Curbing the spread of COVID-19 through effective messaging

Last registered on March 24, 2020

Pre-Trial

Trial Information

General Information

Title
Curbing the spread of COVID-19 through effective messaging
RCT ID
AEARCTR-0005582
Initial registration date
March 23, 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
March 24, 2020, 10:58 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
University of Copenhagen

Other Primary Investigator(s)

PI Affiliation
University of Copenhagen

Additional Trial Information

Status
In development
Start date
2020-03-24
End date
2020-07-31
Secondary IDs
Abstract
We will run an experiment to test different ways of framing a message that promotes social distancing at the time of the COVID-19 crisis. The different variants of the message will differ in their focus, from an emphasis on personal risk to risk for family, other people, and for society as a whole. We will test what are the impacts of receiving different messages on self-reported compliance with social-distancing recommendations, as well as on indicators of behaviour from register data. We will run the experiment with a large sample of Danish residents who will receive the messages through the official channel of communication used by public authorities.
External Link(s)

Registration Citation

Citation
Falco, Paolo and Sarah Zaccagni. 2020. "Curbing the spread of COVID-19 through effective messaging." AEA RCT Registry. March 24. https://doi.org/10.1257/rct.5582-1.0
Experimental Details

Interventions

Intervention(s)
Public authorities across the globe are focusing on lowering the transmission rate of COVID-19 to prevent the health system from being overwhelmed and collapsing. Since, COVID-19 spreads through coughing, sneezing and close contact (e.g., see the information provided by the National Center for Immunization and Respiratory Disease), social distancing can reduce the chances of catching the virus and spreading it by minimising the amount of close contact among people.

Methodology

We will contact a large sample of Danish residents through e-Boks (the official system of communication used by public authorities in the country) with a message describing the benefits of social distancing at the time of the COVID-19 crisis. Specifically, the treatment aims to incentivize people to “stay at home unless they have essential reasons for going out”. We will test 5 different ways of framing the recommendation, ranging from an emphasis on personal risk, to risk for family, other people, and society as a whole. The outcomes of interest will be measure by means of a survey the respondents will receive together with the treatment, and of a follow-up survey they will receive two days after responding to the first message. We will therefore be able to measure both intentions to comply with the message and compliance since receiving the message. In addition, by means of register data to be matched with data from the experiment, we will be able to measure impacts on objective indicators (i.e., not self-reported and verifiable by a third party), such as electricity consumption and expenditure on transport/fuel (this will be subject to data availability). Depending on the availability of funding, it may also be possible to add a second follow-up survey, two weeks after the first one.
Intervention Start Date
2020-03-24
Intervention End Date
2020-04-28

Primary Outcomes

Primary Outcomes (end points)
To measure the outcome of interest (e.g., whether a person chooses to stay at home), we employ two strategies.

First, the survey received together with the treatment will ask respondents for how long they expect they will go out of their homes the following day. This will give us a chance to test whether people’s intentions are impacted by different treatments. As a follow-up, we plan to contact the respondents after 48 hours from their first reply and ask what their actions actually were. This will enable us to verify which of the treatments proved to be most effective in changing behaviour (possibly bridging the intention-to-action gap among subjects). In addition, we will ask about the bahaviour of other people in the household. This will allow us to capture family spillover effects.

In addition, by matching data from the experiment with information linked to people’s national ID numbers, we will test whether the treatments affect tangible non-self-reported outcomes that may proxy relevant dimensions of behaviour (such as, for instance, usage of public transport, expenditure on fuel, working from home, electricity usage at home, etc.).

Specifically, the primary outcomes are the following:

• Time the respondent expects to spend outside his/her home the day after receiving the message
• Distance from home the respondent expects to travel the day after receiving the message
• Time the respondent spent outside his/her home the day before receiving the follow-up message
• Distance from home the respondent travelled the day before receiving the follow-up message
• Time the other members of the family spent outside their home the day before receiving the follow-up message (average)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
• Emotional status of the respondent

Subject to the availability of relevant data:

• Usage of public transport
• Expenditure on fuel
• Electricity usage at home
• Working from home
• Internet usage
• GPS data from mobile phones
• Usage of delivery services
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment consists of sending 5 types of messages to Danish residents between the age of 18 and 69. The messages will all recommend “staying at home as much as possible”, but will provide different motivations. A sixth message will be sent to a control group and will contain no recommendation (only the accompanying survey).

The FIRST MESSAGE focuses on personal risk. The SECOND MESSAGE focuses specifically on the risk for one’s own family. The THIRD MESSAGE focuses on risk for others in general. The FOURTH MESSAGE focuses on the risk that not complying with social distancing may contribute to the collapse of the public health system. The FIFTH MESSAGE will serve as a placebo and will only tell people to stay at home as much as possible, without providing a specific reason.

The first four messages will be further split into two variants, one framed in the loss domain (focusing on the risk of incurring a negative outcome by not complying with the recommendation) and another one framed in the gain domain (focusing on the positive implications of complying with the recommendation). Since the contents of the two variants are identical except for the framing, it will be possible to pool the two variations in the final analysis.
Experimental Design Details
Randomization Method
The different messages will be sent to randomly selected individuals across Denmark. The randomisation will be carried out by Statistics Denmark (and, more specifically, by the branch in charge of conducting projects of this kind, called “DST Survey”). They will draw a random sample of 30,000 Danish residents between the age of 18 and 69 from the general population, and will contact them through e-Boks (the official channel of communication used by public authorities, utility companies, banks, etc., accessible to everyone in the population of interest).
Randomization Unit
Randomisation will be conducted at the individual level across the country.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A (Randomisation at the individual level)
Sample size: planned number of observations
30,000
Sample size (or number of clusters) by treatment arms
The 30,000 respondents will be split in 10 groups of equal size (8 treatment groups and 2 control groups, one receiving a placebo message, the other receiving no message at all).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Assuming a response rate of 30%, which according to Statistics Denmark is to be expected in surveys of this kind, equal across treatments, we should obtain about 1,000 observations per group. With such a sample, the minimum detectable effect size (with power equal to .80) for the main outcomes is the following: • Time the respondent expects to spend outside his/her home the day after receiving the message: 1,04% - 4,18% (based on an estimated control group mean of 60 and values of the sd. ranging from 10 to 40) • Distance from home the respondent expects to travel the day after receiving the message: MDE: 1,88% - 4,39% (based on an estimated control group mean of 10 and values of the sd. ranging from 3 to 7) • Time the respondent spent outside his/her home the day before receiving the message: MDE: 1,04% - 4,18% (based on an estimated control group mean of 60 and values of the sd. ranging from 10 to 40) • Distance from home the respondent traveled the day before receiving the message: MDE: 1,88% - 4,39% (based on an estimated control group mean of 10 and values of the sd. ranging from 3 to 7)
Supporting Documents and Materials

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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