Does discourse breed an appetite for Covid-19 vaccination? An online experiment on group dynamics, arguments, and narratives

Last registered on June 22, 2021

Pre-Trial

Trial Information

General Information

Title
Does discourse breed an appetite for Covid-19 vaccination? An online experiment on group dynamics, arguments, and narratives
RCT ID
AEARCTR-0007850
Initial registration date
June 21, 2021

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 22, 2021, 10:08 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
June 22, 2021, 1:20 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
Utrecht University

Other Primary Investigator(s)

PI Affiliation
University of Hamburg
PI Affiliation
University of Hamburg
PI Affiliation
University of Hamburg

Additional Trial Information

Status
In development
Start date
2021-06-23
End date
2021-09-30
Secondary IDs
Abstract
This study investigates how peer-to-peer communication with vaccination supporters affects the willingness to get vaccinated (henceforth, WGV) against Covid-19 among vaccine skeptics and vice versa. Various large-scale surveys in Germany indicate diverging opinions on newly developed vaccines against Covid-19 across different socio-demographic groups. Without increasing the WGV among these groups, it will be extremely challenging and politically costly for the government to attain herd immunity by vaccination. This challenge is further heightened by the widespread misinformation in online echo chambers and the growing presence of anti-vaxxers communities online. This situation is representative for many other economically and politically relevant situations, where public good provision and the overall welfare depends on coordinated actions of individuals that form their beliefs and motivations within their own social networks. Since online peer-to-peer communication is a relevant source of information for vaccine skeptics, this work aims to shed light on whether and how different types of arguments and persuasion tactics are effective in changing beliefs and motivations.
External Link(s)

Registration Citation

Citation
Koch, Juliane et al. 2021. "Does discourse breed an appetite for Covid-19 vaccination? An online experiment on group dynamics, arguments, and narratives." AEA RCT Registry. June 22. https://doi.org/10.1257/rct.7850-1.1
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Different types of text treatments
Chat vs. non-chat in groups
Intervention Start Date
2021-06-23
Intervention End Date
2021-07-11

Primary Outcomes

Primary Outcomes (end points)
Change in willingness to get vaccinated
Primary Outcomes (explanation)
We measure the willingness to get vaccinated on a 5-point Likert scale.
Additionally, we also measure is whether the subject has been vaccinated against Covid-19 several weeks after the treatments.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
3x2 factorial design between: Chat vs. non-chat and 2 different text primed treatments and 1 control text treatment


Experimental Design Details
We implement two waves of an online survey. In Wave 1, we run a 3x2 design study with a total of 3600 subjects. We will elicit prior willingness to get vaccinated (WGV) against Covid-19 of subjects, along with their pandemic-related knowledge and their social, political and media preferences.

Subjects are equally split into three clusters (T0), (T1) and (T2). (T0) is our control treatment where we simply ask subjects to write two arguments based on what they think are the reasons for and against a Covid-19 vaccination. In (T1), we first show subjects two sets of anecdote-based arguments. In (T2), we first show subjects two sets of fact-based arguments, for and against the same topic used in (T1). Afterwards, as in the control treatment (T0), we ask them to write two arguments based on what they think are the reasons for and against Covid-19 vaccination.

After this step, we randomly assign participants to the chat (C1) and the non-chat (C0) treatment. Once the treatment has been assigned, we exogenously form groups of 3 to 5 persons. Groups are homogeneous with respect to treatments (T0), (T1) and (T2) but heterogenous with respect to their WGV. Participants are then shown the WGV of their assigned group members. Participants in the (C1) treatment are instructed to chat respectfully with one another on the pros and cons of getting vaccinated against Covid-19. This chat treatment variation serves to: (1) identify the impact of interactions on opinion changes, and (2) disentangle chat effect from the group belief-composition effect.

Finally, we will re-elicit the WGV of all participants. For those in (C1) treatment, we also ask about the number of chat partners that used arguments that they find sufficiently convincing to be worth thinking about on both sides. We further ask participants to indicate whether or not they think to have convinced other chat partners with their arguments used in the chat.

In Wave 2, which will be conducted a few weeks after Wave 1, we re-contact all our subjects from that completed Wave 1. We expect the response rate from this rate to be two-third of all participants (i.e. circa. 2400). Our plan is to elicit (1) their WGV, (2) whether they already have an appointment and (3) if they have been vaccinated in the meantime. This wave allows us to investigate the effect of treatments and group chat on the willingness to get vaccinated ex post, especially from those who are vaccine skeptics.

Our main hypotheses are: Group compositions contribute to opinion change, mediated by interactions in the chat groups. The effect is stronger in text primed treatments.
Randomization Method
computer randomization
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
3600
Sample size (or number of clusters) by treatment arms
2400 chat (800 control text treatment, 800 text treatment 1, 800 text treatment 2)
1200 non-chat (400 control text treatment, 400 text treatment 1, 400 text treatment 2)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of Hamburg WiSo Laboratories
IRB Approval Date
2021-01-25
IRB Approval Number
N/A

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials