Abstract
Disinformation–false information intended to cause harm or for profit–is pervasive. While disinformation exists in several domains, one area with great potential for personal harm from disinformation is healthcare. The amount of disinformation about health issues on social media has grown dramatically over the past several years, particularly in response to the COVID-19 pandemic. The study described in this paper sought to determine the characteristics of multimedia social network posts that lead them to believe and potentially act on healthcare disinformation. The study was conducted in a neuroscience laboratory in early 2022. Twenty-six study participants each viewed a series of 20 either honest or dishonest social media posts, dealing with various aspects of healthcare. They were asked to determine if the posts were true or false and then to provide the reasoning behind their choices. Participant gaze was captured through eye tracking technology and investigated through “area of interest” analysis. This approach has the potential to discover the elements of disinformation that help convince the viewer a given post is true. Participants detected the true nature of the posts they were exposed to 69% of the time. Overall, the source of the post, whether its claims seemed reasonable, and the look and feel of the post were the most important reasons they cited for determining whether it was true or false. Based on the eye tracking data collected, the factors most associated with successfully detecting disinformation were the total number of fixations on key words and the total number of revisits to source information. The findings suggest the outlines of generalizations about why people believe online disinformation, suggesting a basis for the development of mid-range theory.
Key Questions
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What is the impact of healthcare disinformation on social media?
Healthcare disinformation can cause significant personal harm, as shown by its dramatic increase during the COVID-19 pandemic.
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What factors influence people to believe healthcare disinformation?
Key factors include the source of the post, the reasonableness of its claims, and the look and feel of the content.
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How well can people detect disinformation in healthcare-related posts?
Participants identified the true nature of posts with 69% accuracy in the study.
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What role does eye-tracking technology play in understanding disinformation?
Eye-tracking data revealed that fixations on key words and revisits to source information were crucial for detecting disinformation.
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How can these findings inform strategies to counter healthcare disinformation?
Insights from the study suggest potential generalizations for understanding why people believe disinformation, aiding in the development of educational and preventative strategies.
