The Mediating Roles of Medical Mistrust, Knowledge, Confidence and Complacency of Vaccines in the Pathways from Conspiracy Beliefs to Vaccine Hesitancy
Authors: Zhang Xiaoning , Guo Yuqing , Zhou Qiong , Tan Zaixiang , Cao Junli 
Published: November 2021

Background: Vaccine hesitancy, associated with medical mistrust, confidence, complacency and knowledge of vaccines, presents an obstacle to the campaign against the coronavirus disease 2019 (COVID-19). The relationship between vaccine hesitancy and conspiracy beliefs may be a key determinant of the success of vaccination campaigns. This study provides a conceptual framework to explain the impact of pathways from conspiracy beliefs to COVID-19 vaccine hesitancy with regard to medical mistrust, confidence, complacency and knowledge of vaccines. Methods: A non-probability study was conducted with 1015 respondents between 17 April and 28 May 2021. Conspiracy beliefs were measured using the coronavirus conspiracy scale of Coronavirus Explanations, Attitudes, and Narratives Survey (OCEANS), and vaccine conspiracy beliefs scale. Medical mistrust was measured using the Oxford trust in doctors and developers questionnaire, and attitudes to doctors and medicine scale. Vaccine confidence and complacency were measured using the Oxford COVID-19 vaccine confidence and complacency scale. Knowledge of vaccines was measured using the vaccination knowledge scale. Vaccine hesitancy was measured using the Oxford COVID-19 vaccine hesitancy scale. Confirmatory factor analysis (CFA) was used to evaluate the measurement models for conspiracy beliefs, medical mistrust, confidence, complacency, and knowledge of vaccines and vaccine hesitancy. The structural equation modeling (SEM) approach was used to analyze the direct and indirect pathways from conspiracy beliefs to vaccine hesitancy. Results: Of the 894 (88.1%) respondents who were willing to take the COVID-19 vaccine without any hesitancy, the model fit with the CFA models for conspiracy beliefs, medical mistrust, confidence, complacency and knowledge of vaccines, and vaccine hesitancy was deemed acceptable. Conspiracy beliefs had significant direct (β = 0.294), indirect (β = 0.423) and total (β = 0.717) effects on vaccine hesitancy; 41.0% of the total effect was direct, and 59.0% was indirect. Conspiracy beliefs significantly predicted vaccine hesitancy by medical mistrust (β = 0.210), confidence and complacency (β = 0.095), knowledge (β = 0.079) of vaccines, explaining 29.3, 11.0, and 13.2% of the total effects, respectively. Conspiracy beliefs significantly predicted vaccine hesitancy through the sequential mediation of knowledge of vaccines and medical mistrust (β = 0.016), explaining 2.2% of the total effects. Conspiracy beliefs significantly predicted vaccine hesitancy through the sequential mediation of confidence and complacency, and knowledge of vaccines (β = 0.023), explaining 3.2% of the total effects. The SEM approach indicated an acceptable model fit (χ2/df = 2.464, RMSEA = 0.038, SRMR = 0.050, CFI = 0.930, IFI = 0.930). Conclusions: The sample in this study showed lower vaccine hesitancy, and this study identified pathways from conspiracy beliefs to COVID-19 vaccine hesitancy in China. Conspiracy beliefs had direct and indirect effects on vaccine hesitancy, and the indirect association was determined through medical mistrust, confidence, complacency, and knowledge of vaccines. In addition, both direct and indirect pathways from conspiracy beliefs to vaccine hesitancy were identified as intervention targets to reduce COVID–19 vaccine hesitancy.