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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