Effect of communication strategy on personal risk perception and treatment adherence intentions

Abstract

Past research suggests that semantic and numerical medical risk descriptors may lead to miscommunication and misinterpretation of risk. However, little research has been conducted on systematic features of this bias, and the resulting potential risks to people contemplating or receiving treatment. Three studies explore the influence of verbal versus numerical medical risk descriptions. In Study 1a, San Francisco Bay area residents (N = 59) were presented with semantic descriptors for low-likelihood events and reported their perceived quantitative risk for the events. In Study 1b, undergraduates (N = 29) were presented with semantic versus numerical information about side effects for a prescribed medication and reported their perceived risk and adherence intentions. In Study 1c, San Francisco Bay area residents (N = 125) were presented with semantic versus numerical information about their risk for a disease and reported their perceived risk and intention to adhere to a prescribed treatment. The results of the first study suggest that people systematically overestimate the likelihood of low probability events described in semantic terms such as “low risk” or “people may occasionally experience.” The results of the second and third experiment suggest that presenting semantic information about the risks of engaging in a new behavior makes people less likely to engage in that behavior, whereas presenting semantic information about the risks of not engaging in a new behavior makes people more likely to engage in the behavior. The decision to present semantic versus probabilistic information is tantamount to a decision about whether to encourage risk acceptance versus risk avoidance.

Keywords:

• risk perception
• risk communication
• overestimation
• semantic versus numerical risk information
• adherence

Acknowledgements

The author wishes to thank Dr. Terry Blaschke, Lee Ross, Kristin Cobb, Benoit Monin, and the Ross lab for support and feedback.

Notes

1. 041 was used as a conservative percentage. We used. 041 (rather than. 04) to increase the credibility of our story.