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

We employ over-the-phone interventions designed to improve 1) social distancing, and 2) knowledge relating to COVID-19.

Social Distancing Treatments:
-SD1: Information on the value of social distancing. We will provide individuals with information on the value of social distancing, emphasizing the positive externality they confer on others by reducing the spread of COVID-19.
-SD2: Community Support for Social Distancing. We will ask individuals whether they themselves support social distancing, and use this information to calculation the fraction of households in the community who support social distancing. We will then ask them to guess the share of households in the community who support social distancing. In a later phone call, households who underestimate the true share of households in the community who support social distancing will be given information on the true (higher) share of support for social distancing. We will accompany this message with information on the value of social distancing, emphasizing the positive externality they confer (same information provided in Treatment SD1).
-SD3: Community leader support for social distancing. Community leaders have also participated in past rounds of our surveys. We will survey community leaders again, and ask them to endorse social distancing in their communities. In this treatment, we will inform households by phone call that these individuals support social distancing in their communities. We will accompany this message with information on the value of social distancing, emphasizing the positive externality they confer (the same information provided in Treatment SD1).

Knowledge Treatments:
-K1: Knowledge Incentives. We will randomly offer a subset of respondents an additional monetary reward for every correct knowledge response on a subsequent phone survey. We will examine the effect of the treatment on future knowledge and behavior.
-K2 & 3: Tailored Feedback. We will randomly give tailored feedback to a subset of respondents 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.

2020-06-15

2020-08-15

For Social Distancing interventions:
-Others’ and self-report of social interactions
-Index of household social distancing behaviors

For Knowledge interventions:
-Index of COVID-19 overall knowledge

For Social Distancing interventions:
-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.

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.

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 done in office by a computer

Household

No

2,000 Households

2,000 Households

2,000 Households

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.