Psychological factors affecting equine performance

For optimal individual performance within any equestrian discipline horses must be in peak physical condition and have the correct psychological state. This review discusses the psychological factors that affect the performance of the horse and, in turn, identifies areas within the competition horse industry where current behavioral research and established behavioral modification techniques could be applied to further enhance the performance of animals. In particular, the role of affective processes underpinning temperament, mood and emotional reaction in determining discipline-specific performance is discussed. A comparison is then made between the training and the competition environment and the review completes with a discussion on how behavioral modification techniques and general husbandry can be used advantageously from a performance perspective

Grouping of decathlon disciplines

The 10 disciplines in the decathlon can be broadly characterised as running, jumping and throwing. However, these simplistic characteristics may not represent the groupings defined by performances in the decathlon. The identification of groups may reveal a recondite advantage for athletes who excel in particular disciplines. Therefore this study used cluster analysis to determine the groupings inherent within the decathlon disciplines. The data set was derived from the top 173 decathletes between the years 1986 to 2005. Six clustering methods were applied to a Euclidean proximity matrix. The highest number of clusters common to all the methods was accepted as the solution. All six methods produced the same 3-cluster ([100m 400m 110H LJ PV HJ][SP DT JT][1500m]), 4-cluster ([100m 400m 110H LJ PV][SP DT JT][HJ][1500m]) and 5-cluster ([100m 400m 110mH LJ][SP DT JT][PV][HJ][1500m]) solutions. Stability tests confirmed the consistency of all the solutions. The 10 disciplines of the decathlon form into five groupings, which can be adequately explained from a physiological perspective. The clustering suggests that athletes who perform better at the sprint/track disciplines may obtain an advantage in the decathlon

Genetic predictors of match performance in sub-elite Australian football players: A pilot study

The current study aimed to determine whether previously identified candidate polymorphisms were associated with match performance in sub-elite Australian Rules Football (ARF) players. The genotypes of thirty players were analysed along with 3x1-kilometre time trial results, ARF-specific skill assessments (handball and kicking), and match performance (direct game involvements) per minute (DGIs/min) to investigate if there was a relationship between any of the variables. Results support previous findings that aerobic time trials are a significant predictor of DGIs/min in sub-elite ARF players. Significant associations were found for genotypes ADRB2 CC (p = .001), PPARGC1A AA (p = .001), PPARGC1A AG (p \u3c .001), ACE ID (p \u3c .001), COMT AA (p = .003), BDNF AG (p = .008), ADRB1 CC (p = .018) and ADRB3 CC (p = .010) and the 3x1-kilometre time trials (p \u3c .001). In the current study, a variant in the DRD2 gene was a strong predictor of handball possessions during a match. Significance was seen for variants in the BDNF and COMTgenes when the kicking and handball skill test results were combined and used in a linear mixed model to predict DGIs/min, suggesting a potential relationship with motor learning. The confirmation of genetic predictors of player performance in a team sport, such as ARF, suggests a portion of the physiological mechanisms of skill and ARF-specific talent may be explained by the expression of a specific number of genes

Thriving Arts: Thriving Small Communities

Presents findings from a study of ten rural Minnesota communities to identify factors related to successful community arts development. Includes recommendations to inform future investment in the arts

Influence of Different Performance Levels on Pacing Strategy During the Women's World Championship Marathon Race.

Purpose To analyse pacing strategies displayed by athletes achieving differing levels of performance during an elite level marathon race. Methods Competitors in the 2009 IAAF Women’s Marathon Championship were split into Groups 1, 2, 3, and 4 comprising the first, second, third, and fourth 25% of finishers respectively. Final, intermediate, and personal best (PB) times of finishers were converted to mean speeds, and relative speed (% of PB speed) was calculated for intermediate segments. Results Mean PB speed decreased from Group 1 to 4 and speed maintained in the race was 98.5 + 1.8%, 97.4 + 3.2%, 95.0 + 3.1% and 92.4 + 4.4% of PB speed for Groups 1-4 respectively. Group 1 was fastest in all segments and differences in speed between groups increased throughout the race. Group 1 ran at lower relative speeds than other groups for the first two 5 km segments, but higher relative speeds after 35km. Significant differences (P<0.01) in the percentage of PB speed maintained were observed between Groups 1 and 4, and 2 and 4 in all segments after 20 km, and Groups 3 and 4 from 20-25 km and 30-35 km. Conclusions Group 1 athletes achieved superior finishing times relative to their PB than athletes in other Groups who selected unsustainable initial speeds resulting in subsequent significant losses of speed. It is suggested that psychological factors specific to a major competitive event influenced decision making by athletes and poor decisions resulted in final performances inferior to those expected based on PB times

Understanding Faculty Out-of-Class Interaction with Undergraduate Students at a Research University

While much has been published about the ways in which students gain from contact with faculty, much less is known about the patterns and correlates of such contact for faculty members. Drawing upon data from a survey of faculty (n=901) conducted at a large, highly selective, research-extensive university in spring 2004, this study explores the factors that promote or inhibit faculty members’ engagement in two types of out-of-class interactions with undergraduate students: research-based activities and other out-of-class activities that are less narrowly focused on academic issues. We test four explanations of faculty engagement using OLS regression, and estimate separate models for research-based and other types of out-of-class involvement. Our results provide little support for two of the most prevalent explanations of factors that inhibit faculty involvement: competing time demands, and a lack of institutional rewards or supports for out-of-class interaction. Two other explanations received more support. First, faculty members’ personal values and beliefs were strongly associated with their extent of engagement in out-of-class interactions, particularly for non-research based interactions. Second, the block of variables reflecting faculty members’ interpersonal knowledge and abilities had the strongest association with engagement in out-of-class interactions; this relationship was nearly twice as strong for activities that were not research-based than for those that were circumscribed as research. Our findings suggest that institutions may best be able to support out-of-class interactions between faculty and undergraduate students by brokering information flows concerning opportunities for engagement and the actual “how to’s” of making such interactions work

Faculty Recital: Pavel Nersessian, piano, October 11, 2018

This is the concert program of the Faculty Recital: Pavel Nersessian, piano on Thursday, October 11, 2018 at 8:00 p.m., at the Tsai Performance Center, 685 Commonwealth Avenue. Works performed were Chants du Rhin (Songs of the Rhine) by Georges Bizet, Drei Klavierstücke D. 946 by Franz Schubert, Kinderszenen Op. 15 by Robert Schumann, and Sonata No. 3 Op. 58 by Frédéric Chopin. Digitization for Boston University Concert Programs was supported by the Boston University Humanities Library Endowed Fund

Performance profiling as an intelligence-led approach to antidoping in sports

The efficient use of testing resources is crucial in the fight against doping in sports. The athlete biological passport relies on the need to identify the right athletes to test, and the right time to test them. Here we present an approach to longitudinal tracking of athlete performance to provide an additional, more intelligence-led approach to improve targeted antidoping testing. The performance results of athletes (male shot putters, male 100 m sprinters, and female 800 m runners) were obtained from a performance results database. Standardized performances, which adjust for average career performance, were calculated to determine the volatility in performance over an athlete's career. We then used a Bayesian spline model to statistically analyse changes within an athlete's standardized performance over the course of a career both for athletes who were presumed "clean" (not doped), and those previously convicted of doping offences. We used the model to investigate changes in the slope of each athlete's career performance trajectory and whether these changes can be linked to doping status. The model was able to identify differences in the standardized performance of clean and doped athletes, with the sign of the change able to provide some discrimination. Consistent patterns of standardized performance profile are seen across shot put, 100 m and 800 m for both the clean and doped athletes we investigated. This study demonstrates the potential for modeling athlete performance data to distinguish between the career trajectories of clean and doped athletes, and to enable the risk stratification of athletes on their risk of doping.Peer reviewe

The Relationship Between Sport Participation, Perceived Athletic Competence and Performance in University Sprinters

Purpose: There is a need for research that investigates confidence, performance, and previous sports involvement among particular sports such as in track and field sprinters. The objective of this study was to investigate relations between previous sport participation, perceived athletic competence, and performance results in university track and field sprinters. Methods: The perceived athletic competence scale and previous sport participation questionnaire were implemented in the form of an online survey. The best performance times were collected from an online results database. All of the participants were enrolled in university and were members of their respective school’s track and field team. Measures of variability and descriptive statistics were calculated, and Analysis of Variance and t-tests were implemented to analyze potential differences amongst the variables of this study. Results: There were a total of 42 university track and field sprinters between the age of 18 and 23. The highest participated sports (sum) were track and field sprints (624), soccer (234), hockey (189), and basketball (164). A repeated measure ANOVA revealed a significant decrease in sports participation across all and between each of the three age groups (ages 8 to 13, 14 to 17, and 18+). Sports participation was the highest in the 8 to 13 age group. A bivariate correlation and linear regression analyses showed statistical insignificance between sport participation and perceived athletic competence. There was a low positive, but not statistically significant relationship from the 8 to 13 age group. Lastly, there was a statistically non-significant positive correlation for the first age (8 to 13) group and sprint performance times. Conclusion: The findings of the study contribute to the areas of sport participation, sport specialization, and athlete development by confirming what is already presently known while adding new support for track and field sprinting as a late specialization sport and the need for further analysis and investigation in the future with a more diverse sample and a larger sample size