Factors Related to Smartphone Addiction in Medical Students at the Universitas Sumatera Utara

Abstract

Background: Smartphones have become an essential device in everyday life in recent years; scientific impetus and the extraordinary evolution of technology have resulted in having to provide information in all subjects anytime and anywhere. Smartphones have grown in popularity among younger generations as a way to stay in touch with others and seek as much information as possible. Being taught too much can negatively affect health, including being easily distracted, fatigue, migraines, neck pain, decreased social engagement and academic achievement, drowsiness, forgetfulness, reduced hearing, and reduced focus. A need to assess circumstances in terms of addiction arises from repetitive individual behaviours that impair everyday functioning and social interactions.Method: A cross-sectional design and a multivariate predictive model was used in this study. Purposive sampling of the non-probability kind was the sampling method employed in this study. Between November 2022 and January 2023, 200 students from the Faculty of Medicine at Universitas Sumatera Utara participated in the study. The study begins by filling in demographic data and the Indonesian version of the Smartphone Addiction Scale-Short Version (SAS-SV). After the results were obtained, data management and analysis were carried out using SPSS software. Linear regression is used when all the required conditions are met. Result:The SAS-SV score was found to be related to independent characteristics such as gender, age, operating system, internet access, parental income, usage length, and sleep duration with p<0.05 and R2=62.8% (showing that the independent factors were related with a SAS-SV score of 62.8%). However, we discovered that independent variables like education level and other smartphone features did not statistically differ from zero (p>0.05). As a result, these variables have no impact on the SAS-SV score. Conclusion:This study indicated that the following independent risk factors were linked to SAS-SV scores in medical students at the Universitas Sumatera Utara: gender, age, operating system, internet access, parental income, usage length, and sleep duration.