Abstract
BackgroundOver 40% of Taiwanese College students experience sleep problems that not only impair their quality of life but also contribute to psychosomatic disorders. Of all the factors affecting the sleep quality, internet surfing is among one of the most prevalent. Female college students are more vulnerable to internet-associated sleep disorders than their male counterparts. Therefore, this study aims to investigate (1) the relationship between internet addiction and sleep quality, and (2) whether significant variations in sleep quality exist among students with different degrees of internet use.MethodsThis structured questionnaire-based cross-sectional study enrolled students from a technical institute in southern Taiwan. The questionnaire collected information on the following three aspects: (1) demography, (2) sleep quality with Pittsburgh Sleep Quality Index (PSQI), and (3) severity of internet addiction using a 20-item Internet Addiction Test (IAT). Multiple regression analysis was performed to examine the correlation between PSQI and IAT scores among the participants. Logistic analysis was used to determine the significance of association between PSQI and IAT scores.ResultsIn total, 503 female students were recruited (mean age 17.05 ± 1.34). After controlling for age, body mass index, smoking and drinking habits, religion, and habitual use of smartphone before sleep, internet addiction was found to be significantly associated with subjective sleep quality, sleep latency, sleep duration, sleep disturbance, use of sleep medication, and daytime dysfunction. Worse quality of sleep as reflected by PSQI was noted in students with moderate and severe degrees of internet addiction compared to those with mild or no internet addiction. Logistic regression analysis of the association between scores on IAT and sleep quality, demonstrated significant correlations between quality of sleep and total IAT scores (odds ratio = 1.05:1.03 ∼ 1.06, p < 0.01).ConclusionThe results of this study demonstrated significant negative association between the degree of internet addiction and sleep quality, providing reference for educational institutes to minimize adverse effects associated with internet use and improve students’ sleep quality.
Highlights
MATERIALS AND METHODSAdequate sleep is essential for growth hormone secretion that is required for normal physical development, in adolescents
The results indicated that the degree of Internet addiction was positively associated with poor sleep quality
Comparison of the scores of Internet addiction between participants with good quality of sleep and those with poor sleep quality revealed significantly lower scores on five out of six of the symptom patterns in the latter, indicating that those with poor sleep quality tended to focus on internet activities, use the internet excessively, have strong anticipation of internet access, exhibit a lack of selfcontrol over the amount of time spent on the internet, and participated in social activities on the internet while neglecting real-world social life
Summary
MATERIALS AND METHODSAdequate sleep is essential for growth hormone secretion that is required for normal physical development, in adolescents. Previous studies revealed sleep problems in up to 40% of Taiwanese college students (Kang and Chen, 2009; Lin et al, 2018). Of all the factors affecting sleep quality in college students, internet use is among one of the most prevalent. A study investigating the correlation between internet use and sleep in 380 medical students concluded that overuse of mobile phones and social networks could impair sleep quality (Mohammadbeigi et al, 2016). Over 40% of Taiwanese College students experience sleep problems that impair their quality of life and contribute to psychosomatic disorders. Of all the factors affecting the sleep quality, internet surfing is among one of the most prevalent. Female college students are more vulnerable to internet-associated sleep disorders than their male counterparts. This study aims to investigate (1) the relationship between internet addiction and sleep quality, and (2) whether significant variations in sleep quality exist among students with different degrees of internet use
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