The non-linear effect of descriptive social norms

Last registered on July 09, 2021
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Pre-Trial

Trial Information

General Information

Title
The non-linear effect of descriptive social norms
RCT ID
AEARCTR-0007938
Initial registration date
July 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
July 09, 2021, 12:45 PM EDT

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

Locations

Country
United Kingdom of Great Britain and Northern Ireland
Region

Primary Investigator

Name
Itzhak Rasooly
Affiliation
Sciences Po & Paris School of Economics
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Other Primary Investigator(s)

PI Name
Jesper Akesson
PI Affiliation
The Behaviouralist
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PI Name
Robert Hahn
PI Affiliation
University of Oxford and Technology Policy Institute
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PI Name
Robert Metcalfe
PI Affiliation
University of Southern California and NBER
Contact Investigator
PI Name
Rena Conti
PI Affiliation
Boston University
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2020-12-12
End date
2020-12-26
Keywords
Behavior
Additional Keywords
Descriptive social norms
JEL code(s)
D90, C93
Secondary IDs
Abstract
This project attempts to improve our understanding of descriptive social norm interventions (i.e., interventions which aim to change behavior by altering individual beliefs about the prevalence of a given activity). We do this by conducting a field experiment in conjunction with a non-profit health organization. In the experiment, participants are first asked what share of survey recipients have signed up to become ‘advocates’ for the organization. They are then matched into different groups and given different signals about the share who have signed up (these signals range from 0% to 100% in 20% intervals). Finally, participants are asked about their posterior beliefs about sign-up rates as well as whether they would themselves like to sign up as advocates. This design allows us to study how exactly signals influence behavior, whether they do so purely by updating beliefs, and the effect of sending very low signal values.
External Link(s)

Registration Citation

Citation
Conti, Rena et al. 2021. "The non-linear effect of descriptive social norms." AEA RCT Registry. July 09. https://doi.org/10.1257/rct.7938-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The experiment proceeds as follows:
1. Participants are asked what share of survey recipients have signed up to become ‘advocates’ for the organization (and their degree of confidence in their answer).
2. Participants are randomly allocated into a control group or one of six treatment groups.
3. Those in each treatment group are given different signals about the share who have signed up as advocates. These signals range from 0% to 100% in 20% intervals and correspond to the actual sign-up rates in groups constructed from a pilot experiment.
4. Participants are themselves given the opportunity to sign up as advocates.
5. Participants are again asked what share of survey recipients have signed up to become advocates for the organization (and their degree of confidence in their answer).
6. Participants are asked to what extent they agree with the following statement: "I can help shape health policy and improve the lives of patients as a member of the LLS Action Team."
Intervention Start Date
2020-12-13
Intervention End Date
2020-12-26

Primary Outcomes

Primary Outcomes (end points)
1. Whether participants sign up as advocates for the organization
2. Participants' beliefs about the share who sign up as advocates
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This is outlined above.
Experimental Design Details
Randomization Method
Using Qualtrics.
Randomization Unit
At the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Several thousand individuals (depending on survey response rates).
Sample size: planned number of observations
Several thousand individuals (depending on survey response rates).
Sample size (or number of clusters) by treatment arms
Several thousand individuals (depending on survey response rates).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Study has received IRB approval. Details not available.
IRB Approval Date
Details not available
IRB Approval Number
Details not available
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