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      Cyberbullying Perpetration and Victimization in Youth: A Meta-Analysis of Longitudinal Studies

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      Journal of Computer-Mediated Communication
      Oxford University Press (OUP)

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          Abstract

          Cyberbullying perpetration (CP) and victimization (CV) are prevalent issues in adolescent development. However, previous meta-analyses focused only on cross-sectional findings. The present study aims to meta-analytically summarize 56 longitudinal studies on CP, CV, and related factors in children and adolescents. Forty meta-analyses on CP and CV as both predictors and outcomes of person-related, Internet activity-related, and contextual factors were performed. Additional moderator analyses took into account study design, sample population, and quality of the studies. Results highlight reciprocal longitudinal effects among CP, CV, and both traditional bullying and victimization: CP causes externalizing problem behaviors over time, whereas CV constitutes a risk factor of internalizing problems, such as depression and anxiety. Conversely, behavioral problems and increased Internet use predict involvement in CP, while depression, anxiety, and Internet use also predict CV over time. Further longitudinal research is needed to provide empirical evidence on understudied concepts.

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          Most cited references66

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          Measuring inconsistency in meta-analyses.

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

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              Is Open Access

              Interrater reliability: the kappa statistic

              The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.
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                Author and article information

                Journal
                Journal of Computer-Mediated Communication
                Oxford University Press (OUP)
                1083-6101
                March 2020
                April 29 2020
                April 04 2020
                March 2020
                April 29 2020
                April 04 2020
                : 25
                : 2
                : 163-181
                Affiliations
                [1 ]Faculty of Communication Sciences, Università della Svizzera italiana, 6900 Lugano, Switzerland
                Article
                10.1093/jcmc/zmz031
                e1e44fd9-bfab-4512-a463-bf843a19f60f
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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