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significant interaction effects. We then performed a two-way ANOVA on the brain activation for each trial type, to find a background × group interaction effect (Supplementary materials, Tables S2 and S3). Moreover, a correlation analysis was

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suggested that cortical thickness is not affected by ICV ( Buckner et al., 2004 ). To assess the brain-behavior relationships, we performed a correlation analysis for gray matter alterations (GMV and cortical thickness in the OFC and the ACC) and the self

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activity and then multiple comparisons between groups used the method of the least significant difference (LSD). Thirdly, using Pearson's correlation analysis to measure the association between physical activity and MPA. Lastly, using Hayes's (2013

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Journal of Behavioral Addictions
Authors: Hyeonseok Jeong, Jin Kyoung Oh, Eun Kyoung Choi, Jooyeon Jamie Im, Sujung Yoon, Helena Knotkova, Marom Bikson, In-Uk Song, Sang Hoon Lee, and Yong-An Chung

correlation analysis between rCMRglu and behavioral characteristics are presented in Supplementary Tables 2 and 3 . At the baseline, rCMRglu in the abovementioned cluster had negative relationships with scores of BAS-fun seeking ( β = −0.54, P = 0.004) and

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since 1st bought LB Boys 0.03 −0.13 −0.04 −0.08 Girls −0.17* −0.07 0.08 −0.11 Notes: * P < 0.05 using the Holm-Bonferroni groupwise error adjustment for multiple comparisons. Loot box Behavioural Correlates A partial correlational analysis was conducted

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Journal of Behavioral Addictions
Authors: Francesco Del Prete, Trevor Steward, Juan F. Navas, Fernando Fernández-Aranda, Susana Jiménez-Murcia, Tian P. S. Oei, and José C. Perales

Non-parametric correlational analysis (Spearman’s rho) was used to test GRCS-S convergent validity with SOGS and specificity with MultiCAGE alcohol and drug scores [using the validity sample ( n  = 137), and the whole factor analysis sample ( n  = 500

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. The results of correlation analysis are shown in Table  2 . According to the results, all subscale scores of the adult ADHD symptoms showed significant correlations with IA, childhood ADHD, AUDIT-K scores, depression, and anxiety symptoms. On the other

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, Scharkow, & Quandt, 2013 ; Kim et al., 2016 ; Männikkö, Billieux, & Kääriäinen, 2015 ; Peng & Liu, 2010 ; Rehbein, Psych, Kleimann, Mediasci, & Mößle, 2010 ). The results from the Pearson’s correlation analysis between both self-rated life satisfaction

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 = .85. Correlations between attentional, evaluative biases, and urge to be online for SNS Internet users To conduct correlational analysis, the following calculations were made: (a) for the gaze dwell time, the mean

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. Table  2 presents the results of zero-order correlation analysis between MSPSS, BSMAS, FSFI (at baseline and follow-up), anxiety (at baseline and follow-up), depression (at baseline and follow-up), FSDS-R (at baseline and follow-up), and URCS. The

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