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Social Science

Discovering why people believe disinformation about healthcare

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Joey F. George

Joey F. George


  Peer Reviewed

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© attribution CC-BY

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rating
588 Views

Added on

2024-10-19

Doi: http://dx.doi.org/10.1371/journal.pone.0300497

Related Subjects
Law
Politics
Economics
Geography
Education
Sociology

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

1. What was the primary objective of the study?

The study aimed to identify the characteristics of multimedia social network posts that lead individuals to believe and potentially act on healthcare disinformation.

2. How was the study conducted?

Twenty-six participants viewed a series of 20 social media posts, each either honest or dishonest, related to various healthcare topics. They were asked to determine the veracity of the posts and provide reasoning for their choices. Eye-tracking technology was used to capture participants' gaze patterns, focusing on "area of interest" analysis.

3. What were the main findings regarding participants' ability to detect disinformation?

Participants correctly identified the true nature of the posts 69% of the time.

4. What factors influenced participants' judgments about the posts?

The source of the post, the reasonableness of its claims, and the overall appearance of the post were the most cited reasons for determining its truthfulness.

5. How did eye-tracking data contribute to understanding participants' detection of disinformation?

The study found that the total number of fixations on key words and the total number of revisits to source information were most associated with successfully detecting disinformation.

Summary

George's study explores the factors that influence individuals' susceptibility to healthcare disinformation on social media. By analyzing participants' gaze patterns and reasoning, the research identifies key elements that contribute to the belief in and potential action on disinformation. The findings suggest that the source credibility, plausibility of claims, and the visual appeal of posts play significant roles in shaping individuals' judgments about healthcare information. Additionally, eye-tracking data indicates that focusing on key words and revisiting source information are associated with better detection of disinformation. These insights are valuable for developing strategies to combat the spread of healthcare disinformation on social media platforms.

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ARTICLE USAGE


Article usage: Oct-2024 to May-2025
Show by month Manuscript Video Summary
2025 May 115 115
2025 April 65 65
2025 March 70 70
2025 February 66 66
2025 January 148 148
2024 December 48 48
2024 November 53 53
2024 October 23 23
Total 588 588
Show by month Manuscript Video Summary
2025 May 115 115
2025 April 65 65
2025 March 70 70
2025 February 66 66
2025 January 148 148
2024 December 48 48
2024 November 53 53
2024 October 23 23
Total 588 588
Related Subjects
Law
Politics
Economics
Geography
Education
Sociology
copyright icon

© attribution CC-BY

  • 0

rating
588 Views

Added on

2024-10-19

Doi: http://dx.doi.org/10.1371/journal.pone.0300497

Related Subjects
Law
Politics
Economics
Geography
Education
Sociology

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