Problematic use of the internet, smartphones, and social media among medical students and relationship with depression: An exploratory study.

Journal: PloS one

Volume: 18

Issue: 5

Year of Publication: 2023

Affiliated Institutions:  Faculty of Medicine, Mbarara University of Science and Technology, Mbarara, Uganda. Department of Psychiatry, Faculty of Medicine, Mbarara University of Science and Technology, Mbarara, Uganda. College of Health Sciences, Makerere University, Kampala, Uganda. CHINTA Research Bangladesh, Savar, Dhaka, Bangladesh. Psychology Department, Nottingham Trent University, Nottingham, United Kingdom.

Abstract summary 

Students in sub-Saharan African countries experienced online classes for the first time during the COVID-19 pandemic. For some individuals, greater online engagement can lead to online dependency, which can be associated with depression. The present study explored the association between problematic use of the internet, social media, and smartphones with depression symptoms among Ugandan medical students.A pilot study was conducted among 269 medical students at a Ugandan public university. Using a survey, data were collected regarding socio-demographic factors, lifestyle, online use behaviors, smartphone addiction, social media addiction, and internet addiction. Hierarchical linear regression models were performed to explore the associations of different forms of online addiction with depression symptom severity.The findings indicated that 16.73% of the medical students had moderate to severe depression symptoms. The prevalence of being at risk of (i) smartphone addiction was 45.72%, (ii) social media addiction was 74.34%, and (iii) internet addiction use was 8.55%. Online use behaviors (e.g., average hours spent online, types of social media platforms used, the purpose for internet use) and online-related addictions (to smartphones, social media, and the internet) predicted approximately 8% and 10% of the severity of depression symptoms, respectively. However, over the past two weeks, life stressors had the highest predictability for depression (35.9%). The final model predicted a total of 51.9% variance for depression symptoms. In the final model, romantic relationship problems (ß = 2.30, S.E = 0.58; p<0.01) and academic performance problems (ß = 1.76, S.E = 0.60; p<0.01) over the past two weeks; and increased internet addiction severity (ß = 0.05, S.E = 0.02; p<0.01) was associated with significantly increased depression symptom severity, whereas Twitter use was associated with reduced depression symptom severity (ß = 1.88, S.E = 0.57; p<0.05).Despite life stressors being the largest predictor of depression symptom score severity, problematic online use also contributed significantly. Therefore, it is recommended that medical students' mental health care services consider digital wellbeing and its relationship with problematic online use as part of a more holistic depression prevention and resilience program.

Authors & Co-authors:  Sserunkuuma Jonathan J Kaggwa Mark Mohan MM Muwanguzi Moses M Najjuka Sarah Maria SM Murungi Nathan N Kajjimu Jonathan J Mulungi Jonathan J Kihumuro Raymond Bernard RB Mamun Mohammed A MA Griffiths Mark D MD Ashaba Scholastic S

Study Outcome 

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Statistics
Citations :  Besalti M, Satici SA. Online learning satisfaction and internet addiction during Covid-19 pandemic: A two-wave longitudinal study. Tech Trends: for Leaders in Education & Training. 2022; 66: 876–82 doi: 10.1007/s11528-022-00697-x
Authors :  11
Identifiers
Doi : e0286424
SSN : 1932-6203
Study Population
Male,Female
Mesh Terms
Humans
Other Terms
Study Design
Exploratory Study,Cross Sectional Study
Study Approach
Country of Study
Uganda
Publication Country
United States