Visual policy narrative messaging improves COVID-19 vaccine uptake

Abstract

In the face of vaccine hesitancy, public health officials are seeking more effective risk communication approaches to increase vaccination rates. We test the influence of visual policy narratives on COVID-19 vaccination behavior through a panel survey experiment conducted in early 2021 (n = 3,900) and then 8 weeks later (n = 2,268). We examine the effects of three visual policy narrative messages that test the narrative mechanism of character selection (yourself, your circle, and your community) and a nonnarrative control on COVID-19 vaccine behavior. Visual risk messages that use narratives positively influence COVID-19 vaccination through serial mediation of affective response to the messages and motivation to get the COVID-19 vaccination. Additionally, character selection matters, as messages focusing on protecting others (i.e. your circle and your community) perform stronger than those of yourself. Political ideology moderated some of the effects, with conservative respondents in the nonnarrative control condition having a higher probability of vaccination in comparison to the protect yourself condition. Taken together, these results suggest that public health officials should use narrative-based visual communication messages that emphasize communal benefits of vaccinations.

Keywords: COVID-19; narrative risk communication; risk perception; vaccine behavior; visual policy narratives.

Fig. 1.

Example of early nonnarrative communication from CDC that employs imperative statements and visual graphics. Found at cdc.gov/coronavirus in 2000.

Fig. 2.

T ₁, wave 1; T₂, wave 2; X_i, experimental conditions; Y₁, outcome variable (received a COVID-19 vaccine); W, moderating variable (beliefs); F_1…j, covariates (risk perception, COVID-19 experience, flu vaccine history, and demographics).

Fig. 3.

T ₁, wave 1; T₂, wave 2; X_i, experimental conditions; M_1–2, mediators (affective response and motivated to vaccinate); Y₁, outcome variable (received a COVID-19 vaccine); W, moderating variable (beliefs); F_1…j, covariates (risk perception, COVID-19 experience, flu vaccine history, and demographics).

Fig. 4.

Three treatment conditions: protect yourself, protect your circle, and protect your community; control condition: get the vaccine. Graphics produced by Todd Radom.

Fig. 5.

Predicted probability of COVID-19 vaccination at T₂, by messaging condition and political ideology at T₁, at mean levels of perceptions of severity of risk, likelihood of risk, age, education, income, COVID-19 infection experience, flu vaccine history, gender, race (white vs. minority), and number of children. Predicted probability of moderates were calculated on the mean of political ideology; liberals at +1 SD and conservatives at −1 SD. Error bars were calculated at the 95% confidence level with standard errors estimated with the delta method using Stata.