gms | German Medical Science

Understanding how people form and revise their perception of risk is central to designing efficient risk communication methods, eliciting risk awareness, and avoiding unnecessary anxiety among the public. Yet public responses to hazardous events such as climate change, contagious outbreaks, and terrorist threats are complex and difficult to anticipate. While many psychological factors influencing risk perception have been identified in the past, it remains unclear how perceptions of risk change when information is propagated from one person to another, and what impact the repeated social transmission of perceived risk has at the population scale.

To examine these questions, we analyze how a risk message detailing the benefits and harms of the widely used but controversial antibacterial agent called Triclosan is communicated from one individual to another in experimental communication chains. Communication chains constitute useful tools for studying the dynamics of social contagion phenomena. A chain mimics the spread of a rumor in a social network: A first participant is “seeded” with a risk message detailing the benefits and harms of Triclosan, and instructed to communicate about it to a second, naÏve participant in an open discussion. After the discussion, the second participant, in turn, is instructed to communicate about Triclosan to a third individual, and so on until end of the chain. In total, we examine 15 different communication chains, each composed of 10 participants. The discussions between every two subsequent subjects were recorded and analyzed, and the subjects' risk judgment of Triclosan was assessed before and after the experiment.

Our analyses show that when messages are propagated through the transmission chains, they tend to become shorter, gradually inaccurate, and increasingly dissimilar between chains. In contrast, the perception of risk is propagated with higher fidelity due to participants manipulating messages to fit their preconceptions, thereby influencing the judgments of subsequent participants. Computer simulations implementing this simple influence mechanism show that small judgment biases tend to become more extreme, even when the injected message contradicts preconceived risk judgments. Our results provide quantitative insights into the social amplification of risk perception, and can help policy makers better anticipate and manage the public response to emerging threats.

The authors declare that they have no competing interests.

The authors declare that a positive ethics committee vote has been obtained.