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Internet addiction and associated factors among undergraduate students of Jimma University; Jimma, South West Ethiopia, institutional based cross-sectional study

BACKGROUND: Internet addiction affects cognitive function, has a harmful impact on students’ academic performance, and increases their risk of experiencing psychological crises. OBJECTIVES: Examining the prevalence of internet addiction and its contributing factors among regular undergraduate studen...

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Detalles Bibliográficos
Autores principales: Amano, Abdulkarim, Ahmed, Gutema, Nigussie, Kabtamu, Asfaw, Henock, Fekadu, Gelana, Hiko, Ahmed, Abdeta, Tilahun, Soboka, Matiwos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552302/
https://www.ncbi.nlm.nih.gov/pubmed/37798719
http://dx.doi.org/10.1186/s12888-023-05197-7
Descripción
Sumario:BACKGROUND: Internet addiction affects cognitive function, has a harmful impact on students’ academic performance, and increases their risk of experiencing psychological crises. OBJECTIVES: Examining the prevalence of internet addiction and its contributing factors among regular undergraduate students at Jimma University in south-west Ethiopia. METHODS: An institutional-based cross-sectional study was conducted among study participants between August 1 and August 30, 2021. A total of 772 Participants were involved in the study using a multistage random sampling technique. Data was collected using pretested and structured questionnaires with self-administered techniques. The Young Internet Addiction Test (YIAT) was used to measure internet addiction. The data was entered into the computer using Epi Data version 4.6, and then it was exported to the Statistical Package for Social Science (SPSS) version 25 for analysis. The association between each independent variable and the outcome variable was examined using bivariate analysis. Variables with a p-value of less than 0.25 in bivariate analysis were included in the multivariate logistic regression model to determine how each independent variable affected the outcome variable. RESULT: The prevalence of internet addiction among study participants was 53.6% (95% Confidence Interval (CI)) (49.99%, 57.15%). Findings from multivariate logistic regression analysis suggested a variety of related factors had significant associations with internet addiction. Being dissatisfied with a major study, having a cumulative grade point average of a promoted grade report, using the internet for entertainment, using the internet for Facebook, using the internet for telegram, depression, social anxiety, and poor social support. CONCLUSION: This study revealed a comparatively high frequency of internet addiction among study participants. Internet addiction has been linked to psychosocial, academic, and purpose-related aspects of internet use. As a result, incorporating stakeholders’ efforts to improve the identified variables would be a helpful start toward lowering this high incidence.