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Abstract
Individuals generally revise their misconceptions when corrected with carefully designed educational materials. However, early reports suggest that correcting COVID-19 misconceptions may be especially challenging, which may be due to conflicts with individuals’ moral values and emotions. This study explores the mechanisms and boundaries of correction effectiveness. Those highest in moral concerns for group cohesion or for individual freedoms were more likely to affectively or cognitively reject corrective information. Corrections of COVID-19 misconceptions should be carefully framed to connect with the morality of recipients and anticipate their emotional and cognitive reactions.
Compounding the public health challenges posed by the COVID-19 pandemic is an infodemic of misinformation regarding risks, prevention, and treatments (WHO, 2020), which may lead to serious and irreversible harm to individuals and communities. Thus, there is an urgent need to identify methods to correct misconceptions1 about COVID-19.
Incorrect beliefs have been frequently corrected by refutation texts (Tippett, 2010). These are brief documents that identify an erroneous belief, refute it, and present several claims that reinforce the best available understanding as a substitute explanation. In doing so, refutation texts promote a specific sequence of cognitive processes theorized to result in knowledge revision (Kendeou et al., 2013, 2014, 2019). Most notably, this includes instigating competitive cognitive conflict between correct and incorrect knowledge that is resolved when misconceptions are overwritten in memory by the quantity and quality of correct supporting explanations.
Beyond revising misconceptions, corrections such as refutation texts typically have positive effects on knowledge, attitudes, and support for related policies (Aguilar et al., 2019; Thacker et al., 2019; Walter & Murphy, 2018; Wood & Porter, 2019). However, several prior attempts to correct misconceptions about controversial or emotionally laden topics have failed (Cook & Lewandowsky, 2016). Correction failures may undermine important collective actions needed in a pandemic, such as wearing face masks and vaccine-acquired herd immunity.
Early reports suggest that correcting COVID-19 misconceptions will face similar barriers. News coverage of the novel viral outbreak has reflected negative emotional reactions and polarization (Daly & Robinson, 2020; Gadarian et al., 2020), the co-occurrence and prominence of which increases the likelihood that vital health information will be undermined by biased reasoning.
One contributor to the current infodemic crisis may be disagreements between moral priorities: Is it most important to provide for the vulnerable, show loyalty to one’s social circle, or protect personal liberties? How individuals answer such questions reflects their moral values that can be categorized as individualizing, focused on well-being and justice for individuals and linked to liberal ideology; binding, focused on protecting group cohesion and social order and linked to conservative ideology; or libertarianism, focused on protecting autonomous exercise of personal liberties (Iyer et al., 2012). Messages that use moral-emotional language are more likely to spread widely online and individuals’ own moral foundations shape whether they accept persuasive messages (Brady et al., 2019; Wolsko et al., 2016). Conflicts between public health messages and moral values evoke emotions, which in turn impact learning (Haidt, 2003; Pekrun, 2006; Trevors, 2020). However, it is unknown to what extent efforts to correct COVID-19 misconceptions may be undermined by such perceived conflict, which is likely to be prevalent in communities with the strongest opposition to public health measures adopted in response to the pandemic. This study sought to test the relations between morality and learning, mediated via emotion2 and belief in the corrective content and moderated by conflict (Figure 1) among a purposeful sample drawn from communities strongly opposed to social distancing measures.
Method
A purposeful sample of 518 U.S. adults (Mage = 39.8, SD = 13.6 years; 56.2% female, 43.2% male, 0.6% other)3 was recruited online May 4 to 6, 2020, from 12 states4 identified in previous research as among the highest to favor immediate return to normal economic activity in a nationally representative survey (covidstates.org) and in actual travel behaviors outside the home as tracked by Apple (www.apple.com/covid19/mobility) as of May 3, 2020. Participants completed five prior knowledge items, a modified version of the Moral Foundations Questionnaire (MFQ; Iyer et al., 2012; Janoff-Bulman & Carnes, 2016), and read five short refutations of common socio-scientific COVID-19 misconceptions (e.g., “The seasonal flu is just as bad if not worse than the new coronavirus”). Immediately after reading, participants self-reported their emotional responses to the refutation, whether its content conflicted with their personal views and/or views of their community, the extent to which they believed the refutation and skimmed it quickly. Learning was assessed via the same knowledge items as the pretest (see the Supplemental Appendix, available on the journal website, for all materials).
Separate exploratory factor analyses were conducted on the MFQ and emotion response items with principal axis factoring and direct oblimin rotation. Consistent with Iyer et al. (2012), three factors were requested from MFQ responses, which explained 38.9% of variance: binding (eight items, α = .82), individualizing (six items, α = .71), and libertarianism (four items, α = .61). On emotion responses, extraction was based on eigenvalues greater than 1, which yielded three factors that explained 55.1% of variance:5 anxious (anxious, scared, hopeless, threatened, α = .75), hopeful (hopeful, relieved, happy, curious, surprised, α = .80), and doubtful (doubtful, bored, angry, confused, α = .85).
Results
In keeping with Educational Researcher’s “Brief” format, study materials and results are included in the Supplemental Appendix (available on the journal website) including concurrent validity evidence for the prior knowledge measure (Table S2) and model coefficients (Tables S3–S5).
Descriptive statistics are reported in Table 1. A paired t test showed that refutations increased factual knowledge from pretest to posttest across the full sample, t(517) = 7.42, p < .0001, d = .33.
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Table 1 Descriptive and Correlational Statistics
Moderated mediation analyses were conducted with Hayes’s (2017) PROCESS macro (v.3). Three moral beliefs were separately entered as predictors, three emotions entered in parallel as a first set mediators, belief entered sequentially as a second mediator, and posttest scores entered as the dependent variable. Prior knowledge scores and skimming were entered as covariates, and binary conflict response was entered as a moderator.
The model accounted for 60% of posttest score variance. Conflict, hopefulness, doubtfulness, and skimming were negative predictors; whereas belief and prior knowledge were positive predictors of learning. Significant interactions were observed between conflict and the moral values of binding and libertarianism, wherein these values negatively predicted posttest scores when corrections conflicted with views.
Table 2 presents indirect effects of moral values on learning conditional on conflict. Binding had negative effects on learning via doubtfulness and belief. Binding and individualizing had negative effects on learning mediated by hopefulness alone, whereas they showed positive effects when mediated by hopefulness and belief, suggesting the importance of connecting affective optimism with cognitive acceptance. Notably, individualizing and libertarianism had opposing responses to conflict. When corrections conflicted with views, high individualizing values positively predicted learning via belief. In contrast, high libertarianism values negatively predicted learning via belief when corrections conflicted with views. In sum, consistent with Figure 1, each moral foundation had at least one indirect effect on learning, mediated by emotions and/or belief and moderated by conflict. Although some paths are shared between moral foundations (e.g., binding and individualizing via hopeful, anxiety, and belief), importantly, there are unique and negative paths for binding and libertarianism on learning via doubtfulness and lower belief.
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Table 2 Indirect Effects of Moral Foundations on Learning Conditional on Conflict
Discussion
We interpret these results to indicate that the effectiveness of refutations may depend on the recipient’s moral values. Specifically, people with strong moral concerns for individual well-being were more likely to update their prior COVID-19 beliefs when corrected. Conversely, others who morally valued either group cohesion or individual freedoms were more likely to affectively or cognitively reject corrective information. The public health responses to the current pandemic, such as stay-at-home orders, school closures, social distancing, and mask wearing, have severely disrupted individuals’ social relations, leisure, and economic activities in order to reduce harm to society overall. As such, these actions may be viewed as undermining valued social ties or personal autonomy held by individuals with binding and libertarianism morality in favor of collective well-being, a value more prominently held by individuals with individualizing morality.
However, when people disagree on basic facts about disease risk, prevention, or treatments, necessary collective actions against the pandemic may be undermined. Therefore, corrections of COVID-19 misconceptions should be adapted to connect with the morality of recipients to mitigate negative emotional and cognitive reactions. For instance, this may be accomplished by creating multiple refutations on public health policies (e.g., mask wearing) using different moral frames that link compliance to concerns for fairness and suffering (individualizing foundation); obeying authority, defending purity from infections, and demonstrating patriotism (binding foundation); or self-protection (libertarianism foundation; see Wolsko et al., 2016).
One limitation is that it is unknown to what extent these effects are stable across time or are limited to the current time frame. Given that moral foundations and political ideology coincide (Hatemi et al., 2019), individuals may rely on their current political leaders’ and other elites’ support or opposition towards some public health measures in deciding to accept or reject corrections (Ember, 2020; Flynn et al., 2017; Hess, 2020). As such, acceptance of corrections may vary as cues from leaders change.
Finally, we interpret our findings to be consistent with contemporary conceptual change theories that describe the heightened challenge to revising incorrect beliefs when integrated with strong personal values (Sinatra et al., 2014; Sinatra & Seyranian, 2016). The findings are also consistent with critiques of the information deficit model of science communication that assumes misconceptions reflect a simple lack of information that can be solved by improving transmission of information to the general public. Both these theoretical lines and our findings converge on the importance of psychological factors of message recipients, including their values and emotions (Suldovsky, 2017; Trevors, 2019). In this vein, future research should examine complex emotion factors such as those observed in the current study since individuals may be motivated to avoid corrective information that induces negative affect (Sharot & Sunstein, 2020). In sum, findings from the current study contribute to theoretical knowledge about how, why, and for whom corrections effectively update misconceptions about controversial topics.
Notes
The study was supported by funding from the College of Education at the University of South Carolina.
1
In the current study, we define misconceptions consistent with Chi’s (2013) concept of false beliefs, which are individual propositions that conflict with to-be-learned material but that can be revised by explicit refutation.
2
We adopt Pekrun’s (2006) definition and theoretical framework of emotions: “Emotions are seen as multi-component, coordinated processes of psychological subsystems including affective, cognitive, motivational, expressive, and peripheral physiological processes” (p. 316) that have consequences for cognitive resources, motivation, learning strategies, and achievement.
3
Full sample demographics are presented in Table S1 in the Supplemental Appendix, available on the journal website.
4
Final sample consisted of participants who passed three attention checks and reported zip codes and geoIP data that are consistent with target regions (AK, AZ, AR, CO, ID, KS, MT, ND, OK, SD, UT, and WY). Data from multiple repeating geoIP were omitted per recommendation (Ahler et al., 2019).
5
Factors were named after their highest loading variable.
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Authors
GREG TREVORS, PhD, is an assistant professor at the University of South Carolina, 820 Main Street, College of Education, Columbia, SC 29208; [email protected]
MELISSA C. DUFFY, PhD, is an assistant professor at the University of South Carolina, 820 Main Street, College of Education, Columbia, SC 29208; [email protected]
