Browsing by Subject "trust in science"

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    Factors Associated with Reported Likelihood to Get Vaccinated for COVID-19 in a Nationally Representative US Survey
    (Elsevier, 2021-06) Agley, Jon; Xiao, Yunyu; Thompson, Esi E.; Golzarri-Arroyo, Lilian; School of Social Work
    Objectives While general principles related to vaccination hesitancy have been well-researched, reports on reluctance to be vaccinated for COVID-19 in the US are somewhat surprising given the disease’s substantive disruption of everyday life. However, the landscape in which people are making COVID-19 vaccination decisions has recently evolved with releases of encouraging vaccine-related data and changes to official messaging about the virus. Therefore, this study sought to identify factors associated with reported likelihood to get vaccinated for COVID-19 among US adults in late January 2021. Study Design We used the Prolific online research panel to survey a nationally representative sample of 1,017 US adults. Methods Respondents were asked about their behavioral intentions toward COVID-19 vaccination, trust in science, perceptions related to COVID-19, and selected sociodemographic factors. We computed associations between those 11 independent variables and likelihood to get vaccinated for COVID-19 using multiple linear regression. Results Around 73.9% of respondents indicated at least some likelihood to get vaccinated for COVID-19. Trust in science and perceived seriousness of COVID-19 were positively associated, and identifying as Black or African American was negatively associated, with intention to get vaccinated. Other factors were moderately, weakly, or not at all associated with intention. Conclusions Building trust in science and truthfully emphasizing the seriousness of catching COVID-19 should be further researched for their potential to support campaigns to encourage COVID-19 vaccination. Data continue to suggest the importance of dialogue with Black communities about COVID-19 vaccination.
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    Trust in science boosts approval, but not following of COVID-19 rules
    (2021-03) Sulik, Justin; Deroy, Ophelia; Dezecache, Guillaume; Newson, Martha; Zhao, Yi; El Zein, Marwa; Tunçgenç, Bahar; Biostatistics, School of Public Health
    How essential is trust in science to prevent the spread of COVID-19? Previous work shows that people who trust in science are more likely to comply with official guidelines, which suggests that higher levels of compliance could be achieved by improving trust in science. However, analysis of a global dataset (n=4341) suggests otherwise. Trust in science had a small, indirect effect on adherence to the rules. It affected adherence only insofar as it predicted people's approval of prevention measures such as social distancing. Trust in science also mediated the relationship between political ideology and approval of the measures (more conservative people trusted science less and in turn approved of the measures less). These effects varied across countries, and were especially different in the USA. Overall, these results mean that any increase in trust in science is unlikely to yield strong immediate improvements in following COVID-19 rules. Nonetheless, given its relationships with both ideology and individuals' attitudes to the measures, trust in science may be leveraged to yield longer-term and more sustained social benefits.
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    Using infographics to improve trust in science: a randomized pilot test
    (BMC, 2021-05-29) Agley, Jon; Xiao, Yunyu; Thompson, Esi E.; Golzarri-Arroyo, Lilian; School of Social Work
    This study describes the iterative process of selecting an infographic for use in a large, randomized trial related to trust in science, COVID-19 misinformation, and behavioral intentions for non-pharmaceutical prevenive behaviors. Five separate concepts were developed based on underlying subcomponents of ‘trust in science and scientists’ and were turned into infographics by media experts and digital artists. Study participants (n = 100) were recruited from Amazon’s Mechanical Turk and randomized to five different arms. Each arm viewed a different infographic and provided both quantitative (narrative believability scale and trust in science and scientists inventory) and qualitative data to assist the research team in identifying the infographic most likely to be successful in a larger study.