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Ying Chen

Xi’an Jiaotong-Liverpool University, China

Title: Perceived epidemic impacts and mental symptom trajectories in adolescents back to school after COVID-19 restriction

Abstract

This study aimed to assess the impacts of COVID-19 epidemic on various life aspects and identify the trajectories of common mental symptoms among adolescents back to school after COVID-19 restriction. Furthermore, potential predictors associated with those trajectories were investigated. This longitudinal study, with five data collection points and a total follow-up of 68.4 days, was conducted among 1393 junior high school students (mean age: 13.8 years; male, 53.3%) shortly after school reopened during the first COVID-19 outbreak in China. Questions on socio-demographics and perceived COVID-19 epidemic impacts were completed at the baseline while the Patient Health Questionnaire, Generalized Anxiety Disorder Scale and Insomnia Severity Index were measured throughout the study for depression, anxiety and insomnia symptoms respectively. Trajectories of mental symptoms were classified by longitudinal latent class analysis, and the associated predictive factors were identified with multivariable multinomial regression modelling. Our study revealed high but steadily declining prevalence of depression, anxiety and insomnia symptoms (p trend < 0.001). Five distinctive trajectories were identified for both depression and anxiety (‘Resistance’, ‘Low symptom’, ‘Recovery’, ‘Chronic dysfunction’ and ‘Delayed dysfunction’) and three for insomnia (‘Resistance’, ‘Low symptom’ and ‘Chronic dysfunction’). Besides the significant association between the mental symptom trajectories and students’ perceived COVID-19 impacts on study practice, family income and family relationship, female gender, lower school grade and higher body mass index were found predictive of high severity trajectories. Our findings may help locate the most psychologically vulnerable adolescents during the pandemic, and foster better implementation of targeted intervention.

Biography

Ying Chen is a biostatistician and epidemiologist working extensively in healthcare research. He has extensive experience in observational and experimental studies, including clinical trials. His research has been focusing on disease surveillance, disease prevention, early diagnosis and intervention, disease management, drug safety, health economic evaluation, environmental epidemiology and public health. He has a particular interest in use of big real-world database. His work uses a very broad of statistical methods, from descriptive statistics, traditional regression analyses for hypothesis testing to novel technologies for large and complex datasets. He contributes to the writing of scientific presentation, report and paper, sometimes as the leading and corresponding author of a multi-authored publication on medical/scientific journals. To date, he has published more than 70 SCI publications, many of which are in the top journals. He serves as a member of Editorial Board for Life (published by MDPI) and Scientific Reports (published by Nature Publishing Group).