Information-seeking, online search tools, and the formation of new norms in health behaviors during the COVID-19 pandemic

This dissertation focuses on how people search for information and how people rely on this information to inform their health behaviors and develop social norms. In academia and policy, the focus in research on information has most often studied the information that is sent to consumers, seeing people as passive receivers of information. This is otherwise known as information 'push'. But, information is also intentionally sought out by individuals;called information pull. My dissertation focuses on individuals as active agents in their search for information and how the information discovered through these push and pull processes relates to the creation of social norms.My first article tests the criterion validity of Google Search Trends as an indicator of computer-mediated information search. I attempt to validate Google Search Trends for use as indicators of attitudes, disease prevalence and political preferences using five different data sources. My analysis revealed no correlation among any of the Google Trends tested and their validated indicators. I demonstrate that there is no criterion validity of Google Trends for the selected cases and social scientists will find no replacement for high quality survey data with Google Trends. Instead, we must only use Google Trends to demonstrate interest or attention.Knowing that Google Trends data only encompasses a small portion of the information-seeking done by modern humans, my second article is motivated by the research question: How do computer-mediated or interpersonal information-seeking strategies vary across populations? Using original survey data of 948 Americans, I investigate their experiences seeking out information about COVID-19 vaccines. I investigate five distinct information seeking modalities, or methods of searching for information: personal connection, doctor, social networking site, online forum, and online search engine. I find that different exposure points, the ways people first are exposed to information without searching for it, and information search modalities hold real world consequences through their associations with COVID-19 vaccination intentions and rates. For example, I find that receiving or seeking out information from a doctor increases COVID-19 vaccination uptake while receiving information from a social networking site is associated with lower odds of vaccination.My final article takes a deeper dive into the formation of social norms governing health behaviors in cases of extreme uncertainty. I specifically use the cases of stay-at-home rates and vaccination rates as responses to public health recommendations to mitigate the COVID-19 pandemic. Using the theories of associative diffusion and the integrated theoretical framework of norms, I test models of behavioral adaption to public health recommendations and patterns of complex contagion (the need for repeated exposures to something novel for it to diffuse) using linear mixed effects models. My results show that complex contagion is a valid framework for the social contagion of new norms during COVID-19. However, I find an important novel moderating effect of signal discordance;if there is diversity in the information received by an ego, contagion is less likely to occur. This paper shows that the contagion process is not fully understood without looking at the context of each exposure to a contagion within the range of contagions one experiences.The introductory chapter provides a summary of the research and an explanation of how this research contributes to sociology, social science, and society. Namely, this paper provides important perspectives on search as an agentic process and how the micro-level information seeking process of an individual can lead to macro-level social norms. I show that information diffusion is disrupted when conflicting information and behaviors are simultaneously diffusing and therein contribute to research on diffusion, social networks, and social norms. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Conservatism and infrequent mask usage: A study of US counties during the novel coronavirus (COVID-19) pandemic.

OBJECTIVE: Although the Centers for Disease Control and Prevention eventually recommended wearing masks in public to slow the spread of the coronavirus, the practice has been unevenly distributed in the United States. METHODS: In this article, we model county-level infrequent mask usage as a function of three pillars of conservatism: (1) Republican political leadership (percentage of votes for Donald Trump in the 2016 presidential election), (2) conservative Protestantism (percentage evangelical Christian), and (3) right-wing media consumption (Google searches for Fox News). RESULTS: Our analyses indicate that mask usage tends to be lower in counties with greater support for President Trump (in majority Trump counties), counties with more evangelical Christians, and areas with greater interest in Fox News. CONCLUSION: Given the effectiveness of masks in limiting the transmission of respiratory droplets, conservative ideological resistance to public health and recommended pandemic lifestyles may indirectly support the spread of the coronavirus.

Love thy Aged? A State-Level Analysis of Religiosity and Mobility in Aging Populations During the Novel Coronavirus (COVID-19) Pandemic.

Objectives: We test whether the association between state religiosity and distance traveled is moderated by population age during the novel coronavirus (COVID-19) pandemic. Methods: Mobility is operationalized as the state-level average median distance traveled from February 24 to May 4 across the contiguous United States. Shelter-in-place rates are operationalized as the state-level percentage of users staying home. State religiosity is measured with an index of aggregated religious identities, beliefs, and practices. Population age is indicated by the state percentage of adults aged 65 years and older. We model population mobility using regression with state clustered robust SEs. Results: We observe that religious states tend to travel more during the early stages of the pandemic. However, the behavioral risks associated with state religiosity are less pronounced in states with larger older populations. Discussion: We contribute to our understanding of the social patterning of pandemic mobility in aging populations.

The Nastiest Question: Does Population Mobility Vary by State Political Ideology during the Novel Coronavirus (COVID-19) Pandemic?

We consider the association between state political ideology and population mobility during the coronavirus (COVID-19) pandemic. We use first-party geo-behavioral data to estimate the average distance traveled by approximately 15,000,000 devices over 10 weeks (February 24, 2020 to April 27, 2020). Regression models with state clustered robust standard errors show lower shelter-in-place rates and higher mobility scores in states with larger percentages of voters who supported Trump in the 2016 presidential election. We also find that shelter-in-place rates increased and mobility scores declined at slower rates in states with greater Trump support. Shelter-in-place rates and average mobility scores were comparable in states governed by Republicans and Democrats. There was some evidence that shelter-in-place rates increased and average mobility scores declined at slower rates in states governed by Republicans. Overall, states with more Trump voters are more resistant to public health recommendations and state stay-at-home orders during the coronavirus pandemic.

The Blood of Christ Compels Them: State Religiosity and State Population Mobility During the Coronavirus (COVID-19) Pandemic.

This paper examines the association between state religiosity and population mobility during the coronavirus (COVID-19) pandemic. We use first-party geo-behavioral data collected through mobile phone operating systems, global positioning systems, and Wi-Fi signals to assess changes in the average median distance traveled by approximately 15,000,000 devices over eight weeks (February 24-April 13) in the contiguous United States. Robust regression results show that more religious states tend to exhibit higher average mobility scores and slower average declines in mobility. Findings also suggest that state stay-at-home orders have a weaker impact on mobility in more religious states.