COVID-19 Misinformation in Portuguese-Speaking Countries: Agreement with Content and Associated Factors

Abstract

In the wake of the COVID-19 pandemic, a complex phenomenon called the “infodemic” has emerged, compromising coping with the pandemic. This study aims to estimate the prevalence of agreement with misinformation about COVID-19 and to identify associated factors. A web survey was carried out in Portuguese-speaking countries in two stages: 1. the identification of misinformation circulating in the included countries; 2. a multicentric online survey with residents of the included countries. The outcome of the study was agreement or disagreement with misinformation about COVID-19. Multivariate analyzes were conducted using the Poisson regression model with robust variance, a logarithmic link function, and 95% confidence intervals. The prevalence of agreement with misinformation about COVID-19 was 63.9%. The following factors increased the prevalence of this outcome: having a religious affiliation (aPR: 1454, 95% CI: 1393–1517), having restrictions on leisure (aPR: 1230, 95% CI: 1127–1342), practicing social isolation (aPR: 1073, 95% CI: 1030–1118), not avoiding agglomeration (aPR: 1060, 95% CI: 1005–1117), not seeking/receiving news from scientific sources (aPR: 1153, 95% CI: 1068–1245), seeking/receiving news from three or more non-scientific sources (aPR: 1114, 95% CI: 1049–1182), and giving credibility to news carried by people from social networks (aPR: 1175, 95% CI: 1104–1251). There was a high prevalence of agreement with misinformation about COVID-19. The quality, similarity, uniformity, and acceptance of the contents indicate a concentration of themes that reflect “homemade”, simple, and easy methods to avoid infection by SARS-CoV-2, compromising decision-making and ability to cope with the disease.

Misinformation about COVID-19 among middle-aged and older migrants residing in Brazil and Portugal

“…The snowball method was adapted for online recruitment ( 15 ) , where participants took on the responsibility of recruiting others from the same category through their social networks. To ensure sample variability and meet methodological requirements, we randomly selected 30 individuals from Portugal and Brazil based on a database of previous studies ( 3 , 16 ) . These individuals formed the initial “seeds” of our sample and were intentionally diversified according to key factors such as geographical location within each country’s regions, native or migrant origin, race/ethnicity (white and non-white), age group (50-60 years, 61 or older), and educational level (elementary/middle school, high school, and postgraduate).…”

“…To achieve this, responses of “agree” and “strongly agree” were grouped together as “agreement” (3). Secondary variables included participants’ social and demographic characteristics, familiarity with COVID-19 (based on testing and knowing individuals who died from the virus), consumption of COVID-19-related content (information sources), decision-making based on content, and willingness to vaccinate ( 3 , 16 ) .…”

“…Category 2 – An online population survey was conducted among individuals originating from the seven Portuguese-speaking countries (Brazil, Portugal, Angola, Cape Verde, Guinea-Bissau, Mozambique, São Tomé and Príncipe) but residing in Brazil or Portugal for more than three months. The objective of this phase was to assess agreement with the content published on the studied social media platforms, as selected in Phase 1 ( 3 , 16 ) .…”

“…Various forms of half-truths and misinformation, including conspiracy theories, false testimonies, and the endorsement of pseudoscientific remedies for COVID-19, quickly gained traction and spread virally, amplified by the prevalence of social media ( 1 , 2 ) . Consequently, this has significantly impacted the response to the pandemic by affected populations ( 3 ) .…”

Detecting and Mitigating the Dissemination of Fake News: Challenges and Future Research Opportunities

“…There have been numerous attempts to alter the religious content [96; 97; 98; 99] and spread the fake information [100] by sharing tampered verses through different media outlets. Hence, detecting the fake religious content which can be in different languages such as Arabic [101], Portuguese [102], Persian, Chinese etc, is one of the future research direction that needs to be addressed.…”