Search Results

You are looking at 61 - 70 of 72 items for :

  • "correlation analysis" x
  • Behavioral Sciences x
  • Refine by Access: All Content x
Clear All
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

Open access
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

Open access

). 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

Open access

'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

Open access

. , & Aiken , L. S. ( 2003 ). Applied multiple regression/correlation analysis for the behavioral science ( 3rd ed. ). Mahwah, NJ : Lawrence Erlbaum . Conklin , C. A. , Robbins , N. , Perkins , K. A. , Salkeld , R. P. , & McClernon , F. J

Open access

, 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

Open access
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

Open access
Journal of Behavioral Addictions
Authors: Eszter Kotyuk, Anna Magi, Andrea Eisinger, Orsolya Király, Andrea Vereczkei, Csaba Barta, Mark D. Griffiths, Anna Székely, Gyöngyi Kökönyei, Judit Farkas, Bernadette Kun, Rajendra D. Badgaiyan, Róbert Urbán, Kenneth Blum, and Zsolt Demetrovics

. mean age for lifetime amphetamine users: 22.52 ± 3.1 years, mean age for those who never used amphetamine in their lifetime: 22.12 ± 3.1 years). In case of the assessed potentially addictive behaviors, correlational analysis showed a negative

Open access
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

Open access

. , Cohen , P. , West , S. G. , & Aiken , L. S. ( 2003 ). Applied multiple regression/correlation analysis for the behavioral sciences ( 3rd ed. ). Mahwah, NJ : Lawrence Erlbaum Associates

Open access