Can a Trusted Messenger Change Behavior when Information is Plentiful? Evidence from the First Months of the COVID-19 Pandemic in West Bengal

Last registered on August 18, 2022
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Pre-Trial

Trial Information

General Information

Title
Can a Trusted Messenger Change Behavior when Information is Plentiful? Evidence from the First Months of the COVID-19 Pandemic in West Bengal
RCT ID
AEARCTR-0009906
Initial registration date
August 11, 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
August 18, 2022, 10:37 AM EDT

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

Locations

Country
India
Region
West Bengal

Primary Investigator

Name
Marcella Alsan
Affiliation
Harvard University
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Other Primary Investigator(s)

PI Name
Abhijit Banerjee
PI Affiliation
Massachusetts Institute of Technology
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PI Name
Esther Duflo
PI Affiliation
Massachusetts Institute of Technology
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PI Name
Emily Breza
PI Affiliation
Harvard University Department of Economics
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PI Name
Arun Chandrasekhar
PI Affiliation
Stanford University
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PI Name
Abhijit Chowdhury
PI Affiliation
John C. Martin Centre for Liver Research and Innovations
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PI Name
Paul Goldsmith-Pinkham
PI Affiliation
Yale University School of Management
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PI Name
Benjamin Olken
PI Affiliation
Massachusetts Institute of Technology
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Additional Trial Information

Status
Completed
Start date
2020-04-21
End date
2020-09-15
Keywords
Health
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Can information from a credible messenger shift behavior in an information-saturated environment? In a randomized controlled trial involving twenty-eight million individuals in West Bengal, we find that SMS-delivered video messages containing information about COVID-19 symptoms and health-preserving behaviors recorded by a credible messenger increased adherence to targeted and non-targeted preventive behaviors, measured by two objective measures (symptoms reported to a health worker, and phone usage at home), as well as self-reported behaviors. We find large spillovers onto non-targeted recipients. Credible light-touch messaging can play an important role in crisis response, even when similar information is widely available.
External Link(s)

Registration Citation

Citation
Alsan, Marcella et al. 2022. "Can a Trusted Messenger Change Behavior when Information is Plentiful? Evidence from the First Months of the COVID-19 Pandemic in West Bengal." AEA RCT Registry. August 18. https://doi.org/10.1257/rct.9906-1.0
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Experimental Details

Interventions

Intervention(s)
We randomize people in West Bengal to delivery of information on COVID-19 symptoms and health-preserving behaviors through a Youtube video delivered by Abhijit Banerjee or a government website.
Intervention Start Date
2020-05-04
Intervention End Date
2020-05-05

Primary Outcomes

Primary Outcomes (end points)
Episodes of fever, cough, and shortness of breath reported to a health worker over the previous three days.

Travel outside of village, interactions, conversations about COVID-19, frequency of washing hands, mask usage, and knowledge of COVID-19 symptoms and precautions.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Population, probability of travel, distance, migration, and Youtube views.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In partnership with telecom operator Reliance Jio, we sent SMS messages containing either a Youtube link or a government website link to people in West Bengal, with a sample consisting of 1,214 PIN codes and 28 million subscribers.

Messages were assigned using a 2 x 2 x 2 cross-randomized design, with each emphasizing (i) a COVID-19 health behavior (i.e. hand-washing), (ii) a rationale for action (cost to self or everyone), and (iii) a social problem (i.e. ostracizing COVID-19 victims is unacceptable).

To evaluate the effect of our intervention, we conducted two phone-based surveys with community health workers and present and former village council members and merged in Facebook population location data.
Experimental Design Details
Randomization Method
Computer randomization.
Randomization Unit
PIN code level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
1,085 PIN codes
Sample size: planned number of observations
28 million subscribers
Sample size (or number of clusters) by treatment arms
1,085 PIN codes were assigned to one of the eight treatments and 129 PIN codes were assigned to the control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
MIT COUHES
IRB Approval Date
Details not available
IRB Approval Number
2003000118
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