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Journal of Behavioral Addictions
Authors: Giacomo Grassi, Stefano Pallanti, Lorenzo Righi, Martijn Figee, Mariska Mantione, Damiaan Denys, Daniele Piccagliani, Alessandro Rossi, and Paolo Stratta

control group Correlation analysis Pearson product-moment correlation coefficients between clinical variables (symptom severity, illness duration, presence or history of tics, presence

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). Standardized root mean squared residual (SRMR), was also computed, with its value <0.08 representing an acceptable fit. Descriptive statistics, internal consistency (≥0.70 representing a satisfactory reliability; Cortina, 1993 ), and correlation analysis were

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.02. Concurrent validity was tested by correlational analysis, whereas Cronbach’s αs were computed to ensure the internal consistency of the (sub)scale. Since different types of gamers are expected to exhibit different configurations of IGD symptoms

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. Statistical analysis A cross-sectional correlational analysis was conducted. All analyses were conducted in SPSS 22. First, Student’s t was used to measure the differences between gamblers and non-gamblers in pathological gambling, emotion

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, descriptive statistics regarding general smartphone use were calculated. Then, correlational analysis was conducted. Finally, to delineate the factors underlying problematic smartphone use, multiple regression analysis was performed using problematic

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Journal of Behavioral Addictions
Authors: Ana Estévez, Paula Jáuregui, Inmaculada Sánchez-Marcos, Hibai López-González, and Mark D. Griffiths

), a correlational analysis using Pearson’s r was conducted to understand the relationship between attachment, gambling disorder, problematic Internet use, video game addiction, and alcohol and drug abuse (Table  2 ). Results showed that the addictive

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's scores on an established social media engagement questionnaire (SMES), and two ‘addictive’ severity scales (BSNAS, SMAQ), mean scores and variability are presented in Table 1 . A Pearson's correlation analysis showed that there were moderate

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according to structures defined in the white matter (WM) Atlas ( Oishi, Faria, Van Zijl, & Mori, 2010 ). Those anatomical regions were used to run correlation analysis with symptoms measured by the Sexual Addiction Screening Test ( Gola et al., 2016 ) and

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Journal of Behavioral Addictions
Authors: Bernadette Kun, Zsofia K. Takacs, Mara J. Richman, Mark D. Griffiths, and Zsolt Demetrovics

using correlation analysis between any personality variable and work addiction. Compared to the previous meta-analytic studies, the present study (i) clearly differentiated between “workaholism” and “work addiction” and only included those studies which

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Journal of Behavioral Addictions
Authors: András N. Zsidó, Gergely Darnai, Orsolya Inhóf, Gábor Perlaki, Gergely Orsi, Szilvia Anett Nagy, Beatrix Lábadi, Kata Lénárd, Norbert Kovács, Tamás Dóczi, and József Janszky

separately for the two groups to test for the direction of the correlation between cortical thickness and trait impulsivity. The significance value of a correlation analysis is highly dependent on the sample size, such that the probability of type II error

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