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Annamari Maaranen, Judy L. Van Raalte and Britton W. Brewer

of physical well-being, the level of energy, and the level of perceived life stress. In addition to the visual inspection of the graphs, intraindividual Pearson correlations were calculated between: (a) both of the flikikammo severity variables (severity of the problem and confidence to perform the

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Clara Teixidor-Batlle, Carles Ventura Vall-llovera, Justine J. Reel and Ana Andrés

in the item-total correlation was deleted. As suggested by Floyd and Widaman ( 1995 ), a cross-validation procedure was applied to the data to assess the internal structure of the instrument; the participants were randomly assigned to one of two groups. In Group 1, the authors conducted an

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Leilani A. Madrigal, Vincenzo Roma, Todd Caze, Arthur Maerlender and Debra Hope

demonstrated through Pearson correlations with existing measures and using the Bonferroni adjustment to correct for multiple comparisons. Results Sample Characteristics A one-way ANOVA was used to determine group differences on various measures between individuals still competing in sports and individuals who

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Alexander T. Latinjak

-week interval between test and retest. It was used to check the stability of the questionnaire across time. The intra-class correlation with 95% CI using a two-way random model (intra-class correlation coefficient [ICC]) was calculated, taking scores of .81 or above as excellent, .61–.80 as good, .41–.60 as

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Byron L. Zamboanga, Nathan T. Kearns, Janine V. Olthuis, Heidemarie Blumenthal and Renee M. Cloutier

subscales based on the revised 7-factor structure and item loadings reported in Zamboanga et al. ( 2019 ). Data Analytic Plan Test-retest reliability To assess for test-retest reliability, we calculated intraclass correlation coefficients (ICCs) for each subscale on the MPDG ( Weir, 2005 ). Importantly

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Esmie P. Smith, Andrew P. Hill and Howard K. Hall

depressive symptoms over time (vulnerability model), (b) burnout and depressive symptoms predicts perfectionism over time (complication/scar model), or (c) the relationship is reciprocal over time (reciprocal relations model). Cross-lagged panel analysis consists of three types of correlations; synchronous

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Jeffrey B. Ruser, Mariya A. Yukhymenko-Lescroart, Jenelle N. Gilbert, Wade Gilbert and Stephanie D. Moore

. Alternative mediation possibilities were ruled out in data analysis. This mediation suggested that more grateful student-athletes were likely to perceive greater social support and be less burned out. In a different study that moved beyond correlational research, it was found that a gratitude-based group

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Shelby J. Martin and Timothy Anderson

was used to determine significant differences in general mental-health help-seeking intentions versus EP help-seeking intentions. Pearson’s bivariate correlations were examined among EP, stigma, EP help-seeking intentions, and negative perfectionism. Given the presence of significant correlations

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Stine Nylandsted Jensen, Andreas Ivarsson, Johan Fallby and Anne-Marie Elbe

confidentially, and that the participants could quit the survey at any time. Analyses All analyses were performed using SPSS Version 24. In addition to conducting descriptive statistics, correlations and two linear regression analyses were performed (with anxiety and depression as independent variables

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Erika D. Van Dyke, Aaron Metzger and Sam J. Zizzi

perfectionism ( r  = .74), concern over mistakes ( r  = .69), and doubts about actions ( r  = .75). It is important to note that negative relationships are reflected in the positive correlations reported because performance improvement is measured through decreased mile time. Although the links between