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The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences.

ABSTRACT: Mass media routinely present data on coronavirus disease 2019 (COVID-19) diffusion with graphs that use either a log scale or a linear scale. We show that the choice of the scale adopted on these graphs has important consequences on how people understand and react to the information conveyed. In particular, we find that when we show the number of COVID-19 related deaths on a logarithmic scale, people have a less accurate understanding of how the pandemic has developed, make less accurate predictions on its evolution, and have different policy preferences than when they are exposed to a linear scale. Consequently, merely changing the scale the data is presented on can alter public policy preferences and the level of worry about the pandemic, despite the fact that people are routinely exposed to COVID-19 related information. Providing the public with information in ways they understand better can help improving the response to COVID-19, thus, mass media and policymakers communicating to the general public should always describe the evolution of the pandemic using a graph on a linear scale, at least as a default option. Our results suggest that framing matters when communicating to the public.

SUBMITTER: Romano A

PROVIDER: S-EPMC7461444 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences.

Romano Alessandro A Sotis Chiara C Dominioni Goran G Guidi Sebastián S

Health economics 20200825 11

Mass media routinely present data on coronavirus disease 2019 (COVID-19) diffusion with graphs that use either a log scale or a linear scale. We show that the choice of the scale adopted on these graphs has important consequences on how people understand and react to the information conveyed. In particular, we find that when we show the number of COVID-19 related deaths on a logarithmic scale, people have a less accurate understanding of how the pandemic has developed, make less accurate predict ...[more]

PMID: 32844495

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Project description:Transgender rights and discrimination against transgender people are growing public policy issues. Theorizing from social, cognitive, and evolutionary psychology suggests that beyond attitudes, discrimination against transgender people may derive from folk theories about what gender is and where it comes from. Transgender identity is met with hostility, in part, because it poses a challenge to the lay view that gender is determined at birth, and based on observable physical and behavioral characteristics. Here, in two pre-registered studies (N = 1323), we asked American adults to indicate the gender of a transgender target who either altered their biology through surgical interventions or altered their outward appearance: to what extent is it their birth-assigned gender or their self-identified gender? Responses correlate strongly with affect toward transgender people, measured by feeling thermometers, yet predict views on transgender people's right to use their preferred bathrooms above and beyond feelings. Compared to male participants, female participants judge the person's gender more in line with the self-identified gender than the birth-assigned gender. This is consistent with social and psychological theories that posit high status (e.g., men) and low status (e.g., women) members of social classification systems view group hierarchies in more and less essentialist ways respectively. Gender differences in gender category beliefs decrease with religiosity and conservatism, and are smaller in higher age groups. These results suggest that folk theories of gender, or beliefs about what gender is and how it is determined have a unique role in how transgender people are viewed and treated. Moreover, as evident by the demographic variability of gender category beliefs, folk theories are shaped by social and cultural forces and are amenable to interventions. They offer an alternative pathway to measure policy support and possibly change attitude toward transgender people.

Project description:ImportancePolicies to promote social distancing can minimize COVID-19 transmission but come with substantial social and economic costs. Quantifying relative preferences among the public for such practices can inform locally relevant policy prioritization and optimize uptake.ObjectiveTo evaluate relative utilities (ie, preferences) for COVID-19 pandemic social distancing strategies against the hypothetical risk of acquiring COVID-19 and anticipated income loss.Design, setting, and participantsThis survey study recruited individuals living in the Missouri area from May to June 2020 via randomly distributed unincentivized social media advertisements and local recruitment platforms for members of minority racial and ethnic groups. Participants answered 6 questions that asked them to choose between 2 hypothetical counties where business closures, social distancing policy duration, COVID-19 infection risk, and income loss varied.Main outcomes and measuresReweighted population-level relative preferences (utilities) for social distancing policies, subgroups, and latent classes.ResultsThe survey had a 3% response rate (3045 of 90 320). Of the 2428 respondents who completed the survey, 1669 (75%) were 35 years and older, 1536 (69%) were women, and 1973 (89%) were White. After reweighting to match Missouri population demographic characteristics, the strongest preference was for the prohibition of large gatherings (mean preference, -1.43; 95% CI, -1.67 to -1.18), with relative indifference to the closure of social and lifestyle venues (mean preference, 0.05; 95% CI, -0.08 to 0.17). There were weak preferences to keep outdoor venues (mean preference, 0.50; 95% CI, 0.39 to 0.61) and schools (mean preference, 0.18; 95% CI, 0.05 to 0.30) open. Latent class analysis revealed 4 distinct preference phenotypes in the population: risk averse (48.9%), conflicted (22.5%), prosocial (14.9%), and back to normal (13.7%), with men twice as likely as women to belong to the back to normal group than the risk averse group (relative risk ratio, 2.19; 95% CI, 1.54 to 3.12).Conclusions and relevanceIn this survey study using a discrete choice experiment, public health policies that prohibited large gatherings, as well as those that closed social and lifestyle venues, appeared to be acceptable to the public. During policy implementation, these activities should be prioritized for first-phase closures. These findings suggest that policy messages that address preference heterogeneity (eg, focusing on specific preference subgroups or targeting men) could improve adherence to social distancing measures for COVID-19 and future pandemics.

Dataset Information

The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences.

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The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences.

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