Digital Device Use, Computer Vision Syndrome, and Sleep Quality among an African Undergraduate Population

Prince Kwaku Akowuah,Asafo Agyei Frimpong,Jeremiah Fummey,Augustine N Nti,Stephen Ankamah-Lomotey,Kofi Osei-Poku,Prince Boadi,Joseph Adjei-Anang,Hamidreza Karimi-Sari

doi:10.1155/2021/6611348

Abstract

Background. The purpose of the study was to determine the prevalence of computer vision syndrome (CVS) and poor sleep quality among university students and assess the relationship between digital device usage, CVS, and sleep quality. Methods. A cross-sectional study including undergraduate students was conducted in Ghana between January–March 2020. Information on digital device use and CVS symptoms was collected using a structured questionnaire. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Logistic regression was used to determine the relationship between CVS and digital device use behavior, and linear regression analysis was used to explore the association between sleep quality and digital device use behavior. Statistical significance was set atp < 0.05. Results. Mean (SD) age of participants was 20.95 (1.68) years and most (54.97%) of them were females. The prevalence of CVS was 64.36%. Factors associated with CVS included hours of digital device use per day (OR = 4.1,p < 0.001), years of digital device use (OR = 3.0,p < 0.001), adjustment of digital device screen contrast to the surrounding brightness (OR = 1.95,p = 0.014), and presence of glare (OR = 1.79,p = 0.048). Prevalence of poor sleep quality was 62.43%. There was a significant association between poor sleep quality and number of years participants had used a digital device (p = 0.015) and the number of hours they used a digital device per day (p = 0.005). Conclusion. There is a high prevalence of both CVS and poor sleep quality among undergraduate students in Ghana. This represents a significant public health issue that needs attention.

Highlights

Computer vision syndrome (CVS) is a cluster of eye and vision problems experienced in relation to, or during, the use of digital devices
Binary logistic regression analysis was performed to determine the relationship between CVS and participant characteristics and digital device use behavior, and linear regression analysis was used to explore the association between the global Pittsburgh Sleep Quality Index (PSQI), its individual components and years of digital device use, and digital device use per day
Computer Vision Syndrome. e prevalence of CVS was 64.36%

Summary

Introduction

Computer vision syndrome (CVS) is a cluster of eye and vision problems experienced in relation to, or during, the use of digital devices. Prolonged digital device use results in significant reduction in sleep amount and quality. Sleep quality is expected to be poorer in students with heavy digital device use [21]. No attempt has yet been made to examine the relationship between digital device use and sleep quality among undergraduates in Africa. E aim of the current study was to examine CVS and its association with sleep quality among an undergraduate population in Ghana. Binary logistic regression analysis was performed to determine the relationship between CVS and participant characteristics and digital device use behavior, and linear regression analysis was used to explore the association between the global PSQI, its individual components and years of digital device use, and digital device use per day (hours). At 95% confidence interval, p ≤ 0.05 was considered statistically significant

Results

Discussion

Participants characteristic Gender Age

Conclusion