NORC, 55 East Monroe Street 30th Floor, Chicago, IL 60603, United States.
Department of Sociology, University of Chicago, 1126 East 59th Street, Chicago, IL 60637, United States; Center for International Social Science Research, University of Chicago, 5828 South University Avenue, Chicago, IL 60637, United States.
Vaccine. 2023 Apr 17;41(16):2671-2679. doi: 10.1016/j.vaccine.2023.03.016. Epub 2023 Mar 13.
Using a nationally representative household sample, we sought to better understand types of medical mistrust as a driver of COVID-19 vaccine hesitancy. We used survey responses to conduct a latent class analysis to classify respondents into categories and explained this classification as a function of sociodemographic and attitudinal variables using multinomial logistic regression models. We then estimated the probability of respondents agreeing to receive a COVID-19 vaccine conditional on their medical mistrust category. We extracted a five-class solution to represent trust. The high trust group (53.0 %) is characterized by people who trust both their doctors and medical research. The trust in own doctor group (19.0 %) trust their own doctors but is ambiguous when it comes to trusting medical research. The high distrust group (6.3 %) neither trust their own doctor nor medical research. The undecided group (15.2 %) is characterized by people who agree on some dimensions and disagree on others. The no opinion group (6.2 %) did not agree nor disagree with any of the dimensions. Relative to the high trust group, those who trust their own doctors are almost 20 percentage points less likely to plan to get vaccinated (average marginal effect (AME) = 0.21, p <.001), and those who have high distrust are 24 percentage points less likely (AME = -0.24, p <.001) to report planning to get the vaccine. Results indicate that beyond sociodemographic characteristics and political attitudes, people's trust archetypes on parts of the medical field significantly predict their probability of wanting to get vaccinated. Our findings suggest that efforts to combat vaccine hesitancy should focus on building capacity of trusted providers to speak with their patients and parents of their patients, to recommend COVID-19 vaccination and build a trusting relationship; and increase trust and confidence in medical research.
利用全国代表性的家庭样本,我们试图更好地理解医学不信任作为 COVID-19 疫苗犹豫的驱动因素的类型。我们使用调查回复进行潜在类别分析,将受访者分为不同类别,并使用多项逻辑回归模型,以社会人口统计学和态度变量来解释这种分类。然后,我们估计了受访者同意接种 COVID-19 疫苗的概率,条件是他们的医疗不信任类别。我们提取了一个五类别解决方案来表示信任。高信任组(53.0%)的特征是既信任医生又信任医学研究的人。信任自己医生组(19.0%)信任自己的医生,但在信任医学研究方面存在模糊性。高不信任组(6.3%)既不信任自己的医生,也不信任医学研究。未决定组(15.2%)的特点是在一些方面同意,在另一些方面不同意。无意见组(6.2%)对任何维度都既不同意也不反对。与高信任组相比,那些信任自己医生的人计划接种疫苗的可能性低近 20 个百分点(平均边际效应(AME)= 0.21,p<.001),而那些高度不信任的人计划接种疫苗的可能性低 24 个百分点(AME=-0.24,p<.001)。结果表明,除了社会人口统计学特征和政治态度外,人们对医疗领域的信任模式显著预测了他们想要接种疫苗的概率。我们的研究结果表明,为了对抗疫苗犹豫,应该努力提高受信任的提供者的能力,与他们的患者和患者的家长交谈,推荐 COVID-19 疫苗接种,并建立信任关系;并增加对医学研究的信任和信心。