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Aim: To evaluate the correlation between Internet addiction and academic performance among high school students.
Materials and methods: The current study was a cross-sectional, descriptive observational study conducted in the psychiatry department. The study included English medium 11th grade students from Central Board of Secondary Education (CBSE) affiliated schools based on the inclusion criteria listed below. The internet addiction test (IAT) developed by Young was used to determine the presence of internet addiction. The IAT is scored on a five-point Likert scale ranging from 20 to 100. According to Young's original scheme, three types of internet users were identified: Internet Addicts, Possible Internet Addicts (PIA), and Non-Addicts (NA). Pearson's correlation coefficient was used to assess the correlation between the variables. A p 0.05 was considered statistically significant.
Results: 140 (70%) of the entire sample were non-internet addicts (NIA) or non-addicts (NA), 50 (25%) were probable internet addicts (PIA), and 10 (5%) were internet addicts. As a result, the prevalence of internet addiction was discovered to be 5%. The overall prevalence of IA (including PIA and IA) was determined to be 30%. Of the 20 students who utilised the internet for academic purposes, 19 (95%) had no online addiction, 1 (5%) had PIA, and no students were Internet addicts. The majority of students (100) utilised the internet for both academic and nonacademic reasons. 80 pupils solely accessed the internet for non-academic reasons. The distinction between using the internet for academic, nonacademic, or both reasons, as well as internet addicts, PIA, and NA, was shown to be statistically significant (p-value = 0.003). Of the entire 10 internet addicted students, 7 (70%) scored 60% and 3 (30%) achieved 60% in the test. Out of a total of 140 NIA students, 133 (95%) achieved 60% on the test and 7 (5%) got 60% on the exam. The grades earned by pupils in the three sub-groups differed significantly (p-value 0.001).
Conclusion: This research found that among high school students, 5% of internet addicts and 30% of individuals with both PIA and internet addiction had IA. Students who used the internet for both schoolwork and personal reasons had a higher rate of addiction. Students are a particularly vulnerable population, thus it is imperative that educational initiatives aimed at preventing and responding to IA, as well as programmes aimed at preventing unsafe internet usage, rehabilitation centres, support groups, and the integration of training workshops, be supported.