Political vs. expert: the impact of influencer type on vaccination willingness

During a pandemic, influencers played a key role in promoting vaccination. This study examines the impact of influencer types (political vs. expert) on vaccination in the context of a future pandemic caused by a novel virus.

A 2 × 2 between-subjects experimental design was employed, with 287 valid adult participants recruited from China. Among all participants, 41.81% were male and 58.19% were female, with an average age of 30.20 years (SD = 7.64). Participants were exposed to simulated social media posts that manipulated influencer types (political vs. expert) and message framing (gain vs. loss). Influencers were presented with different profile pictures, nicknames and background descriptions, while follower counts remained unchanged. Message framing was manipulated by presenting vaccination information using a gain frame (emphasizing the benefits of vaccination) or a loss frame (emphasizing the risks of non-vaccination). Analysis of variance (ANOVA) was used to test the impact of influencer type, and its interaction with message framing on vaccination intentions. Meanwhile, the mediating effect of perceived credibility was tested using the PROCESS Macro Model 4 in R.

Results indicate a key main effect of influencer type on vaccination willingness (p < 0.01, η _p ² = 0.04). Political influencers (M = 5.93, SD = 0.93) were more persuasive than expert influencers (M = 5.60, SD = 0.81) in promoting vaccination. This effect was mediated by perceived credibility (b = 0.17, boot CI = [0.003, 0.332]). A significant interaction existed between influencer type and message framing (p < 0.05, η _p ² = 0.015).

Our findings highlight the importance of political influencers during pandemics, a discovery consistent with the informational entropy-based notion of value. This persuasive effect is achieved by enhancing perceived credibility, which can be explained by meaning transfer. Political influencers often align with mainstream authorities, and audiences view their messages as the government's stance. Therefore, the public's trust in the government shifts to political influencers, thus enhancing their influence during the pandemic. Interaction analysis indicates that correctly matching influencer type and message framing enhances vaccination intention. This matching effect is driven by the image the influencer represent. These findings contribute to more effective vaccine promotion during pandemics.