Abstract

The proportion of problematic internet usage (PIU) varies from 7.3 to 51% globally due to population variety. The purpose of this study is to identify correlates of problematic internet use among telangana undergraduate medical students and to develop a model for distributing new courses across different internet user groups. Material and Methods: From May 1 to June 30th, 2022, 201 medical undergraduate students at medical colleges in Telangana participated in a cross-sectional survey. Demographic data and elements affecting PIU were gathered using a semi-structured, pre-tested questionnaire. PIU was evaluated using Dr. Kimberly Young's Internet Addiction Test (IAT) instrument. In order to evaluate the correlates of PIU, binary logistic regression has been used, and stepwise discriminant analysis (DA) has been used to create a model for allocating new subjects among different groups of internet users. The statistical analysis was performed using SPSS Inc.'s (Chicago, IL) Statistical Package for Social Sciences (Trial version 27.0). Result: PIU was present in all 41.3 percent of the individuals. However, in binary logistic regression, chatting, emotional support, and watching online adult content were significant risk factors for PIU. Univariate analysis demonstrates that internet use for emotional support, watching adult content, and gambling were significantly linked with PIU. The average and problematic internet user categories were accurately assigned to 66.2 percent of respondents by the discriminant model. Conclusion: The foundation course of the curriculum implementation support programme (CISP) for MBBS students could include a discussion of problematic internet use and its possible negative effects.

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