Background. Numeracy, how facile people are with basic probability and mathematical concepts, is associated with how people perceive health risks. Performance on simple numeracy problems has been poor among populations with little as well as more formal education. Here, we examine how highly educated participants performed on a general and an expanded numeracy scale. The latter was designed within the context of health risks. Method. A total of 463 men and women aged 40 and older completed a 3-item general and an expanded 7-item numeracy scale. The expanded scale assessed how well people 1) differentiate and perform simple mathematical operations on risk magnitudes using percentages and proportions, 2) convert percentages to proportions, 3) convert proportions to percentages, and 4) convert probabilities to proportions. Results. On average, 18% and 32% of participants correctly answered all of the general and expanded numeracy scale items. Approximately 16% to 20% incorrectly answered the most straightforward questions pertaining to risk magnitudes (e.g., Which represents the larger risk: 1%, 5%, or 10%?). A factor analysis revealed that the general and expanded risk numeracy items tapped the construct of global numeracy. Conclusions. These results suggest that even highly educated participants have difficulty with relatively simple numeracy questions, thus replicating in part earlier studies. The implication is that usual strategies for communicating numerical risk may be flawed. Methods and consequences of communicating health risk information tailored to a person’s level of numeracy should be explored further.

Perception of health risk can affect medical decisions and health behavior change. Yet the concept of risk is a difficult one for the public to grasp. Whether perceptions of risk affect decisions and behaviors often relies on how messages of risk magnitudes (i.e., likelihood) are conveyed. Based on expert opinion, this article offers, when possible, best practices for conveying magnitude of health risks using numeric, verbal, and visual formats. This expert opinion is based on existing empirical evidence, review of papers and books, and consultations with experts in risk communication. This article also discusses formats to use pertaining to unique risk communication challenges (e.g., conveying small-probability events, interactions). Several recommendations are suggested for enhancing precision in perception of risk by presenting risk magnitudes numerically and visually. Overall, there are little data to suggest best practices for verbal communication of risk magnitudes. Across the 3 formats, few overall recommendations could be suggested because of 1) lack of consistency in testing formats using the same outcomes in the domain of interest, 2) lack of critical tests using randomized controlled studies pitting formats against one another, and 3) lack of theoretical progress detailing and testing mechanisms why one format should be more efficacious in a specific context to affect risk magnitudes than others. Areas of future research are provided that it is hoped will help illuminate future best practices.

Making evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric estimates improves patients’ risk perception and leads to better informed decision making. This paper summarises current “best practices” in communication of evidence-based numeric outcomes for developers of patient decision aids (PtDAs) and other health communication tools.

This paper 1) provides reasons why graphics should be effective aids to communicate risk; 2) reviews the use of visuals, especially graphical displays, to communicate risk; 3) discusses issues to consider when designing graphs to communicate risk; and 4) provides suggestions for future research. Key articles and materials were obtained from MEDLINE® and PsychInfo® databases, from reference article citations, and from discussion with experts in risk communication. Research has been devoted primarily to communicating risk magnitudes. Among the various graphical displays, the risk ladder appears to be a promising tool for communicating absolute and relative risks. Preliminary evidence suggests that people understand risk information presented in histograms and pie charts. Areas that need further attention include 1) applying theoretical models to the visual communication of risk, 2) testing which graphical displays can be applied best to different risk communication tasks (e.g., which graphs best convey absolute or relative risks), 3) communicating risk uncertainty, and 4) testing whether the lay public's perceptions and understanding of risk varies by graphical format and whether the addition of graphical displays improves comprehension substantially beyond numerical or narrative translations of risk and, if so, by how much. There is a need to ascertain the extent to which graphics and other visuals enhance the public's understanding of disease risk to facilitate decision-making and behavioral change processes. Nine suggestions are provided to help achieve these ends.

Numeracy—that is, how facile people are with mathematical concepts and their applications—is gaining importance in medical decision making and risk communication. This article proposes six critical functions of health numeracy. These functions are integrated into a theoretical framework on health numeracy that has implications for risk communication and medical decision-making processes. The authors examine practical underpinnings for targeted interventions aimed at improving such processes as a function of health numeracy. They hope that the proposed functions and theoretical framework will spur more research to determine how an understanding of health numeracy can lead to more effective communication and decision outcomes.

The authors conduct two experiments that indicate that the effectiveness of loss- versus gain-framed messages depends on the affective state of the message recipient. In Experiment 1, the authors find that participants induced with a positive mood are more persuaded by the loss-framed message, whereas participants induced with a negative mood are more persuaded by the gain-framed message. In addition, the authors observe that participants in a positive mood have higher risk estimates and lower costs in response to the loss frame than the gain frame, whereas the reverse is true for participants in a negative mood. The authors replicate these effects in Experiment 2 in which they measure rather than induce the participants' affective state.