RESEARCH ARTICLE


Exploring Associations between Internet Addiction, Depressive Symptoms, and Sleep Disturbance among Saudi Nursing Students



Mohammed AlAmer1, *, Emad Shdaifat1, Amira Alshowkan1, Aleya G. Eldeen2, Aysar Jamama1
1 Department of Community Nursing, College of Nursing, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
2 Psychiatric and Mental Health Nursing Department, Faculty of Nursing, Alexandria University, Alexandria, Egypt


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Creative Commons License
© 2020 AlAmer et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Community Nursing, College of Nursing, Imam Abdulrahman Bin Faisal University, 8795 Ali Al Ansari Street, Ar Rakah Ash Shamaliyah District, Dammam, 34225-3368, Saudi Arabia; Tel: +966547885660
E-mail: mmamer@iau.edu.sa


Abstract

Background:

Excessive internet usage is a worldwide problematic issue among young adults and college students. Previous studies showed that Saudi young adults are involved in this problem.

Objectives:

To determine the prevalence of Internet Addiction (IA), and to find out its relation with depressive symptoms, sleep quality, and demographic variables.

Methods:

This study used a cross-sectional design. Data were collected from 341 nursing students in Saudi Arabia using three scales: Young’s Internet Addiction Test, Central Epidemiologic Scale for Depression and Pittsburgh Sleep Quality Index.

Results:

The results showed that 35.1% of students were suffering from frequent problems and 0.9% were suffering from significant problems due to heavy internet usage. The correlation results found a positive moderate correlation between IA and depression (r = 0.401, p < 0.001) and a positive weak correlation with sleep quality (r = 0. 196, p = 0.002). Sleeping and depression were weakly correlated (r = 0.274, p < 0.001). Regression analysis revealed that IA was associated with: smoking status, high family income, duration of usage (3-6 hours and >6 hours), and depressive symptoms. The depressive level was associated with duration of usage (>6 hours), students’ grading point average (GPA), IA, and sleep quality. Sleep quality was found to be associated with duration of usage (>6 hours) and having depressive symptoms.

Conclusion:

The findings illustrate the need for proper management of internet usage, as well as developing plans to avoid the negative consequences of internet addiction on psychological wellbeing by incorporating nursing education programs about appropriate internet usage.

Keywords: Addiction, Depression , Depressive symptoms, Internet, Sleep quality .