Predictors of misperceptions, risk perceptions, and personal risk perceptions about COVID-19 by country, education and income

Abstract

Government interventions, such as mandating the use of masks and social distancing, play crucial roles in controlling the spread of pandemic infection. Adherence depends on public perceptions about pandemic risk. The goal was to explore the roles of education, income, and country on misperceptions, risk perceptions and personal risk perceptions about COVID-19. Data were extracted from 3 preregistered surveys. Binary logistic regressions were conducted to investigate the roles country, education, and income had on outcome variables. Across the USA, Canada, and UK, individuals in the highest income quartile were significantly less likely to hold misperceptions (OR=0.61, 95% CI 0.45 to 0.83) and to perceive personal risk (OR=0.38, 95% CI 0.20 to 0.75) regarding COVID-19 compared with individuals in the lowest income quartile. When comparing these income quartiles in the USA, the difference in perceived risk was heightened (OR=0.21, 95% CI 0.07 to 0.57). Citizens of the UK were more likely to have risk perceptions compared with citizens of the USA (OR=1.50, 95% CI 1.20 to 1.88). Citizens of Canada were less likely to perceive personal risk compared with US citizens (OR=0.40, 95% CI 0.23 to 0.69). Proper risk perception and understanding of COVID-19 are necessary for adherence to public health initiatives. The lowest income quartile was shown to have more misperceptions and personal risk perceptions across all 3 countries, highlighting the disproportionate impact of COVID-19 in this group. Our findings support the importance of education and income in affecting health perceptions and outcomes. Further research is needed to explore interventions to minimize misperceptions, accurately shape risk perception, and effectively communicate science.

COVID‐19 contamination through food: A study with Brazilian consumers of different socioeconomic and demographic characteristics

“…The high mention of the category no risk and negative attitudes and feelings can express the lack of scientific information on the part of participants with primary education and secondary school, respectively, due to less experience in medicine and science and greater susceptibility to believe rumors and conflicting information from different media. Bhuiya, Klares III, Conte, and Cervia ( 2021 ) reported that individuals with lower socioeconomic or educational status are more likely to have misperceptions regarding COVID‐19.…”

“…Bhuiya, Klares III, Conte, and Cervia (2021) reported that individuals with lower socioeconomic or educational status are more likely to have misperceptions regarding COVID-19.Participants with the formation in the food field attributed the low risk of spreading the SARS-CoV-2 virus to good hygiene and good handling practices with high mention of categories like no risk, low risk, food security, and food handling. Moreover, they mentioned less negative attitudes and feelings, sanitization, and places of purchase and consumption.…”

Excess Mortality in California by Education During the COVID-19 Pandemic

“…Such groups have used fewer news resources during the COVID-19 pandemic, and may be improperly informed about risk-minimization strategies. [25][26][27][28] Public health messaging regarding COVID-19 may have been difficult to follow. [29][30][31] Low literacy may make individuals vulnerable to conflicting or inconsistent messages.…”

Characteristics associated with optimistic or pessimistic perception about the probability of contracting COVID-19: A cross-sectional study of Japanese older adults

“…We examined various characteristics of the participants measured by the self-reported questionnaires: age; sex; marital status (married and spouse is alive; others); education level (low, ≤ 9 years; middle, 10–12 years; high, ≥ 13 years); living with someone or alone; perceived financial conditions measured by asking, “How do you think about your daily life from a financial viewpoint?” (poor, intermediate, well); engaging in paid work or not; depressive symptoms measured using the 15-item Geriatric Depression Scale (not depressed: ≤4 points, moderately depressed: 5–9 points, severely depressed: ≥10 points) ( Burke et al, 1991 ; Wada, T., Ishine, M., Kita, T., Fujisawa, M., & Matsubayashi, K., 2003 ); Instrumental activities of daily living (IADL) measured using the Tokyo Metropolitan Institute of Gerontology Index of Competence (fully capable: 5 points, less capable: <5 points) ( Koyano et al, 1991 ); self-reported disease diagnoses (stroke, heart diseases, diabetes, respiratory diseases, cancer, and others (hypertension, hyperlipidemia, gastrointestinal diseases, kidney or prostate gland diseases, musculoskeletal diseases, traumatic injury, blood or immune system diseases, depression, dementia, Parkinson’s disease, eye diseases, ear diseases, and other diseases)); providing care measured by asking “Do you look after someone when he/she is sick and confined to a bed for a few days?”; trust in information from media and people that was measured by asking “Which media or people did you refer to the most for taking action during the declaration of a state of emergency?” (TV news programs, TV information programs [an entertaining TV program where celebrities, commentators, or professionals discuss various information], the Internet, government-issued newsletters, family members, friends, and medical staff [multiple answers were allowed]). We selected these covariates, referencing related previous studies ( Bavel et al, 2020 ; Bhuiya et al, 2021 ; Chen et al, 2021 ; Hammad et al, 2021 ).…”