Vaccine sharing behaviour in the COVID-19 pandemic: the impact of narratives and peer effects

Last registered on October 27, 2021

Pre-Trial

Trial Information

General Information

Title
Vaccine sharing behaviour in the COVID-19 pandemic: the impact of narratives and peer effects
RCT ID
AEARCTR-0008422
Initial registration date
October 25, 2021
Last updated
October 27, 2021, 11:16 AM EDT

Locations

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Primary Investigator

Affiliation
Nuffield College and Department of Economics, University of Oxford and University of Hagen

Other Primary Investigator(s)

PI Affiliation
UNU-MERIT and Maastricht University, School of Business and Economics
PI Affiliation
Nuffield College and Department of Economics, University of Oxford

Additional Trial Information

Status
In development
Start date
2021-12-01
End date
2022-05-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct a virtual lab experiment to understand individuals' vaccine sharing attitudes and behaviour in the context of altruistic and self-interested narratives, with and without peer effects. A 2-by-3 factorial design is used to determine the isolated impact as well as the interaction of these treatments on vaccine sharing with resource-poor countries, which is approximated by monetary donations from subject payments to the vaccine access initiative COVAX. The main interventions are complemented by detailed socio-economic surveys, including attitudes towards vaccines and vaccine history.
External Link(s)

Registration Citation

Citation
Finster, Simon, Michelle González Amador and Edwin Lock. 2021. "Vaccine sharing behaviour in the COVID-19 pandemic: the impact of narratives and peer effects." AEA RCT Registry. October 27. https://doi.org/10.1257/rct.8422-1.0
Experimental Details

Interventions

Intervention(s)
We introduce a 3x2 factorial design, where subjects are randomly assigned to one of six experimental conditions. In the first dimension, we present our subjects with facts appealing to either altruism or self-interest (plus control group) as a narrative for sharing vaccines. These facts are presented by means of a short video. Subjects then have the opportunity to share any amount of their earnings from the experiment as a donation to the vaccine access initiative COVAX. In the second dimension, we observe peer effects: after learning the average sharing behaviour of their peer group, subjects can revise their pledge. For all subjects, we also collect relevant covariates such as data on vaccine history, exposure to hardship during the pandemic, risk attitudes, inequity aversion, baseline level of altruism, and standard demographics.
Intervention Start Date
2021-12-01
Intervention End Date
2022-05-31

Primary Outcomes

Primary Outcomes (end points)
Dependent Variable 1: Amount of money (in GBP) that subjects pledge towards COVAX, from their earnings on the experiment (initial and final pledge).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Dependent variable 2: Indicator that takes on the value 1 if subjects revise their donation, and zero otherwise.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
All treatments + control are introduced to the survey and consent is confirmed. Treatments A, S, PA, and PS (see full pre-analysis plan for reference to treatment names) view informational video with altruism or self-interest narrative. All treatments + control group learn their earnings (8 GBP) and can make a pledge towards COVAX. Treatments P, PA, PS are informed that they are participating in a group (defined by 'within session' and 'within treatment'), and will see the group’s total and average-per-person donation subsequent to their pledge, while their own donation choice will remain confidential. Subjects are not informed that there will be an opportunity to revise the pledge. Treatments P, PA, PS are shown their group’s total and average-per-person donation. All treatments + control can revise their pledge. All treatments + control are asked to complete an unpaid survey.
Experimental Design Details
Not available
Randomization Method
Randomization done by OTree Software, by a computer.
Randomization Unit
Randomized unit: individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
1500
Sample size (or number of clusters) by treatment arms
250 subjects per treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We perform a simulation-based, between-subject ANOVA power analysis in order to estimate the minimum sample sized needed to minimise the probability of incurring a Type II error. Our a priori calculation uses Caldwell and Läkens’ Superpower R package, whose algorithm relies on 10,000 Monte Carlo data set simulations with attributes specified by the researcher. We have defined the input parameters, mu = [2,1,4.5,2.5,5.5,4.5] {Each mean corresponds to the following condition, respectively: Control with Peer Effects, Control, Altruism Narrative with Peer Effects, Altruism Narrative, Self-Interest Narrative with Peer Effects, Self-Interest Narrative.} and sigma = 2.89$, based on a linear approximation of Metzger and Günther's (2019) experimental mean and standard deviation whose design is similar to ours. We adapt these numbers to our hypotheses. With a power score of 100 for the narrative factor, 100 for the peer effects factor, and 81.4 for the interaction between these two factors, a sample size of n = 250 per experimental condition suffices to reach the recommended power level (Cohen, 1988), when alpha = 0.05. Cohen’s f estimates of 0.5, 0.23 and 0.08 (respectively) coincide with benchmark big, medium and small effect sizes (0.4, 0.25, 0.1).
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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