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 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.

Adulthood Employment Trajectories and Later Life Mental Health before and after the Onset of the COVID-19 Pandemic.

BACKGROUND: This life course study has two aims. First, to explore how diverse employment trajectories across adulthood are related to older people's mental health in Chile, a country with no research in this field, and second, to analyze these associations before and after the onset of the COVID-19 pandemic. METHODS: We use data from the nationally-representative and longitudinal 'Chilean Social Protection Survey' sequence analysis to reconstruct employment trajectory types, and bivariate and multivariate analyses to measure their association with depressive symptoms. RESULTS: Our findings indicate that formal labor force patterns in adulthood show the lowest burden of depressive symptomology before and after the onset of the overwhelming COVID-19 pandemic when controlling for traditional risk factors. CONCLUSION: We emphasize that policymakers in both the labor market and public health domains must consider the relationship between informal employment pathways in adulthood and poorer mental health in old age. Public policies should improve the conditions and quality of jobs during adulthood and promote more formalization in the labor market to address the high uncertainty involving low social protection, which is strongly associated with severe mental health problems in later life.