An updated of meta-analysis on the relationship between mobile phone addiction and sleep disorder.

"Using digital media or sleeping ... that is the question". A meta-analysis on digital media use and unhealthy sleep in adolescence

Associations of sleep problems with non-physical bullying perpetration and victimization among adolescents: A cross-lagged panel study.

Objective: This study was conducted to determine the effect of internet addiction on the sleep quality of adolescents during the Coronavirus (COVID) period. Materials and Methods: This cross-sectional, descriptive, and correlational design study was conducted in the high schools located in a city center between March-June 2021. The universe of the study consisted of students aged between 13 and 18 years old and the study was completed with 413 students. Demographic information form, internet addiction scale for adolescents (IASA) and Pittsburgh sleep quality index (PSQI) were used to collect data. In order to evaluate the data, number, mean, percentile distributions, t-test, analysis of variance (ANOVA), Kruskal-Wallis test and Spearman correlation analysis tests were used in SPSS 21 statistical program. Results: A total of 40.9% of the participants were found to spend 4-6 hours on the Internet during the pandemic and 85.2% had poor sleep quality. While the total mean scores obtained from the IASA was 20.30±8.87, it was 8.19±2.50 from the PSQI. The time spent daily on the Internet for non-educational purposes during COVID and the characteristics of the time spent on the internet compared to the pre-COVID period were significantly correlated with the mean total scores of IASA (p<0.05). A weak positive significant relationship was found between the total mean scores of the adolescents' IASA and PSQI scales (r=0.216, p<0.000). Conclusion: In the study, more sleep problems were observed among the adolescents as their internet addiction levels increased throughout the study. Amaç: Bu çalışmanın amacı, Koronavirüs (COVID) pandemisi sürecinde ergenlerde internet bağımlılığının uyku kalitesi üzerine etkisini belirlemektir. Gereç ve Yöntem: Araştırma kesitsel, tanımlayıcı ve ilişki arayıcı tipte olup bir il merkezinde bulunan liselerde Mart-Haziran 2021 tarihleri arasında gerçekleştirilmiştir. Araştırmanın evrenini, bu liselerde eğitim gören 13-18 yaş aralığındaki öğrenciler oluşturmuş olup çalışma 413 öğrenci ile tamamlanmıştır. Verilerin toplanmasında tanıtıcı bilgi formu, internet bağımlılığı ölçeği ve Pittsburgh uyku kalitesi indeksi (PUKÍ) kullanılmıştır. Verilerin değerlendirilmesi için, SPSS 21 istatistik programında sayı, ortalama, yüzdelik dağılımlar, t-testi, varyans analizi (ANOVA), Kruskal-Wallis testi ve spearman korelasyon analizi testlerinden yararlanılmıştır. Bulgular: Pandemi sürecinde ergenlerin %40,9'unun günde 4-6 saat internette vakit geçirdiği ve %85,2'sinin kötü uyku kalitesine sahip olduğu saptanmıştır. Ergenlerin internet bağımlılığı ölçeği (ÍBÖ) toplam puan ortalamaları 20,30±8,87 ve PUKÍ toplam puan ortalamaları 8,19±2,50 olarak saptanmıştır. COVID sürecinde eğitim amacı dışında günlük internet ile geçirilen süre ve COVID öncesi sürece göre internet ile geçirilen sürenin özelliği ile ÍBÖ toplam puan ortalamaları arasında istatiksel olarak anlamlı bir ilişki saptanmıştır (p<0,05). Ergenlerin ÍBÖ ve PUKÍ ölçek toplam puan ortalamaları arasında anlamlı, pozitif yönde ve zayıf bir ilişki olduğu (r=0,216, p<0,000) saptanmıştır. Sonuç: Ergenlerin internet bağımlılık düzeyleri arttıkça daha fazla uyku problemleri yaşadıkları görülmektedir.

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Effect of Internet Addiction on the Sleep Quality of Adolescents During COVID-19 Pandemia Duration Period

Although smartphone addiction has recently become a concern about that based on the usage habits of individual smartphone users, it can be challenging to anticipate the number of problem smartphone users. Smartphones are increasingly ingrained in our daily lives as a result of their rapid uptake. This study aimed to find the possibility of predicting smartphone addiction levels based on their use of smartphones. A survey was created to collect the raw data from people 15 to 25 years old. The data were examined using Machine learning techniques(SVM, Logistic Regression, KNN, Decision tree, Random forest, AdaBoost, XGBoost, LightGBM) in addition to hypothesis tests, integrating fundamental personal traits and smartphone usage data. There were 23 different factors used to predict the extent of smartphone addiction, and the SVM(0.82) model had the best accuracy rate while the Decision tree had the lowest (0.60) with the feature chi-square. And without the feature, the highest accuracy rate was 0.76 in the logistic regression model. Other models almost remain the same. The result showed that group gender had little bearing on how dependent they were on their smartphones. For future studies, we will try to examine how real-time mood swings vary with smartphone usage and more detailed uses of smartphones to get more accuracy. 

Severity Detection of Problematic Smartphone Usage (PSU) and its Effect on Human Lifestyle using Machine Learning

Prior studies have suggested a link between sleep problems and problematic smartphone use. However, the causal relationships between these two variables have not been identified, particularly in adolescence. Utilizing longitudinal panel data from Taiwan, this report examined the temporal relationships between sleep problems and problematic smartphone use among adolescents. One thousand and thirty-nine students (Grades 7-12) were surveyed at two-time points with a 6-month interval. The results of cross-lagged panel analysis showed that sleep problems at Time 1 significantly predicted problematic smartphone use at Time 2. Problematic smartphone use at Time 1 also significantly predicted sleep problems at Time 2. These findings applied to boys and girls and suggested that temporal relationships between sleep problems and problematic smartphone use among teenagers are reciprocal. Accordingly, increasing sleep quality may prevent future problematic smartphone use, while reducing problematic smartphone use may prevent sleep problems in adolescents.

https://www.mdpi.com/1660-4601/18/14/7438/pdf

Wen Chi Wu

Papers

Reciprocal Relationships between Sleep Problems and Problematic Smartphone Use in Taiwan: Cross-Lagged Panel Study.