profile of different athletic levels, as shown by Fontana et al. 7 They used the logistic regression method to classify 3 levels of rugby athletes using anthropometric variables. Moreover, Jaksic et al 8 classified the morphological types of physical education university students using the multilayer
Biomechanical and Anthropometric Factors That Differentiate National- and Regional-Level Judo Players
Felipe Guimarães Teixeira, Paulo Tadeu Cardozo Ribeiro Rosa, Roger Gomes Tavares Mello, and Jurandir Nadal
Predicting the Presence of Active Schools: A National Survey of School Principals in the United States
Brian Dauenhauer, Taemin Ha, Collin Webster, Heather Erwin, Erin Centeio, Jillian Papa, and Charlene Burgeson
researchers to determine the percentages of active schools across different levels of the categorical variables and to assess associations within the variables. Significant variables from the chi-square analysis were added to a hierarchical logistic regression model. Control variables (ie, principal and
Renewable Energy Source Diffusion in Professional Sport Facilities
Liz Wanless, Chad Seifried, and Tim Kellison
. Data Analysis Analyses employed for this investigation span descriptive (for both RQs), multidiffusion model (RQ1), and logistic regression model (RQ2/hypotheses test). Descriptive statistics regarding stadia and adoptions of renewable energy sources were aggregated for the U.S. and Canadian sample
Physical Activity and Psychological Distress in Older Men: Findings From the New South Wales 45 and Up Study
Emma S. George, Louisa Jorm, Gregory S. Kolt, Hilary Bambrick, and Sanja Lujic
Physical activity is an important factor in healthy aging and has been shown to reduce depressive symptoms. This association, however, is relatively understudied in older men. This study was a cross-sectional analysis of the association between physical activity (Active Australia Survey) and psychological distress (Kessler-10). Participants were a sample of 17,689 men age ≥65 yr drawn from a large-scale Australian cohort study of people age 45 years and over (The 45 and Up Study). The likelihood of reporting high or very high levels of psychological distress decreased with increasing weekly sessions of physical activity. Compared with participants reporting no sessions of physical activity, the fully adjusted odds ratio for high or very high psychological distress was .66 (95% CI .51–.85) for men who undertook 1–6 sessions of physical activity per week and decreased to .57 (95% CI, .43–.79) for men who reported 16 or more weekly sessions. The cross-sectional findings show that older men who are more active are less likely to report psychological distress, regardless of their level of functional limitation. Further research, informed by these findings, is required to investigate causal pathways and the temporal sequence of events.
Mediating Effects of Peripheral Vision in the Life Event Stress/Athletic Injury Relationship
Tracie J. Rogers and Daniel M. Landers
The mediating effect of peripheral narrowing in the negative life event stress (N-LES)/athletic injury relationship was investigated. LES and other psychosocial variables were measured, and peripheral vision was assessed in nonstressful (practice day) and stressful (game day) sport situations. Results showed that total LES, N-LES, and psychological coping skills significantly contributed to the prediction of the occurrence of athletic injury. Additionally, psychological coping skills buffered the N-LES/athletic injury relationship. Peripheral narrowing during stress significantly mediated 8.1% of the N-LES/athletic injury relationship. The findings support the predictions of the model of stress and injury, provide evidence for peripheral narrowing as a mechanism in the LES/athletic injury relationship, and suggest directions for future research examining mediating effects in the model of stress and injury.
Using Athletes’ World Rankings to Assess Countries’ Performance
Rita M. Malcata, Tom J. Vandenbogaerde, and Will G. Hopkins
There is a need for fair measures of country sport performance that include athletes who do not win medals.
To develop a measure of country performance based on athlete ranks in the sport of swimming.
Annual top-150 ranks in Olympic pool-swimming events were downloaded for 1990 through 2011. For each athlete of a given rank, a score representing the athlete’s performance potential was estimated as the proportion of athletes of that rank who ever achieved top rank. A country’s scores were calculated by summing its athletes’ scores over all 32 events. Reliability and convergent validity were assessed via year-to-year correlations and correlations with medal counts at major competitions. The method was also applied to ranks at the 2012 Olympics to evaluate countries’ swimming performance.
The performance score of an athlete of a given rank was closely approximated by 1/rank. This simpler score has 1 practical interpretation: An athlete ranked 7th (for example) has a chance of 1/7 of ever achieving top rank; for purposes of evaluating country performance, 7 such athletes are equivalent to 1 athlete of the top rank. Country scores obtained by summing 1/rank of the country’s athletes had high reliability and validity. This approach produced scores for 168 countries at the Olympics, whereas only 17 countries won medals.
The authors used the sport of swimming to develop a fair and inclusive measure representing a country’s performance potential. This measure should be suitable for assessing countries in any sports with world rankings or with athletes at major competitions.
Gait Slip-Induced Fall-Type Assessment Based on Regular Gait Characteristics in Older Adults
Shuaijie Wang, Yi-Chung (Clive) Pai, and Tanvi Bhatt
Chicago. Table 1 Predictive Validity of Demographic Variables Using Univariate Logistic Regression for 105 Fallers (Feet-Forward Falls: n = 44; Split Falls: n = 61) Variables Mean (SD) P SE Sen Spe Acc Fwd fall Split fall Weight, kg 68.9 (13.4) 78.9 (13.2) <.001* 0.02 54.5 78.7 68.6 Height, m 1.65 (0
Correlates of Sedentary Time Among Children and Adolescents in Ethiopia: A Cross-Sectional Study
Sibhatu Biadgilign, Tennyson Mgutshini, Bereket Gebremichael, Demewoz Haile, Lioul Berhanu, Stanley Chitekwe, and Peter Memiah
showed statistically significant associations at P < .2 in the bivariate analysis, were included in the final regression model building for logistic regression models. Multivariable logistic regression models with robust estimation of standard errors were fitted to determine the associations between
Does Physical Fitness Predict Future Karate Success? A Study in Young Female Karatekas
Óscar Martínez de Quel, Ignacio Ara, Mikel Izquierdo, and Carlos Ayán
, Hedge g effect sizes were calculated for each anthropometric and fitness variable. Effect sizes were interpreted using Hopkins 15 scale: <0.2 (trivial), 0.2 to 0.6 (small), 0.6 to 1.2 (moderate), 1.2 to 2.0 (large), and 2.0 to 4.0 (very large). Binary logistic regression models were built to
Application of Convolutional Neural Network Algorithms for Advancing Sedentary and Activity Bout Classification
Supun Nakandala, Marta M. Jankowska, Fatima Tuz-Zahra, John Bellettiere, Jordan A. Carlson, Andrea Z. LaCroix, Sheri J. Hartman, Dori E. Rosenberg, Jingjing Zou, Arun Kumar, and Loki Natarajan
body-fixed accelerometer, 62 studies were identified as using a variety of ML models, including artificial neural networks (32), support vector machines (18), random forest (RF) (12), decision trees (11), and logistic regression (LR) (7) ( Farrahi, Niemelä, Kangas, Korpelainen, & Jämsä, 2019 ). Farrahi