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      How technostress and self-control of social networking sites affect academic achievement and wellbeing

      , ,
      Internet Research
      Emerald

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          Abstract

          Purpose

          Social networking sites (SNS) are heavily used by university students for personal and academic purposes. Despite their benefits, using SNS can generate stress for many people. SNS stressors have been associated with numerous maladaptive outcomes. The objective in this study is to investigate when and how SNS use damages student achievement and psychological wellbeing.

          Design/methodology/approach

          Combining the theoretical perspectives from technostress and the strength model of self-control, this study theoretically develops and empirically tests the pathways which explain how and when SNS stressors harm student achievement and psychological wellbeing. The authors test the research model through a two-wave survey of 220 SNS using university students.

          Findings

          The study extends existing research by showing that it is through the process of diminishing self-control over SNS use that SNS stressors inhibit achievement and wellbeing outcomes. The study also finds that the high use of SNS for academic purposes enhances the effect of SNS stressors on deficient SNS self-control.

          Originality/value

          This study further opens up the black box of the social media technostress phenomenon by documenting and validating novel processes (i.e. deficient self-control) and conditions (i.e. enhanced academic use) on which the negative impacts of SNS stressors depend.

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          Most cited references116

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          Common method biases in behavioral research: A critical review of the literature and recommended remedies.

          Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
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            Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

            G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
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              A new criterion for assessing discriminant validity in variance-based structural equation modeling

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                Author and article information

                Contributors
                Journal
                Internet Research
                INTR
                Emerald
                1066-2243
                March 28 2022
                March 28 2022
                : 32
                : 7
                : 280-306
                Article
                10.1108/INTR-06-2021-0394
                52a6998c-5f28-4eb1-950c-0faeaaae3f92
                © 2022

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