Assessing changes in US public trust in science amid the COVID-19 pandemic
Jon Agley, Jon Agley
Abstract
Objectives: The emergence of the coronavirus disease 2019 (COVID-19) and subsequent pandemic has led to the most substantive large-scale, open, and public social discussion of epidemiology and science in recent history. In the United States (US), extensive debate has ensued as to the risk posed by the disease, whether the health system is prepared to manage a high volume of critical cases, whether any number of public health responses are necessary and appropriate, and the appropriate ways to prevent, manage, and treat the pandemic. I hypothesized that the interplay between scientists, policymakers, and the public in an open forum was associated with increased overall public trust in science and scientists, but that this was moderated by political orientation and/or religious commitment. In the context of a public health emergency, it is important to understand the degree to which science and scientists are trusted to produce information that can provide reassurance and also can explain the details of a highly complex event such as a viral pandemic while providing actionable recommendations.
Study design: The study design was analytic cross-sectional.
Methods: Data were obtained on March 17-18, 2020, from a sample of 242 US-based Amazon Mechanical Turk users. Respondents completed a 49-question survey consisting of key sociodemographic variables, political affiliation, religious commitment, and two iterations of the Trust in Science and Scientist Inventory (one for March 2020, and one for December 2019 using retrospective recall). Changes in mean level of trust and interaction with political affiliation and/or religious commitment were assessed using mixed ANOVA via the general linear model.
Results: On a scale from 1 (low trust) to 5 (high trust), the mean level of trust in science and scientists was static; 3.82 in December 2019 and 3.81 in March 2020. Conservative political orientation and high religious commitment were associated with significantly less overall trust in science; the interaction effect suggested that liberal trust in science decreased slightly from December 2019 to March 2020, whereas conservative trust increased slightly.
Conclusions: Counter to my expectations, the overall level of trust in science remained static after the first several months of COVID-19 in the US, although there is some evidence that political orientation was associated with magnitude and directionality of change in trust. Continued examination of these trends is important for understanding public response to epidemiologic recommendations.
Keywords: 2019-nCoV; COVID-19; Coronavirus; Epidemiology; Trust.
Copyright © 2020 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
References
- Holshue M.L., DeBolt C., Lindquist S. First case of 2019 novel coronavirus in the United States. N Engl J Med. 2020;382:929–936.
- Borges do Nascimento I.J., Marusic A., Cacic N. Novel coronavirus (Covid-19) infection in humans: a scoping review and meta-analysis. Available at: SSRN:
- Dong E., Du H., Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis. 2020 doi: 10.1016/S1473-3099(20)30120-1.
- Ioannidis J.P.A. A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data. 2020. Published March 17.
- Gans J. Flattening the coronavirus curve is not enough. 2020. Published March 16.
- Fauci A.S., Lane C., Redfield R.R. Covid-19 – navigating the uncharted. N Engl J Med. 2020;382:1268–1269.
- Maragakis L.L. 2020. Coronavirus disease 2019 vs. the flu. Published April 24.
- Owens B. Excitement around hydroxychloroquine for treating COVID-19 causes challenges for rheumatology. Lancet Rheumatol. 2020 doi: 10.1016/S2665-9913(20)30089-8.
- Goldstein D., Wiedemann J. Who do you trust? The consequences of partisanship and trust in government for public responsiveness to COVID-19. April 19, 2020. Available at: SSRN:
- Llewellyn S. Covid-19: how to be careful with trust and expertise on social media. BMJ. 2020;368:m1160.
- Chiolero A. Covid-19: a digital epidemic. BMJ. 2020;368:m764.
- Nadelson L., Jorcyk C., Yang D. I just don't trust them: the development and validation of an assessment instrument to measure trust in science and scientists. Sch Sci Math. 2014;114(2):76–86.
- Larson H.J. Vaccine trust and the limits of information. Science. 2016;353(6305):1207–1208.
- Steup M., Neta R. Epistemology. In: Zalta E.N., editor. The Stanford Encyclopedia of Philosophy. 2020. (Summer 2020 Edition). Forthcoming:
- Jones D.S. History in a crisis – lessons for Covid-19. N Engl J Med. 2020 doi: 10.1056/NEJMp2004361.
- Little T.D., Chang R., Gorrall B.K. The retrospective pretest-posttest design redux: on its validity as an alternative to traditional pretest-posttest measurement. Int J Behav Dev. 2020;44(2):175–183.
- Mellis A.M., Bickel W.K. Mechanical Turk data collection in addiction research: utility, concerns and best practices. Addiction. 2020 doi: 10.1111/add.15032.
- Gadarian S.K., Goodman S.W., Pepinsky T.B. Partisanship, health behavior, and policy attitudes in the early stages of the COVID-19 pandemic. March 27, 2020. Available at: SSRN:
Source: PubMed