Factors Related to Indonesian Version of Smartphone Addiction Scale-Short Version (SAS-SV) Among Medical Student during COVID-19 Pandemic
Background: Smartphone has been one of the most prominent breakthroughs in not just communication but also daily function right on the tip of the fingers which is more likely to put individuals to excessive smartphone usage. Massive number of people are tend to develop dependence to smartphone usage which leads to less interpersonal relationship and decreased real social interactions that result in isolation and loneliness.
Aim: Investigating smartphone addiction among medical students in Medan, Indonesia, but also to evaluate factors and Sociodemographic characteristics that are related to smartphone addiction particularly during COVID-19 pandemic.
Method: This cross sectional multivariate study conducted in April to May 2021 involves 200 medical students and focuses on investigating the relationship between several independent variables and smartphone addiction by using Indonesian version of Smartphone Addiction Scale Short Version (SAS-SV). The questionnaire was distributed through Google Form. All data were then analyzed by means of SPSS (Statistical Package for the Social Sciences) version 22. Linear regression was used when all required condition were fulfilled. Results: Independent factors such as age, parent’s income, usage duration, sleeping duration, medical education stage and gender are found to be related to SAS-SV score with p value of less than 0.05 and adjusted R2 of 62.8% (indicating that independent factors are related to SAS-SV score for as much as 62.8%). In the other hand we found that independent factors, such as phone’s operating system, parents education, internet access, kinship, and other function of smartphone are not statistically significant (p>0.05). Hence, these factors are not related to SAS-SV score.
Conclusion: From this study, we found that independent risk factors related to SAS-SV score among medical students during pandemic are as in the following; age, gender, parents income, medical education stage, usage and sleeping duration. By knowing these factors, it is hoped that clinicians and public policy regulators are able to give more attention and set up more appropriate psychotherapy or support as early as possible toward those with smartphone addiction