Evaluating the Impact of Attempts to Correct Health Misinformation on Social Media: A Meta-Analysis

By Nathan Walter, John J. Brooks, Camille J. Saucier, Sapna Suresh. Health Communication, 2020

295 citations recorded by the source corpus.

ABSTRACT Social media poses a threat to public health by facilitating the spread of misinformation. At the same time, however, social media offers a promising avenue to stem the distribution of false claims – as evidenced by real-time corrections, crowdsourced fact-checking, and algorithmic tagging. Despite the growing attempts to correct misinformation on social media, there is still considerable ambiguity regarding the ability to effectively ameliorate the negative impact of false messages. To address this gap, the current study uses a meta-analysis to evaluate the relative impact of social media interventions designed to correct health-related misinformation (k = 24; N = 6,086). Additionally, the meta-analysis introduces theory-driven moderators that help delineate the effectiveness of social media interventions. The mean effect size of attempts to correct misinformation on social media was positive and significant (d = 0.40, 95% CI [0.25, 0.55], p =.0005) and a publication bias could not be excluded. Interventions were more effective in cases where participants were involved with the health topic, as well as when misinformation was distributed by news organizations (vs. peers) and debunked by experts (vs. non-experts). The findings of this meta-analysis can be used not only to depict the current state of the literature but also to prescribe specific recommendations to better address the proliferation of health misinformation on social media.

Subfields: General Health Professions, Health, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/5b90a36f19b9d8ae6321acb87fce02acfcc72a4d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Health Professions

1. Emily K. Vraga
2. Leticia Bode

In Health

1. Emily K. Vraga
2. Leticia Bode

In Sociology and Political Science

1. Emily K. Vraga
2. Leticia Bode
3. Elmie Nekmat

Citations in the corpus

• Correction Experiences on Social Media During COVID-19 (2021, methodology): “…Nyhan et al., 2014; Nyhan & Reifler, 2010), meta-analyses of this type of responsive correction have demonstrated that it is consistent if modestly effective (Walter & Murphy, 2018), including specifically in the domain of correction of health misinformation on social media (Walter et al., 2020).”