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
回眸牟发布了新的文献求助80
2秒前
瑶啊瑶完成签到,获得积分10
5秒前
完美世界应助浩博木东采纳,获得10
6秒前
解语花031发布了新的文献求助30
7秒前
田様应助五六七采纳,获得10
8秒前
9秒前
10秒前
Lucas应助sylnd126采纳,获得10
14秒前
14秒前
14秒前
堂岛之龙完成签到,获得积分20
15秒前
15秒前
XQQDD发布了新的文献求助10
16秒前
所所应助余钝的一个人采纳,获得10
19秒前
小蘑菇应助kkjust采纳,获得10
20秒前
负责吃饭完成签到,获得积分10
20秒前
堂岛之龙发布了新的文献求助10
20秒前
21秒前
xiaoming完成签到 ,获得积分10
21秒前
21秒前
暗月青影完成签到,获得积分10
24秒前
嘛呱发布了新的文献求助10
25秒前
五六七发布了新的文献求助10
25秒前
26秒前
传奇3应助xjs采纳,获得10
27秒前
28秒前
空空1213完成签到 ,获得积分10
28秒前
爆米花应助堂岛之龙采纳,获得10
28秒前
FashionBoy应助解语花031采纳,获得30
29秒前
快乐含蕾发布了新的文献求助10
29秒前
NexusExplorer应助回眸牟采纳,获得10
29秒前
天天快乐应助王佟采纳,获得10
29秒前
30秒前
32秒前
32秒前
sylnd126发布了新的文献求助10
33秒前
33秒前
34秒前
34秒前
小李完成签到,获得积分10
34秒前
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
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
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 6355051
求助须知:如何正确求助?哪些是违规求助? 8170176
关于积分的说明 17199368
捐赠科研通 5411087
什么是DOI,文献DOI怎么找? 2864158
邀请新用户注册赠送积分活动 1841760
关于科研通互助平台的介绍 1690150