Gao Wen-Juan, Hu Yan, Ji Jun-Lin, Liu Xin-Qiao
Institute of Higher Education, Beihang University, Beijing 100191, China.
School of Public Administration, Beihang University, Beijing 100191, China.
World J Psychiatry. 2023 Jun 19;13(6):361-375. doi: 10.5498/wjp.v13.i6.361.
Existing research has demonstrated that depression is positively related to smartphone addiction, but the role of sleep has not been discussed thoroughly, especially among engineering undergraduates affected by the coronavirus disease 2019 pandemic.
To evaluate sleep as a mediator of the association between smartphone addiction and depression among engineering undergraduates.
Using a multistage stratified random sampling method, a cross-sectional survey was conducted among 692 engineering undergraduates from a top engineering university in China, and data were collected by self-reported electronic questionnaires. The data included demographic characteristics, such as age, gender, the Smartphone Addiction Scale-Short Version (SAS-SV), the 9-item Patient Health Questionnaire, and the Pittsburgh Sleep Quality Index. Pearson correlation and multiple linear regression analyses were used to examine the association between smartphone addiction and depression, while structural equation models were established to evaluate the possible mediating role of sleep.
Based on the cutoffs of the SAS-SV, the rate of smartphone addiction was 63.58 percent, with 56.21 percent for women and 65.68 percent for men, among 692 engineering students. The prevalence of depression among students was 14.16 percent, with 17.65 percent for women, and 13.18 percent for men. Smartphone addiction was positively correlated with depression, and sleep played a significant mediating effect between the two, accounting for 42.22 percent of the total effect. In addition, sleep latency, sleep disturbances, and daytime dysfunction significantly mediated the relationship between depression and smartphone addiction. The mediating effect of sleep latency was 0.014 [ < 0.01; 95% confidence interval (CI): 0.006-0.027], the mediating effect of sleep disturbances was 0.022 ( < 0.01; 95%CI: 0.011-0.040), and the mediating effect of daytime dysfunction was 0.040 ( < 0.01; 95%CI: 0.024-0.059). The influence of sleep latency, sleep disturbances, and daytime dysfunction accounted for 18.42%, 28.95%, and 52.63% of the total mediating effect, respectively.
The results of the study suggest that reducing excessive smartphone use and improving sleep quality can help alleviate depression.
现有研究表明，抑郁症与智能手机成瘾呈正相关，但睡眠的作用尚未得到充分讨论，尤其是在受2019冠状病毒病疫情影响的工科本科生中。
评估睡眠在工科本科生智能手机成瘾与抑郁症之间的关联中所起的中介作用。
采用多阶段分层随机抽样方法，对中国一所顶尖工科大学的692名工科本科生进行横断面调查，并通过自填式电子问卷收集数据。数据包括人口统计学特征，如年龄、性别、智能手机成瘾量表简版（SAS-SV）、9项患者健康问卷和匹兹堡睡眠质量指数。采用Pearson相关性分析和多元线性回归分析来检验智能手机成瘾与抑郁症之间的关联，同时建立结构方程模型来评估睡眠可能的中介作用。
在692名工科学生中，根据SAS-SV的临界值，智能手机成瘾率为63.58%，其中女生为56.21%，男生为65.68%。学生中抑郁症的患病率为14.16%，其中女生为17.65%，男生为13.18%。智能手机成瘾与抑郁症呈正相关，睡眠在两者之间起显著的中介作用，占总效应的42.22%。此外，入睡潜伏期、睡眠障碍和日间功能障碍在抑郁症与智能手机成瘾之间的关系中起显著中介作用。入睡潜伏期的中介效应为0.014[<0.01；95%置信区间（CI）：0.006-0.027]，睡眠障碍的中介效应为0.022（<0.01；95%CI：0.011-0.040），日间功能障碍的中介效应为0.040（<0.01；95%CI：0.024-0.059）。入睡潜伏期、睡眠障碍和日间功能障碍的影响分别占总中介效应的18.42%、28.95%和52.63%。
研究结果表明，减少过度使用智能手机和改善睡眠质量有助于缓解抑郁症。
