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Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008805/ https://www.ncbi.nlm.nih.gov/pubmed/36933985 http://dx.doi.org/10.1016/j.vaccine.2023.03.016 |
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author | Lamuda, Phoebe A. Azar, Ariel Taylor, Bruce G. Balawajder, Elizabeth Flanagan Pollack, Harold A. Schneider, John A. |
author_facet | Lamuda, Phoebe A. Azar, Ariel Taylor, Bruce G. Balawajder, Elizabeth Flanagan Pollack, Harold A. Schneider, John A. |
author_sort | Lamuda, Phoebe A. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10008805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100088052023-03-13 Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization Lamuda, Phoebe A. Azar, Ariel Taylor, Bruce G. Balawajder, Elizabeth Flanagan Pollack, Harold A. Schneider, John A. Vaccine Article 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. The Author(s). Published by Elsevier Ltd. 2023-04-17 2023-03-13 /pmc/articles/PMC10008805/ /pubmed/36933985 http://dx.doi.org/10.1016/j.vaccine.2023.03.016 Text en © 2023 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Lamuda, Phoebe A. Azar, Ariel Taylor, Bruce G. Balawajder, Elizabeth Flanagan Pollack, Harold A. Schneider, John A. Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization |
title | Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization |
title_full | Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization |
title_fullStr | Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization |
title_full_unstemmed | Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization |
title_short | Latent class analysis of medical mistrust and COVID-19 vaccine hesitancy among adults in the United States just prior to FDA emergency use authorization |
title_sort | latent class analysis of medical mistrust and covid-19 vaccine hesitancy among adults in the united states just prior to fda emergency use authorization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008805/ https://www.ncbi.nlm.nih.gov/pubmed/36933985 http://dx.doi.org/10.1016/j.vaccine.2023.03.016 |
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