COVID-19, fake news and religious tensions: experimental evidence from India

Last registered on June 07, 2022

Pre-Trial

Trial Information

General Information

Title
COVID-19, fake news and religious tensions: experimental evidence from India
RCT ID
AEARCTR-0006564
Initial registration date
October 07, 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
October 08, 2020, 7:33 AM EDT

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

Last updated
June 07, 2022, 9:45 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
LSE & IFS

Other Primary Investigator(s)

PI Affiliation
IFS
PI Affiliation
NOVA SBE, NOVAFRICA, IFS

Additional Trial Information

Status
Completed
Start date
2020-06-17
End date
2021-04-30
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
While fake news spreading misinformation about COVID-19 is a global concern, it is a particular pervasive problem in India. In this paper, we study how to debunk fake news and combat misinformation in slums of India. While studies found that communication technologies and social media can be effective communication tools, we know little about what role the identity of the messenger plays. Our first research question adds to this knowledge gap, by providing evidence on: How effective are doctors’ messages to counter misinformation about ways to prevent COVID-19? Accompanying the pandemic, we also experienced globally riots and protests linked to discrimination events. Given religious tensions in India, we also address the question: How does religion identity moderate the processing of new information? We will do so making use of technologies of information through mobile phones. Yet, uptake of messages via phone technologies can be extremely low and hence, the effectiveness of these tools can be limited. Thus, we also study: Can higher financial rewards lead to higher uptake of messages? We will conduct a field experiment to study these research questions in the context of slums in Lucknow and Kanpur, Uttar Pradesh. We rely on a recently collected census data of more than 30,000 households, and we will collect baseline and follow-up surveys through mobile phones for almost 4,000 randomly sampled households.
External Link(s)

Registration Citation

Citation
Armand, Alex, Britta Augsburg and Antonella Bancalari. 2022. "COVID-19, fake news and religious tensions: experimental evidence from India." AEA RCT Registry. June 07. https://doi.org/10.1257/rct.6564
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Experimental Details

Interventions

Intervention(s)
We will address three research questions (RQ):
RQ1: How effective are doctors’ messages to counter misinformation about ways to prevent COVID-19?
RQ2: How does religion identity moderate the processing of new information?
RQ3: Can higher financial rewards lead to higher uptake of messages?

Our intervention makes use of technologies of information through mobile phones (i.e. Whastapp chatbot and voice messages).
Intervention Start Date
2020-09-26
Intervention End Date
2020-10-26

Primary Outcomes

Primary Outcomes (end points)
RQ1: Knowledge about COVID-19 prevention
RQ2: Religion bias
RQ3: Exposure to intervention
Primary Outcomes (explanation)
1. RQ1: Knowledge about COVID-19 prevention: measured as the extent to which the participant agrees with statements on different (confirmed and not confirmed) ways to prevent COVID-19.
2. RQ2: Religion bias: elicited by randomly varying the names of citizens that agree with different statements (not confirmed ways) about how to prevent COVID-19 and asking participants the extent to which they also agree with the statements. We use names that clearly convey the gender and religion of the citizen. For this, we use the most common names in our household Census for each identity.
3. RQ3: Exposure to intervention: number of participants that watched the video and listened to the audio; extent to which participants recall receiving a video through Whatsapp or voice message related to COVID-19.

Secondary Outcomes

Secondary Outcomes (end points)
1. Acquiring and spreading information
2. Risk perception
3. Trust
4. Attitudes towards vaccination
5. Complying with policy guidelines
Secondary Outcomes (explanation)
1. Acquiring and spreading information: the extent of discussion about COVID-19 with other people; time spent in acquiring COVID-19 related information; knowledge about COVID-19 symptoms.
2. Risk perception: the extent to which respondents believe a member of the household can get COVID-19; how anxious they feel about the pandemic.
3. Trust: the extent to which participants trust doctors and people from other religion, in comparison to people in their State in general.
4. Attitudes towards vaccination: the extent to which the participant is willing to vaccinate (having to pay or not) when the vaccine for COVID-19 becomes available; attitude towards people that don’t want to vaccinate.
5. Complying with policy guidelines: behaviour related to better hygiene and physical distance

Experimental Design

Experimental Design
We address the research questions using a field experiment through mobiles phones in 142 slums in the cities of Lucknow and Kanpur, Uttar Pradesh. We have a 2 x 2 x 2 cross-randomized design, resulting in 8 treatment arms.
Experimental Design Details
We address the research questions using a field experiment through mobiles phones in 142 slums in the cities of Lucknow and Kanpur, Uttar Pradesh.

We randomly allocate households (one or more mobile phones in each household) to receive one of the variations of the following three treatments:

T1: Doctor messages vs. Control messages

T2: Hindu citizen vs. Muslim citizen

T3: High incentive vs. Low incentive

We end up having a 2 x 2 x 2 cross-randomized design, resulting in 8 treatment arms.

To allocate households to the treatment arms, we stratify the sample by religion (Hindu or other) and by city of study (Lucknow or Kanpur).

The distribution of households across treatment arms is as follows:
- 498 households allocated to the “Doctor-High Incentive-Hindu” treatment arms
- 505 households allocated to the “Doctor-Low Incentive-Hindu” treatment arms
- 507 households allocated to the “Doctor-High Incentive-Muslim” treatment arms
- 492 households allocated to the “Doctor-Low Incentive-Muslim” treatment arms
- 505 households allocated to the “Control-High Incentive-Hindu” treatment arms
- 479 households allocated to the “Control-Low Incentive-Hindu” treatment arms
- 503 households allocated to the “Control-High Incentive-Muslim” treatment arms
- 502 households allocated to the “Control-Low Incentive-Muslim” treatment arm
Randomization Method
The statistical software Stata, and specifically the random number generator, will be used to apply this procedure.
Randomization Unit
Randomisation into the experimental arms is conducted at the household level given that the intervention is directed one-to-one through mobile phones. Randomising at the household level allows us to take advantage of greater variation in response to the intervention within slums.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We will not conduct a clustered RCT, but our households are part of 142 slums.
Sample size: planned number of observations
3,991 households, with a mean of 28 households per slum.
Sample size (or number of clusters) by treatment arms
~500 units by treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Within each slum, we sample up to 60 households, aiming for an average of 30 households per slum. Our sampling procedure is informed by the power calculation used in the initial study registered in the AEA Registry Number AEARCTR-0003087.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
LSE Research Ethics Committee
IRB Approval Date
2020-05-15
IRB Approval Number
REC ref. 1132
Analysis Plan

Analysis Plan Documents

Pre-Analysis Plan

MD5: e633b06ccbb2db46454cfccfb318fd0d

SHA1: 535d4c8a00c5f498422973680e00ef2c42c97653

Uploaded At: October 07, 2020

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
January 15, 2021, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
January 22, 2021, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
3,991 households.
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
3,816 in firs follow-up and 3,906 in second follow-up.
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials