Relationship among screen time，depressive symptoms and sleep parameters among college students
10.16835/j.cnki.1000-9817.2024090
- VernacularTitle:大学生视屏时段与抑郁症状和睡眠状况的关联
- Author:
ZHAO Pei, SHI Huanxia, WANG Lianzhen
1
Author Information
1. Faculty of Education, Beijing City University, Beijing (101399) , China
- Publication Type:Journal Article
- Keywords:
Fixation,ocular;
Depression;
Sleep;
Mental health;
Regression analysis;
Students
- From:
Chinese Journal of School Health
2024;45(3):402-405
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the relationship between daytime or nighttime screen time, sleep duration, bedtime, sleep quality and depressive symptoms, so as to provide reference for preventing depression symptoms in college students.
Methods:A total of 1 259 college students in one university in Beijing were recruited by using a cluster random sampling method for online and offline questionnaire surveys in October 2022 and April to May 2023. The sleeping quality, depression symptoms and screen time of participants were measured with the Pittsburgh Sleep Quality Index(PSQI), Chinese Version of the Beck Depression Inventory-II (BDI-II-C) and Screen Time Questionnaire. Logistic ordered regression and multiple linear regression were used to analyze the correlation among screen time, sleep parameters and depressive symptoms.
Results:The prevalence of depressive symptoms was 24.9 %. There was no significant correlation between daytime screen time and depressive symptoms for a week after controlling for night screen time in a week, gender and age ( OR= 1.00 , 95%CI=1.00-1.01, P >0.05). There was a significant correlation between night screen time and depressive symptoms for a week ( OR=1.05, 95%CI=1.03-1.06, P <0.01) after controlling for daytime screen time in a week, gender and age. However, after controlling for the weekday sleep duration, weekend bedtime, and sleep quality step by step, there was no significant correlation between the night screen time for a week and the depressive symptoms ( OR=1.01, 95%CI= 0.99 -1.02, P >0.05). After adjusting for gender and age, multiple linear regression analysis found that the duration of one week s night vision screen had statistical significance in predicting weekday sleep duration, weekend sleep time and sleep quality ( β=-0.29, 0.45, 0.26, P <0.05). There were positive correlation between the duration of sleep on study days, the duration of sleep on rest days, and the quality of sleep with depressive symptoms（ OR =1.27,1.39,1.45， P <0.01）.
Conclusions:Excessive night screen time has a greater impact on sleep problems and depressive symptoms. Reducing nighttime video and improving sleep habits are potential intervention goals for reducing depression symptoms in college students.
