ArticleHeliyon2024
Cyberbullying among secondary school students: Analyzing prediction and relationship with background, social status, and ICT use.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Study of the Relationship Between Cyberbullying and Mental Health in Adolescents-A Systematic Review.Children (Basel, Switzerland) · 2026Review
- Why individuals with trait anger and revenge motivation are more likely to engage in cyberbullying perpetration? The online disinhibition effect.Frontiers in public health · 2025Article
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Authors and funding
2 authors.
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Abstract
This study explored the predictions of and relationships between background, social status, and the use of information and communication technology (ICT) in cyberbullying among 2430 secondary school students from schools affiliated with Thailand's Office of the Basic Education Commission. The stratified sampling method was used along with the Cyberbullying Questionnaire, Sociometric Status Questionnaire, Perceived Popularity Questionnaire, and ICT Use Questionnaire and data were collected through the CU Smart Sociometry web application and Google Forms. Data analysis was conducted to determine 1) demographic data using descriptive statistics; 2) correlation analysis of students' backgrounds, sociometric status, and ICT use against cyberbullying using the chi-square test; and 3) variables that predict cyberbullying among secondary school students using multinomial logistic regression. Results showed a link between cyberbullying and secondary school students' backgrounds, social status, and ICT use. Students with different backgrounds (sex and academic performance), social statuses (social preference and perceived popularity), and ICT use partook in different cyberbullying roles. Independent variables of sex, academic performance, social preference, perceived popularity, and ICT use all predicted cyberbullying by 33.3 % with statistical significance. Male students were noted to have a higher likelihood of being cyberbullies than female students, whereas female students were more likely to be cybervictims and bystanders. Moreover, students with low academic performance were more likely to be cyberbullies and cybervictims than high-performing students, with rejected students having the highest likelihood of being cyberbullies. Interestingly, the higher a student's popularity, the higher was their likelihood of being cyberbullies. Finally, cyberbullies had the highest average daily internet use, and students who had never had their guardians monitor their internet usage were more likely to be cyberbullies; students with moderate and good social media behavior were mostly bystanders.
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