BackgroundSmartphone addiction (SA) is associated with adverse consequences, especially for freshmen. Evidence indicates that SA is associated with depression, and it is necessary to conduct a longitudinal study to explore the association further.MethodsSA (measured by the Smartphone Addiction Scale-Short Version) and depression (measured by the Zung's Self-Rating Depression Scale) among 1,186 freshmen were surveyed at baseline and a respective 12-month follow-up for each participant. The application of a cross-lagged panel model approach (CLPM) revealed an association between SA and depression after adjusting for demographic variables.ResultsThe CLPM results showed a significant path from baseline SA to follow-up depression (β = 0.08, P < 0.001) and a significant path from baseline depression to follow-up SA (β = 0.08, P < 0.001). Compared with the overall cross-lagged model, the cross-lagged coefficient of the path from baseline SA to follow-up depression increased in the female group (β = 0.10, P = 0.015), and the cross-lagged coefficient of the path from baseline depression to follow-up SA also increased significantly (β = 0.15, P < 0.001). In contrast, the cross-lagged model in the male group showed no predictive effect between SA and depression (P > 0.05).ConclusionsThe current study showed a significant bidirectional association between smartphone addiction and depression among freshmen, but only in the female population.
With the development of genome sequencing, many researchers have investigated the mechanism by which the intestinal microbiota influences sleep across the brain-gut axis. However, the relationship between gut microbiota and sleep disorder remains unclear. Thus, we studied the difference in gut microbiota composition between poor sleep quality- and normal populations, which helps set the ground for future research. The recruited college students provided baseline information and stool samples and completed the Pittsburgh Sleep Quality Index (PSQI). We compared the two groups’ gut microbiota composition and functional differentiation by using the 16S rRNA gene sequencing analysis. The main bacterial difference and the most critical effect were mainly concentrated within Tenericutes and Elusimicrobia. Compared with the healthy control group, some functions of the gut microbiota were impaired in the poor sleep quality group, such as butanoate metabolism and propanoate metabolism. Bacterial taxa with significant differences raised the possibility for future diagnosis and treatment of sleep problems.
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