Are Assessed Risks and Optimism Bias Affected by Partisan Information Cues

Last registered on November 12, 2021
View Trial History

Pre-Trial

Trial Information

General Information

Title
Are Assessed Risks and Optimism Bias Affected by Partisan Information Cues
RCT ID
AEARCTR-0008547
Initial registration date
November 09, 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
November 12, 2021, 5:50 PM EST

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

Locations

Country
United States of America
Region
National

Primary Investigator

Name
Amy Wolaver
Affiliation
Bucknell University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
John Doces
PI Affiliation
Bucknell University
Contact Investigator
PI Name
Jack Goldberg
PI Affiliation
Stevens Institute of Technology
Contact Investigator

Additional Trial Information

Status
In development
Start date
2021-11-15
End date
2021-12-31
Keywords
Behavior, Electoral
Additional Keywords
partisanship, COVID-19, climate change, terrorism, risk, optimism bias, vaccine mandates
JEL code(s)
Z18 Public Policy
Secondary IDs
I18 Government Policy • Regulation • Public Health ; o K32 Energy, Environmental, Health, and Safety Law
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Objective: To determine whether assessed risks to oneself, assessed risks to the general population, and optimism bias about a variety of policy topics are affected by partisan informational cues. Half of the respondents will be randomized to receive a politically neutral version of the risk area and half to a version including a partisan clue. For example, risk of infection from COVID versus risk of infection from the flu; risk from a natural disaster with no attributed cause versus risk from a natural disaster caused by climate change, etc... Respondents will then be asked for their level of support for policies related to each of the topical areas used in the risk assessement.
External Link(s)

Registration Citation

Citation
Doces, John, Jack Goldberg and Amy Wolaver. 2021. "Are Assessed Risks and Optimism Bias Affected by Partisan Information Cues." AEA RCT Registry. November 12. https://doi.org/10.1257/rct.8547-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Views about the risk from a variety of policy areas have become increasingly polarized in the United States. Prior research has documented that Democrats rated the risks associated with COVID-19 as much higher than Republicans. Optimism bias, the rating of one’s own risk as lower than a peer’s, is an important correlate with a variety of behaviors and views. We propose to test whether partisan framing cues affect the assessed risk to self, the assessed risk to a peer, and the level of optimism bias for a number of policy issues. For each policy, we randomize between a liberal, conservative or neutral cue (see figure for examples). We include a neutral traffic accident scenario as a control. Following the assessment of risk, we ask for levels of support for policies related to each risk scenario and test for impacts on both COVID-19 and flue vaccination status/intentions.
We will test for the following hypotheses:
COVID-19 will raise the risk assessment for Democrats/liberals/non-Trump voters and depress the risk assessment for Republicans/conservatives/Trump voters.
On the other issues:
Liberal cues will raise the risk assessment for the scenario for Democrats/liberals/non-Trump voters relative to the neutral or conservative cues.
Conservative cues will raise the risk assessment for the scenario for Republicans/conservatives/Trump voters relative to the neutral or conservative cues.
Higher levels of risk assessment will increase support among the partisan group for the related policy action.
Research Questions:
Will the levels of risk-to-self versus risk-to-a-peer be affected differently by the partisan cues (thus affecting optimism bias)?
What effect, if any, will optimism bias have on support for policy action?
Intervention Start Date
2021-11-15
Intervention End Date
2021-12-31

Primary Outcomes

Primary Outcomes (end points)
Level of assessed personal risk and risk to another, similar person, level of optimism bias, level of support for policy, and vaccination status and intentions.
Primary Outcomes (explanation)
Optimism bias will be constructed indirectly from the assessed personal risk and assessed risk to another, similar person

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Different topical scenarios will be randomized between liberal, conservative and neutral partisan cues in questions assessing the respondent's personal risk and their assessed risk of harm to another, similar person from the scenario.
Experimental Design Details
Following the questions assessing risk for various scenarios which randomized between including liberal, conservative, and neutral cues, respondents will be asked for their level of support for policies related to the risk topics. We will tests for the impact of receiving partisan cues on a topic on policy support and whether this support is mediated through changes in assess risks and optimism bias in the scenario.


Questions eliciting policy support:
For each of the following policies, please indicate your level of support where 5=strongly support, 4=somewhat support, 3=neutral/don’t know, 2=somewhat oppose, and 1 = strongly oppose

Mandating COVID vaccinations.
Increasing support for improving roads, bridges, etc…
Banning assault weapons.
Increasing the number of refugees admitted to the country.
Increasing regulations on carbon emissions.


VACCINE QUESTIONS:

Question 3

What are your intentions regarding the flu vaccine in the next 6 months?

I have already gotten a flu vaccine
I am planning on getting the flu vaccine
I am not getting the flu vaccine
I have not decided whether to get the flu vaccine or not


Question 4

What is your COVID-19 vaccine status?

● I have had a first dose of the vaccine
● I am fully vaccinated but have not had a booster
● I am fully vaccinated and have had a booster
● I am not vaccinated

SKIP PATTERN: IF THEY RESPOND “I am not vaccinated” on Question 4

Follow up with

QUESTION 4Ai:


Which of the following statements best represents your intentions about the COVID-19 vaccination?

● I will not get the vaccine
● I will get the vaccine if I am required to do so for work, school, etc..
● I am waiting for more information about the vaccine before I decide
● Other (please explain):___________________


SKIP PATTERN: IF THEY RESPOND “I am fully vaccinated but have not had a booster” on Question 4

Follow up with
QUESTION 4Aii :

a) Which vaccine did you receive?

Moderna (2nd dose)
Pfizer (2nd dose)
Johnson (1 dose)
I have received more than one type of vaccine
Don’t know

b) Do you plan on getting a COVID vaccine booster when eligible?

Yes
No
I don’t know


SKIP PATTERN: IF THEY RESPOND “I am fully vaccinated and have had a booster” on Question 4

Follow up with
QUESTION 4Aiii :

a) Which vaccines did you receive initially?

Moderna (2nd dose)
Pfizer (2nd dose)
Johnson (1 dose)
I have received more than one type
Don’t know

b) Which booster shot have you received?

Moderna
Pfizer
Johnson
I have received more than one type
Don’t know


SKIP PATTERN: IF THEY RESPOND “I have had a first dose of the vaccine” on Question 4

Follow up with
QUESTION 4Aiv :

a) Which vaccine did you receive?

Moderna
Pfizer
Johnson
Don’t know

Q5 Do you plan on getting a second dose or a booster (if your first vaccine was Johnson & Johnson)?

Yes
No
I don’t know/I’m not sure

Q6

After being fully vaccinated, do you plan on getting a booster shot when eligible?
Yes
No
I don’t know/I’m not sure

FOR EVERYONE (not part of skip pattern)
Question 7:

Since February 2020 have you experience symptoms of COVID-19?
Yes, and I tested positive
Yes, I have not been tested/did not test positive
No
Randomization Method
Randomization by computer in the online survey questions.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000-1200 individuals
Sample size: planned number of observations
1000-1200 individuals
Sample size (or number of clusters) by treatment arms
500-600 for most interventions, 300-400 for one intervention with 3 randomization levels.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Bucknell University Institutional Review Board
IRB Approval Date
2021-11-08
IRB Approval Number
2122-040
Analysis Plan

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