measured during a 7-min submaximal trial, in which the participants were tasked with adhering to a set submaximal goal velocity either with (0-5 min) or without (5-7 min) additional feedback provided by the researcher. Analyses included between-group comparisons (ANOVA) and within-group comparisons (correlation) (p < 0.05). Results: Adolescents were less accurate in their estimation of the task duration. The adolescents' overestimation of task duration of the 4-km time trial was accompanied by pacing behavior characteristics resembling a longer trial (i.e. more even power output distribution, lower RPE, more pronounced end-spurt). Contrary to the adults, the adolescents deviated relatively more from the goal velocity during the 7-min submaximal trial, when no additional feedback was provided by the researcher. Within the adolescent group, estimation of task duration (r = 0.48) and adherence to goal velocity (r = 0.59) correlated with age. Conclusions: The (meta-) cognitive functions involved in the pre-exercise planning and the monitoring and adaptation of the distribution of effort during exercise underpin the development of pacing behavior during adolescence. Feedback from the (social) environment can be used to aid the monitoring and adaptation of effort expenditure in adolescents.
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The influence of pacing strategy on VO2 and supramaximal kayak performance
Article
Full-text available
  • May 2002
D. BISHOP, D. BONETTI, and B. DAWSON. The influence of pacing strategy on V̇O2 and supramaximal kayak performance. Med. Sci. Sports Exerc., Vol. 34, No. 6, pp. 1041-1047, 2002. Purpose: The purpose of this study was to investigate the effects of manipulating pacing strategy on V̇O2 and kayak ergometer performance in well-trained paddlers. Methods: Eight well-trained kayak paddlers (500-m time = 115-125 s) first performed a graded exercise test for determination of V̇O2max and lactate (La-) parameters. On subsequent days and in a random, counterbalanced order, subjects performed a 2-min, kayak ergometer test using either an all-out start or even pacing strategy. Results: There was a significantly greater peak power (747.6 ± 152.0 vs 558.3 ± 110.1 W) and average power (348.5 ± 47.6 vs 335.5 ± 44.8 W) using the all-out start strategy, when compared with the even-paced strategy. There was however, no significant difference between the two pacing strategies for peak V̇O2, accumulated oxygen deficit (AOD), peak [La-], or posttest pH. Using the all-out start, total V̇O2 was significantly greater (7.3 ± 0.8 vs 6.9 ± 0.8 L). Conclusion: The results of this study indicate that 2-min kayak ergometer performance is significantly greater following an all-out start strategy when compared with an even-paced strategy. The improved performance appears to be attributable to faster V̇O2 kinetics, without a significant change in the total AOD (although the AOD distribution was altered).
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Hyperoxia improves 20 km cycling time trial performance by increasing muscle activation levels while perceived exertion stays the same
Article
Full-text available
  • Dec 2007
Increasing inspiratory oxygen tension improves exercise performance. We tested the hypothesis that this is partly due to changes in muscle activation levels while perception of exertion remains unaltered. Eleven male subjects performed two 20-km cycling time-trials, one in hyperoxia (HI, FiO2 40%) and one in normoxia (NORM, FiO2 21%). Every 2km we measured power output, heart rate, blood lactate, integrated vastus lateralis EMG activity (iEMG) and ratings of perceived exertion (RPE). Performance was improved on average by 5% in HI compared to NORM (P<0.01). Changes in heart rate, plasma lactate concentration and RPE during the trials were similar. For the majority of the time-trials, power output was maintained in HI, but decreased progressively in NORM (P<0.01) while it increased in both trials for the last kilometre (P<0.0001). iEMG was proportional to power output and was significantly greater in HI than in NORM. iEMG activity increased significantly in the final kilometer of both trials (P<0.001). This suggests that improved exercise performance in hyperoxia may be the result of increased muscle activation leading to greater power outputs. The finding of identical RPE, lactate and heart rate in both trials suggests that pacing strategies are altered to keep the actual and perceived exercise stress at a similar level between conditions. We suggest that a complex, intelligent system regulates exercise performance through the control of muscle activation levels in an integrative manner under conditions of normoxia and hyperoxia.
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The anticipatory regulation of performance: The physiological basis for pacing strategies and the development of a perception-based model for exercise performance
Article
Full-text available
  • Mar 2009
  • BRIT J SPORT MED
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 influence of pacing strategy on &OV0312;O2 and supramaximal kayak performance
Article
  • Jun 2002
D. BISHOP, D. BONETTI, and B. DAWSON. The influence of pacing strategy on V̇O2 and supramaximal kayak performance. Med. Sci. Sports Exerc., Vol. 34, No. 6, pp. 1041–1047, 2002. Purpose: The purpose of this study was to investigate the effects of manipulating pacing strategy on V̇O2 and kayak ergometer performance in well-trained paddlers. Methods: Eight well-trained kayak paddlers (500-m time = 115-125 s) first performed a graded exercise test for determination of V̇O2max and lactate (La−) parameters. On subsequent days and in a random, counterbalanced order, subjects performed a 2-min, kayak ergometer test using either an all-out start or even pacing strategy. Results: There was a significantly greater peak power (747.6 ± 152.0 vs 558.3 ± 110.1 W) and average power (348.5 ± 47.6 vs 335.5 ± 44.8 W) using the all-out start strategy, when compared with the even-paced strategy. There was however, no significant difference between the two pacing strategies for peak V̇O2, accumulated oxygen deficit (AOD), peak [La−], or posttest pH. Using the all-out start, total V̇O2 was significantly greater (7.3 ± 0.8 vs 6.9 ± 0.8 L). Conclusion: The results of this study indicate that 2-min kayak ergometer performance is significantly greater following an all-out start strategy when compared with an even-paced strategy. The improved performance appears to be attributable to faster V̇O2 kinetics, without a significant change in the total AOD (although the AOD distribution was altered).
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V˙O2 Response in Supramaximal Cycling Time Trial Exercise of 750 to 4000 m
Article
  • Jan 2009
  • MED SCI SPORT EXER
Limited research has been done on the .VO2 response to time trial exercise in the supramaximal domain or during free range exercise typical of competition. The present study was designed to measure and to model the .VO2 response during supramaximal time trial exercise. Well-trained cyclists (n = 9) performed a 1-min incremental exercise test to obtain maximal power output (P (.VO2max)) and four cycle ergometer time trials of different distances (750, 1500, 2500, and 4000 m). Athletes were instructed to finish in as little time as possible. .VO2 was measured breath-by-breath and modeled monoexponentially over the first 54 s (750 m) or 114 s (1500, 2500, and 4000 m) of the time trials. Mean P (.VO2max) in the incremental test was 383 +/- 28 W. Mean .VO(2max) was 4.5 +/- 0.2 L.min(-1). All time trials were characterized by an initial burst in power output during the first 15 s (175 +/- 23%, 149 +/- 14%, 145 +/- 14%, 139 +/- 10% P (.VO2max) being largest for 750 m. Simultaneously, the mean response time was significantly smaller in 750 m compared with all other trials (18.8 +/- 2.2, 20.9 +/- 1.9, 20.8 +/- 1.5, and 21.2 +/- 2.2 s). Near maximal values of .VO2 can be reached within 2 min of strenuous exercise. The larger initial burst in power output in 750 m was accompanied by a faster .VO2 response and seems to be of importance to trigger the aerobic system maximally.
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Effects of oxygen fraction in inspired air on rowing performance
Article
  • Apr 1995
The present study examined the effect of oxygen fraction in inspired air (FIO2) on exercise performance and maximum oxygen consumption (VO2max). Six national level male rowers exercised three 2500-m all-out tests on a Concept II rowing ergometer. Each subject performed one test in normoxia (FIO2 20.9%), one in simulated hyperoxia (FIO2 62.2%) and one in simulated hypoxia (FIO2 15.8%) in a randomized single-blind fashion. The mean final rowing time was 2.3 +/- 0.9% (P < 0.01; 95% CI 1.4-3.2) shorter in hyperoxia and 5.3 +/- 1.8% (P < 0.01; 95% CI 3.1-7.5) longer in hypoxia when compared with normoxia. The effect of FIO2 on VO2max exceeded its effect on exercise performance as VO2max was 11.1 +/- 5.7% greater (P < 0.01; 95% CI 5.1-17.1) in hyperoxia and 15.5 +/- 3.2% smaller in hypoxia (P < 0.01; 95% CI 12.2-19.0) than in normoxia. Blood lactate concentration and O2 consumption per power unit (ml O2.W-1) failed to indicate statistically significant differences in anaerobic metabolism between normoxia and the other two conditions. These data suggest that there are other parameters besides those of energy metabolism that affect exercise performance as FIO2 is modified. These possible mechanisms are discussed in this paper.
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Concept of an extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiologial feedback
Article
  • Jun 1996
  • Experientia
Efferent motor signals to skeletal muscles concern not only the space/ time pattern of motion, but also the setting of muscular performance and through this the control of the current metabolic rate. For an optimal adjustment of metabolic rate during heavy exercise-e.g. in athletic competitions-a feedback control system must exist, including a programmer that takes into consideration a finishing point (teleoanticipation). The presented experiments, using Borg's scale, indicate the existence and functioning of a system for optimal adjustment of performance during heavy exercise and the relevance of teleoanticipatory effects. Thus motor learning includes not only somatosensory control, but also metabolic control. With regard to migratory birds, such metabolic control would have to operate in the individual as well as in the migrating flock as a whole.
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Reduced neuromuscular activity and force generation during prolonged cycling
Article
  • Jul 2001
We examined neuromuscular activity during stochastic (variable intensity) 100-km cycling time trials (TT) and the effect of dietary carbohydrate manipulation. Seven endurance-trained cyclists performed two 100-km TT that included five 1-km and four 4-km high-intensity epochs (HIE) during which power output, electromyogram (EMG), and muscle glycogen data were analyzed. The mean power output of the 4-km HIE decreased significantly throughout the trial from 319 +/- 48 W for the first 4-km HIE to 278 +/- 39 W for the last 4-km HIE (P < 0.01). The mean integrated EMG (IEMG) activity during the first 4-km HIE was 16.4 +/- 9.8% of the value attained during the pretrial maximal voluntary contraction (MVC). IEMG decreased significantly throughout the trial, reaching 11.1 +/- 5.6% during the last 4-km HIE (P < 0.01). The study establishes that neuromuscular activity in peripheral skeletal muscle falls parallel with reduction in power output during bouts of high-intensity exercise. These changes occurred when <20% of available muscle was recruited and suggest the presence of a central neural governor that reduces the active muscle recruited during prolonged exercise.
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