Temporal changes in factors associated with COVID-19 vaccine hesitancy among Chinese adults: Repeated nationally representative survey

Mingze Ma; Xiaoman Wu; Qiuping Zhao; Rongmei Liu; Quanman Li; Xinghong Guo; Zhanlei Shen; Clifford Silver Tarimo; Yifei Feng; Lipei Zhao; Beizhu Ye; Jian Wu; Yudong Miao

doi:10.1016/j.ssmph.2023.101574

Temporal changes in factors associated with COVID-19 vaccine hesitancy among Chinese adults: Repeated nationally representative survey

SSM Popul Health. 2023 Dec 10:25:101574. doi: 10.1016/j.ssmph.2023.101574. eCollection 2024 Mar.

Authors

Mingze Ma^{1

2}, Xiaoman Wu^{1

2}, Qiuping Zhao³, Rongmei Liu³, Quanman Li^{1

2}, Xinghong Guo^{1

2}, Zhanlei Shen^{1

2}, Clifford Silver Tarimo^{1

4}, Yifei Feng^{1

2}, Lipei Zhao^{1

2}, Beizhu Ye^{1

2}, Jian Wu^{1

2}, Yudong Miao^{1

2}

Affiliations

¹ Department of Health Management, College of Public Health, Zhengzhou University, Henan, China.
² Henan Province Engineering Research Center of Health Economy & Health Technology Assessment, Zheng Zhou, Henan, China.
³ Henan Key Laboratory for Health Management of Chronic Diseases, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zheng Zhou, Henan, China.
⁴ Department of Science and Laboratory Technology, Dar es Salaam Institute of Technology, Dar es Salaam, Tanzania.

Abstract

Background: COVID-19 vaccine hesitancy has been cited as one of the main obstacles impacting vaccine coverage. However, factors that affect hesitancy may change over time. Understanding these evolving concerns and adapting strategies accordingly are crucial for effectively addressing vaccine hesitancy effectively and promoting public health. We aimed to explore the temporal changes in factors associated with COVID-19 VH during the COVID-19 pandemic and assess the dynamic evolution of VH.

Methods: In August 2022 and February 2023, repeated online surveys were undertaken to collect information from 5378 adults across four regions of China. Multiple linear regression models assessed the influencing factors of COVID-19 VH. The association between protective motive theory (PMT) (perceived severity, susceptibility, benefits, barriers, and self-efficacy) and VH was evaluated by structural equation modeling (SEM).

Results: Repeated measures showed that 573 (10.7%) and 1598 (29.7%) of the 5378 participants reported COVID-19 VH in the baseline and follow-up surveys, respectively. Educational levels, chronic disease, history of allergy, COVID-19 infection, and trust in medical staff and vaccine developers were positively associated with COVID-19 VH (P＜0.05). The application of SEM revealed that perceived severity, susceptibility, vaccination barriers, and self-efficacy in the PMT directly impacted on VH (P＜0.05). In addition, severity, susceptibility, benefits, and barriers had a significant direct effect on self-efficacy as β = 0.113, β = 0.070, β = 0.722, β = -0.516 respectively with P < 0.001.

Conclusion: The prevalence of COVID-19 VH was relatively low in the baseline survey and much higher in the follow-up survey, with a significant increase in hesitancy rates among mainland Chinese residents. Acknowledging the substantial impact on the shaping of COVID-19 VH, one must consider factors including perceived severity, susceptibility, vaccination barriers, and self-efficacy.

Keywords: COVID-19 vaccine; China; Protection motivation theory; Structural equation modeling; Vaccine hesitancy.