About

Briony Swire-Thompson is a cognitive psychologist and assistant professor at Northeastern University, where she directs the Psychology of Misinformation Lab. Her research investigates what drives belief in inaccurate information, why people refrain from belief change in the face of good corrective evidence, and how corrections can be designed to maximize impact. She is affiliated with the Northeastern University's Political Science Department and the Network Science Institute. Prior to joining Northeastern, she was at the University of Western Australia’s Cognitive Science Laboratories and was a Fulbright scholar at the Massachusetts Institute of Technology. She is currently funded by the National Cancer Institute to study cancer misinformation.

Selected publications

• Corrections outperform expertise‐based interventions for countering misinformation from alternative medicine sources

  Applied Psychology Health and Well-Being · 2026-04-01

  articleSenior author

  Given that health-based misinformation can cause serious harm, designing effective interventions is paramount. Recently, misinformation interventions that target a source's relevant expertise have shown promise, with findings suggesting they may provide a comparative advantage to corrections for countering misinformation spread by disinformation health sources. However, whether such a benefit extends to other sources of health misinformation, such as alternative medicine practitioners, remains to be empirically assessed. Across two preregistered experiments (N = 1,410) participants were exposed to cancer misinformation attributed to an alternative medicine source (e.g., a homeopath), before receiving either a no-intervention control, a correction intervention, a generic low expertise intervention (Experiment 1), or a targeted low expertise intervention, which either did or did not reveal that the source was deceitful (Experiment 2). All interventions reduced belief in misinformation and perceptions of source credibility relative to the control condition. However, across both studies presenting corrections was equivalent to, or more effective than, all low expertise conditions, even when the expertise-based intervention revealed that the source had deceptively misrepresented their credentials. This suggests that correcting false claims is more effective than highlighting an alternative medicine practitioner's lack of expertise, emphasizing the need to tailor interventions to the misinformation source.

  PublisherDOI

• Countering AI-generated misinformation with pre-emptive source discreditation and debunking

  Royal Society Open Science · 2025-06-01 · 10 citations

  articleOpen access

  Despite widespread concerns over AI-generated misinformation, its impact on people’s reasoning and the effectiveness of countermeasures remain unclear. This study examined whether a pre-emptive, source-focused inoculation—designed to lower trust in AI-generated information—could reduce its influence on reasoning. This approach was compared with a retroactive, content-focused debunking, as well as a simple disclaimer that AI-generated information may be misleading, as often seen on real-world platforms. Additionally, the extent to which trust in AI-generated information is malleable was also tested with an intervention designed to boost trust. Across two experiments (total N = 1223), a misleading AI-generated article influenced reasoning regardless of its alleged source (human or AI). In both experiments, the inoculation reduced general trust in AI-generated information, but did not significantly reduce the misleading article’s specific influence on reasoning. The additional trust-boosting and disclaimer interventions used in Experiment 1 also had no impact. By contrast, debunking of misinformation in Experiment 2 effectively reduced its impact, although only a combination of inoculation and debunking eliminated misinformation influence entirely. Findings demonstrate that generative AI can be a persuasive source of misinformation, potentially requiring multiple countermeasures to negate its effects.

  PublisherDOI

• Development and validation of the Misinformation Susceptibility Self-Report (MiSS)

  2025-07-11

  preprintOpen accessSenior author

  The ability to discern between true and false information is a skill that varies between individuals. As such, an accurate measure of self-reported individual susceptibility to misinformation is crucial for both research and intervention development. While discernment-based instruments currently exist, there is a lack of effective and generalizable tools with good psychometric properties that capture the factors which drive susceptibility. To address this, we developed and validated the 15-item Misinformation Susceptibility Self-Report (MiSS) using a political headline discernment task. The MiSS was found to display good internal consistency as well as strong predictive validity (r = 0.52–.64) as measured using the Misinformation Susceptibility Test (MIST-20; Maertens et al., 2024), and a political and health claim discernment task. An assessment of the factor structure and test information characteristics also revealed the ability of the MiSS to provide unique insights into attitudes and behaviors underlying susceptibility across levels of misinformation discernment ability. Being the first psychometrically validated self-report scale for assessing individual differences in misinformation susceptibility, the MiSS presents a number of novel opportunities for advancing theoretical understanding, and has the potential to become an invaluable tool for the development of targeted misinformation interventions.

  PublisherOA PDFDOI

• Specific Media Literacy Tips Improve AI-generated Visual Misinformation Discernment

  2025-02-15

  preprintOpen access

  Images generated using artificial intelligence (AI) have become increasingly realistic, sparking discussions and fears about an impending “infodemic” where we can no longer trust what we see on the internet. In this preregistered study, we examine whether providing specific media literacy tips about how to spot AI-generated images can reduce susceptibility to AI-generated visual misinformation (AIVM). Participants were randomly assigned to one of three conditions, reading specific media literacy tips, general media literacy tips, or no media literacy tips (control). The general tips provided tips on how to spot misinformation, while the specific tips provided more detailed tips for how to detect AIVM. Results showed that specific tips increased headline discernment between true and false information more than general tips. Both media literacy interventions reduced belief in AIVM compared to control, but specific tips reduced belief in AIVM more than general tips. Finally, both specific and general tips also reduced belief in real headlines compared to control, with no difference between them. In an information environment that sees increasing prevalence of AIVM, it may be worth being specific about how to detect misinformation online rather than only providing general information.

  PublisherDOI

• Assessing Cancer Patients’ Exposure to Treatment Misinformation

  Journal of Cancer Education · 2025-09-06

  article
  PublisherDOI

• Using psychological science to understand and fight health misinformation: An APA consensus statement.

  American Psychologist · 2025-10-20 · 26 citations

  articleOpen access

  There is widespread concern that misinformation poses dangerous risks to health, well-being, and civic life. Despite a growing body of research on the topic, significant questions remain about the psychological factors that render people susceptible to misinformation, the extent to which it affects real-world behavior, how it spreads online and offline, and intervention strategies that counter and correct misinformation effectively. This report reviews the best available psychological science research to reach consensus on each of these crucial questions, particularly as they pertain to health-related misinformation. In addition, the report offers eight specific recommendations for scientists, policymakers, and health professionals who seek to recognize and respond to misinformation in healthcare and beyond. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

  PublisherDOI

• Corrections are Effective for Science Misinformation

  2025-06-27

  preprintOpen accessSenior author

  In their impactful pre-registered meta-analysis, Chan and Albarracín aimed to determine the degree to which the public updates science-relevant misinformation following a correction (e.g., p.1514, paragraph 3). Based on an impressive 74 studies and 205 effect sizes, the authors concluded that “attempts to debunk science-relevant misinformation were, on average, not successful (d=0.19, P=0.131, 95% CI −0.06 to 0.43)”; p.1514), with the effect of corrections “smaller than those identified in all other areas” (p.15171; e.g., politics and health). In this commentary we show that the reported null effect was due to the inappropriate pooling of two distinct effect types into a single estimate. This clarification is necessary because meta-analyses are often perceived as the ‘gold standard’ of evidence, and numerous papers have cited Chan and Albarracín1 as evidence that corrections have little-to-no effect on science-relevant misinformation (35% by our estimates; see Supplementary Table 1).

  PublisherOA PDFDOI

• The truth sandwich format does not enhance the correction of misinformation

  2025-03-14

  preprintOpen access1st authorCorresponding

  The “truth sandwich” correction format, in which false information is bookended by factual information, has frequently been presented as an optimal method for correcting misinformation. Despite recurring recommendations, there is little empirical evidence for enhanced benefits. In two pre-registered experiments (total N = 1046), we evaluated the effectiveness of the truth sandwich correction format against a “bottom-loaded” refutation format, in which the misinformation is first presented prior to factual statements. In Experiment 1, participants first rated belief in cancer misinformation. The misinformation was then corrected using the truth sandwich, corrected using a bottom-loaded refutation, or left uncorrected (control). Participants subsequently rerated their belief in the claims. Experiment 2 replicated and extended Experiment 1 by including a two-week test delay. We found that both correction formats were highly effective. However, there was no evidence that the truth sandwich format enhanced the effectiveness of corrections either immediately after reading or after a two-week delay period, with Bayesian analyses providing consistent evidence for a null effect of correction format. We repeated our analyses isolated to participants who endorsed complementary and alternative medicines, given this subgroup is particularly likely to believe cancer misinformation. We again found no evidence for any superiority of the truth sandwich correction format. These findings suggest that clear and detailed corrections can be powerfully effective against misinformation regardless of format, and advocacy for the truth sandwich correction above other simpler formats are unwarranted.

  PublisherOA PDFDOI

• Corrections are effective for science misinformation

  Nature Human Behaviour · 2025-10-06 · 2 citations

  articleSenior author
  PublisherDOI

• Corrections are Effective for Science Misinformation

  2025-07-17

  preprintOpen accessSenior author

  In their impactful pre-registered meta-analysis, Chan and Albarracín aimed to determine the degree to which the public updates science-relevant misinformation following a correction (e.g., p.1514, paragraph 3). Based on an impressive 74 studies and 205 effect sizes, the authors concluded that “attempts to debunk science-relevant misinformation were, on average, not successful (d=0.19, P=0.131, 95% CI −0.06 to 0.43)”; p.1514), with the effect of corrections “smaller than those identified in all other areas” (p.15171; e.g., politics and health). In this commentary we show that the reported null effect was due to the inappropriate pooling of two distinct effect types into a single estimate. This clarification is necessary because meta-analyses are often perceived as the ‘gold standard’ of evidence, and numerous papers have cited Chan and Albarracín1 as evidence that corrections have little-to-no effect on science-relevant misinformation (35% by our estimates; see Supplementary Table 1).

  PublisherDOI