Association Between Screen Time, and Depression Among Undergraduate Students in Lead City University Ibadan

No Thumbnail Available

Date

2023-12

Journal Title

Journal ISSN

Volume Title

Publisher

Lead City University, Ibadan

Abstract

The research investigation focused on exploring the "Relationship Between Screen Time and Depression Among Undergraduate Students at Lead City University, Ibadan." The study utilized a meticulously designed, validated, and reliable questionnaire to gather data from 420 participants. The distribution of questionnaires employed a cluster sampling approach. The research adopted a cross-sectional methodology, and data analysis was conducted using the statistical package for social sciences. When assessing the prevalence of depression among undergraduate students at Lead City University, the findings revealed that 45% of the respondents exhibited mild depressive symptoms, 41% experienced moderate depressive symptoms, while 4% reported severe depressive symptoms. Only 10% of the participants showed no signs of depressive symptoms. Moreover, the study disclosed that 85.5% of the participants spent less than 4 hours using screen devices for relaxation or leisure on weekdays, whereas only 14.2% exceeded the 4-hour threshold. Importantly, the research did not identify any significant association between screen time and depression among the students. In conclusion, to proactively address the potential escalation of depressive symptoms among undergraduate students, it is advisable to incorporate a screen time threshold and encourage the adoption of other healthy lifestyle habits into their daily routines. Additionally, there is a pressing need to enhance awareness regarding the prevention and management of depression among students, especially considering the presence of severe depressive symptoms among some undergraduate students. Keywords: Screen time, Depression, Symptom, Cluster Sampling Method, Cross-sectional Technique Word Count – 235

Description

Keywords

Screen time, Depression, Symptom, Cluster Sampling Method, Cross-sectional Technique

Citation

Kate Turabia