A Latent Transition Analysis of Internet Addiction in Early Adolescents and Its Contributing Factors. (May 2023)

• Record Type: Journal Article
• Authors: Hu, Xiaojin; Chen, Yuling; Wang, Zhihang; Huebner, E. Scott; Ling, Yu
• Is Part Of: Journal of early adolescence. Volume 43:Number 5(2023)
• Page Start: 603
• Page End: 631
• Publication Date: 2023-05
• Subjects: early adolescents -- internet addiction -- latent class analysis -- latent transition analysis; Adolescence -- United States -- Periodicals; Adolescent -- Periodicals; Adolescence -- États-Unis -- Périodiques; 305.235
• DOI: 10.1177/02724316221116045
• Languages: English
• ISSNs: 0272-4316

Abstract

The purpose of the present study was to identify the patterns of Internet addiction in early adolescents and their associated protective factors in order to prevent and/or ameliorate internet addiction as early as possible. A 2-year longitudinal study was conducted among 621 Chinese early adolescents. Latent class and latent transition analyses were used to identify classes of the development of internet addiction. Three latent classes were identified, including a "Non-Internet Addiction Group" (43%), "Low Internet Addiction Group" (43%) and "High Internet Addiction Group" (14%). A Latent Transition Analysis of Adolescents in the Non-Internet Addiction Group and Low Internet Addiction Group demonstrated relative stability in class membership, whereas adolescents in the High Internet Addiction Group tended to change to the Low Internet Addiction Group. Results of multinomial logistic regression and latent transition analyses revealed that low impulsivity, high family care, and high student engagement in school all contributed to membership in the latent classes of internet use and transitions. Implications of these results for prevention and intervention and for future research are discussed.