THE IMPACT OF INCENTIVES FOR VACCINATION: INFORMATION PROVISION SWEDEN

Last registered on June 15, 2022

View Trial History

Pre-Trial

Trial Information

General Information

Title

THE IMPACT OF INCENTIVES FOR VACCINATION: INFORMATION PROVISION SWEDEN

RCT ID

AEARCTR-0009584

Initial registration date

June 14, 2022

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 15, 2022, 10:00 AM EDT

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

Locations

Country

Sweden

Region

Primary Investigator

Name

Florian Schneider

Affiliation

University of Zurich

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Armando Meier

PI Affiliation

University of Lausanne

PI Name

Pol Campos-Mercade

PI Affiliation

University of Copenhagen

PI Name

Stephan Meier

PI Affiliation

Columbia University

PI Name

Erik Wengström

PI Affiliation

Lund University

PI Name

Devin Pope

PI Affiliation

University of Chicago

Additional Trial Information

Status

In development

Start date

2022-06-15

End date

2023-08-31

Keywords

Behavior, Health

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

This study consists of an information provision experiment to study whether people react differently when a governmental agency pays for COVID-19 vaccination as opposed to researchers paying. The new study exploits the fact that i) most people in Sweden are not aware of a Swedish RCT that paid people for COVID-19 vaccination and ii) the previous RCT was implemented in collaboration with a governmental organization.

External Link(s)

Registration Citation

Citation

Campos-Mercade, Pol et al. 2022. "THE IMPACT OF INCENTIVES FOR VACCINATION: INFORMATION PROVISION SWEDEN." AEA RCT Registry. June 15. https://doi.org/10.1257/rct.9584-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2022-06-15

Intervention End Date

2022-06-30

Primary Outcomes

Primary Outcomes (end points)

Suppose that there would be a new outbreak of the COVID-19 pandemic in 6 months and the Swedish authorities would recommend people to take an additional COVID-19 vaccine shot (regardless of the number of shots they got in the past). What is your best guess, would you take an additional shot? (Yes / No)

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

i) Perceived safety and efficacy: Average answer to the following 3 items (Scales: 5-point Likert scale):
- In general, COVID-19 vaccines are safe
- I am worried about the side effects from COVID-19 vaccines (reverse coded)
- In general, COVID-19 vaccines are highly effective at protecting my health

ii) Moral values and norms: Average answer to the following 3 items (Scales: 5-point Likert scale):
- I would be willing to take the personal costs of getting an additional COVID-19 vaccine (e.g., time, discomfort, mild side effects) for the greater good of society
- I think people would have a civic duty or a moral obligation to get an additional COVID-19 vaccine
- Not taking the COVID-19 vaccine would be generally viewed as socially inappropriate in this situation

Secondary Outcomes (explanation)

Experimental Design

Some randomly selected participants in this new study will be told that researchers participated in the implementation of the incentive program. Other participants will be told that the Public Health Agency of Sweden participated in the implementation of the incentive program.

Experimental Design Details

Randomization Method

Randomization is done by a computer

Randomization Unit

Randomization is done at the individual level

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1000 individuals

Sample size: planned number of observations

1000 individuals

Sample size (or number of clusters) by treatment arms

500 individuals in each of the two treatment arms

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Our power calculations show that 1,000 participants would give us 80% power to detect an effect size of 0.2 standard deviations on whether there is a difference between researchers and governmental organizations being involved in offering payments.

Supporting Documents and Materials

IRB