Effect of Narrative Reports about Vaccine Adverse Events and Bias-Awareness Disclaimers on Vaccine Decisions

Author:

Betsch Cornelia1,Renkewitz Frank1,Haase Niels1

Affiliation:

1. Center for Empirical Research in Economics and Behavioral Science, University of Erfurt, Erfurt, Germany

Abstract

Background. As the number of individuals who search for health information in interactive online environments is increasing, patient networks deserve more scientific attention. Objective. To quantitatively examine if and how reading statistical and/or narrative information as typically displayed in patient networks (e.g., patientslikeme.com ) affects decisions for pharmaceuticals. Previous work suggests that narrative information (e.g., about vaccine adverse events, VAE) affects risk perceptions and intentions. The authors compare the effect of narrative and statistical information about VAE on vaccination decisions and examine if a disclaimer reduces the narrative bias as well as if low numeracy leads to increased use of the narratives. Method and Design. In an online experiment, 458 participants were randomly assigned to a 3 (relative frequency of vaccine adverse events in 1, 7, or 17 of 20 cases) × 3 (type of information: narratives, summary statistics, or both) × 2 (bias awareness v. control disclaimer) between-subjects design. Measurements. Perceived risk, vaccination intention, and subjective numeracy. Results. A higher relative frequency of cases reporting VAE decreased the intention to get vaccinated. This relation was mediated by increased risk perception. The type of information moderated the contents’ impact: Summary statistics had the smallest impact, whereas narrative information was more influential, and the presence of both types of information had the greatest impact on risk perception. Individuals who received the bias-awareness disclaimer were less influenced by the patient network. Highly numerate individuals were generally more sensitive to the provided information independent of its format. Conclusions. Patient networks can influence vaccination decisions by delivering risk-related information. Disclaimers may help to reduce the influence if desired.

Publisher

SAGE Publications

Subject

Health Policy

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