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      The Relationship Between Self-Control and Internet Addiction Among Students: A Meta-Analysis

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          Abstract

          As past studies of self-control and Internet addiction showed mixed results, this meta-analysis of 83 primary studies with 80,681 participants determined whether (a) these students with less self-control had greater Internet addiction, and (b) age, culture, gender, Internet addiction measures, or year moderated these relations. We used a random-effects meta-analysis of Pearson product-moment coefficients r with Fisher’s z-transformation and tested for moderation with the homogeneity tests. The results showed a positive link between impulsivity and Internet addiction ( r = 0.371, 95% CI = [0.311, 0.427]) and a negative link between restraint and Internet addiction ( r = −0.362, 95% CI = [−0.414, −0.307]). The moderation analysis indicated that the correlation between impulsivity indicators and greater Internet addiction was stronger among undergraduates (18–22 years old) than among adolescents (10–17 years old). Furthermore, the negative link between a restraint indicator and Internet addiction was greater (a) among students in East Asia than those in Western Europe/North America, (b) among males than females and (c) when using the Internet addiction measures GPIUS or IAT rather than CIAS. Hence, these results indicate a negative link between self-control and Internet addiction, and this link is moderated by age, culture, gender, and Internet addiction measure.

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          Most cited references142

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          Bias in meta-analysis detected by a simple, graphical test

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            A basic introduction to fixed-effect and random-effects models for meta-analysis.

            There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriate model is important to ensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves to place the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation of the statistics. In this paper we explain the key assumptions of each model, and then outline the differences between the models. We conclude with a discussion of factors to consider when choosing between the two models. Copyright © 2010 John Wiley & Sons, Ltd. Copyright © 2010 John Wiley & Sons, Ltd.
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              Assessing heterogeneity in meta-analysis: Q statistic or I2 index?

              In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I(2) index has been proposed to quantify the degree of heterogeneity in a meta-analysis. In this article, the performances of the Q test and the confidence interval around the I(2) index are compared by means of a Monte Carlo simulation. The results show the utility of the I(2) index as a complement to the Q test, although it has the same problems of power with a small number of studies.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                24 November 2021
                2021
                : 12
                : 735755
                Affiliations
                [1] 1Graduate School of Education, Peking University , Beijing, China
                [2] 2School of Education, Guangzhou University , Guangzhou, China
                [3] 3Department of Special Education and Counselling, The Education University of Hong Kong, Tai Po , Hong Kong SAR, China
                [4] 4Institute of Curriculum and Instruction, Faculty of Education, East China Normal University , Shanghai, China
                Author notes

                Edited by: Bojana M. Dinic, University of Novi Sad, Serbia

                Reviewed by: Darko Hinic, University of Kragujevac, Serbia; Magdalena Ramos Navas-Parejo, University of Granada, Spain; Daniela Šincek, Josip Juraj Strossmayer University of Osijek, Croatia

                *Correspondence: Hao Lei, leihao8998@ 123456163.com

                This article was submitted to Personality and Social Psychology, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2021.735755
                8653951
                34899477
                293a5d1a-de17-4c44-8b38-3a18b45d34c6
                Copyright © 2021 Li, Ren, Chiu, Wang and Lei.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 July 2021
                : 07 October 2021
                Page count
                Figures: 5, Tables: 4, Equations: 0, References: 144, Pages: 16, Words: 13114
                Categories
                Psychology
                Original Research

                Clinical Psychology & Psychiatry
                self-control,meta-analysis,internet addiction,moderator analysis,students

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