Influenza Vaccine: the combined influence of preferences and information about risks and benefits

Last registered on September 01, 2020

Pre-Trial

Trial Information

General Information

Title
Influenza Vaccine: the combined influence of preferences and information about risks and benefits
RCT ID
AEARCTR-0005857
Initial registration date
May 14, 2020

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
May 15, 2020, 2:15 PM EDT

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

Last updated
September 01, 2020, 4:28 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
UZH Student of Economics

Other Primary Investigator(s)

PI Affiliation
University of Zurich

Additional Trial Information

Status
Completed
Start date
2020-04-27
End date
2020-05-15
Secondary IDs
Abstract
Influenza vaccination is important as it can reduce the risk of not only getting, but also spreading influenza. We evaluated how self-reported regret for not having gotten an influenza vaccination depends on individual preferences and information about the importance of vaccines. We run a 3-arm RCT providing either no information, information about the importance of vaccines to reach herd immunity or the possible importance of influenza vaccination regarding COVID-19. The RCT is embedded in a survey conducted on the employees of the University of Zurich, collecting demographic data, self-reported economic preferences, and beliefs about vaccinations and the medical sector.
External Link(s)

Registration Citation

Citation
Balmer, Jonas and Pietro Biroli. 2020. "Influenza Vaccine: the combined influence of preferences and information about risks and benefits." AEA RCT Registry. September 01. https://doi.org/10.1257/rct.5857-1.2000000000000002
Experimental Details

Interventions

Intervention(s)
Survey participants in the different treatment groups are presented with written informative text about the potential benefits of flu vaccines.
The text is meant to prime them to have certain considerations in mind when reporting their willingness to get vaccinated.

Specifically, the informative text appears after 2 pages in the survey, and contains the following:
[Herd-Immunity] “According to the BAG, every year between 112’000 and 275’000 people seek medical advice in connection with seasonal influenza in Switzerland. Many people confuse the seasonal influenza with a simple cold. However, the “real” influenza in contrast to the simple cold, can lead to severe complications, such as heart muscle and lung infections. The people who are the most vulnerable to contracting the seasonal influenza and whose health can negatively affect the severity of the infection, are in many cases not healthy enough to get vaccinated. Therefore, they rely on herd immunity.

Vaccinating is the single most effective way to protect people that rely on herd immunity. It is key to have the seasonal influenza vaccination rate as high as possible due to the limited effectiveness of the vaccination. Therefore, it is essential that as many people as possible get vaccinated. According to a study conducted by Spanish scientists, a rate of approximately 85% is needed to protect the ones who rely on herd immunity.

The overall population of the Kanton Zurich has an influenza vaccination rate of approximately 16% which is equal to the vaccination rate of the employees at the University of Zurich. This is surprising, since the employees, in contrast to most of the rest of the population, can get vaccinated for free.”


[COVID-19] “Discussing the potential connection between influenza vaccination and the covid-19 (Coronavirus) pandemic, Dr. Albert Ko, a professor and department chair at the Yale School of Public Health, said the following:

“I do think immunizing people against influenza has a very important indirect effect,"
(https://www.livescience.com/getting-flu-shot-help-coronavirus-outbreak.html)

He further explains that reducing the amount of influenza infections can “relieve pressure” from hospitals also treating patients with covid-19.”
Intervention Start Date
2020-04-27
Intervention End Date
2020-05-15

Primary Outcomes

Primary Outcomes (end points)
The primary outcome of interest is regret for not having undergone vaccination during the previous flu season.

Specifically, the question is "Did you get vaccinated for the influenza season 19/20?" and the possible answers are "Yes"; "No, but I wish would have"; "No, and I do not wish would have".

We will construct a dummy equal to one if answering "No, but I wish would have" and zero otherwise.
Primary Outcomes (explanation)
Since the information provided by the RCT cannot change past behaviour, we do not expect a higher number of people responding "Yes" (if not because of experimenter demand, which we plan to test for), but we expect a higher share of people expressing regret for not being vaccinated.

Secondary Outcomes

Secondary Outcomes (end points)
We will further test whether priming leads to an increased willingness to potentially vaccinate against COVID-19,
and if it also changes the reasoning behind vaccination decision, when considering to protect others.
Also, if priming influences expected influenza complications and presumed effectiveness of influenza vaccination.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We run a 3-arm Randomized Controlled Trial (RCT) providing either no information, or information about the importance of vaccines to reach herd immunity, or the possible importance of influenza vaccination to protect against COVID-19.
The RCT is embedded in an online survey sent to all of the employees of the University of Zurich, collecting demographic data, self-reported economic preferences, and beliefs about vaccinations and the medical sector. Completing the online survey is voluntary.
Experimental Design Details
Randomization Method
Randomization of treatment assignment is accomplished by using shuffle function which is based upon a pseudo-random number generator called Mersenne Twister.
Randomization Unit
We randomize at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
-
Sample size: planned number of observations
The planned sample size is 780.
Sample size (or number of clusters) by treatment arms
The planned sample size is 780.
Both treatments are expected to increase regret for not having undergone vaccination by 7.5 to 10%.
To show an increase of 7.5%, 540 participants, 180 per arm, are needed. Further, an additional 30% is needed to account for people that are vaccinated, resulting in a total of 780 needed participants.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

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