08_chapter 2

22
Chapter II
REVIEW OF RELATED LITERATURE
The related literature reviewed for better understanding of
the problem and to interpret the results is presented in this chapter.
The
review
was confined to the
libraries of Manonmaniam
Sundaranar University, Tirunelveli, Dr. Sivanthi Aditanar College of
Physical Education, Tiruchendur and through the Internet (web
sources).
The literature in any field forms the foundation upon
which all future work will be built.
If we fail to build upon the
foundation of knowledge provided by the review of literature, the
scholar might miss some work already done on the same topic. The
reviews are classified under the following headings:
1.
Studies on motor variables.
2.
Studies on physiological variables.
3.
Studies on psychological variables.
4.
Summary of the literature.
1. Studies on motor variables
Speed
Carr, (2005) conducted a study on long jump. Most young
athletes will have difficulty in performing the Hitch- kick, because it
requires considerable speed and sufficient time in the air to perform
23
well. However, an elementary long jump and a rudimentary form of
the hang technique are well within reach of young athletes.
Remember that the most important requirements in this event are
speed and springing abilities. An athlete does not have to perform a
hitch-hick or a hang to jump good distance.
Rogers, (2005), investigated a study on the long jump.
This is an event which requires speed and powerful jumping ability.
Speed is self evident but power needs to be defined as a very fast
application of force, in other words a combination of speed and
strength. The long jumper is required to generate maximum
controllable speed on the run way to achieve the best results. The
maximum controllable speed is determined by the athlete’s sprint
speed and how quickly maximum force can be applied into the
ground at the take-off board. Therefore, the training emphasis will
focus upon the development of (1) Sprint speed, (2) muscular
strength, and (3) power.
Li, et al., (2005), conducted a Kinematics study on the
technical parameters demonstrated by Chinese and foreign elite
female long jumpers which showed that the main methods of
improving long jump results were as follows: increasing the absolute
speed during the run-up and the angle of take-off, as well as
achieving an optimal relationship between the initial velocity and the
angle of take-off.
24
Xie, (2005), conducted a study on the effect of utilization
ratio of speed in the long jump run-up of Chinese female long
jumpers. The run-up speed of 49 elite female long jumpers was
investigated. It was found that the main factor affecting long jump
results was the utilization ratio of speed in the run-up. It was
determined that the approximate scope of speed utilization ratio for
achieving excellent long jump result was between 95.6% and 98.2%,
which provides a scientific basis of reference for coaches.
Mackenzie, (2005), conducted a study to find out what
does the takeoff leg really do? The immediate implication of this
study to the coach is that speed is critical to all jumpers
Mackenzie, (2005), conducted a study on determining the
force the take-off leg exerts in the long and high jumps, concluded
that long jumpers should approach the take-off board at maximum
speed and get as high as possible.
Vladimir Popov, (2002), We must keep in mind that the
additional load created by interval forces of the run up increase the
muscular contraction capacity and therefore improves the take off.
For this reason we are looking for optimal speed in the high jump
run up and maximal speed in the run up of the horizontal jumps.
Shepherd, (2005), conducted a study on the run up and
take-off in the long jump, The key to long jumping is speed and the
25
greatest performance comes from a forceful and correctly angled run
up and take off.
Leg explosive power
Cronin and Hansen, (2005), investigated the relationship
between strength and power and measures of first-step quickness
(5-m time), acceleration (10-m time), and maximal speed (30-m
time). The maximal strength (3 repetition maximum [3RM]), power
(30-kg jump squat, countermovement, and drop jumps), isokinetic
strength measures (hamstring and quadriceps peak torques and
ratios at 60 degrees .s(-1) and 300 degrees .s(-1)) and 5-m, 10-m,
and 30-m sprint times of 26 part-time and full-time professional
rugby league players (age 23.2 +/- 3.3 years) were measured. To
examine the importance of the strength and power measures on
sprint performance, a correlational approach and a comparison
between means of the fastest and slowest players was used. It was
suggested that improving the power to weight ratio as well as
plyometric training involving countermovement and loaded jumpsquat training may be more effective for enhancing sport speed in
elite players.
Power,
et
al.,
(2004),
examined
whether
a
static
stretching (SS) routine decreased isometric force, muscle activation,
and jump power while improving range of motion (ROM). Twelve
participants were tested pre- and post- (POST, 30, 60, 90, and 120
26
min) SS of the quadriceps and plantar flexors (PF) or a similar
period of no stretch (control). Measurements during isometric
contractions included maximal voluntary force (MVC), evoked
contractile properties (peak twitch and tetanus), surface integrated
electromyographic (iEMG) activity of the agonist and antagonistic
muscle groups, and muscle inactivation as measured by the
interpolated
measurements
twitch
technique
included
(ITT).
unilateral
Vertical
jump
(VJ)
concentric-only
(no
countermovement) jump height as well as drop jump height and
contact time. ROM associated with seated hip flexion, prone hip
extension, and plantar flexion-dorsiflexion was also recorded. The
parallel duration of changes in ROM and quadriceps isometric force
might suggest an association between stretch-induced changes in
muscle compliance and isometric force output.
Chelly and Denis (2001), determined sprint performance
while running at maximal velocity. Results that include both of
these characteristics have not been directly obtained in previous
studies on human runners. They studied the link between leg
power, leg stiffness, and sprint performance. The acceleration and
maximal running velocity developed by 11 subjects (age 16 +/- 1)
during a 40-m sprint were measured by radar. Their leg muscle
volumes
were
estimated
anthropometrically.
Leg
power
was
measured by an ergometric treadmill test and by a hopping test.
Each subject executed a maximal sprint acceleration on the
27
treadmill equipped with force and speed transducers, from which
forward power was calculated. A hopping jump test was executed at
2 Hz on a force platform. Leg stiffness was calculated using the
flight and contact times of the hopping test. Although muscle power
is needed for acceleration and maintaining a maximal velocity in
sprint performance, high leg stiffness may be needed for high
running speed. The ability to produce a stiff rebound during the
maximal running velocity could be explored by measuring the
stiffness of a rebound during a vertical jump.
Terzis,
et
al.,
(2003), investigated the relationship
between shot put performance and triceps brachii muscle fiber type
composition
and
strength
capacity.
Thirteen
male
physical
education students were selected to participate in the study based
upon their shot put performance after 5 weeks of shot put technique
instruction. At the completion of this technique-instruction period,
they performed the following tests: shot put with a 6-kg shot,
isokinetic torque measurements of the elbow extensors at 0, 0.52,
1.04, 1.57, 2.09, 3.14, and 4.19 rad.s(-1), maximal strength (1 RM)
and explosive-throwing bench-press tests, one-arm seated shot put
with 1-, 2-, 3-, 4-, 5- and 6kg shot. Wholebody and dominant upper
arm bioimpedance measurements were used to estimate whole body
and upper arm muscle mass. Muscle biopsy samples from the long
head of the dominant triceps brachii were obtained and analyzed for
fiber type composition with ATPase histochemistry. Shot put
28
performance was significantly correlated with type II fiber area, onearm seated shot put, elbow extensors' isokinetic torque, bench-press
tests and estimated arm muscle cross-sectional area. These results
suggest that fiber type composition and the functional capacity of
triceps brachii muscle explained a part of shot put performance. The
magnitude of the correlation coefficients between shot put and the
upper body power tests suggested that other body parts (e.g., lower
extremities) may play a significant role in this event.
Bora, (2005), investigated a study on the determinants of
the high jump results in male physical education students. The
analysis shows that the high jump results depend on the following
factors: body size, body fat mass, explosive strength physical fitness
test, technique and motor coordination.
Peterson, et al., (2006), conducted a study on the
contribution of maximal force production to explosive movement
among young collegiate athletes. The purpose of this investigation
was to examine the relationships between lower body muscular
strength and several fundamental muscular strength and several
fundamental explosive performance measures. Fifty four men and
women collegiate athletes were tested to determine lower body
muscular strength, countermovement vertical jump height and peak
power out put, standing broad jump distance, agility and sprint
velocity. Correlation data demonstrated that significant strong linear
29
relationships were indicated between muscular strength and power.
Muscular strength, vertical jumping ability, peak power out put,
standing broad jump, agility and sprint acceleration and sprint
velocity were all shown to be highly related.
Stockbrugger, (2003), examined the factors contributing
to performance of a medicine ball throw across 2 types of athletes
(jump athletes and non jump athletes). Twenty male volleyball
players (jump athletes) and twenty wrestlers(non jump athletes)
were evaluated on 4 measures of power, including B-MBT, chest
medicine ball throw (C-MBT), countermovement vertical jump (CMJ)
and power index. The results of the study indicated that B-MBT was
strongly correlated with C-MBT and CMJ. Only non jump athletes
demonstrated strong correlations with strength for absolute LP and
BP+ LP strength. The interaction of upper and lower body strength
power in the performance of a B-MBT appears complex, with the
contributing factors differing for athletes with divergent skills and
performance demands.
Agility
Barnes, et al., (2007), studied to (a) quantify vertical and
horizontal force during a COD task, (b) identify possible predictors of
court-sport–specific
performance
agility
difference
performance,
between
National
and
(c)
Collegiate
examine
Athletic
Association Division I, II, and III athletes. Twenty-nine collegiate
30
female
volleyball
players
completed
a
novel
agility
test,
countermovement (CM) and drop jump tests, and an isometric leg
extensor test. The number of athletes by division was as follows: I (n
= 9), II (n = 11), and III (n = 9). The agility test consisted of 4 5-meter
sprints with 3 180° turns, including 1 on a multiaxial force platform
so that the kinetic properties of the COD could be identified. This
study indicates that individuals with greater CM performance also
have quicker agility times and suggests that training predominantly
in the vertical domain may also yield improvements in certain types
of agility performance. This may hold true even if such agility
performance requires a horizontal component.
Vescovi, and Mcguigan, (2008), studied the relationships
between various field tests in female athletes. Altogether, 83 high
school soccer, 51 college soccer, and 79 college lacrosse athletes
completed tests for linear sprinting, countermovement jump, and
agility in a single session. Linear sprints (9.1, 18.3, 27.4, and 36.6
m) and agility tests (Illinois and pro-agility) were evaluated using
infrared timing gates, while countermovement jump height was
assessed using an electronic timing mat. The relationship between
countermovement jump height and linear sprinting was stronger
with the longer distances (27.4 and 36.6 m) than with the shorter
distances (9.1 and 18.3 m), and showed a stronger relationship
within the college athletes (r = -0.658 to -0.788) than high school
soccer players (r = -0.491 to -0.580). The results of this study
31
indicate that linear sprinting, agility, and vertical jumping are
independent locomotor skills and suggest a variety of tests ought to
be included in an assessment protocol for high school and college
female athletes.
Little and Williams, (2005), assessed 106 professional
soccer players for 10-m sprint (acceleration), flying 20-m sprint
(maximum
speed),
and
zigzag
agility
performance.
Although
performance in the three tests were all significantly correlated (p <
0.0005), coefficients of determination (r(2)) between the tests were
just 39, 12, and 21% for acceleration and maximum speed,
acceleration
and
agility,
and
maximum
speed
and
agility,
respectively. Based on the low coefficients of determination, it was
concluded that acceleration, maximum speed, and agility are
specific qualities and relatively unrelated to one another. The
findings suggested that specific testing and training procedures for
each speed component should be utilized when working with elite
players.
Coh,
et
al.,
(2002),
examined
the
anthropometric
characteristics of elite junior javelin throwers on a sample of eleven
male
and
twelve
female
finalists
of
the
European
Junior
Championship in Athletics. The chosen subjects were measured
with a set of nine anthropometric variables, according to the
methodology
recommended
by
the
International
Biological
32
Programme. The results show that no common constitutional type of
a junior male or female javelin thrower exists, but that the
anthropometric characteristics are very individually defined. At least
two constitutional types exist for each gender, ensuring equal
success in javelin. Correlational analysis shows that no statistically
significant correlations exist between the individual anthropometric
characteristics of the
male
and female
throwers
with their
competitive result. Success in this track and field discipline is
therefore more a synthesis of anthropometric characteristics and
motor abilities, as well as an optimal technique.
Vescovi, (2007), conducted a study on relationships
between sprinting, agility and jump ability in female athletes. The
results indicated that the relationship between countermovement
jump height and linear sprinting was stronger with the longer
distances than the shorter distances and showed a stronger
relationship within the college athletes than the school soccer
players.
2. Studies on Physiological Variables
Resting pulse rate
Dasgupta, et al., (2000), selected short distance runners,
middle distance runners and long distance runners who were
subjected to grade exercise on a treadmill. The maximum aerobic
power (VO2 max) and other indices related to oxygen transport
33
system viz. heart rate, ventilation volume, breathing reserve,
dyspnoeic index, O2 pulse and RQ were recorded at respective VO2
max work loads, and the values were compared. Long distance
runners and middle distance runners showed a significantly higher
VO2 max than the short distance runners when VO2 max was
expressed per unit of body weight. Among the endurance runners,
long distance runners had a significantly lower resting pulse rate as
well as the maximum heart rate during work than the middle
distance runners. On comparison, Ventilation Volume, Breathing
reserve, Dyspnoeic index, O2 pulse and RQ at VO2 max workloads
do not differ significantly among different categories of runners.
Campbell, (1995), studied of 221 competitors in a
University
half
marathon
in
1993
and
1998
replied
to
a
questionnaire before the race which asked for details of training,
age, height, weight and resting pulse rate. Finishing times of all
competitors were recorded. In a multiple regression analysis
significant predictors of running speed were: amount of training,
expressed as distance run per week and number of weeks training
for the event, the Body Mass Index (weight/height) and resting pulse
rate. We conclude that for assessing running speed amongst
competitors with similar amounts of training, the Body Mass Index
and the resting pulse rate are useful substitutes for more elaborate
and expensive measures.
34
Anaerobic Power
Tessitore, et al., (2006), provided aerobic and anaerobic
profiles of senior (55 +/- 5 years) basketball players (n = 10), and
evaluated the physiological load and the match analysis of a senior
basketball match. Participants were administered a maximal oxygen
consumption (VO2 max)) and anaerobic tests (jump tests: counter
movement jump (CMJ) and bounce jump (BJ), and running tests:
10-m sprint and running 10 m while bouncing the ball (10-m(BB)).
During a senior basketball match, the players' heart rate (HR),
electrocardiogram (ECG), blood lactate concentration (LA) and motor
activities were recorded. Older basketball players undergoing a
training
regimen
of
1.5
h.week(-1)
showed
good
anaerobic
characteristics and a moderate aerobic capacity. Although the senior
basketball match required high intensities (only 3% of total match
time spent at HR <70% of HR(max)), the ECG Holter monitoring
showed
no
adverse
event,
ST-segment
changes
or
complex
arrhythmias. Finally, their play did not include the technical skills
recently introduced to basketball.
Busso and Chatagnon, (2006), applied a mathematical
model of performance describing aerobic and anaerobic energy
production during exercise to middle-distance running data from
world records (WR) and from a group of elite runners (NL). The
model is based on the assumption that, above a critical power (Pc), a
continuous rate of anaerobic energy production occurs, until the
35
entire anaerobic stores (W') were depleted. The fraction of metabolic
power above Pc provided by anaerobic metabolism is denoted alpha.
A second power threshold (Pt) sets the limit above which any further
increase in power is met exclusively by anaerobic sources. The
oxygen uptake kinetics was described by a monoexponential
equation with time constant tau. The results showed that the model
successfully fit the WR over 1,500-5,000 m. However, in the range of
distances from 800 to 5,000 m the performance over 800 and 1,000
m
were
overestimated.
Contrary
to
Pc
and
the
anaerobic
contribution at steady state oxygen uptake, the estimate of W' was
sensitive to the value assigned to tau in the range from 0 to 30 s.
Using best performances from 1,500 to 5,000 m in NL resulted in Pc
estimates not significantly different from the metabolic power at the
lactate threshold. The anaerobic contribution at steady state oxygen
uptake increased from zero at Pc to 8.3% (WR) and 7.8+/-3.1% (NL)
at Pt. This suggested that a substantial contribution of anaerobic
processes occurred in the range between Pc and Pt, even though the
exercise does not elicit maximal aerobic power.
Kasabalis, et al., (2005), evaluated the anaerobic power of
elite male volleyball players, using the Wingate Anaerobic Test to
examine the relationship between anaerobic power and jumping
performance. Athletes (n=56) and Nonathletes (n=53) were divided
into three age groups: Adults (18-25 yr.), Juniors (15-16 yr.), and
Youth (10-11 yr.). Measurements of height, body mass, vertical jump
36
and Wingate scores indicated higher values for athletes. The specific
training effects of anaerobic power were more pronounced at the age
of 10-11 years than for Nonathletes. A significant correlation
coefficient between peak power and vertical jump was found for
Athletes (r=.86) and for the total group (r=.82). These results
indicated that vertical jump may predict the maximal anaerobic
power and could be used by coaches as a practical and easy-toapply field screening test for evaluation in volleyball training.
Sinnett, et al., (2001), investigated the relationship
between several field tests of anaerobic power and distance running
performance. Thirty-six trained runners (20 men and 16 women;
mean +/- SD age, 27.9 +/- 5.7 years) participated in this study.
Tests of anaerobic power consisted of a 50-m sprint; vertical jumps
from a static take-off position and with a countermovement, a
plyometric leap test, and a 300-m sprint. The results indicated that
gender, height, weight, percent body fat, 50-m sprint time, the
height and power of both types of vertical jumps, plyometric leap
distance, and the 300-m sprint time were significantly correlated
with 10-km run time (p < or = 0.05) in the total subject pool (N =
36). Stepwise multiple regressions identified the plyometric leap
distance to explain 73.9% of the variance in run time. When
combined with 300-m sprint time, 77.9% of the variance (standard
error of the estimate, 2.92 minutes) was explained. The regression
equation developed is Y' (10-km time) = 57.22 - 5.15(plyometric leap
37
distance in meters) + 0.27(300-m sprint time in seconds). The
results indicated that anaerobic power was significantly related to
distance running performance and might explain a meaningful
percentage of variability in 10-km run time. Therefore, it may be
beneficial for distance runners to supplement aerobic training with
some power and speed development such as plyometrics and
sprinting.
Meckel
et
al.,
(1995),
compared
physiological
characteristics of three different levels of 100 m female sprinters.
The 30 subjects in this study (20 female track athletes and 10
recreationally trained females) were assigned, according to their 100
m running time, to one of three different groups: "Fast" (11.8 +/- 0.1
sec), "Average" (12.7 +/- 0.1) and "Slow" (14.2 +/- 0.1 sec). All
subjects were tested for performance in the Wingate Anaerobic Test
(WAnT), strength (squat exercise), fat % (hydrostatic weighing),
reaction time, flexibility (sit-and-reach test), aerobic power (peak
VO2) and running skill. The ANOVA indicated significant differences
among all three groups for performance in the Wingate Anaerobic
Test and relative strength. Significant differences in fat % and
running skill were found between the fast and the slow groups and
between the average and the slow groups. However, no significant
difference in fat % and running skill existed between the fast and
the average groups. The differences in reaction time were significant
only between the fast and the average groups. No two groups were
38
significantly different from each other for flexibility and peak VO2.
Pearson correlation coefficients (r) were calculated to determine the
relationships between the 100m running time and each of the
variables tested. Significant and negative correlations were found
between the 100m running time and skill, relative strength, and
performance in the WAnT. Significant and positive correlations were
found between running time and fat %. No significant correlations
were found between running time and peak VO2 reaction time and
flexibility.
Stepwise
regression
analysis
indicated
that
the
combination of performance in the WAnT and strength provided the
most efficient (R = 0.92) prediction of 100 m run times. This study
demonstrated that the main difference among female sprinters of
different performance levels lies in their ability to produce muscular
power,
strength
and
running
technique.
Other
physiological
components, such as flexibility, peak VO2, and reaction time do not
differ among female sprinters of different performance levels as
represented in the tested groups.
Ronnie, et al., (2004), the obvious requirement for
100mts sprint is the immediate availability of energy that a sprinter
develops relies mostly on the rate that energy is being produced in
the working muscles. This energy is released through the anaerobic
pathways of adenosine tri phosphate (ATP), Creatine phosphate(CP)
and Glycolysis.
39
VO2 max
Rotstein, et al., (2005), examined the preferred transition
speed (PTS) between walking and running and the energetically
optimal transition speed (ETOS), in runners and non runners. A
total of 19 young men were asked to walk on a treadmill at 5 km.h
(-1). Speed was then increased by 0.2 km.h(-1) every minute.
Subjects were instructed to start running at a particular speed they
felt was easier. PTS for each subject was determined as the mean of
the walk-run and the run-walk transitions. Subjects were also asked
to walk and to run for 5 min at each of the following velocities: PTS 1 km.h(-1), PTS - 0.5 km.h(-1), PTS, PTS + 0.5 km.h(-1), and PTS + 1
km.h(-1). This procedure was performed twice, once walking and
once running, at all speeds. Physiologic measurements of oxygen
consumption, heart rate, and rate of perceived exertion (RPE) were
performed at each stage. EOTS was determined by plotting
individual curves for each subject with the energy cost of locomotion
as a function of velocity. This study indicated that 1) the preferred
PTS was slower than the EOTS, and 2) the PTS and EOTS were not
dependent on the aerobic capacity or the training status.
Lysenko, (2001), investigated the 54 elite male athletes
aged 19-24, specializing in different running distances (100, 800
and 5000 m), the influence of specific character of long-term
adaptation in the body of athletes on general level of aerobic power
and conditions of maximum manifestation of cardio respiratory
40
system
aerobic
capacity
was
demonstrated.
The
determine
maximum level of aerobic capacity in the athletes, motor tests that
take into account the features of maximum aerobic capacity
mobilization conditions due to specifics of sports specialization were
selected.
Billat, et.al., (2002), examined the influence of time run
at maximal oxygen uptake (VO2 max) on the off-transient pulmonary
oxygen uptake phase after supra-lactate threshold runs. This study
showed that among the velocities eliciting VO2 max, vdelta75 is the
velocity at which the longer the duration of the time at VO2 max, the
longer is the off-transient phase of oxygen uptake kinetics. It may be
possible that at vdelta50 there is not an accumulated oxygen deficit
during the plateau of VO2 at VO2 max and that the duration of the
time at VO2 max during the exhaustive runs at vdelta100, could be
too short to induce an accumulating oxygen deficit affecting the
oxygen recovery.
Larsen, et al., (2002), developed a submaximal, 1.5-mile
endurance test for college-aged students using walking, jogging, or
running exercise. College students (N = 101: 52 men, 47 women),
ages 18-26years, successfully completed the 1.5-mile test twice, and
a maximal graded exercise test. Participants were instructed to
achieve a "somewhat hard" exercise intensity (rating of perceived
exertion = 13) and maintain a steady pace throughout each 1.5-mile
41
test. Multiple linear regression generated the following prediction
equation: VO2 max = 65.404 + 7.707 x gender (1 = male; 0 =female) 0.159 x body mass (kg) - 0.843 x elapsed exercise time (min;
walking, jogging or running). This equation shows acceptable
validity (R = .86, SEE = 3.37 ml x kg(-1) min(-1)) similar to the
accuracy of comparable field tests, and reliability (ICC = .93) is also
comparable to similar models. The statistical shrinkage is minimal
(R(press) = 0.85, SEE(press) = 3.51 ml x kg(-) x min(-1)); hence, it
should provide comparable results when applied to other similar
samples. A regression model (R =.90, and SEE = 2.87 ml x kg(-1)
min(-1)) including exercise heart rate was also developed: VO2 max
= 100.162 +/- 7.301 x gender(1 = male; 0 =female) - 0.164 x body
mass (kg) - 1.273 x elapsed exercise time -0.156 x exercise heart
rate, for those who have access to electronic heart rate monitors.
This sub maximal 1.5-mile test accurately predicts maximal oxygen
uptake (VO2 max) without measuring heart rate and is similar to the
1.5-mile run in that it allows for mass testing and requires only a
flat,
measured
distance
and
a
stopwatch.
Further,
it
can
accommodate a wide range of fitness levels (from walkers to
runners).
Legaz Arrese, et al., (2005), assessed the relationship
between VO2 max (mL x kg(-1) x min(-1)) and running performance
in cross-sectional studies. Follow-up studies of the long-term effects
of running training on the changes in performance and VO2 max
42
have not been undertaken. Twenty-five male endurance-trained
(MET) and 8 female endurance-trained (FET) athletes were tracked
over 4 years. In each event the athletes were divided into Class A,
including half the number of athletes with the best performances,
and Class B. VO2 max, examined at the end of the competitive
season, and the best performance was chosen each year. This study
shows that in older runners with more years of training, heavy
training does not produce improvements in running performance
neither changes in the VO2 max. It is possible that these elite
athletes have reached the plateau in their performance; although
unlikely, some improvement in training techniques may happen and
break the present limit. In younger runners with less years of
training,
heavy
training
produce
improvements
in
running
performance without changes in the VO2 max. These athletes that
had not attained the biological limits at the beginning of study
improved the performance in competition and it is quite probable
that this improvement be due to training. The changes in
performance were not related to changes in VO2 max. Consequently,
another physiological or psychological variables must be studied by
longitudinal form to explain the variability of performance in
competition.
Hawkins, et al., (2001), determined the longitudinal
change in VO2 max and HR max in male and female master
endurance runners and to compare these changes based upon
43
gender, age, and change in training volume. Eighty-six male (53.9
+/- 1.1 yr) and 49 female (49.1 +/- 1.2 yr) master endurance
runners were tested at an average of 8.5 yr apart. Subjects were
grouped by age at first visit, change in VO2 max, and change in
training volume. Measurements included body composition by
hydrostatic weighing, maximal exercise testing on a treadmill, and
training history by questionnaire. Data were analyzed by ANOVA
and multiple regression. In conclusion, these data suggest that VO2
max declines in male and female master athletes at a rate similar to
or greater than that expected in sedentary older adults. Additionally,
these data suggest that maintenance of LBM and VO2 max were
associated in men, whereas in women, estrogen replacement and
maintenance of training volume were associated with maintained
VO2 max.
Sharwood, et al., (2002), determined whether oxygen
consumption during sub maximal running increases in proportion
to years of accumulated training and racing in masters runners
after a bout of downhill running. They selected seventeen male
masters distance runners (45-55 years) with a range of training
(3,536 km to 79,320 km) and racing (205 km to 12,218 km)
experience. A 40-minute continuous treadmill run was given at 70%
of peak treadmill running speed, consisting of two horizontal runs of
10 minutes each, separated by a 20-minute downhill (-10%) run.
Heart rate and oxygen consumption were measured continuously
44
during the run. Data were analyzed to identify correlations between
the end of the first horizontal section (minute 10) and the first
minute of the second horizontal run (minute 31). Delta values were
related to current training mileage (km/wk), total accumulated
racing distance (km), and total accumulated training distance (km).
The results of this study suggest either that sub maximal oxygen
consumption is not a sensitive marker of changes in neuromuscular
activity or that the downhill protocol did not impose a sufficient
eccentric stress for the subjects.
Pakkala, et al., (2005), determined during exercise the
maximum related oxygen transport viz, maximum heart rate (max
HR), dyspnoeic index (DI), oxygen pulse (O2 pulse), recovery heart
rate in an athletic and a non-athletic group. Both study groups were
subjected to graded treadmill exercise testing and pulmonary
function test (PFT) was done using an electronic spirolyser. Results
were compared and analysed. Significantly higher values in athletes
were observed as compared to non-athletes regarding the following
parameters: VO2 max, V(E) max, delta heart rate and max O2 pulse
where resting heart rate, DI at VO2 max and recovery heart rate
were lower in athletes while there was no significant change in both
the groups in observed value of: MW, BR at VO2 max HR. The
observations suggested an overall higher adaptability of the
cardiovascular
system and the
relative
refractoriness
of the
respiratory system to the effects of training and the maximum
45
oxygen consumption in both the groups show similar values as that
from other parts of the country while MW, V(E) max, BR at VO2 and
DI at VO2 max differ. A higher delta heart rate in athletes suggested
a lesser risk for cardiovascular mortality in this group.
Arrese et al, (2005), The VO2 max values of groups of
athletes on different levels of performance is considered important
for determining the maximal performance limit of an athlete.
Baxter-Jones A. et al., (1993), Study design was of a
mixed longitudinal type with five age cohorts (8, 10, 12, 14 and 16
yr) followed for 3 consecutive years. 453 athletes drawn from soccer,
swimming, gymnastics, and tennis. A multilevel regression modeling
procedure was used to identify the independent effects of predictor
variables while accounting for the effects of growth, such as changes
in body size. When age, height, and weight were controlled for, VO2
max in males significantly increased with pubertal status, indicated
by the coefficient value of 0.15 l/min being greater than its
associated SE of 0.07 l/min. Females showed a similar pattern, with
a coefficient value of 0.13 +/- 0.07 l/min, although the significant
increase in VO2 max (P < 0.05) found in males in the latter stages of
puberty was not shown in females. Swimmers had the highest VO2
max values (P < 0.001) at all ages.
46
3. Studies on Psychological Variables
Anxiety
Robazza, et al., (2008), examined the impact of emotions
on athletic performance within the frameworks of the Individual
Zones of Optimal Functioning (IZOF) model and the directional
perception approach. Intensity, functional impact, and hedonic tone
of trait and state anxiety, self-confidence, idiosyncratic emotions,
and bodily symptoms were assessed in high-level Italian swimmers
and track and field athletes (N = 56). Three standards of
performance (poor, average, and good), derived from retrospective
self-ratings across one to three competitions (a total of 90
observations), were used as independent variables in the analysis of
variance of intensity, intra-individual, and direction scores of
anxiety,
self-confidence,
idiosyncratic
emotions,
symptoms. The results provided support for the
and
bodily
predictions
stemming from both the IZOF model and the directional approach,
as well as help in interpreting direction of anxiety and other
idiosyncratic emotions within the IZOF framework.
Millet, et al., (2005), investigated the effects of 40-week
training on anxiety and perceived fatigue in four elite triathletes.
Anxiety and perceived fatigue were self-reported by the subjects
twice a week by the way of a specific questionnaire and were linked
by a mathematical model to the training loads calculated from the
47
exercise heart rate. A significant relationship between the training
loads and anxiety was identified using a two-component model: a
first, negative (i.e., anxiety decreased) short-term function and a
second, positive long-term function. The relationship between the
training loads and perceived fatigue was significant (r=0.30;
p<0.001), with one negative function. This mathematical model can
potentially describe the relationships between training loads and
anxiety or perceived fatigue and may improve both the adjustment
of the duration of tapering and the early detection of staleness.
Mullen, et al., (2005), investigated the effects of anxiety
on motor performance. The aim of the study was to examine the
conscious
processing
anxiety/performance
hypothesis
as
relationship.
an
explanation
Findings
of
indicated
the
that
performance was impaired in the high anxiety shadowing and tonecounting
conditions,
supporting
an
attentional
threshold
interpretation.
Mullen and Hardy, (2000), examined an alternative
explanation for the robustness under stress of implicit task
performance. They tested this interpretation while controlling for a
further
rival
hypothesis
generated
by
Eysenck's
Processing
Efficiency Theory. They also examined the effect of increased state
anxiety
on
the
kinematic
processes
underlying
performance
breakdowns. For task performance, they found evidence that
48
partially supported the conscious processing hypothesis, while the
results of the kinematic analysis of the putting stroke were
equivocal. Analysis of self-reported effort scores provided partial
support for processing efficiency theory.
Russell,
(2001),
studied
the
relationship
between
competitiveness and paratelic dominance on intensity and directions
of precompetitive state anxiety. Competitiveness appears to be
important in moderating appraisal of anxiety and out come, while
goal expectancy may moderate the relationship between anxiety
appraisal and paratelic dominance.
Parfitt, (1999), this study considered the influence of
competitive anxiety and self-confidence state responses upon
components of performance. Basketball players (n = 12) were trained
to self-report their cognitive anxiety, somatic anxiety and selfconfidence as a single response on several occasions immediately
before going on court to play. Performance was video-recorded and
aspects of performance that could be characterized as requiring
either largely anaerobic power (height jumped) or working memory
(successful passes and assists) were measured. Intra-individual
performance scores were computed from these measures and the
data from seven matches were subjected to regression analyses and
then hierarchical regression analyses. The results indicated that, as
anticipated, somatic anxiety positively predicted performance that
49
involved anaerobic demands. Self-confidence, and not cognitive
anxiety, was the main predictor of performance scores with working
memory demands. It would appear that different competitive state
responses
exert
differential
effects
upon
aspects
of
actual
performance. Identifying these differences will be valuable in
recommending
intervention
strategies
designed
to
facilitate
performance.
Achievement Motivation
Skordilis, et al., (2003), examined the differences in sport
achievement orientation among 35 professional, 36 amateur, and 35
wheelchair
basketball
athletes,
these
men
completed
three
subscales of Competitiveness, Win orientation, and Goal orientation
of the 25-item Sport Orientation Questionnaire. A multivariate
analysis of variance indicated significant differences among groups.
Win orientation was the factor, through discriminant function
analysis, that significantly separated the athletes into the three
groups. The highest win score was obtained by the professional,
followed by the amateur and wheelchair groups. Replication study
was necessary to confirm the present findings.
Harwood, et al., (2003), studied imagery use in elite
youth sport participants: Reinforcing the applied significance of
achievement goal theory, the findings of the study concluded that
50
role of achievement motivation in influencing young athletes
behavioural investments in mental strategies.
Kim, (2001), investigated a study on the relationship
between achievement motivation, affect and coping strategies among
Korean intercollegiate athletes and the results indicated that the
way a Korean athlete feels has better predictability of the coping
process than do motivational factors.
These findings will be
discussed in terms of theoretical applicability of achievement goal
theory and implications for further understanding the coping
behaviours of Korean athletes.
Thomassen and Halvari, (1996), tested 213 pupils
(M=17.2 yr.) on the motive to achieve success, the motive to avoid
failure,
future
time
orientation,
perceived
instrumentality
of
cognitive and physical tasks at school, and the involvement in sport
competitions. Analysis shows a significant positive correlation
between the scores on motive to achieve success and the amounts of
competitive involvement in sport. Conversely, the motive to avoid
failure was negatively correlated with the involvement in sport.
Further, a positive significant correlation for the involvement in
sport competitions with perceived instrumentality of physical or
sport tasks at school appeared. The relations were similar for both
girls and boys. A hypothetical model based on hierarchical
51
regression of the data showed that all independent variables affected
involvement in sport competitions directly or indirectly.
Self Confidence
Bekiari et al., (2006) examined the relation of verbal
aggressiveness and state anxiety (somatic, cognitive, and selfconfidence) in sports settings based on the ratings by volleyball
coaches and their athletes. The sample consisted of volleyball
athletes (n=208; 98 men and 110 women) and their coaches (n=20;
16 men and 4 women). Analysis showed that male volleyball players
rated somatic anxiety higher and were more affected by the verbal
aggressiveness of their coaches than female volleyball players. No
mean differences were significant for male and female coaches on
somatic
or
cognitive
anxiety,
self-confidence,
or
verbal
aggressiveness. Also, correlation between subscale scores for male
and female
volleyball players and coaches was
found. The
correlations of verbal aggressiveness with self-confidence and
anxiety were positive for these athletes, leading them to better
behavior. This relationship needs further examination in sport
settings.
Mellalieu,
et
al.,
(2006),
examined
whether
self-
confidence mediated the relationship between competitive anxiety
intensity and direction. Elite (n = 102) and non elite (n = 144)
participants
completed
the
self-confidence
subscale
of
the
52
Competitive Trait Anxiety Inventory-2 and the worry and somatic
subscales from the Sport Anxiety Scale. Consistent with procedures
recommended by Baron and Kenny (1986), linear regression
analyses were used. The findings for elite athletes revealed worry
intensity to significantly predict self-confidence and worry direction.
However, when self-confidence was controlled, worry intensity did
not predict worry direction over that which was significantly
predicted by self-confidence. Within the analysis for somatic
symptoms, only self-confidence was found to predict somatic
symptom direction. For the non elite athletes, worry and somatic
symptom intensity predicted both self-confidence and direction, and
direction when self-confidence was controlled. The findings for the
elite athletes suggested self-confidence mediates the relationship
between performers' worry symptoms and subsequent directional
interpretations. However, the findings suggested that high levels of
self-confidence and low symptom intensity were needed for non elite
athletes to demonstrate a less debilitative interpretation.
O’Brien, et al., (2005), investigated differences in the
labeling of symptoms associated with pre-competition anxiety and
self-confidence as a function of goal attainment expectation and
competition goal generation. Team sport performers (N = 96) were
divided into outcome, performance and process goal groups. Anxiety
intensity and direction, and self-confidence were then examined as a
function of goal expectancy (positive or negative) and perceived input
53
into goal production (input or no input). MANOVA and follow-up
ANOVA supported the study predictions. Specifically, participants
who reported positive expectations of goal achievement and
indicated some input into the goal generation process experienced
the most facilitative interpretations of cognitive symptoms and
greater self-confidence. The results highlighted the need to consider
how goals were generated when attempting to foster a sense of
control and helped athletes cope with the psychological demands of
competition.
Kais and Raudsepp, (2004), examined the influence of
competitive anxiety and self-confidence state responses upon
athletic performance. 66 male beach volleyball players completed
the translated and modified Competitive State Anxiety Inventory-2,
which included the original intensity scale and a direction scale of
Jones and Swain. Players' performance was scored from the video
records using a standard rating scales. Correlations indicated scores
on Direction subscale of modified Competitive State Anxiety
Inventory-2 and Self-confidence were moderately positively (r=.27 to
.51) correlated with different skill components and sum of skill
components of beach volleyball. Stepwise multiple regressions
indicated that, as anticipated, directional perceptions of cognitive
and somatic anxiety and self-confidence were significant predictors
of beach volleyball performance but accounted for only 42% of
variance. Original Intensity subscales of somatic and cognitive
54
anxiety did not predict performance. Findings support the notion
that direction of anxiety responses must be taken into consideration
when examining anxiety-performance association in sport.
Zchao kou, (2003), investigated a study on effects of
Cognitive Anxiety, Somatic Anxiety, Self-Confidence and Trait
Anxiety in Performance in Taiwanese Weightlifters. The result of the
study indicated that there were significant differences between male
and female weightlifters in somatic anxiety and self confidence; male
weight lifters were more stable in somatic state anxiety and they had
higher self-confidence than female weight lifters.
Craft,
et
al.,
(2003), investigated a study on the
relationship between the competitive state anxiety inventory-2 and
sport performance: a meta- analysis, the findings revealed that the
exploratory modeling showed that self-confidence displayed the
strongest and most consistent relationship with performance.
Hanton and Connaughton, (2002), examined performers'
retrospective explanations of the relationship between anxiety
symptoms, self-confidence, and performance. Interviews were used
to determine how the presence of symptoms and the accompanying
directional interpretation affected performance in six elite and six
subelite swimmers. Causal networks revealed that perceived control
was the moderating factor in the directional interpretation of anxiety
and not the experience of anxiety symptoms alone. Symptoms
55
perceived to be under control were interpreted to have facilitative
consequences for performance; however, symptoms not under
control were viewed as debilitative. Increases or decreases in selfconfidence were perceived to improve or lower performance.
Findings reveal how cognitive
and somatic information was
processed, what strategies were adopted, and how this series of
events related to performance.
Kjormo and Halvari, (2002), tested among 136 Norwegian
Olympic-level athletes yielded two paths related to performance. The
first path indicated that self-confidence, modeled as an antecedent
of competitive anxiety, is negatively correlated with anxiety.
Competitive
anxiety
in
turn
is
negatively
correlated
with
performance. The second path indicated that group cohesion is
positively correlated with group goal-clarity, which in turn is
positively correlated with performance. Competitive anxiety mediates
the relation between self-confidence and performance, whereas
group goal-clarity mediates the relation between group cohesion and
performance. Results from multiple regression analyses supported
the model in the total sample and among individual sport athletes
organized in training groups (n = 100). Among team sport athletes
(n = 36), personality and group measures were more strongly
intercorrelated than among individual sport athletes, and the
relation with performance was more complex for the former group.
56
The interaction of self-confidence and competitive anxiety was
related to performance among team sport athletes.
4. Summary of literature
The reviews are presented under the following three
sections, namely studies on motor variables (n=18) [Speed [n=8), leg
explosive power [n=7) and agility [n=3)], physiological variables
(n=17) [Resting pulse rate (n=2), Anaerobic power (n=6) and VO2
max (n=9)] and Psychological variables (n=17) [anxiety (n=5),
achievement motivation (n=4) and self confidence (n=8)].
A serious review of literature helped the scholar from the
methodological point of view too.
It was learnt that most of the
research studies cited in this chapter on analysis as the appropriate
methods for finding out suitable remedy.
The present study may serve as a foundation and main
ingredient for future research to enhance the athletic performance
variables.

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