The relationship between internet addiction and peer bullying level of sixth and seventh grade secondary school students.

  • Published In: Journal of Child & Adolescent Psychiatric Nursing, 2023, v. 36, n. 3. P. 248 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Gülbetekin, Eda; Gül Can, Fatma 3 of 3

Abstract

Problem: The research aimed to determine the relationship between internet addiction and peer bullying in sixth and seventh‐grade students. Method: The population of the study consisted of students in the sixth and seventh grades of secondary schools in a province in eastern Turkey. The data were collected throughout the 2021–2022 academic year from 1201 sixth and seventh graders who voluntered to participate in the research. The data were collected using the Bullying Scale and the Internet Addiction Scale for Adolescents (IAA). Finding: It was determined that gender, grade level, status of having a mobile phone, and age influenced children's participation in peer bullying. Also, variables of gender, grade level, and status of having a mobile phone affected internet addiction levels. Furthermore, when the correlation between the two scales was analyzed, a strong positive correlation was determined. Conclusions: In line with the findings of this study, interventions that may lower levels of bullying include delivering training on bullying and internet addiction to families, encouraging children to participate in activities that would reduce the amount of time they spend on the internet, and investigating the reasons for bullying. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Child & Adolescent Psychiatric Nursing. 2023/08, Vol. 36, Issue 3, p248
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2023
  • ISSN:1073-6077
  • DOI:10.1111/jcap.12420
  • Accession Number:169726971
  • Copyright Statement:Copyright of Journal of Child & Adolescent Psychiatric Nursing is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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