Abstract: One of the most concerning notions for science communicators, fact-checkers, and advocates of truth, is the backfire effect; this is when a correction leads to an individual increasing their belief in the very misconception the correction is aiming to rectify. There is currently a debate in the literature as to whether backfire effects exist at all, as recent studies have failed to find the phenomenon, even under theoretically favorable conditions. In this review, we summarize the current state of the worldview and familiarity backfire effect literatures. We subsequently examine barriers to measuring the backfire phenomenon, discuss approaches to improving measurement and design, and conclude with recommendations for fact-checkers. We suggest that backfire effects are not a robust empirical phenomenon, and more reliable measures, powerful designs, and stronger links between experimental design and theory could greatly help move the field ahead.
Keywords: Backfire effectsBelief updatingMisinformationContinued influence effectReliability
General Audience Summary: A backfire effect is when people report believing even more in misinformation after they have seen an evidence-based correction aiming to rectify it. This review discusses the current state of the backfire literature, examines barriers to measuring this phenomenon, and concludes with recommendations for fact-checkers. Two backfire effects have gained popularity in the literature: the worldview backfire effect and the familiarity backfire effect. While these both result in increased belief after a correction, they occur due to different psychological mechanisms. The worldview backfire effect is said to occur when a person is motivated to defend their worldview because a correction challenges a person's belief system. In contrast, the familiarity backfire effect is presumed to occur when misinformation is repeated within the retraction. Failures to find or replicate both backfire effects have been widespread. Much of the literature has interpreted these failures to replicate to indicate that either (a) the backfire effect is difficult to elicit on the larger group level, (b) it is extremely item-, situation-, or individual-specific, or (c) the phenomenon does not exist at all. We suggest that backfire effects are not a robust empirical phenomenon, and that improved measures, more powerful designs, and stronger links between experimental design and theory, could greatly help move the field ahead. Fact-checkers can rest assured that it is extremely unlikely that their fact-checks will lead to increased belief at the group level. Furthermore, research has failed to show backfire effects systematically in the same subgroup, so practitioners should not avoid giving corrections to any specific subgroup of people. Finally, avoiding the repetition of the original misconception within the correction appears to be unnecessary and could even hinder corrective efforts. However, misinformation should always be clearly and saliently paired with the corrective element, and needless repetitions of the misconceptions should still be avoided.
Practical Recommendations
Regarding the worldview backfire effect, fact-checkers can rest assured that it is extremely unlikely that, at the broader group level, their fact-checks will lead to increased belief in the misinformation. Meta-analyses have clearly shown that corrections are generally effective and backfire effects are not the norm (e.g., Chan, Jones, Hall Jamieson, & Albarracín, 2017; Walter & Murphy, 2018). Furthermore, given that research has yet to systematically show backfire effects in the same subgroups, practitioners should not avoid giving corrections to any specific subgroups of people. Fact-checkers can therefore focus on other known issues such as getting the fact-checks to the individuals who are most likely to be misinformed.
Regarding the familiarity backfire effect, avoiding the repetition of the original misconception within the correction appears to be unnecessary and could even hinder corrective efforts (Ecker et al., 2017, Kendeou and O’Brien, 2014). We therefore instead suggest designing the correction first and foremost with clarity and ease of interpretation in mind. Although the familiarity backfire effect lacks evidence, we must be aware that the illusory truth effect in the absence of corrections or veracity judgments is extremely robust. Therefore, when designing a correction, the misinformation should always be clearly and saliently paired with the corrective element, and needless repetitions of the misconception should still be avoided. For instance, given that many individuals do not read further than headlines (Gabielkov, Ramachandran, Chaintreau, & Legout, 2016), the misconception should not be described in the headline alone with the correction in smaller print in the text below (Ecker, Lewandowsky, Chang, & Pillai, 2014; Ecker, Lewandowsky, Fenton, & Martin, 2014). Adding the corrective element within the headline itself, even if it is simply a salient “myth” tag associated with the misconception, can be considered good practice.
Future Research
Although improvements in both experimental measures and designs are important, Oberauer and Lewandowsky (2019) highlight that another cause of poor replicability is weak logical links between theories and empirical tests. Future research could more explicitly manipulate key factors presumed to influence belief updating, whether it be fluency, perceived item importance, strength of belief, complexity of the item wording, order of corrective elements, internal counter-arguing, source of the message, or participants’ communicating disagreement with the correction. Focusing on theoretically meaningful factors could help to better isolate the potential mechanisms behind backfire effects or the continued influence effect in general. Furthermore, it would be beneficial to be aware of other competing factors to avoid confounds. For example, when investigating the effects of familiarity, one could avoid exclusively using issues presumed to elicit worldview backfire effects (e.g., vaccines, Skurnik et al., 2007). Additionally, given that responses to corrections are likely heterogeneous, it would be beneficial to use a wide variety of issues in experiments that vary on theoretically meaningful criteria to dissociate when backfire effects occur and when they do not.
Future research should also empirically investigate common recommendations that stem from the familiarity backfire effect notion which have yet to be thoroughly examined. For example, it is unclear whether belief updating is fostered by presenting a “truth sandwich” to participants, stating the truth twice with the falsehood between (Sullivan, 2018). Preliminary findings suggest that a “bottom-loaded” correction, which first states the misconception followed by two factual statements, could be more effective than the truth sandwich (Anderson, Horton, & Rapp, 2019), although further research is required prior to firm recommendations being made.
Finally, there are additional occasions where corrections could be counter-productive that require empirical investigation. For instance, correcting facts in public political debate might not always be advisable, because it involves the acceptance of someone else's framing, allowing the person who promulgated the original falsehood to set the agenda (Lakoff, 2010; Lewandowsky, Ecker, & Cook, 2017). Furthermore, broadcasting a correction where few people believe in the misconception could be a legitimate concern, since the correction may spread the misinformation to new audiences (Kwan, 2019, Schwarz et al., 2016). For example, if the BBC widely publicized a correction to a misconception that its readership never believed to begin with, it will not reap the benefits of belief reduction, and those who do not trust this source may question its conclusion. The next crucial step is to examine such instances with real-world scenarios on social media or fact-checking websites.
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