Perfectionism and attitudes towards doping in junior athletes

Recent theory and research suggest that perfectionism is a personal factor contributing to athletes’ vulnerability to doping (using banned substances/drugs to enhance sporting performance). So far, however, no study has examined what aspects of perfectionism suggest a vulnerability in junior athletes. Employing a cross-sectional design, this study examined perfectionism and attitudes towards doping in 129 male junior athletes (mean age 17.3 years) differentiating four aspects of perfectionism: perfectionistic strivings, perfectionistic concerns, parental pressure to be perfect, and coach pressure to be perfect. In the bivariate correlations, only parental pressure showed a positive relationship with positive doping attitudes. In a multiple regression analysis controlling for the overlap between the four aspects, perfectionistic strivings additionally showed a negative relationship. Moreover, a structural equation model examining the relationships between all variables suggested that coach pressure had a negative indirect effect on attitudes towards doping via perfectionistic strivings. The findings indicate that perceived parental pressure to be perfect may be a factor contributing to junior athletes’ vulnerability to doping, whereas perfectionistic strivings may be a protective factor

Perfectionism and burnout in junior athletes: A three-month longitudinal study

Perfectionism in sports has been shown to be associated with burnout in athletes. Whether perfectionism predicts longitudinal changes in athlete burnout, however, is still unclear. Using a two-wave cross-lagged panel design, the present study examined perfectionistic strivings, perfectionistic concerns, and athlete burnout in 101 junior athletes (mean age 17.7 years) over 3 months of active training. When structural equation modeling was employed to test a series of competing models, the best-fitting model showed opposite patterns for perfectionistic strivings and perfectionistic concerns. Whereas perfectionistic concerns predicted increases in athlete burnout over the 3 months, perfectionistic strivings predicted decreases. The present findings suggest that perfectionistic concerns are a risk factor for junior athletes contributing to the development of athlete burnout whereas perfectionistic strivings appear to be a protective factor

Athletes’ perfectionism and reasons for training: Perfectionistic concerns predict training for weight control

Exercise and training for sports are associated with a number of psychological and health benefits. Research on exercise, however, suggests that such benefits depend on the reasons why individuals participate in sport. The present study investigated whether individual differences in perfectionism predicted different reasons for training and examined four dimensions of perfectionism (perfectionistic strivings, perfectionistic concerns, coach pressure to be perfect, parental pressure to be perfect) and three reasons for training (avoidance of negative affect, weight control, mood improvement) in 261 athletes (mean age 20.9 years). Regression analyses showed that perfectionistic concerns positively predicted avoidance of negative affect and weight control, whereas perfectionistic strivings positively predicted mood improvement. The findings suggest that individual differences in perfectionism help explain why athletes train for different reasons

Linking the performance of endurance runners to training and physiological effects via multi-resolution elastic net

A multiplicative effects model is introduced for the identification of the factors that are influential to the performance of highly-trained endurance runners. The model extends the established power-law relationship between performance times and distances by taking into account the effect of the physiological status of the runners, and training effects extracted from GPS records collected over the course of a year. In order to incorporate information on the runners' training into the model, the concept of the training distribution profile is introduced and its ability to capture the characteristics of the training session is discussed. The covariates that are relevant to runner performance as response are identified using a procedure termed multi-resolution elastic net. Multi-resolution elastic net allows the simultaneous identification of scalar covariates and of intervals on the domain of one or more functional covariates that are most influential for the response. The results identify a contiguous group of speed intervals between 5.3 to 5.7 m?s?1 as influential for the improvement of running performance and extend established relationships between physiological status and runner performance. Another outcome of multi-resolution elastic net is a predictive equation for performance based on the minimization of the mean squared prediction error on a test data set across resolutions

The reliability of measuring gross efficiency during high intensity cycling exercise

Purpose: To evaluate the reliability of calculating gross efficiency (GE) conventionally and using a back extrapolation (BE) method during high-intensity exercise (HIE). Methods: A total of 12 trained participants completed 2 HIE bouts (P1 = 4 min at 80% maximal aerobic power [MAP]; P2 = 4 min at 100%MAP). GE was calculated conventionally in the last 3 minutes of submaximal (50%MAP) cycling bouts performed before and after HIE (Pre50%MAP and Post50%MAP). To calculate GE using BE (BGE), a linear regression of GE submaximal values post-HIE were back extrapolated to the end of the HIE bout. Results: BGE was significantly correlated with Post50%MAP GE in P1 (r = .63; P = .01) and in P2 (r = .85; P = .002). Reliability data for P1 and P2 BGE demonstrate a mean coefficient of variation of 7.8% and 9.8% with limits of agreement of 4.3% and 4.5% in relative GE units, respectively. P2 BGE was significantly lower than P2 Post50%MAP GE (18.1% [1.6%] vs 20.3% [1.7%]; P = .01). Using a declining GE from the BE method, there was a 44% greater anaerobic contribution compared with assuming a constant GE during 4-minute HIE at 100%MAP. Conclusion: HIE acutely reduced BGE at 100%MAP. A greater anaerobic contribution to exercise as well as excess postexercise oxygen consumption at 100%MAP may contribute to this decline in efficiency. The BE method may be a reliable and valid tool in both estimating GE during HIE and calculating aerobic and anaerobic contributions

A model for performance enhancement in competitive cycling

A 3D cycling model is presented that combines bicycle dynamics, a tyre model, rider biomechanics and environmental factors into a single dynamic system. The system is constructed using Matlab toolboxes (SimMechanics/Simulink) with the aim of identifying mechanical mechanisms that can influence performance in a road cycling time trial. Initial conditions are specified and a variable step ODE solver numerically integrates solutions to the equations of motion. Initial validation compared rider-less self-stability presented in a published “benchmark” with model simulation and found an error of <1.5%. Model results included the weave eigenvalue becoming negative at 4.2 m/s and the capsize eigenvalue approaching a positive value at 6.1 m/s. The tyre model predicted peak front tyre slip and camber forces of 130 N and 17 N respectively which were within 0.9% of values reported in the literature. Experimental field validation compared actual and model predicted time taken by 14 experienced cyclists to complete a time trial over an undulating 2.5 mile road course. An error level of 1.4% (±1.5%) was found between actual and predicted time. This compares well with the average 1.32% error reported by existing road cycling models over simpler courses

Modeling Intermittent Running from a Single-visit Field Test

This study assessed whether the distance-time relationship could be modeled to predict time to exhaustion (TTE) during intermittent running. 13 male distance runners (age: 33 ± 14 years) completed a field test and 3 interval tests on an outdoor 400 m athletic track. Field-tests involved trials over 3600 m, 2400 m and 1200 m with a 30-min rest between each run. Interval tests consisted of: 1000 m at 107 % of CS with 200 m at 95 % CS; 600 m at 110 % of CS with 200 m at 90 % CS; 200 m at 150 % of CS with 200 m at 80 % CS. Interval sessions were separated by 24 h recovery. Field-test CS and D′ were applied to linear and non-linear models to estimate the point of interval session termination. Actual and predicted TTE using the linear model were not significantly different in the 1000 m and 600 m trials. Actual TTE was significantly lower (P = 0.01) than predicted TTE in the 200 m trial. Typical error was high across the trials (range 334–1709 s). The mean balance of D′ remaining at interval session termination was significantly lower when estimated from the non-linear model (− 21.2 vs. 13.4 m, P < 0.01), however no closer to zero than the linear model. Neither the linear or non-linear model could closely predict TTE during intermittent running

Motivation mediates the perfectionism–burnout relationship: A three-wave longitudinal study with junior athletes

Perfectionism in sports has been shown to predict longitudinal changes in athlete burnout. What mediates these changes over time, however, is still unclear. Adopting a self-determination theory perspective and using a three-wave longitudinal design, the present study examined perfectionistic strivings, perfectionistic concerns, autonomous motivation, controlled motivation, and athlete burnout in 141 junior athletes (mean age 17.3 years) over 6 months of active training. When multilevel structural equation modeling was employed to test a mediational model, a differential pattern of between- and within-person relationships emerged. Whereas autonomous motivation mediated the negative relationship that perfectionistic strivings had with burnout at the between- and within-person level, controlled motivation mediated the positive relationship that perfectionistic concerns had with burnout at the between-person level only. The present findings suggest that differences in autonomous and controlled motivation explain why perfectionism predicts changes in athlete burnout over time

The Effect of Cycling Intensity on Cycling Economy During Seated and Standing Cycling

BACKGROUND: Previous research has shown that cycling in a standing position reduces cycling economy compared with seated cycling. It is unknown whether the cycling intensity moderates the reduction in cycling economy while standing. PURPOSE: The aim was to determine whether the negative effect of standing on cycling economy would be decreased at a higher intensity. METHODS: Ten cyclists cycled in 8 different conditions. Each condition was either at an intensity of 50% or 70% of maximal aerobic power, at a gradient of 4% or 8% and in the seated or standing cycling position. Cycling economy and muscle activation level of 8 leg muscles were recorded. RESULTS: There was an interaction between cycling intensity and position for cycling economy (P = 0.03), the overall activation of the leg muscles (P = 0.02) and the activation of the lower leg muscles (P = 0.05). The interaction showed decreased cycling economy when standing compared with seated cycling, but the difference was reduced at higher intensity. The overall activation of the leg muscles and the lower leg muscles respectively increased and decreased, but the differences between standing and seated cycling were reduced at higher intensity. CONCLUSIONS: Cycling economy was lower during standing cycling than seated cycling, but the difference in economy diminishes when cycling intensity increases. Activation of the lower leg muscles did not explain the lower cycling economy while standing. The increased overall activation therefore suggests that increased activation of the upper leg muscles explains part of the lower cycling economy while standing