Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization. Issue 16 (17th April 2023)

• Record Type: Journal Article
• Authors: Lamuda, Phoebe A.; Azar, Ariel; Taylor, Bruce G.; Balawajder, Elizabeth Flanagan; Pollack, Harold A.; Schneider, John A.
• Is Part Of: Vaccine. Volume 41:Issue 16(2023)
• Page Start: 2671
• Page End: 2679
• Publication Date: 2023-04-17
• Subjects: Vaccine hesitancy -- COVID-19 -- Medical mistrust; AME Average marginal effect -- BIC Bayesian Information Criterion -- CDC Centers for Disease Control -- LCA Latent class analysis -- NIS National Immunization Survey -- PCP Primary care provider -- MM Medical mistrust -- ACS American Community Survey; Vaccines -- Periodicals; 615.372
• DOI: 10.1016/j.vaccine.2023.03.016
• Languages: English
• ISSNs: 0264-410X

Abstract

Highlights: General population distinguishes between trust in their own doctor and medical research. People's race and ethnicity good predictor of medical mistrust archetype. Medical mistrust a stronger predictor than political affiliation for COVID-19 vaccine hesitancy. Abstract: 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.