title: Debunking vaccination myths: strong risk negations can increase perceived vaccination risks.
abstract: OBJECTIVE
  Information about risks is often contradictory, especially in the health domain. A vast amount of bizarre information on vaccine-adverse events (VAE) can be found on the Internet; most are posted by antivaccination activists. Several actors in the health sector struggle against these statements by negating claimed risks with scientific explanations. The goal of the present work is to find optimal ways of negating risk to decrease risk perceptions.
  
  
  METHODS
  In two online experiments, we varied the extremity of risk negations and their source. Perception of the probability of VAE, their expected severity (both variables serve as indicators of perceived risk), and vaccination intentions.
  
  
  RESULTS
  Paradoxically, messages strongly indicating that there is "no risk" led to a higher perceived vaccination risk than weak negations. This finding extends previous work on the negativity bias, which has shown that information stating the presence of risk decreases risk perceptions, while information negating the existence of risk increases such perceptions. Several moderators were also tested; however, the effect occurred independently of the number of negations, recipient involvement, and attitude. Solely the credibility of the information source interacted with the extremity of risk negation: For credible sources (governmental institutions), strong and weak risk negations lead to similar perceived risk, while for less credible sources (pharmaceutical industries) weak negations lead to less perceived risk than strong negations.
  
  
  CONCLUSIONS
  Optimal risk negation may profit from moderate rather than extreme formulations as a source's trustworthiness can vary.
authors.affiliation: Center for Empirical Research in Economics and Behavioral Sciences (CEREB), University of Erfurt, Germany. cornelia.betsch@uni-erfurt.de
authors.forename: Cornelia
authors.initials: C
authors.lastname: Betsch
authors.forename: Katharina
authors.initials: K
authors.lastname: Sachse
mesh_terms: D000328:Adult; D005260:Female; D058015:Health Communication / Q000379:methods*; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D020407:Internet; D008297:Male; D018570:Risk Assessment; D014611:Vaccination / Q000523:psychology*