Can theories of social identity help increase uptake of a COVID-19 vaccine?
Last registered on April 24, 2021

Pre-Trial

Trial Information
General Information
Title
Can theories of social identity help increase uptake of a COVID-19 vaccine?
RCT ID
AEARCTR-0007478
Initial registration date
April 06, 2021
Last updated
April 24, 2021 7:50 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
UCSB
Other Primary Investigator(s)
PI Affiliation
UCSB
PI Affiliation
UC Berkeley Haas
Additional Trial Information
Status
On going
Start date
2021-04-07
End date
2021-04-30
Secondary IDs
Abstract
To end the COVID-19 pandemic without millions of deaths, the United States needs very high uptake of a vaccine. We hypothesize that we can apply theories of social identity to design effective, targeted messaging to reduce vaccine hesitancy among sub-populations where vaccine resistance is high (e.g., African Americans, political conservatives) or vaccine importance is high (e.g., the elderly). We will test if intent to take a hypothetical vaccine is higher if each segment receives customized messages about risks of COVID-19 to oneself, risks to others, endorsement of the vaccine, and benefits of the vaccine.
External Link(s)
Registration Citation
Citation
Charness, Gary, David Levine and Lucas Reddinger. 2021. "Can theories of social identity help increase uptake of a COVID-19 vaccine?." AEA RCT Registry. April 24. https://doi.org/10.1257/rct.7478-2.1.
Experimental Details
Interventions
Intervention(s)
Consult attached documents.
Intervention Start Date
2021-04-07
Intervention End Date
2021-04-30
Primary Outcomes
Primary Outcomes (end points)
Stated intent to take a hypothetical COVID-19 vaccine. Stated delay to take a hypothetical COVID-19 vaccine. Stated intent to obtain a hypothetical COVID-19 vaccine for one’s child.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We survey US residents on the Prolific survey platform. Our goal is to survey individuals who have not yet taken a COVID-19 vaccine dose. Because Prolific offers a pre-screening question on this, we start with individuals who have previously reported to Prolific as not yet having taken a vaccine dose (N=5912 as of April 2). Because this status changes quickly for individuals, we conduct our own pre-screening as well. We will target recruitment towards African-Americans, people who identify as Hispanic or Latina/o/x, people who voted for Trump in 2020, and those who participate in weekly religious activities.

The survey begins with an introduction and some demographic questions.

Treatment depends on five particular segments: African-Americans, those who identify as Hispanic or Latina/o/x, those who report having voted for Trump in the 2020 presidential election (or if neither a Biden nor Trump voter, consider themselves conservative), those who report participating in weekly religious activities, and parents. Because subjects can be members of multiple segments, we have 32 sub-segments in total on which treatment may depend.

We present message components about a hypothetical COVID-19 vaccine. Some message components are shown to all subjects. Other message components vary between subjects, dependent on the subject’s sub-segment. For example, a Black parent’s message components will be randomly drawn from one set, whereas a religious conservative’s message components will be randomly drawn from a different set. These are outlined in the attached supporting documents.

After receiving about 10 message components, subjects are given an incentivized manipulation check question. Subjects are then asked questions about their intent to vaccinate, their intended delay in vaccination, their intent to vaccinate their children (if a parent), and their history of COVID-19.
Experimental Design Details
Randomization Method
Qualtrics balanced randomizers.
Randomization Unit
Treatment is jointly determined by individual-level randomization and individual characteristics.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
Individual characteristics result in 32 sub-segment quasi-clusters.
Sample size: planned number of observations
Our initial plan was to collect responses from 6,500 to 7,000 individuals. However, our sample pool is much more limited than we predicted. We anticipate stopping data collection with about 4,000 individuals.
Sample size (or number of clusters) by treatment arms
The experiment creates an intensity of treatment. For exact randomization procedures, please consult attached documents.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
Documents
Document Name
Survey elements (text/HTML)
Document Type
survey_instrument
Document Description
Survey elements presented to subjects (text/HTML only)
File
Survey elements (text/HTML)

MD5: 79d5663cc88320b5cc95135ca997c7d8

SHA1: 1e3b8ef9cc3deb85d8ee3f6106dc9738eb196879

Uploaded At: April 24, 2021

Document Name
Survey export from Qualtrics
Document Type
survey_instrument
Document Description
Includes survey flow (logic and randomization) but excludes styled messages with images
File
Survey export from Qualtrics

MD5: 75fe827fb4bcd0e7ca29231f49282b36

SHA1: 1205d2d3eced0032d8b9e1282dee0291f7995f5f

Uploaded At: April 24, 2021

Document Name
Summary of treatment assignment
Document Type
survey_instrument
Document Description
Summarizes the randomization of survey elements based on demographic characteristics
File
Summary of treatment assignment

MD5: a2848b2d6fb2d89600c546ae0140d941

SHA1: b98c58405bc7c3c407a8c645428d4c8b14b00bd4

Uploaded At: April 06, 2021

IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
UCSB Human Subjects Committee
IRB Approval Date
2020-10-01
IRB Approval Number
60-20-0658
Analysis Plan
Analysis Plan Documents
Stata code: 00_main.do

MD5: 1389d9ea085128a740d431b5796ec673

SHA1: 8f54d43d8f73a6c3f5d25bb33390f8fc2ed18c2f

Uploaded At: April 24, 2021

Stata code: 10_data_process.do

MD5: 8e3d7dc6b65d5f32af734e3494c77241

SHA1: a65949438228c070d3bdf86ab325c36a631fd0c2

Uploaded At: April 24, 2021

Stata code: 11_data_clean.do

MD5: 7f58c3416144e38239873294878f2ff6

SHA1: d8aa1164ec03645c942932be09b2a8f7529a3a4b

Uploaded At: April 24, 2021

Stata code: 12_analysis.do

MD5: 9a92f07294d41bc2dceada1585511ce9

SHA1: 7e2ae98baa13a64c1e8c61b136f469488aee1579

Uploaded At: April 24, 2021

Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is 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