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

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Sserunkuuma, J, Kaggwa, MM, Muwanguzi, M, Najjuka, SM, Murungi, N, Kajjimu, J, Mulungi, J, Kihumuro, RB, Mamun, MA, Griffiths, MD ORCID: https://orcid.org/0000-0001-8880-6524 and Ashaba, S, 2023. Problematic use of the internet, smartphones, and social media among medical students and relationship with depression: an exploratory study. PLOS ONE, 18 (5): e0286424. ISSN 1932-6203

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Official URL: https://doi.org/10.1371/journal.pone.0286424

Abstract

Background: 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.

Methods: 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.

Results: 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).

Conclusion: 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.

Item Type:	Journal article
Publication Title:	PLOS ONE
Creators:	Sserunkuuma, J., Kaggwa, M.M., Muwanguzi, M., Najjuka, S.M., Murungi, N., Kajjimu, J., Mulungi, J., Kihumuro, R.B., Mamun, M.A., Griffiths, M.D. and Ashaba, S.
Publisher:	Public Library of Science (PLoS)
Date:	26 May 2023
Volume:	18
Number:	5
ISSN:	1932-6203
Identifiers:	Number Type 10.1371/journal.pone.0286424 DOI 1766404 Other
Rights:	© 2023 Sserunkuuma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Divisions:	Schools > School of Social Sciences
Record created by:	Laura Ward
Date Added:	31 May 2023 09:45
Last Modified:	31 May 2023 09:45
URI:	https://irep.ntu.ac.uk/id/eprint/49094