Addiction Among Adolescents to Social Networking Sites in Malaysia: A Hierarchical Multiple Linear Regression Analysis

• Main Authors: Ying, Wong Khung, Md Mizanur, Rahman, Andrew, Kiyu
• Format: Article
• Language: English
• Published: Bangladesh Medical Research Council 2022
• Subjects: R Medicine (General)
• Online Access: http://ir.unimas.my/id/eprint/39263/1/Social%20Networking%20Sites1.pdf; http://ir.unimas.my/id/eprint/39263/; https://bmrcbd.org/Bulletin/bulletin_pdf/4801/480102.pdf; https://doi.org/10.3329/bmrcb.v48i1.60655
• Institution: Universiti Malaysia Sarawak

Background: Social networking sites (SNSs) have changed the ways that we interact with each other. The use of social networking sites by adolescents is addictive, with numerous negative consequences. Various factors influence social networking sites addiction among adolescents. Objective: We aimed to determine the prevalence of gender-specific social networking sites addiction among adolescents and the factors influence social networking sites addiction. Methods: A quantitative, cross-sectional community-based research was conducted by face-to-face interviews among adolescents in all 11 administrative divisions of Sarawak, Malaysia. The multistage cluster sampling technique was followed, with an adolescent selected systematically from each household. An adapted and validated questionnaire, which included 20 items of social networking sites addiction, was used to collect data. We analysed 1344 adolescent’s data using IBM SPSS Version 22.0. A partial least square structural path with mediation analysis was done using WarpPLS version 7.0. Results: Three-quarters of the adolescents (76.2%) used social networking sites, but only two-fifths of them (40.4%) were addicted, with 15% having moderate-severe addiction to social networking sites. The most frequently used social networking sites was YouTube (77.9%), followed by Facebook (75.2%) and Instagram (59.0%). Self-esteem had a negative correlation, while adolescent risk behaviours directly affected social networking sites addiction (p<0.001). The most potent predictors for social networking sites addiction were YouTube, Instagram, and Pinterest (p<0.05). Conclusion: Tackling risk behaviours and enhancing adolescents’ self-esteem would reduce the tendency to be addicted to social networking sites.