Temporal associations among loneliness, anxiety, and depression during the COVID‐19 pandemic period

孤独 焦虑 心理学 萧条(经济学) 临床心理学 2019年冠状病毒病(COVID-19) 精神科 医学 疾病 内科学 宏观经济学 经济 传染病(医学专业)
作者
Jianfen Wu,Yunpeng Wu,Yu Tian
出处
期刊:Stress and Health [Wiley]
卷期号:38 (1): 90-101 被引量:27
标识
DOI:10.1002/smi.3076
摘要

Numerous studies have reported that individuals' loneliness, anxiety, and depression levels increased during the COVID-19 pandemic period. However, reciprocal associations among loneliness, anxiety, and depression, as well as gender differences in these associations, have not been investigated. Therefore, temporal associations among loneliness, anxiety, and depression and gender differences in these associations were examined in a longitudinal study during the COVID-19 pandemic period. The loneliness, anxiety, and depression levels of 458 university students were evaluated at three timepoints (T1, T2, and T3) during the COVID-19 pandemic period in China. The timepoints were separated by 1 month. Cross-lagged panel designs were used to examine reciprocal associations among loneliness, anxiety, and depression as well as the stability and gender differences of these associations. Cross-lagged panel analysis revealed that T1 depression positively predicted T2 anxiety and loneliness, T1 loneliness positively predicted T2 depression, T2 anxiety positively predicted T3 depression, T2 depression positively predicted T3 anxiety and loneliness, T2 loneliness positively predicted T3 depression, and T1 loneliness positively predicted T3 anxiety through the mediating role of T2 depression. No gender differences were observed in the cross-lagged associations. During the COVID-19 pandemic period, loneliness and depression predicted each other across time, and loneliness predicted anxiety across time, mediated by depression. No gender differences were observed in the cross-lagged associations among loneliness, anxiety, and depression.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI2S应助予秋采纳,获得10
2秒前
125mmD91T完成签到,获得积分10
3秒前
cyj完成签到 ,获得积分10
12秒前
12秒前
mumian完成签到 ,获得积分10
12秒前
韩恩轩完成签到,获得积分10
17秒前
Dawn_666发布了新的文献求助10
18秒前
会写日记的乌龟先生完成签到,获得积分10
19秒前
阿弥陀佛完成签到 ,获得积分10
25秒前
Jackcaosky完成签到 ,获得积分10
35秒前
方琼燕完成签到 ,获得积分10
38秒前
Dawn_666完成签到,获得积分10
47秒前
科研菜鸟望毕业完成签到 ,获得积分10
49秒前
49秒前
Augenstern完成签到,获得积分10
56秒前
释怀发布了新的文献求助10
57秒前
dagger完成签到,获得积分10
58秒前
张宇宁完成签到 ,获得积分10
1分钟前
张真源完成签到 ,获得积分10
1分钟前
xiaoyi完成签到 ,获得积分10
1分钟前
大力牌皮揣子完成签到 ,获得积分10
1分钟前
笑点低涟妖完成签到 ,获得积分10
1分钟前
波波波波波6764完成签到 ,获得积分10
1分钟前
1分钟前
急诊守夜人完成签到 ,获得积分10
1分钟前
踏实的书包完成签到,获得积分10
1分钟前
lll发布了新的文献求助10
1分钟前
racill完成签到 ,获得积分10
1分钟前
1分钟前
罗晴完成签到 ,获得积分10
1分钟前
玻璃弹珠发布了新的文献求助10
1分钟前
黑眼圈完成签到 ,获得积分10
1分钟前
玻璃弹珠完成签到,获得积分20
1分钟前
一只盒子完成签到 ,获得积分10
1分钟前
科目三应助lll采纳,获得10
1分钟前
青年晚报完成签到,获得积分10
1分钟前
逢场作戱__完成签到 ,获得积分10
2分钟前
活力的问安完成签到 ,获得积分10
2分钟前
Rxtdj完成签到 ,获得积分10
2分钟前
laber完成签到,获得积分0
2分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6358938
求助须知:如何正确求助?哪些是违规求助? 8172953
关于积分的说明 17211612
捐赠科研通 5413926
什么是DOI,文献DOI怎么找? 2865319
邀请新用户注册赠送积分活动 1842737
关于科研通互助平台的介绍 1690806