UNASSIGNED: We included data on 8019 residents aged 18 years and above, which we retrieved from the 2018 and 2020 waves of the China Family Panel Studies. We used latent profile analysis to categorise individuals\' internet usage patterns and multiple linear regression to determine their association with depressive symptoms.
UNASSIGNED: Higher socioeconomic status (SES) was associated with fewer depressive symptoms (τ = -0.08; 95% confidence interval (CI) = -0.36, -0.18). Individuals in the high-dependence group presented a greater likelihood of developing depressive symptoms (τ = 0.04; 95% CI = 0.007, 0.66). We observed no significant difference in the interaction effect between individual-level SES and the four patterns of internet usage. However, compared with urban-dwelling respondents, those in rural areas had a stronger association between internet usage patterns and depressive symptoms, especially those in the high-dependence group (τ = -0.07; 95% CI = -1.47, -0.20).
UNASSIGNED: Our findings indicate a significant association between depressive symptoms and internet usage patterns, indicating a need for interventions related to internet use, especially those targeted at reducing the risk of depressive symptoms in individuals of lower SES.
■我们包括了8019名18岁及以上居民的数据,我们从中国家庭小组研究的2018年和2020年浪潮中检索到的。我们使用潜在特征分析对个人的互联网使用模式和多元线性回归进行分类,以确定他们与抑郁症状的关联。
■较高的社会经济地位(SES)与较少的抑郁症状相关(τ=-0.08;95%置信区间(CI)=-0.36,-0.18)。高依赖性组的个体出现抑郁症状的可能性更大(τ=0.04;95%CI=0.007,0.66)。我们观察到个体水平的SES和四种互联网使用模式之间的交互效应没有显着差异。然而,与城市居住的受访者相比,农村地区的人在互联网使用模式和抑郁症状之间有更强的联系,尤其是高依赖性组(τ=-0.07;95%CI=-1.47,-0.20)。
■我们的研究结果表明,抑郁症状与互联网使用模式之间存在显着关联,表明需要与互联网使用相关的干预措施,特别是那些旨在降低SES较低个体抑郁症状风险的人。