Online misinformation regarding COVID-19 has undermined public health efforts to control the novel coronavirus. To date, public health organizations’ efforts to counter COVID-19 misinformation have focused on identifying and correcting false information on social media platforms. Citing extant literature in health communication and psychology, we argue that these fact-checking efforts are a necessary, but insufficient, response to health misinformation. First, research suggests that fact-checking has several important limitations and is rarely successful in fully undoing the effects of misinformation exposure. Second, there are many factors driving misinformation sharing and acceptance in the context of the COVID-19 pandemic—such as emotions, distrust, cognitive biases, racism, and xenophobia—and these factors both make individuals more vulnerable to certain types of misinformation and also make them impervious to future correction attempts. We conclude by outlining several additional measures, beyond fact-checking, that may help further mitigate the effects of misinformation in the current pandemic.

Background: Health misinformation on social media can negatively affect knowledge, attitudes, and behaviors, undermining clinical care and public health efforts. Therefore, it is vital to better understand the public’s experience with health misinformation on social media. Objective: The goal of this analysis was to examine perceptions of the social media information environment and identify associations between health misinformation perceptions and health communication behaviors among US adults. Methods: Analyses used data from the 2022 Health Information National Trends Survey (N=6252). Weighted unadjusted proportions described respondents’ perceptions of the amount of false or misleading health information on social media (“perceived misinformation amount”) and how difficult it is to discern true from false information on social media (“perceived discernment difficulty”). Weighted multivariable logistic regressions examined (1) associations of sociodemographic characteristics and subjective literacy measures with misinformation perceptions and (2) relationships between misinformation perceptions and health communication behaviors (ie, sharing personal or general health information on social media and using social media information in health decisions or in discussions with health care providers). Results: Over one-third of social media users (35.61%) perceived high levels of health misinformation, and approximately two-thirds (66.56%) reported high perceived discernment difficulty. Odds of perceiving high amounts of misinformation were lower among non-Hispanic Black/African American (adjusted odds ratio [aOR] 0.407, 95% CI 0.282-0.587) and Hispanic (aOR 0.610, 95% CI 0.449-0.831) individuals compared to White individuals. Those with lower subjective health literacy were less likely to report high perceived misinformation amount (aOR 0.602, 95% CI 0.374-0.970), whereas those with lower subjective digital literacy were more likely to report high perceived misinformation amount (aOR 1.775, 95% CI 1.400-2.251). Compared to White individuals, Hispanic individuals had lower odds of reporting high discernment difficulty (aOR 0.620, 95% CI 0.462-0.831). Those with lower subjective digital literacy (aOR 1.873, 95% CI 1.478-2.374) or numeracy (aOR 1.465, 95% CI 1.047-2.049) were more likely to report high discernment difficulty. High perceived misinformation amount was associated with lower odds of sharing general health information on social media (aOR 0.742, 95% CI 0.568-0.968), using social media information to make health decisions (aOR 0.273, 95% CI 0.156-0.479), and using social media information in discussions with health care providers (aOR 0.460, 95% CI 0.323-0.655). High perceived discernment difficulty was associated with higher odds of using social media information in health decisions (aOR 1.724, 95% CI 1.208-2.460) and health care provider discussions (aOR 1.389, 95% CI 1.035-1.864). Conclusions: Perceptions of high health misinformation prevalence and discernment difficulty are widespread among social media users, and each has unique associations with sociodemographic characteristics, literacy, and health communication behaviors. These insights can help inform future health communication interventions.

Background: Sharing data from wearable health and activity trackers (wearables) with others may improve the health and behavioral outcomes of wearable users by generating social support and improving their ability to manage their health. Investigating individual factors that influence US adults’ willingness to share wearable data with different types of individuals may provide insights about the population subgroups that are most or least likely to benefit from wearable interventions. Specifically, it is necessary to identify digital health behaviors potentially associated with willingness to share wearable data given that the use of and engagement with various technologies may broadly influence web-based health information–sharing behaviors. Objective: This study aims to identify sociodemographic, health, and digital health behavior correlates of US adults’ willingness to share wearable data with health care providers and family or friends. Methods: Data for the analytic sample (N=1300) were obtained from the 2019 Health Information National Trends Survey of the National Cancer Institute. Digital health behavior measures included frequency of wearable device use, use of smartphones or tablets to help communicate with providers, use of social networking sites to share health information, and participation in a web-based health community. Multivariable logistic regression analysis of weighted data examined the associations between digital health behaviors and willingness to share wearable device data, controlling for sociodemographics and health-related characteristics. Results: Most US adults reported willingness to share wearable data with providers (81.86%) and with family or friends (69.51%). Those who reported higher health self-efficacy (odds ratio [OR] 1.97, 95% CI 1.11-3.51), higher level of trust in providers as a source of health information (OR 1.98, 95% CI 1.12-3.49), and higher level of physical activity (OR 2.00, 95% CI 1.21-3.31) had greater odds of willingness to share data with providers. In addition, those with a higher frequency of wearable use (OR 2.15, 95% CI 1.35-3.43) and those who reported use of smartphones or tablets to help communicate with providers (OR 1.99, 95% CI 1.09-3.63) had greater odds of willingness to share data with providers. Only higher level of physical activity was associated with greater odds of willingness to share wearable data with family or friends (OR 1.70, 95% CI 1.02-2.84). Sociodemographic factors were not significantly associated with willingness to share wearable data. Conclusions: The findings of this study suggest that, among US adult wearable users, behavior-related factors, rather than sociodemographic characteristics, are key drivers of willingness to share health information obtained from wearables with others. Moreover, behavioral correlates of willingness to share wearable data are unique to the type of recipient (ie, providers vs family or friends). Future studies could use these findings to inform the development of interventions that aim to improve the use of patient-generated data from wearable devices in health care settings.

Research shows that health misinformation is widespread online and poses a potentially significant threat to public health. Visual misinformation has been largely overlooked, a notable gap given the unique features and ubiquity of visual content. In this essay, we (a) provide a working definition of visual misinformation, (b) summarize the main categories of visual misinformation, (c) offer examples of the functions visuals can serve within misinformation content, and (d) outline priorities for advancing research on visual misinformation. A systematic approach to studying visual misinformation can improve efforts to mitigate health misinformation and optimize science communication in the current information environment.

American Journal of Public Health (AJPH) from the American Public Health Association (APHA) Racism and Xenophobia in a Pandemic: Interactions of Online and Offline Worlds, an article from American Journal of Public Health, Vol 111 Issue 5