Who would take part in a pandemic preparedness cohort study? The role of vaccine-related affective polarisation: cross-sectional survey

This cross-sectional survey in Switzerland reveals that while socioeconomic factors like education and income strongly predict willingness to join a pandemic preparedness cohort study, affective polarisation regarding COVID-19 vaccination significantly modifies this willingness, with polarised supporters being more likely to participate and both polarised and non-polarised opponents being less likely to do so.

The Gist

Imagine the world is a giant neighborhood that just survived a massive storm (the COVID-19 pandemic). Now, the neighborhood watch (public health officials) wants to build a permanent "Storm Watch" team. This team would be a group of neighbors who agree to stay connected, share information, and help scientists understand how future storms might hit, so everyone can be better prepared next time.

But here's the problem: Who actually wants to join this team?

This paper is like a giant survey sent out to 15,000 homes in the Canton of Bern, Switzerland, to ask: "Would you sign up for our Storm Watch team?" The researchers wanted to know not just who said yes, but why, and how people's feelings about vaccines (a major topic of debate during the storm) influenced their answer.

Here is the breakdown of what they found, using some simple analogies:

1. The "Who" of the Team: The High-End Club vs. The Rest

Think of the people willing to join the Storm Watch team as a specific type of club member.

• The VIPs: The people most likely to say "Yes!" were those with higher education and higher incomes. It's like a club where the members are comfortable, have time, and feel confident navigating complex forms.
• The Struggling Members: People with less education, lower incomes, or who were older were much less likely to join. They might feel too busy, too skeptical, or just think, "This isn't for people like me."
• The Location Factor: People living in the city (Bern) were more willing to join than those in the quiet countryside.

2. The Vaccine "Team Jersey" Effect

The researchers noticed something fascinating about how people felt about vaccines. Imagine vaccines are like a sports team jersey.

• The Die-Hard Fans: People who loved vaccines (and felt very strongly about it) were super eager to join the research team. They saw it as a way to help their "team" win.
• The Opponents: People who hated vaccines were very unwilling to join. They didn't trust the organizers.
• The "Affective Polarization" Twist: This is the most interesting part. The researchers measured something called "Affective Polarization."
  • What is it? Imagine you are at a party. If you love the people who agree with you and hate the people who disagree with you, you are "polarized." You aren't just different; you have strong feelings against the other side.
  • The Finding: If you were a vaccine supporter AND you had strong feelings against non-vaxxers, you were even more likely to join the research team. You wanted to prove your side right!
  • The Flip Side: If you were a vaccine opponent AND you had strong feelings against vaccine supporters, you were the least likely to join. You didn't just disagree; you didn't want to be in the same room as the researchers.

3. Why Join? (The "Why" of the Team)

When the researchers asked the "Yes" crowd why they wanted to join, the answers were like a warm hug:

• "I want to help my neighbors." (Altruism)
• "I want to stop the next storm." (Preparation)
• "I'm curious about science."

When they asked the "No" crowd why they refused, the answers were like cold walls:

• "I don't care." (Lack of interest)
• "I don't trust you with my secrets." (Privacy concerns)
• "I don't believe in your science." (Mistrust)

4. The Pet Factor

The study also asked, "Would you let your kids or pets join?"

• People were less willing to sign up their children than themselves. (Parents are protective!)
• They were most willing to sign up their rodents (guinea pigs, hamsters), followed by dogs and cats. (Maybe because pets are seen as less "human" and therefore less risky to involve?)

The Big Takeaway

The main lesson from this paper is that feelings matter more than facts when it comes to joining research.

If you want to build a strong "Storm Watch" team for the next pandemic, you can't just send out a flyer. You have to realize that:

1. Socioeconomics matter: You need to reach out to people who feel left out (lower income, less education).
2. Emotions drive decisions: If people feel angry or hostile toward a specific group (like vaccine opponents), they will likely refuse to work with scientists.
3. Trust is key: To get everyone on board, researchers need to bridge the gap between the "fans" and the "opponents" and show that the research is for everyone's safety, not just one side's victory.

In short: To prepare for the next pandemic, we need to stop treating research like a political battle and start treating it like a community project where everyone feels safe enough to join the team.

Technical Summary

1. Problem Statement

Cohort studies are critical for public health research regarding emerging infectious diseases and pandemic preparedness. However, recruitment for such studies is often hindered by declining participation rates, mistrust in science, and limited time. While socioeconomic and demographic factors influencing research participation are well-documented, the role of affective polarisation—defined as an affinity for those with similar views and hostility toward those with opposing views—remains under-explored. Specifically, it is unclear how feelings regarding COVID-19 vaccination and the resulting polarisation affect an individual's willingness to participate in future pandemic preparedness research.

2. Methodology

• Study Design: Cross-sectional online survey.
• Setting: Canton of Bern, Switzerland (population ~1.07 million), selected for its demographic similarity to the national average.
• Sampling:
  • A random sample of 15,000 private households was drawn from the Cantonal Administration registry.
  • Oversampling: Larger households (3+ members) were oversampled to ensure sufficient data for a future household-based cohort study (the "BEready" project).
  • Participants: One adult (18+) per household was randomly selected as the primary contact.
• Data Collection:
  • Invitations were sent via surface mail in September 2022, with reminders in October and November. The survey closed in December 2022.
  • The questionnaire covered demographics, social mixing, motivations for participation, and specific metrics on COVID-19 vaccination attitudes.
  • Key Measures:
    • Willingness to Participate: Measured on a 4-point scale (Yes, Probably Yes, Probably No, No).
    • Vaccination Opinion: 0–10 scale (0 = complete rejection, 10 = complete support).
    • Affective Polarisation: Measured using a "feeling thermometer" (–5 to +5) for both vaccinated and unvaccinated people. The absolute difference between these scores created a polarisation index (0–10).
• Statistical Analysis:
  • Inverse probability weighting was applied to correct for the oversampling of larger households.
  • Logistic regression (univariable and multivariable) was used to estimate Odds Ratios (OR) and Adjusted Odds Ratios (aOR).
  • Interaction terms were included to test the effect modification of affective polarisation on the relationship between vaccination opinion and willingness to participate.
  • Sensitivity analyses were conducted regarding neutral vaccination scores and polarisation cut-offs.

3. Key Contributions

• Novelty in Measurement: This is one of the first studies to quantify affective polarisation specifically regarding COVID-19 vaccination and link it directly to research participation willingness.
• Interaction Effects: It demonstrates that the relationship between vaccination stance and research participation is not linear but is significantly modified by the intensity of polarised feelings.
• Household Context: The study specifically addresses willingness to include children and pets in research, a crucial component for "One Health" pandemic preparedness.
• Post-Pandemic Insight: It provides baseline data on research engagement attitudes in Switzerland immediately following the acute phase of the COVID-19 pandemic.

4. Key Results

• Response Rate: 22.8% (3,425/15,000) of households responded; 3,394 provided data on willingness to participate.
• Overall Willingness: The weighted proportion of respondents willing to participate was 49.8% (95% CI: 47.9–51.8).
• Socioeconomic Determinants:
  • Education: Higher education was the strongest predictor of willingness (Tertiary education: aOR 2.48 vs. Compulsory education).
  • Income: Higher monthly income (>9,000 CHF) was strongly associated with willingness (aOR 1.92).
  • Demographics: Older age and larger household sizes were associated with lower willingness.
• Vaccination Attitudes & Polarisation:
  • Opposition: Those opposing vaccination were significantly less willing to participate (aOR 0.53).
  • Polarisation Effect:
    • Among vaccination supporters, being polarised (hostile toward opposers) increased willingness to participate compared to non-polarised supporters (aOR 1.51).
    • Among vaccination opposers, being polarised drastically reduced willingness to participate (aOR 0.26) compared to non-polarised supporters.
• Motivations:
  • Top reasons for participation: Altruism ("contribute to health of others," 56%) and pandemic preparedness (41%).
  • Top reasons for non-participation: Lack of interest (42%), privacy concerns, and mistrust.
• Children and Pets: Willingness to include children (40.0%) and pets (46.1%) was lower than for oneself.

5. Significance and Implications

• Recruitment Bias: The study highlights a significant risk of selection bias in future pandemic cohorts. If recruitment relies on standard methods, these cohorts may over-represent highly educated, wealthy, and polarised vaccination supporters, while under-representing older adults, lower-income groups, and vaccination skeptics.
• Role of Polarisation: Affective polarisation acts as a double-edged sword. It drives engagement among those who support public health measures but creates a "hard-to-reach" barrier for those who oppose them.
• Public Health Strategy: To improve participation in pandemic preparedness:
  • Researchers must address socioeconomic disparities (e.g., offering flexible participation options for lower-income groups).
  • Community engagement is needed to rebuild trust and address privacy concerns, particularly among vaccination skeptics.
  • Communication strategies should acknowledge that polarised individuals are highly motivated by their in-group identity; framing research as a collective defense against a common threat may be effective for supporters, while different approaches are needed for opposers.
• Future Research: The findings suggest that longitudinal monitoring of affective polarisation within cohorts (like the BEready study) is necessary to understand how crisis solidarity evolves over time.

Conclusion: Willingness to participate in pandemic preparedness research is moderate but stratified by socioeconomic status and vaccination attitudes. Affective polarisation significantly modifies these attitudes, suggesting that future research recruitment strategies must be multidisciplinary and tailored to overcome mistrust and engagement barriers across diverse political and social spectrums.