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Impacts of Information through Text Messages, Voice Recordings, and Phone calls on False Beliefs during the Covid-19 Crisis

Last registered on June 15, 2020

Pre-Trial

Trial Information

General Information

Title
Impacts of Information through Text Messages, Voice Recordings, and Phone calls on False Beliefs during the Covid-19 Crisis
RCT ID
AEARCTR-0005947
Initial registration date
June 15, 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
June 15, 2020, 11:42 AM EDT

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

Locations

Region

Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation
University of Michigan
PI Affiliation
University of Michigan

Additional Trial Information

Status
In development
Start date
2020-06-16
End date
2020-07-20
Secondary IDs
Abstract
We will randomize study subjects to receive information on Covid-19 through one of three modes: text messages, voice recordings, and phone calls. We will compare the three groups to see which method causes the largest change in beliefs, and whether these effects are moderated by short-term memory.
External Link(s)

Registration Citation

Citation
Adhvaryu, Achyuta, Sadish D and Anant Nyshadham. 2020. "Impacts of Information through Text Messages, Voice Recordings, and Phone calls on False Beliefs during the Covid-19 Crisis." AEA RCT Registry. June 15. https://doi.org/10.1257/rct.5947-1.0
Experimental Details

Interventions

Intervention(s)
We will randomize study subjects to receive information on Covid-19 through one of three modes: text messages, voice recordings, and phone calls. The content of the message will remain unchanged for all interventions.
Intervention Start Date
2020-06-17
Intervention End Date
2020-06-30

Primary Outcomes

Primary Outcomes (end points)
1. Beliefs Index
2. Mental Health Index (PHQ8)
Primary Outcomes (explanation)
Beliefs Index: A sum of nine binary variables that indicate whether or not an individual knows each of nine symptoms of Covid-19, and six binary variables that measure subjects’ beliefs related to Covid-19. The binary variables capturing beliefs are constructed using data collected on a 3-point scale: “Yes”, “Don’t Know”, and “No”. The “Don’t Know” option will be coded as zero. This index is an outcome to be measured both before and after the intervention.
Below is a description of how variables are encoded to create the Beliefs Index:
- Knows the symptom: Cough [No = 0, Yes = 1]
- Knows the symptom: Fever [No = 0, Yes = 1]
- Knows the symptom: Breathing Difficulty [No = 0, Yes = 1]
- Knows the symptom: Congestion in nose and throat [No = 0, Yes = 1]
- Knows the symptom: Runny nose [No = 0, Yes = 1]
- Knows the symptom: Feeling tired [No = 0, Yes = 1]
- Knows the symptom: Body aches [No = 0, Yes = 1]
- Knows the symptom: Diarrhoea [No = 0, Yes = 1]
- Knows the symptom: Loss of taste or smell [No = 0, Yes = 1]
- If someone does not show any symptom of the novel coronavirus, could they still have the disease? [No = 0, Don’t Know = 0, Yes = 1]
- Do you think there is any medicine or herb that helps against the novel coronavirus? [Yes = 0, Don’t Know = 0, No = 1]
- Suppose a person you know has symptoms of the novel coronavirus. Would you advise them to take antibiotics? [Yes = 0, Don’t Know = 0, No = 1]
- Would you advise them to drink cow’s urine? [Yes = 0, Don’t Know = 0, No = 1]
- If a person takes turmeric every day, do you think they will be less likely to get the novel coronavirus? [Yes = 0, Don’t Know = 0, No = 1]
- Do you think people of some religions are more likely to spread the novel coronavirus? [Yes = 0, Don’t Know = 0, No = 1]

We will also create a weak version of the belief index that is less absolute in that “Yes”, “No”, and “Don’t Know” will be coded as ternary variables with values -1, 1, and 0 rather than binary variables with values 0 and 1 only. We will do this in order to measure less definitive changes in belief, which are nonetheless important.

Mental Health Index (PHQ4): A sum of four questions about mental health on a four-point scale (0 to 3). This index is an outcome to be measured both before and after the intervention. Below is a description of how variables are encoded to create the Mental Health Index (PHQ-4):
- How often do you have little interest or pleasure in doing things? [Not at
all = 0, Several Days = 1, More than half the days = 2, Nearly everyday
= 3]
- How often do you feel down, depressed or hopeless? [Not at all = 0, Several Days = 1, More than half the days = 2, Nearly everyday = 3]
- How often do you feel nervous, anxious, or on edge? [Not at all = 0, Several Days = 1, More than half the days = 2, Nearly everyday = 3]
- How often do you feel like you are not able to stop or control worrying? [Not at all = 0, Several Days = 1, More than half the days = 2, Nearly everyday = 3]

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will run a randomized controlled experiment where we randomly choose whether a study subject receives information relevant to the Covid-19 pandemic in one of three modes: text message, voice recording, or phone call. The content of the message will remain constant for all three modes.

Subjects: The subjects are current and former garment factory employees in India who are internal migrants of Odiya origin.

Stratified Randomization: We will group subjects into strata, and randomize individuals within strata. Each strata will indicate a unique combination of the at least following four binary or categorical variables:
1. Whether a subject is female
2. Whether a subject is highly educated
3. Whether a subject has left their job
4. The factory of employment

Measures: We will measure the following constructs in addition to the outcomes:

Short-Term Memory: The longest sequence of one-digit numbers an individual can recall within 5 seconds of hearing it. This variable will be measured before the intervention, but not after.

Numeracy: A sum of three binary variables that indicate whether an individual can solve simple addition, subtraction, and multiplication problems mentally. This variable will be measured before the intervention, but not after.

Hypotheses: We will test the following hypotheses:

1. Beliefs Index will be higher for subjects treated with voice recordings compared to subjects treated with text messages.
2. Beliefs Index will be higher for subjects treated with phone calls compared to subjects treated with text messages.
3. Beliefs Index will be higher for subjects treated with phone calls compared to subjects treated with voice recordings.
4. The difference in Beliefs Index between subjects treated with either voice recordings or phone calls compared to subjects treated with text messages will be positive, and larger for individuals with higher short-term memory.
5. The difference in Beliefs Index between subjects treated with either voice recordings or phone calls compared to subjects treated with text messages will be the same for individuals regardless of their numeracy.
6. The difference in the Depression Index between subjects treated with voice recordings compared to subjects treated with text messages will be zero.
7. The difference in the Depression Index between subjects treated with phone calls compared to subjects treated with text messages will be zero.
8. The difference in the Depression Index between subjects treated with phone calls compared to subjects treated with voice recordings will be zero.
Experimental Design Details
Randomization Method
Randomizaiton using a computer program
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
.
Sample size: planned number of observations
We plan to include a minimum of 750 individuals in the study. We plan to collect survey data for each individual once before the intervention, and once after.
Sample size (or number of clusters) by treatment arms
We will divide the subjects in the ratio 2:2:1 to receive phone calls, voice recordings, and text messages respectively. Sample size calculations for the Beliefs Index assume:
1. Probability of Type-I error: 0.05
2. Probability of Type-II error: 0.2
3. One pre-intervention and one post-intervention measure of outcome
4. A correlation of 0.75 between outcome measurements before and after intervention.
5. ANCOVA specification
6. The same standard deviation for all treatment groups

With about 425 subjects, we are powered to detect a minimum effect of 20 percent of standard deviation between the group receiving phone calls and that receiving voice recordings, and a minimum effect of 25 percent of standard deviation between the group receiving text message, and either of the other groups.

With about 750 subjects, we are powered to detect a minimum effect of 15 percent of standard deviation between the group receiving phone calls and that receiving voice recordings, and a minimum effect of 20 percent of standard deviation between the group receiving text message, and either of the other groups.

For the Mental Health index, we assume a correlation of 0.55 between outcome measurements before and after intervention.

Then, with about 450 subjects, we are powered to detect a minimum effect of 25 percent of standard deviation between the group receiving phone calls and that receiving voice recordings, and a minimum effect of 30 percent of standard deviation between the group receiving text message, and either of the other groups.

With about 750 subjects, we are powered to detect a minimum effect of 20 percent of standard deviation between the group receiving phone calls and that receiving voice recordings, and a minimum effect of 25 percent of standard deviation between the group receiving text message, and either of the other groups.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See "Sample size" section
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Michigan ethics committee
IRB Approval Date
2020-05-27
IRB Approval Number
Office of Human Research Protections Registration Number: IRB00000246
IRB Name
GBL ethics committee
IRB Approval Date
2020-05-19
IRB Approval Number
GBL0520

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