Literature DB >> 23079360

Predicting adolescent perpetration in cyberbullying: an application of the theory of planned behavior.

Wannes Heirman1, Michel Walrave.   

Abstract

This study aims to contribute to the research field on cyberbullying by offering a comprehensive theoretical framework that helps to predict adolescents' perpetration of cyberbullying. One thousand forty-two pupils from 12 to 18 years old in 30 different Belgian secondary schools participated in two surveys within a three-month interval. Structural equation modeling was used to test whether the overall model of theory of planned behavior (TPB) helps to predict adolescents' self-reported perpetration in cyberbullying. Overall, the present study provides strong support for the theoretical utility of the TPB in cyberbullying research. The model accounted for 44.8% of the variance in adolescents' behavioral intention to cyberbully and 33.2% of the variance in self-reported cyberbullying perpetration. We found a strong positive relationship between adolescents' attitude towards cyberbullying and their behavioral intention to perpetrate it. Perceived behavioral control and subjective norm, the other two TPB-constructs, were also significant albeit relatively less important predictors of adolescents' intention to cyberbully. The finding that adolescents' attitude is the most important predictor of perpetration, entails that prevention and intervention strategies should aim at reducing the perceived acceptability of cyberbullying among adolescents by converting neutral or positive attitudes towards this anti-social behavior into negative evaluations.

Mesh:

Year:  2012        PMID: 23079360

Source DB:  PubMed          Journal:  Psicothema        ISSN: 0214-9915


  14 in total

1.  Prevention 2.0: targeting cyberbullying @ school.

Authors:  Ralf Wölfer; Anja Schultze-Krumbholz; Pavle Zagorscak; Anne Jäkel; Kristin Göbel; Herbert Scheithauer
Journal:  Prev Sci       Date:  2014-12

2.  Online gaming and risks predict cyberbullying perpetration and victimization in adolescents.

Authors:  Fong-Ching Chang; Chiung-Hui Chiu; Nae-Fang Miao; Ping-Hung Chen; Ching-Mei Lee; Tzu-Fu Huang; Yun-Chieh Pan
Journal:  Int J Public Health       Date:  2014-12-31       Impact factor: 3.380

3.  Gender Differences in the Factors Explaining Risky Behavior Online.

Authors:  Hagit Sasson; Gustavo Mesch
Journal:  J Youth Adolesc       Date:  2016-03-25

4.  Longitudinal Relations among Cyber, Physical, and Relational Bullying and Victimization: Comparing Majority and Minority Ethnic Youth.

Authors:  Christopher P Barlett; Michelle F Wright
Journal:  J Child Adolesc Trauma       Date:  2017-07-25

5.  Parent-child Communication, Social Norms, and the Development of Cyber Aggression in Early Adolescence.

Authors:  Anna Bullo; Peter J Schulz
Journal:  J Youth Adolesc       Date:  2022-05-20

6.  Assessing Related Factors of Intention to Perpetrate Dating Violence among University Students Using the Theory of Planned Behavior.

Authors:  Wen-Li Hou; Chung-Ying Lin; Yu-Ming Wang; Ying-Hua Tseng; Bih-Ching Shu
Journal:  Int J Environ Res Public Health       Date:  2020-02-02       Impact factor: 3.390

7.  Factors Related to Intentions to Commit Dating Violence among Taiwanese University Students: Application of the Extended Theory of Planned Behavior.

Authors:  Chung-Ying Lin; Ying-Hua Tseng; Mei-Ling Lin; Wen-Li Hou
Journal:  Int J Environ Res Public Health       Date:  2021-02-17       Impact factor: 3.390

8.  To Help or Not to Help: Intervening in Cyberbullying Among Chinese Cyber-Bystanders.

Authors:  Angel Nga Man Leung
Journal:  Front Psychol       Date:  2021-07-14

9.  You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites.

Authors:  Angel N M Leung; Natalie Wong; JoAnn M Farver
Journal:  Front Psychol       Date:  2018-04-23

10.  Ideas for addressing electronic harassment among adolescents attending a video blogging convention.

Authors:  Ellen Selkie; Yolanda Evans; Adrienne Ton; Nikita Midamba; Megan A Moreno
Journal:  BMC Public Health       Date:  2018-08-06       Impact factor: 3.295

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