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Sasha Gorrell and Drew A. Anderson

entered as covariates in both models. Results Preliminary Analyses Analyses included bivariate correlations assessing the relation of all variables within the study (see Table  1 ). Descriptive statistics for all variables of interest are presented in Table  2 . Table 1 Bivariate Correlations for

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J.D. DeFreese and Alan L. Smith

levels of social support and low-to-moderate levels of negative social interactions for all study waves relative to response set options. Bivariate correlations among aggregate means of study variables (see Table  2 ) were significant, in expected directions, and consistent with athlete burnout research

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Sofie Kent, Kieran Kingston and Kyle F. Paradis

mentioned, data were then screened for multivariate outliers and tested for normality, linearity, and homoscedasticity ( Tabachnick & Fidell, 2007 ). Evaluation of assumptions for carrying out multiple regression analysis included Pearson’s bivariate correlations and collinearity diagnostics and assessment

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Shelby Waldron, J.D. DeFreese, Brian Pietrosimone, Johna Register-Mihalik and Nikki Barczak

skewness and kurtosis values, and pairwise scatterplots. In addition, all six psychometric scales demonstrated acceptable internal consistency reliability (α > 0.70). Descriptive statistics and bivariate correlations were performed to examine relationships among targeted study variables. Confirmatory

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Maria Grazia Monaci and Francesca Veronesi

scores were computed for each factor. Table 1 Descriptive Statistics and Correlations Between the Study Variables in Male and Female Tennis Players 1 2 3 4 5 6 7 8 9 Mean SD 1. Femininity — .16 −.17 .13 −.02 −.13 −.13 .08 −.14 3.63 0.57 2. Masculinity − .33 — −.06 .21 .01 − .22 −.02 − .27 .20 3.59 0.64 3

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J.D. DeFreese, Travis E. Dorsch and Travis A. Flitton

removed; therefore, we opted to retain both cases in the final analyses, which are based on the 214 valid cases sampled. Descriptive Statistics Means, standard deviations and bivariate correlations for study variables are presented in Table  1 . Burnout and engagement means and standard deviations were

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Emily Kroshus, Sara P.D. Chrisman, David Coppel and Stanley Herring

what to do if a student is experiencing a mental health crisis, with response options of Yes/ No/ I don’t know. Demographic characteristics Coaches indicated their sex and age. Analysis Descriptive statistics were calculated for all variables. Pearson pairwise correlations were conducted between

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Ralph Appleby, Paul Davis, Louise Davis and Henrik Gustafsson

multivariate analysis. Firstly, descriptive statistics and bivariate correlations were conducted on all of the variables. Secondly, to assess whether the proposed TBQ (adapted from Raedeke & Smith, 2001 ) is a reliable measure of an athlete’s perception of teammates’ burnout. Confirmatory Factor Analysis (CFA

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Martin J. Turner, Stuart Carrington and Anthony Miller

, where present data was equal to norm data. Correlation coefficients (Table  2 ) revealed that all irrational beliefs were positively and significantly related to all psychological distress variables, and with each other. These inferential statistics, alongside past research ( DiLorenzo et al., 2007

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Laura K. Fewell, Riley Nickols, Amanda Schlitzer Tierney and Cheri A. Levinson

symptomatology and impairment, depression, worry, and BMI (in AN) between the athlete and non-athlete groups at treatment admission. Meng’s test of differences ( Meng, Rosenthal, & Rubin, 1992 ) was also conducted to test for differences among zero-order correlations of ED symptomatology, depression, worry, and