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Is Open Access

Positive outcome expectancy mediates the relationship between social influence and Internet addiction among senior high-school students

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      Background and aims

      Based on the foundations of Bandura’s social cognitive theory and theory of triadic influence (TTI) theoretical framework, this study was designed to examine the mediating role of positive outcome expectancy of Internet use in the relationship between social influence and Internet addiction (IA) in a large representative sample of senior high-school students in Taiwan.


      Using a cross-sectional design, 1,922 participants were recruited from senior high schools throughout Taiwan using both stratified and cluster sampling, and a comprehensive survey was administered.


      Structural equation modeling and bootstrap analyses results showed that IA severity was significantly and positively predicted by social influence, and fully mediated through positive outcome expectancy of Internet use.

      Discussion and conclusions

      The results not only support Bandura’s social cognitive theory and TTI framework, but can also serve as a reference to help educational agencies and mental health organizations design programs and create policies that will help in the prevention of IA among adolescents.

      Related collections

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         P Shrout,  N Bolger (2002)
        Mediation is said to occur when a causal effect of some variable X on an outcome Y is explained by some intervening variable M. The authors recommend that with small to moderate samples, bootstrap methods (B. Efron & R. Tibshirani, 1993) be used to assess mediation. Bootstrap tests are powerful because they detect that the sampling distribution of the mediated effect is skewed away from 0. They argue that R. M. Baron and D. A. Kenny's (1986) recommendation of first testing the X --> Y association for statistical significance should not be a requirement when there is a priori belief that the effect size is small or suppression is a possibility. Empirical examples and computer setups for bootstrap analyses are provided.
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          A comparison of methods to test mediation and other intervening variable effects.

          A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect.

            Author and article information

            [ 1 ]Department of Educational Psychology and Counseling, National Taiwan Normal University , Taipei City, Taiwan
            [ 2 ]Department of Counseling and Guidance, National University of Tainan , Tainan, Taiwan
            [ 3 ]Center for Studies of Psychological Application & School of Psychology, South China Normal University , Guangzhou, China
            Author notes
            [* ]Corresponding author: Min-Pei Lin; Department of Educational Psychology and Counseling, National Taiwan Normal University, No. 162, Sec. 1, Heping E. Rd., Da-an District, Taipei City 106, Taiwan; Phone: +886 2 7734 3770; Fax: +886 2 2341 3865; E-mail: lmmpp@
            Journal of Behavioral Addictions
            J Behav Addict
            Akadémiai Kiadó (Budapest )
            27 June 2018
            June 2018
            : 7
            : 2
            : 292-300
            © 2018 The Author(s)

            This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

            Figures: 1, Tables: 1, Equations: 0, References: 53, Pages: 9
            Funding sources: This study was supported in part by the Ministry of Science and Technology in Taiwan (grant no.: MOST 106-2511-S-003-034-MY2 and MOST 102-2511-S-003-016-MY3).


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