A Longitudinal Study of Loneliness Before the End of the COVID-19 Pandemic: Trajectories, Predictors, and Impact on Chinese Adolescent Mental Health

Abstract

Jingyi Wang,1,* Wei Zhang,1,* Peige Song,2,* Tingting Wang,3 Ye Yao,1 Yun Chen,4 Haijiang Lin,3 Xiaoqi Yang,1 Xiaoxiao Chen,1,3 Chaowei Fu1 1School of Public Health; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, People’s Republic of China; 2School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 3Taizhou City Center for Disease Control and Prevention, Taizhou, Zhejiang Province, People’s Republic of China; 4Yale School of Nursing, Orange, CT, 06477, USA*These authors contributed equally to this workCorrespondence: Chaowei Fu, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, 200032, People’s Republic of China, Email [email protected] Xiaoxiao Chen, Taizhou City Center for Disease Control and Prevention, Taizhou, Zhejiang Province, 318000, People’s Republic of China, Email [email protected]: COVID-19 threatened global health, however little is known about the long-term courses of loneliness and their effect on mental health in adolescents. This study aimed to explore the trajectories of loneliness among adolescents in Taizhou, Zhejiang Province, China, during the last phase of the pandemic. We also aimed to identify risk factors in each loneliness course and the impact of loneliness on emotional problems, peer problems, hyperactivity and conduct problems.Methods: The study employed multistage cluster sampling to collect four waves of data from 2347 Chinese adolescents (average baseline age of 14.7 years) covering a period of 20 months (October 2021 – May 2023). The UCLA 3-Item Loneliness Scale and the Strengths and Difficulties Questionnaire were utilized to assess loneliness and mental health problems, respectively. Growth mixture modelling was employed to identify latent classes of loneliness trajectories. Associated risk factors were investigated using multinomial logistic regression model. Mixed-effects logistic regression models were constructed to examine the long-term impact of loneliness classes on mental health outcomes.Results: The overall percentage of loneliness increased from 22.9% at baseline to 32.2% at the fourth wave in our sample. Three classes of loneliness were identified: Decreasing Low Loneliness (58.71%), Increasing Medium Loneliness (36.52%), and Increasing High Loneliness (4.77%). Risk factors for poorer loneliness trajectories included lack of physical exercise habits, poorer mental health literacy, medium or low perceived social support, having study difficulties, being female, higher grades, and lower economic status. Loneliness classes were associated with the severity and variability of emotional problems, peer problems, hyperactivity and conduct problems (ORs for the highest loneliness class: 10.24, 4.21, 3.87, 2.68, respectively). Individuals in the higher loneliness classes experienced a significant increase in these mental health problems over time (p < 0.05 for interactions between loneliness classes and time).Conclusion: During the last phase of the pandemic, a large proportion of adolescents in our study endured medium to high levels of loneliness with no signs of improvement. Both unfavorable loneliness trajectories adversely affected internalizing and externalizing problems and displayed an upward trend in these difficulties. Results highlight the importance of tackling loneliness and improving mental health in adolescents.Keywords: adolescents, loneliness, risk factors, internalizing problems, externalizing problems, COVID-19

Keywords

• adolescents
• loneliness
• risk factors
• internalizing problems
• externalizing problems
• covid-19