Combatting COVID-19: Measuring and Changing Beliefs, Knowledge and Behaviors

Last registered on August 18, 2021

Pre-Trial

Trial Information

General Information

Title
Combatting COVID-19: Measuring and Changing Beliefs, Knowledge and Behaviors
RCT ID
AEARCTR-0005862
Initial registration date
May 26, 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
May 26, 2020, 4:53 PM EDT

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

Last updated
August 18, 2021, 12:16 PM EDT

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

Locations

Primary Investigator

Affiliation
University of Michigan

Other Primary Investigator(s)

PI Affiliation
University of Michigan
PI Affiliation
University of Michigan
PI Affiliation
University of Michigan
PI Affiliation
Beira Operational Research Center
PI Affiliation
University of Michigan

Additional Trial Information

Status
Completed
Start date
2020-06-01
End date
2020-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We seek to support the Mozambican COVID-19 response, in collaboration with the government’s health research center for the central region, by following up on a study sample of a randomized controlled trial in Mozambique. Sample households will be contacted by phone and administered several rounds of surveys regarding COVID-19 knowledge, beliefs, and behavior. We will randomize novel over-the-phone interventions to test if we can 1) encourage social distancing by accelerating changes in community norms, and 2) improve knowledge about COVID-19 via incentives and tailored feedback. Our findings will support the Mozambican response by informing policymakers of the public's COVID-19 knowledge and behaviors and on which public health messaging strategies are best to pursue given limited resources.

Registration Citation

Citation
Allen IV, James et al. 2021. "Combatting COVID-19: Measuring and Changing Beliefs, Knowledge and Behaviors." AEA RCT Registry. August 18. https://doi.org/10.1257/rct.5862
Sponsors & Partners

Sponsors

Partner

Type
government
URL
Experimental Details

Interventions

Intervention(s)
We implement over-the-phone interventions to 1) encourage social distancing by accelerating changes in community norms, and 2) improve knowledge about COVID-19

Social Distancing Treatments:
-SD1: Community Support for Social Distancing. We will ask individuals whether they themselves support social distancing, and use this information to calculate the fraction of households in the community who support social distancing. Then, in a later phone call, we will ask individuals to guess the share of households in the community who support social distancing. Individuals who underestimate the true share of households in the community that support social distancing will be given information on the true (higher) share of support for social distancing, and individuals correctly guessing the true share will be told that their guess is correct.
-SD2: Community leader support for social distancing. We will survey community leaders and ask them to endorse social distancing in their communities. In this treatment, we will inform households by phone call that their leaders support social distancing in their communities.

Knowledge Treatments:
-K1: Knowledge Incentives. We will randomly offer a subset of respondents 5 Mozambican meticais (MT) for every correct knowledge response on a subsequent phone survey. We will examine the effect of the treatment on future knowledge and behavior. If they answer all 40 questions correctly, respondents can earn a maximum of 200MT (approx. US$2.86).
-K2: Tailored Feedback. We will randomly give tailored feedback to a subset of respondents based on their response to COVID-19 knowledge questions, by informing them of a subset of their correct responses and correcting a subset of their incorrect responses. We will examine if tailored feedback improves relevant knowledge and behavior in a subsequent telephone survey.
Intervention Start Date
2020-06-15
Intervention End Date
2020-08-15

Primary Outcomes

Primary Outcomes (end points)
For Social Distancing interventions:
-An indicator for the respondent practicing social distancing.

For Knowledge interventions:
-Index of COVID-19 overall knowledge
Primary Outcomes (explanation)
For Social Distancing interventions:
The primary outcome will be an indicator for the respondent practicing social distancing. It will be constructed from two component indicators: the own report of practicing social distancing, and others’ report of the respondent’s practicing social distancing. The primary outcome will be equal to one if both the own report and others’ report of practicing social distancing is equal to one, and zero otherwise. Some detail below and see Analysis Plan for further details.
-Others’ and self-report of social interactions: Others’ reports of social interactions with respondent. Taken from the question ask for up to 10 other study participants in one’s social network and neighbors within 200m: Did you talk to / stand within 1.5 meters / shake hands or otherwise touch (insert name) in last 14 days?
-Index of household social distancing behaviors: Ask about whether or not the household attends social gatherings, leaves the household area, avoids crowded areas, keeps a distance of 1.5 meters from others, frequently wash hands, informs others if sick, and more…
◦ Is this something you think people should be doing?
◦ Is this something your household has been doing for the last 7 days?

For Knowledge interventions:
-Index of COVID-19 overall knowledge - number of correct responses to knowledge questions about coronavirus symptoms, prevention, how it spreads, and who is most at risk; household social distancing and self-prevention behaviors. Confidence with which responses are given.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomize our over-the-phone interventions to test if we can 1) encourage social distancing by accelerating changes in community norms, and 2) improve knowledge about COVID-19 via incentives and tailored feedback. We consider the intent-to-treat (ITT) effect of the randomized interventions on a standardized version of our outcomes: indices of perceived social distancing norms and household social distancing behavior.
Experimental Design Details
All interventions will be implemented in the Round 2 Survey; this is because some treatments require input from the Round 1 Survey and will allow for comparison across treatments. Based on our power analysis, we limit to four treatment arms to detect effects of reasonable size. Thus, we will cross-randomize Social Distancing Treatments and Knowledge Treatments. Within each treatment family, the control group will be 40% of the sample and each of the three treatment arms will be 20% of the sample. Therefore, 16% of the sample will be a strict control group, neither receiving a Social Distancing treatment nor a Knowledge Treatment.
Randomization Method
Randomization done in office by a computer
Randomization Unit
Household
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,000 Households
Sample size: planned number of observations
2,000 Households
Sample size (or number of clusters) by treatment arms
2,000 Households
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The study has sufficient power to detect effects of reasonable size in the analyses for our primary hypotheses. For these power calculations, we consider the intent-to-treat (ITT) effect of the randomized interventions on a standardized version of our outcomes: indices of perceived social distancing norms and household social distancing behavior. The study sample will be drawn from the 3,135 individuals for whom we have phone numbers. We assume a conservative response rate of 54%—drawn from a follow-up telephone survey conducted in 2019—which we aim to improve through repeated calls at different times of the day. We calculate the minimum detectable effect (MDE) of comparing the control group to one of the three treatment groups (i.e., each group is one fourth of the responding sample). The MDE is 0.1929, meaning that our study is sufficiently powered to detect a difference of 0.2 standard deviations in our standardized outcome measures between the control group and each treatment group.
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Michigan Health Sciences and Behavioral Sciences Institutional Review Board
IRB Approval Date
2020-04-15
IRB Approval Number
HUM00113011
Analysis Plan

Analysis Plan Documents

Accelerating Changes in Norms about Social Distancing to Combat COVID‐19

MD5: b2ffa211e04cd56b88649c3470391656

SHA1: ae18dd6fa56a1e7f7711df5428de8a7f6b263090

Uploaded At: August 25, 2020

Learning about COVID-19: Improving Knowledge via Incentives and Feedback

MD5: 54eff705a0afb7e1bcefdeb81b6a8992

SHA1: 5d6db9b08d00e2ec49bca703fa0c66d0251751ce

Uploaded At: August 25, 2020

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