Can locally-targeted feedback encourage the use of COVID contact tracing apps? Control Experiment
Last registered on May 24, 2021

Pre-Trial

Trial Information
General Information
Title
Can locally-targeted feedback encourage the use of COVID contact tracing apps? Control Experiment
RCT ID
AEARCTR-0007713
Initial registration date
May 24, 2021
Last updated
May 24, 2021 8:54 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
University of Bonn
Other Primary Investigator(s)
PI Affiliation
University of Bonn, National University of Singapore
PI Affiliation
National University of Singapore
Additional Trial Information
Status
In development
Start date
2021-05-25
End date
2021-06-30
Secondary IDs
Abstract
One important tool in the controlling of the COVID-19 pandemic lies in fast and effective detection of individuals who have been in close contact with infected persons. In this context, contact tracing apps such as the German "Corona-Warn-App" (CWA) can play an important role.
Installation and use of the contact tracing app represents a public good: everyone, even those who do not install an app, benefits from faster tracking of suspicious cases. Recent updates to the functionality of the CWA allow for significantly enhanced tracing effectiveness by introducing a Check-in function as well as reporting of rapid antigen test results.

In our main experiment (AEARCTR-0006529), we investigated whether and how targeted feedback on local COVID-19 incidence rates and social comparisons with other regions can increase the willingness to install the CWA. We tested this on a large-scale through targeted social media ads. One interesting finding was that the increases in click-through rates were to a significant part predicted by incrases in initial level of attention. In this control experiment, we aim to further examine the behavioral mechanisms underlying the results from our main experiment. In particular, we plan to test modifications of our original interventions to study the roles of information targeting and perceptual salience.
External Link(s)
Registration Citation
Citation
Chen, Zihua, Ximeng Fang and Lorenz Goette. 2021. "Can locally-targeted feedback encourage the use of COVID contact tracing apps? Control Experiment." AEA RCT Registry. May 24. https://doi.org/10.1257/rct.7713-1.0.
Experimental Details
Interventions
Intervention(s)
For our main interventions, we deliver ads on Facebook that are targeted on county/city level and provide feedback on the local incidence rates as well as a comparison with other counties/cities in Germany.
Intervention Start Date
2021-05-25
Intervention End Date
2021-06-05
Primary Outcomes
Primary Outcomes (end points)
Click-through rate of the Facebook ads, which link to the official homepage of the Corona-Warn-App
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Views of ad video as intermediary outcome
Secondary Outcomes (explanation)
Treatment could in essence affect click rates through both the extensive margin (engaging with the ad) and the intensive margin (response to ad content). Video view metrics can help us disentangle the two, at least if selection effects are limited.
Experimental Design
Experimental Design
Video ads on Facebook:
1) Control group: conventional ad for CWA (from actual Marketing campaign), includes info slogan about effectiveness of ad in stopping infection chains
2) Targeted feedback + Salience: feedback on local incidence rate on comparison with rest of state; the video makes the comparison salient and adds an injunctive norm
3) Targeted feedback (no salience): like Treatment 2, but no salient comparison frames
4) Non-targeted feedback: like Treatment 3, but feedback on overall German incidence rate
Experimental Design Details
Randomization Method
Randomization through Facebook's A/B testing functionalitiy
Randomization Unit
Randomization on individual user level
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Aim for about 1 million impressions on Facebook
Sample size: planned number of observations
same as clusters
Sample size (or number of clusters) by treatment arms
Roughly equal number of observations in each treatment condition
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
2020-09-26
IRB Approval Number
XwNHKAuc
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