The Link between the Great Depression and Vaccine Misinformation | Today’s MedPage

Researchers have found that depressive symptoms are associated with a higher likelihood of believing in false information about the COVID vaccine.

Based on a low-probability weighted internet survey, the presence of depression is associated with a high likelihood of supporting false information about the vaccine, reports Dr. Roy Perlis of the Massachusetts General Hospital in Boston. did.And colleagues, write JAMA network open..

The group said previous surveys covered the reasons for the spread of false information, but “there are less simple demographics and cross-party personal characteristics associated with increased sensitivity to false information. Not understood. “

Researchers hypothesized that negative biases could play a role, “general biases against negative biases in information selection, processing, and recall exacerbate misinformation exposure. It may cause you to do it. ” The Perlis team pointed out that both anger and anxiety are associated with “promoting beliefs about certain types of false stories.”

The author “wrong such symptoms” because one-quarter of adults “consistently support moderate or higher depressive symptoms” and depressive symptoms can contribute to negative bias. We set out to find out if there is a greater receptivity to information and a potential deeper link to health. Related actions. “

Researchers analyzed data from two waves of non-probability internet surveys in 50 states. COVID State Project.. The team said, “Participants are unaware that they have completed a COVID-19-focused survey. […] To limit selection bias “

The authors measured incorrect information about the vaccine by asking if it was a COVID-19 vaccine.

• Includes a microchip that can track people

• Includes aborted fetal lung tissue

• May cause infertility and make pregnancy difficult

Participants replied whether the statement was “correct, inaccurate,” or “not sure.” At the end of the investigation, the Perlis team said participants were informed of which items were incorrect in order to prevent the spread of false information about the vaccine.

Participants have also completed 9 questions about patient health (PHQ-9) Measures the symptoms of major depression over the past 2 weeks. A score of 10 or higher represents “at least moderate depression,” as the author stated that it was used as a threshold for treatment in a primary care environment.

Participants were also asked which news sources they used as sources of COVID information in the last 24 hours and about their use of social media platforms.

Overall, the April and May 2021 surveys had 15,464 respondents, with an average age of about 48 years. About 64% were female and 77% were white. Approximately 27% showed moderate or greater depressive symptoms, and approximately 20% approved at least one of the false statements of vaccine information to be accurate.

A reweighted analysis found that 29% of people with moderate or higher depressive symptoms “approved” incorrect information about the vaccine, compared to 15% of those without depressive symptoms.

Not surprisingly, respondents who supported false alarms were less likely to be vaccinated (aOR 0.45, 95% CI 0.40-0.51) and less likely to have vaccinated families. (AOR 0.55, 95% CI 0.49-0.62). The authors stated that among unvaccinated people, those who supported the false information were more than twice as likely to “report vaccine resistance” (aOR 2.68, 95% CI 2.89-3.13). ).

The Perlis team also surveyed a cohort of 2,809 people who responded to subsequent June and July surveys. They averaged 51 years old, two-thirds female and 81% white. Of these, 18% were at least moderately depressed, and 13% supported at least one false statement of information.

In the course of the two studies, if an individual showed symptoms of depression in the first study in April and May, it could support more vaccine misinformation in June and July than in the first study. High (aOR 1.72, 95% CI 1.11-2.67), the author wrote.

The main limitation of the data is its cross-cutting nature, and the Perlis group pointed out that this cannot prove a causal relationship. They also cited potential confounding factors such as the use of social media that contribute to depressive symptoms, and said that social media is also likely to contribute to false information.

“Although inevitably relevant, our results are to directly test causality in future experiments, for example by manipulating negative bias and measuring receptivity to false information. It suggests more broadly the importance, “the team concluded.