This Interpretation is based on work published in: https://doi.org/10.1098/rsos.201721
The interviews and the survey responses combined help give us an overall view of the public’s information needs regarding their personal COVID-19 risk, as of July 2020.
The majority of participants clearly showed a desire for quantitative information about COVID-19 (much of which was not, at the time of this survey, available). The comments from the primary care physicians suggested that they viewed patients as perhaps becoming used to being given simplified instructions rather than information on which to base their own decisions. However, the results from the surveys implied that the majority of the public would actually appreciate being given more detailed information on which to base their own risk decisions.
The quantitative survey emphasized that there was a clear public concern about the virus and its potential consequences, and people’s perception of chances of themselves dying of the virus if they caught it were not highly correlated with the actual chances as calculated from a personalized risk calculator given the health information participants gave us, with only a weak relationship between the two.
Some of this discrepancy seemed very likely to be due to the way that most people think about ‘risks’—as a subjective impression, not easily translated into a numerical concept [1]. Even when pushed to quantify their feeling of risk, most members of the public in our interviews described the risk in terms of a ‘persona’ that they had in their mind to represent that level of risk: a person who embodied the major risk factors that would exemplify that level of risk (such as age and relevant health attributes).
Given that only a minority of people in the surveys wanted simply to be told that their risk fell into a simple category such as ‘low’ (as well as the practical and ethical difficulties of doing that given that an absolute risk and relative risk would need to be combined in some way), it would be useful to consider further ways in which to help people understand the likelihood figure of them dying from COVID-19 should they catch it.
The other themes emerging from the interviews were useful in determining important endpoints to measure in future work developing a personalised communication tool: levels of perceived uncertainty, perceptions of the quality of the underlying evidence, trust (in the data itself and in the source of the data) and degree of worry associated with the results. Trustworthiness is a crucial dimension to consider during the design of any communication—something previously emphasized in the risk communications literature (e.g. [2]). In line with previous research (e.g. [3]), the interviews suggested that trustworthiness and relevance were enhanced by appropriate branding and making it clear that the results presented were based on research (ideally from a trustworthy source) and on relevant data. Previous experience (e.g. [3]) suggests that people are sensitive to cues of quality of evidence (such as sizes of datasets and relevance of the population on which the evidence is based), as well as assessing the information’s source.