Frontiers in Public Health (Sep 2022)

Prevalence and influencing factors of pandemic fatigue among Chinese public in Xi'an city during COVID-19 new normal: a cross-sectional study

  • Ling Xin,
  • Ling Xin,
  • Liuhui Wang,
  • Liuhui Wang,
  • Xuan Cao,
  • Xuan Cao,
  • Yingnan Tian,
  • Yisi Yang,
  • Kexin Wang,
  • Kexin Wang,
  • Zheng Kang,
  • Zheng Kang,
  • Miaomiao Zhao,
  • Chengcheng Feng,
  • Xinyu Wang,
  • Xinyu Wang,
  • Nana Luo,
  • Nana Luo,
  • Huan Liu,
  • Huan Liu,
  • Qunhong Wu,
  • Qunhong Wu

DOI
https://doi.org/10.3389/fpubh.2022.971115
Journal volume & issue
Vol. 10

Abstract

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ObjectiveThis study aimed to assess Chinese public pandemic fatigue and potential influencing factors using an appropriate tool and provide suggestions to relieve this fatigue.MethodsThis 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 knowledge, attitude, and practice toward COVID-19. 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.ResultNearly 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.ConclusionThe 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.

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