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Jason C. Immekus, Franklin Muntis and Daniela Terson de Paleville

. Descriptive statistics were used to examine students’ standing across the study variables. Spearman rank-order correlations were used to estimate the strength and direction of the variables given the ordinal nature of several variables (e.g., grades). Correlations also served to gather convergent validity

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Giovanni Mario Pes, Maria Pina Dore, Alessandra Errigo and Michel Poulain

sleep (Sleep Time, ST), and the Resting Index (RI%), calculated by the formula (RT / ST × 100). Statistical Analysis Comparisons between groups were performed using the non-parametric Mann-Whitney U-test for continuous and ordinal variables, and Pearson’s χ 2 test for categorical variables. Correlation

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Marcus Colon, Andrew Hodgson, Eimear Donlon and James E.J. Murphy

effect on age-related telomere shortening with studies ( LaRocca et al., 2010 ; Østhus et al., 2012 ) showing a positive correlation between maximal oxygen intake V ˙ O 2 max and TL. Krauss et al. ( 2011 ) have even gone as far as showing increased exercise capacity had longer telomeres equating to

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Ciarán P. Friel and Carol Ewing Garber

data are reported as means and SD s for continuous variables, while frequencies and percentages are given for categorical variables. To evaluate associations between each dimension of motivational regulations and PA, bivariate correlations and internal consistency reliability (Cronbach’s alpha) were

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Ian David Boardley, Doris Matosic and Mark William Bruner

), middle (6–8 weeks), and end (12–16 weeks) of the regular season. Results Data Screening, Descriptive Statistics, Scale Reliabilities, and Correlations There were just eight missing data points out of the 34,188 responses, representing just 0.02% of the study data. Normality of all study variables was

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Pai-Yun Cheng, Hsiao-Feng Chieh, Chien-Ju Lin, Hsiu-Yun Hsu, Jia-Jin J. Chen, Li-Chieh Kuo and Fong-Chin Su

tasks. A Pearson correlation test was conducted for the purpose of revealing the relationship between the EN value, the dominant hand subtest from the Purdue Pegboard Test, and the NIRS signal. Results EN Value The EN values of 15 young adults and 15 older adults were collected to reveal the differences

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Salomé Aubert, Joel D. Barnes, Nicolas Aguilar-Farias, Greet Cardon, Chen-Kang Chang, Christine Delisle Nyström, Yolanda Demetriou, Lowri Edwards, Arunas Emeljanovas, Aleš Gába, Wendy Y. Huang, Izzeldin A.E. Ibrahim, Jaak Jürimäe, Peter T. Katzmarzyk, Agata Korcz, Yeon Soo Kim, Eun-Young Lee, Marie Löf, Tom Loney, Shawnda A. Morrison, Jorge Mota, John J. Reilly, Blanca Roman-Viñas, Natasha Schranz, John Scriven, Jan Seghers, Thomas Skovgaard, Melody Smith, Martyn Standage, Gregor Starc, Gareth Stratton, Tim Takken, Tuija Tammelin, Chiaki Tanaka, David Thivel, Richard Tyler, Alun Williams, Stephen H.S. Wong, Paweł Zembura and Mark S. Tremblay

). 38 Findings suggested the presence of a complex variety of strengths and limitations across the participating countries, with some universal patterns emerging when comparing countries by continent, HDI, or income inequality. For example, a strong positive correlation was found between the source of

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Antje Hill, Linda Schücker, Norbert Hagemann and Bernd Strauß

assumption can be explained by correlations between heartbeat perception and the perception of signals of other modalities, such as gastrointestinal signals ( Herbert, Muth, Pollatos, & Herbert, 2012 ). There is also evidence of existing differences between individuals in the awareness of interoceptive

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Cody L. Sipe, Kevin D. Ramey, Phil P. Plisky and James D. Taylor

effect in the study sample, which limited the analyses. Two studies have reported significant positive correlations between lower body strength (another factor for fall risk) and YBT-LQ in older women ( Lee, Kim, Ha, & Oh, 2014 ; Lee et al., 2015 ) indicating that it might be a useful test. To determine

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Juliessa M. Pavon, Richard J. Sloane, Carl F. Pieper, Cathleen S. Colón-Emeric, David Gallagher, Harvey J. Cohen, Katherine S. Hall, Miriam C. Morey, Midori McCarty, Thomas L. Ortel and Susan N. Hastings

, 2016 ). Despite the need for information about patient mobility, it is not clear how consistently activity data is collected and displayed in electronic health records (EHRs). In this study, we examined (a) the availability of physical activity information in the EHR; (b) the correlation between