Demographic Predictors of Misperceptions Regarding COVID-19 across USA, Canada, and the UK Richard J Klares
1 III ,
Madellena
1Donald
1 Conte ,
Tanzim
1 Bhuiya and
and Barbara Zucker School of Medicine at Hofstra/Northwell
Background
Hypothesis We hypothesized that individuals who are relatively poor or lack a college degree in the USA will have greater misperceptions regarding COVID-19 when compared to higher income or college degree holding individuals within the USA. Furthermore, we believe this difference will hold true when comparing these individuals to lower income and college degree lacking counterparts in Canada and the United Kingdom.
Results Predictors of Misperception Regarding COVID-19 by Country, Education, and Income
Education Demographics
65.75% College Degree 34.25% No College Degree
Predictor Variable
On March 11th COVID-19 was declared a pandemic by the World Health Organization (WHO) and by April 4th there were over 1 million cases of COVID-19 worldwide. Government interventions in a pandemic play a crucial role in controlling the spread of disease.1 However, there is a disconnect between policy and public actions, as seen by lack of adherence. This can be attributed to the public’s misperceptions, overall risk perceptions, and personal risk perceptions. Previous work has explored the role of political ideology and cognitive sophistication in explaining attitudes and misperceptions about COVID, however, there is a gap in our understanding of other influential factors.2,3 In this substudy we report on the roles of education and income in predicting misperceptions regarding COVID-19 among residents in the US, Canada, and UK.
Joseph Cervia,
1 MD
**
Highest Income Quartile
**
Second Highest Income Quartile
Country Demographics
Third Highest Income Quartile
32.61% Canada 34.89% USA 32.51% UK
UK Canada
Income Demographics
**
College Degree 0.0
0.5
1.0
1.5
20.71% 20.05% 42.84% 16.40%
Highest Quartile Second Highest Quartile Third Highest Quartile Lowest Quartile
Odds Ratio Income quartiles defined as follows: Highest Quartile (>$90,000), Second Highest Quartile ($60,000-$89,000), Third Highest Quartile ($30,000-59,999), and Lowest Quartile (<$29,999). Reference income for analysis is the Lowest Quartile. Reference country is USA. Reference for College Degree is No College Degree. * = p<0.05; ** = p<0.01; # = p<0.001
Methods
Discussion
Future Directions
The data set used in this study was supplied by Pennycook et al.4 Data was extracted from three pre-registered surveys conducted by the polling firm Prolific. Parallel quota sampling was conducted for residents from the U.S.A (N=689) and the U.K (N=642). Convenience sampling was conducted for residents from Canada (N=644). Three key outcome variables were analyzed this study: 1) Misperceptions about COVID-19, 2) Risk perceptions about COVID-19, and 3) Personal risk perceptions about COVID19. Binary logistic regressions were conducted in order to investigate the roles country of residence, education and household income had on the outcome variables.
Individuals in the highest quartile and second highest quartile of income were less likely to hold misperceptions regarding COVID-19 than individuals in the lowest quartile of income (OR=0.61 (0.45-0.83) and OR=0.66 (0.49-0.88), respectively). Furthermore, individuals with a college degree held fewer misperceptions than those without a college degree (OR=0.74 (0.610.91)).
Insight into what factors can accurately predict the public’s level of risk perception, misperception of falsehoods, and personal risk perception is quintessential for ensuring adherence to future public health policies so as to minimize spread of disease in our current and future pandemics.
Conclusion
Resources
Our analysis suggests that individuals with less income or education have difficulty differentiating between falsehoods and reality regarding COVID-19. This puts the impetus on the scientific community to make statements regarding COVID-19 more readily accessible, not just in terms of which platform, but also in terms of language and presentation style.
1. Coronavirus Disease (COVID-19) - events as they happen. (n.d.). Retrieved October 12, 2020, from https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen 2. Duan, T., Jiang, H., Deng, X., Zhang, Q., & Wang, F. (2020). Government intervention, risk perception, and the adoption of protective action recommendations: Evidence from the COVID-19 prevention and control experience of China. International Journal of Environmental Research and Public Health, 17(10), 3387. 3. Jones, C. L., Jensen, J. D., Scherr, C. L., Brown, N. R., Christy, K., & Weaver, J. (2015). The health belief model as an explanatory framework in communication research: exploring parallel, serial, and moderated mediation. Health communication, 30(6), 566-576. 4. Gordon Pennycook Jonathon McPhetres Bence Bago David Rand. (n.d.). Predictors of attitudes and misperceptions about COVID-19 in Canada, the U.K., and the U.S.A. https://doi.org/10.31234/osf.io/zhjkp