자료유형  

 학위논문

Control Number  

0016933659

International Standard Book Number  

9798379565435

Dewey Decimal Classification Number  

150

Main Entry-Personal Name  

Adkins, Madison J.

Publication, Distribution, etc. (Imprint  

[S.l.] : University of Michigan., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(153 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 84-12, Section: B.

General Note  

Advisor: Shah, Priti.

Dissertation Note  

Thesis (Ph.D.)--University of Michigan, 2023.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Restrictions on Access Note  

This item must not be added to any third party search indexes.

Summary, Etc.  

요약Researchers have long studied how data visualizations influence risk perception. It's possible that the spread of COVID throughout the population could have been reduced by using best practices from the data visualization and risk perception literatures to develop public communications about the severity of COVID that were effective and unbiased. In this dissertation I discuss three lines of research examining how people understood common data visualizations presented to the public during the pandemic and how understanding of COVID data was related to attitudes towards preventative measures. In Chapter 2, I show that people over- or under-estimated the exponential growth of COVID depending on the linearity of the data, that viewing tables of data improved forecasting accuracy compared to graphs, that viewing graphs was associated with false confidence in one's forecasts, and some evidence that attitudes towards social distancing was positively correlated with the magnitude of participants' forecasts. In Chapter 3, I show that people misunderstood the relationship between daily and cumulative case curves and that participating in a brief video intervention improved understanding of accumulation. The effects of the intervention were long lasting and transferred to contexts outside of COVID. Participating in the intervention was also associated with more favorable attitudes towards social distancing and social distancing policies. In Chapter 4, I show that viewing icon arrays illustrating the 1 in 1 million chance of experiencing the reported side effect from the Johnson & Johnson vaccine prevented significant increases in aversion towards the Johnson & Johnson vaccine as well as all COVID vaccines. Lastly, in Chapter 5, I provide a synthesis of the literature conducted during the pandemic on how people understood COVID visualizations and describe three main findings: (1) people misunderstood commonly used COVID visualizations, (2) data visualizations influenced risk perception, and (3) graphs were sometimes used to mislead the public during the pandemic. This research informs how data should be communicated with the public and provides guidelines for how data should be explained to the public with visualizations.

Subject Added Entry-Topical Term  

Psychology.

Subject Added Entry-Topical Term  

Social psychology.

Subject Added Entry-Topical Term  

Cognitive psychology.

Index Term-Uncontrolled  

Data visualization

Index Term-Uncontrolled  

COVID-19

Index Term-Uncontrolled  

Risk perception

Index Term-Uncontrolled  

Media communications

Index Term-Uncontrolled  

Pandemic

Added Entry-Corporate Name  

University of Michigan Psychology

Host Item Entry  

Dissertations Abstracts International. 84-12B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:641011