PREVALENCE OF INTERNET ADDICTION AND ITS DEMOGRAPHIC DETERMINANTS: A CROSS-SECTIONAL ANALYSIS IN MALAYSIA - Md Zahir Abdul Hamid; Nor Shafrin Ahmad; Rahimi Che Aman, (JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM), 2024)
This study examines the prevalence of Internet addiction (IA) and its demographic determinants among adolescents in Kedah, Malaysia, aiming to inform targeted interventions and policies. A cross-sectional survey was conducted with 376 students aged 16-17 from urban and rural districts. The Chen Internet Addiction Scale (CIAS) was used to assess IA levels, and chi-square tests analyzed relationships between IA and demographic factors, including gender, race, family income, weekly Internet usage, smartphone ownership, and home Wi-Fi access. The study found that 26.86% of participants met the criteria for IA, with 14.10% at risk. Significant associations were observed between IA and gender (χ² = 8.437, p = .015), race (χ² = 29.951, p < .001), family income (χ² = 16.484, p = .002), weekly Internet usage (χ² = 21.496, p < .001), smartphone ownership (χ² = 8.597, p = .014), and home Wi-Fi access (χ² = 9.250, p = .010). Female students showed higher addiction rates (28.80%) compared to males (23.31%). Students from lower-income families (<RM1500.00) exhibited higher addiction rates (31.43%) than those from higher-income backgrounds. Interestingly, home Wi-Fi access was associated with lower addiction rates (20.40%) compared to those without (34.29%). No significant differences were found between urban and rural locations or age groups. The findings highlight the complex interplay of socio-economic, cultural, and technological factors influencing adolescents' online behaviors and underscore the need for interventions tailored to address gender, racial, and economic disparities. This study recommends community-based awareness programs, improved digital literacy, and support for vulnerable groups. Future research should focus on longitudinal studies and incorporate objective measures to better understand the development of IA over time.