AUTHOR=Xin Ling , Wang Liuhui , Cao Xuan , Tian Yingnan , Yang Yisi , Wang Kexin , Kang Zheng , Zhao Miaomiao , Feng Chengcheng , Wang Xinyu , Luo Nana , Liu Huan , Wu Qunhong TITLE=Prevalence and influencing factors of pandemic fatigue among Chinese public in Xi'an city during COVID-19 new normal: a cross-sectional study JOURNAL=Frontiers in Public Health VOLUME=Volume 10 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.971115 DOI=10.3389/fpubh.2022.971115 ISSN=2296-2565 ABSTRACT=Objective: This study aimed to assess Chinese public pandemic fatigue and potential influencing factors using an appropriate tool and provide suggestions to relieve this fatigue. Methods: This study used a stratified sampling method by age and region and conducted a cross-sectional questionnaire survey of citizens in Xi’an, China, from January to February 2022. A total of 1500 participants completed the questionnaire, which collected data on demographics, health status, coronavirus disease 2019 (COVID-19) stressors, pandemic fatigue, COVID-19 fear, COVID-19 anxiety, personal resiliency, social support, community resilience, and COVID-19 knowledge, attitude, and practice. Ultimately, 1354 valid questionnaires were collected, with a response rate of 90.0%. A binary logistic regression model was used to examine associations between pandemic fatigue and various factors. Result: Nearly half of the participants reported pandemic fatigue, the major manifestation of which was “being sick of hearing about COVID-19”(3.353 ± 1.954). The logistic regression model indicated that COVID-19 fear (OR = 2.392, 95% CI =1.804–3.172), sex (OR = 1.377, 95% CI = 1.077–1.761), the pandemic’s impact on employment (OR = 1.161, 95% CI = 1.016–1.327), and COVID-19 anxiety (OR = 1.030, 95% CI = 1.010–1.051) were positively associated with pandemic fatigue. Conversely, COVID-19 knowledge (OR = 0.894, 95% CI = 0.837–0.956), COVID-19 attitude (OR = 0.866, 95% CI = 0.827–0.907), COVID-19 practice (OR = 0.943, 95% CI = 0.914–0.972), community resiliency (OR = 0.978, 95% CI = 0.958–0.999), and health status (OR = 0.982, 95% CI = 0.971–0.992) were negatively associated with pandemic fatigue. Conclusion: The prevalence of pandemic fatigue among the Chinese public was prominent. COVID-19 fear and COVID-19 attitude were the strongest risk factors and protective factors, respectively. These results indicated that the government should carefully utilize multi-channel promotion of anti-pandemic policies and knowledge.