Positive Attribute Framing Increases COVID-19 Booster Vaccine Intention for Unfamiliar Vaccines

Abstract

Positive framing has been proposed as an intervention to increase COVID-19 vaccination intentions. However, available research has examined fictitious or unfamiliar treatments. This pre-registered study (aspredicted#78369) compared the effect of standard negatively framed EU patient information leaflets (PILs), with new positively framed PILs, on booster intentions (measured pre- and post-intervention) for AstraZeneca, Pfizer, and Moderna COVID-19 vaccines. A representative sample of 1222 UK-based adults was randomised to one of six groups in a factorial design with framing (Positive vs. Negative) and vaccine familiarity (same (as previous), familiar, unfamiliar) as factors. The benefit of positive framing was hypothesised to be strongest for the least familiar vaccine (Moderna). Framing was moderated by familiarity, where only the unfamiliar vaccine showed a benefit of positive relative to negative Framing. Framing and familiarity also interacted with baseline Intention with the effect of framing on the unfamiliar vaccine especially pronounced at low baseline Intent. Conversely, standard negative framing appeared to increase intentions for familiar vaccines at low baseline intent. Findings provide important evidence that positive framing could improve vaccine uptake globally when switches or new developments require individuals to receive less familiar vaccines. Positive framing of familiar vaccines, however, should be treated with caution until better understood.

Keywords: COVID-19; attribute framing; positive framing; vaccination; vaccine hesitancy; vaccine intention.

Figure 1

(a). Positive and negative wording used to frame common and uncommon side effects (wording for all prevalence categories can be found in Supplementary Materials S1.3); (b). frequency of participants from each postal area of the UK plotted against the vaccination rates reported by the UK government on 3 November (the final week of data collection).

Figure 2

Overview of the design, including the item wording for primary and secondary outcomes. Nb. Satisfaction, happiness, and anxiety were rated separately as part of the booster acceptance measure. Primary and secondary outcomes employed a 100-point VAS with the following anchors: booster intention (‘definitely would not accept vaccine’ vs. ‘definitely would accept vaccine’); booster side effect severity (‘not at all severe’ vs. ‘extremely severe’); perceived booster risk (‘extremely low risk’ vs. ‘extremely high risk’); and booster acceptance (‘not at all’ vs. ‘extremely’).

Figure 3

Descriptive statistics regarding sample demographics, as well as vaccine and COVID-19 history of the full sample (N = 1222).

Figure 4

Model estimated mean differences in the primary outcome (Booster Intention), depicted for the whole sample ((a,b); sample size by condition presented in Table 1), and for realistic switches occurring as part of the UK booster programme ((c,d); AstraZeneca/Unfamiliar N = 206, AstraZeneca/Familiar N = 204, Pfizer/Unfamiliar N = 202, sample size by condition presented in Figure 2). (e) presents data demonstrating that side effect familiarity ratings scaled with the factorial levels of vaccine familiarity (within-subjects, full sample N = 1222). All error bars represent ± 1SEM.