Using Data Science to Quantify the Impact of Misinformation, Mistrust, and Other Key Psychosocial Factors on Vaccine Hesitancy Among Vulnerable People Experiencing Psychopathology
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 1K01MH132899-01A1
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Key facts
Disease
COVID-19, UnspecifiedStart & end year
20242025Known Financial Commitments (USD)
$187,261Funder
National Institutes of Health (NIH)Principal Investigator
POSTDOC Michael BronsteinResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF MINNESOTAResearch Priority Alignment
N/A
Research Category
Policies for public health, disease control & community resilience
Research Subcategory
Vaccine/Therapeutic/ treatment hesitancy
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Other
Occupations of Interest
Not applicable
Abstract
People with severe mental illness (SMI) are ~3x more likely to contract and ~7x more likely to die from vaccine- preventable disease. And yet, vaccine uptake is significantly lower among people with SMI, likely due to greater vaccine delay/refusal despite availability ("hesitancy"). Critical knowledge gaps - including extremely limited knowledge of whether and how unique features of SMI modulate hesitancy - impede selection of interventions on vaccination for people with SMI. This K01's purpose is to determine unique reasons for hesitancy among people with SMI (Aim 1), reveal causal pathways to hesitancy in people with SMI and forecast which variables in these pathways are likely the best intervention targets (Aim 2), and examine the impact of education about herd immunity - which improves vaccine intentions in the general population - on vaccine intentions and uptake in people with SMI (Aim 3). In Study 1, we will recruit people with SMI and two comparison groups: people with depression/anxiety and healthy people. Participants will complete measures of SARS-CoV-2 and influenza vaccine intentions/uptake, of factors that may be uniquely relevant to hesitancy in people with SMI, and of variables implicated in general population models of vaccine hesitancy. We will compare groups' willingness to vaccinate, their level of concern about vaccines' dangerousness, and their endorsement of anti-vaccine information (Aim 1). We will use active-learning causal discovery algorithms and intervention calculus to reveal causal pathways to hesitancy in people with SMI, quantify the lower-bound total causal effect of variables in these pathways on hesitancy, and prescribe future experiments to resolve any uncertainties in these causal pathways (Aim 2). In Study 2, we will use established natural language processing tools to analyze rates of and attitudes to anti- vaccine misinformation in Tweets from Study 1 participants. This analysis will complement our laboratory assessments of anti-vaccine misinformation endorsement for Aim 1. In Study 3, we will recruit a subset of participants from Study 1's healthy and SMI groups. We will compare the effects of education about herd immunity across these groups, with the goal of identifying differential efficacy and examining the need to tailor existing interventions to people with SMI (Aim 3). Our rigorous characterization of unique aspects of vaccine hesitancy among people with SMI, along with causal pathways we reveal, our corresponding predictions about the impact of manipulating variables in these pathways, and our quantification of herd immunity education's effect on vaccine decisions, will provide critical road-maps for empirically-informed interventions on hesitancy in people with mental illness. These road-maps will move us closer to a world where effective, evidence-based interventions on hesitancy are deployed to protect people with SMI from vaccine-preventable disease.