Thinking & Reasoning

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Analytic-thinking predicts hoax beliefs and helping

behaviors in response to the COVID-19 pandemic

Matthew L. Stanley, Nathaniel Barr, Kelly Peters & Paul Seli

To cite this article: Matthew L. Stanley, Nathaniel Barr, Kelly Peters & Paul Seli (2021) Analytic-
thinking predicts hoax beliefs and helping behaviors in response to the COVID-19 pandemic,
Thinking & Reasoning, 27:3, 464-477, DOI: 10.1080/13546783.2020.1813806

To link to this article: https://doi.org/10.1080/13546783.2020.1813806

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THINKING & REASONING
2021, VOL. 27, NO. 3, 464–477
https://doi.org/10.1080/13546783.2020.1813806

REPORT

Analytic-thinking predicts hoax beliefs and

helping behaviors in response to the COVID-
19 pandemic
Matthew L. Stanleya,b, Nathaniel Barrc,d, Kelly Petersc and Paul Selia,b
a
Department of Psychology and Neuroscience, Duke University, Durham, NC, USA;
b
Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; cBEworks
Toronto, Toronto, ON, CanadadSchool of Humanities and Creativity, Sheridan College,
Oakville, ON, Canada

ABSTRACT
The COVID-19 outbreak was labeled a global pandemic by the WHO in March
of 2020. During that same month, the number of confirmed cases and the
death rate grew exponentially in the United States, creating a serious public-
health emergency. Unfortunately, many Americans dismissed the pandemic
as a hoax and failed to properly engage in helpful behaviors like social-dis-
tancing and increased hand-washing. Here, we examine a disposition—
engagement in analytic-thinking—that might predict beliefs that the pan-
demic is a hoax and failures to change behavior in positive ways during that
critical early period in March. Our results indicate that individuals less likely to
engage effortful, deliberative, and reflective cognitive processes were more
likely to believe the pandemic was a hoax and less likely to have recently
engaged in social-distancing and hand-washing in March. We discuss possible
implications of these results for understanding and addressing the COVID-
19 pandemic.

ARTICLE HISTORY Received 8 May 2020; Accepted 13 August 2020

KEYWORDS COVID-19; cognitive reflection test; analytic; prosocial; misinformation

Introduction
Confirmed COVID-19 cases in the United States increased exponentially,
quickly leading to a pandemic in 2020, which created a serious public-
health emergency. During the period in which the COVID-19 began to rap-
idly spread throughout the United States, there was a pressing need for

CONTACT Matthew L. Stanley matthew.stanley@duke.edu

Supplemental data for this article is available online at https://doi.org/10.1080/13546783.
2020.1813806.
De-identified data are available at https://osf.io/f9evs/
ß 2020 Informa UK Limited, trading as Taylor & Francis Group
 THINKING & REASONING 465

Americans to take the pandemic seriously and to engage in both self-pre-

serving and prosocial changes to behavior. The World Health Organization
(WHO) and the Centers for Disease Control (CDC) consistently and adam-
antly encouraged people to socially distance themselves from others and to
frequently and thoroughly wash their hands. These concrete steps should
have been taken to mitigate the spread of the virus in American commun-
ities, minimizing possible harms to individuals and society at-large while
preventing the healthcare system from becoming overwhelmed.
Unfortunately, many Americans dismissed the seriousness of the COVID-
19 pandemic during this early period of rapid spread in March (Jacobo,
2020; Schnell, 2020). Given the grave consequences of failing to change
behavior for individuals and society at-large, it is imperative that policy-
makers understand why constituents resist compliance. These insights have
the potential to inform the development of mandates and communications
strategies to encourage consistent implementation of expert
recommendations.
To understand why many people have not changed their behavior,
examining the veracity and quality of information in the public sphere
seems critical. From the earliest days of the outbreak, misinformation and
disinformation about COVID-19 circulated widely across social media, radio
talk shows, and national news media (Frenkel et al., 2020; Russonello, 2020).
In a nationally representative poll conducted by The Economist/YouGov
from March 8th to 10th, 13% of Americans reported that COVID-19 was
probably or definitely a hoax, and only 62% of Americans expressed cer-
tainty that COVID-19 was not a hoax. Those individuals who believe that it
is a hoax represent a serious threat to properly responding to the pandemic
in a way that minimizes harms to themselves and society at-large.
In an effort to understand who is failing to change behavior, we investi-
gate whether individual differences in analytic cognitive style predict beliefs
about the COVID-19 pandemic being a hoax and engagement in helpful
behaviors like social-distancing and increased hand-washing. The founda-
tion for this proposed psychological explanation rests on dual-process the-
oretical accounts of human cognition. Theorists have made a distinction
between more automatic, intuitive processing (System 1) and more delib-
erative, reflective, and analytic processing (System 2; Evans & Stanovich,
2013; De Neys, 2012; Kahneman, 2011; Pennycook, Fugelsang, et al., 2015).
This distinction is illustrated by the following problem from the Cognitive
Reflection Test (CRT; Frederick, 2005):
If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100
machines to make 100 widgets?

This problem elicits a fast, intuitive response (100 minutes), but upon
reflection, 100 minutes cannot be the right answer. By overriding the fast,
466 M. L. STANLEY ET AL.

intuitive response of 100 minutes and engaging in more reflective, effortful

thinking, an individual might arrive at the correct answer of 5 minutes.
Performance on these kinds of problems is thought to reflect people’s
willingness or propensity to think reflectively and analytically (Pennycook,
Fugelsang, et al., 2015; Thomson & Oppenheimer, 2016; Toplak et al., 2011,
2014). Humans often avoid using more effortful, resource-demanding cog-
nitive processes to make judgments and decisions, especially when more
automatic, effortless, and intuitive processes are good enough (Kahneman,
2011; Stanovich & West, 2000). However, a failure to engage more effortful,
deliberative, and reflective cognitive processes is associated with poorer
performance across some judgment and decision-making tasks. For
example, higher CRT scores predict resistance to conjunction fallacies
(Oechssler et al., 2009) and reduced susceptibility to framing effects (Cokely
& Kelley, 2009; Frederick, 2005).
More recently, researchers have linked performance on the CRT to skep-
ticism about epistemically-suspect beliefs (Pennycook, Cheyne, et al., 2015).
People who perform better on the CRT are less likely to hold paranormal
beliefs (Pennycook et al., 2012), less likely to believe that conspiracy theo-
ries are veridical (Swami et al., 2014), better at differentiating real and fake
news reports (Bronstein et al., 2019; Pennycook & Rand, 2020), and less
likely to find pseudo-profound bullshit compelling (Pennycook, Cheyne,
et al., 2015). If individuals who are less willing to engage effortful, delibera-
tive, and reflective cognitive processes tend to be more willing to hold epis-
temically-suspect beliefs, then those same individuals might be more likely
to believe that the COVID-19 pandemic is a hoax. In turn, those same indi-
viduals might be less likely to engage in helpful behaviors like social-dis-
tancing and hand-washing, perhaps because they believe that the
pandemic is a hoax. If people who believe the pandemic is a hoax are less
likely to engage in actual helpful behaviors, then these hoax beliefs might
have real-world impacts on the health and livelihoods of many people.

Overview of study
Data for this study were collected on Saturday, March 21, 2020, around the
time that the rate of confirmed COVID-19 cases began to skyrocket in the
United States. We administered the CRT, and participants reported their
beliefs about whether the pandemic is a hoax as well as their engagement
in helpful behaviors (i.e., social-distancing and hand-washing) to help com-
bat the pandemic over the previous week. We hypothesized that those indi-
viduals who perform worse on the CRT (i.e., individuals less willing to
engage effortful, deliberative, and reflective cognitive processes) would be
more likely to believe the pandemic is a hoax and less likely to have
 THINKING & REASONING 467

engaged in helpful behaviors over the prior week. We also hypothesized

that CRT performance would be indirectly related to engagement in helpful
behaviors via beliefs about the COVID-19 pandemic being a hoax.
Participants who perform worse on the CRT should have been less likely to
engage in helpful behaviors, perhaps because they believe it is a hoax.
This study was formally pre-registered: https://osf.io/f9evs/. We report all
exclusion criteria, all conditions included, and all independent and depend-
ent measures. We did not deviate from the pre-registration.

Materials and method

Participants
Three-hundred American residents with at least 500 completed HITs and an
approval rating above 95% voluntarily participated in this study on
Amazon’s Mechanical Turk (AMT) for monetary compensation (US $1.50) on
March 21, 2020. Twenty-two participants were excluded for failing the
attention check (see pre-registration for details); so, data were analyzed
with the remaining 278 individuals (Mage ¼ 42 years old, SD ¼ 13, age range
¼ [20–78], 134 males, 143 females, 1 no response). A power analysis indi-
cated that, to detect small-to-moderate correlations (r ¼ .20) with power of
.90 and alpha set to .05, 258 participants were needed. Three-hundred par-
ticipants completed the task with the expectation of having at least 258
participants after exclusions. Data were analyzed only after the required
sample size target was met, and the sample size was determined prior to
data collection (see pre-registration). We recruited participants through
AMT to obtain a more representative sample of the United States popula-
tion than traditional convenience samples obtained through undergraduate
participant pools. The Duke University Campus Institutional Review Board
approved the procedure for this study.

Materials
Cognitive reflection test (CRT)
We used a seven-item CRT: The original three-item CRT (Frederick, 2005)
was included along with the four items from the non-numeric version of
the CRT developed by Thomson and Oppenheimer (2016). This same seven-
item CRT has been implemented in recent work (Pennycook & Rand, 2020).
The two versions of the CRT were strongly correlated (r(276) ¼ .60, p <
.001), and the full seven-item CRT had acceptable reliability (Cronbach’s
alpha ¼ .81). Importantly, prior exposure to the CRT does not seem to
adversely affect the predictive validity of the CRT, and people continue to
468 M. L. STANLEY ET AL.

incorrectly respond to the same items in subsequent exposures (Bialek &

Pennycook, 2018; Meyer et al., 2018; Stagnaro et al., 2018). The CRT was
scored by computing the proportion correct for each participant.

COVID-19 questions
Participants were asked: “Do you believe that the coronavirus (COVID-19)
pandemic is a hoax?” (1 ¼ definitely not a hoax, 6 ¼ definitely a hoax). We
intentionally used the “hoax” language from the The Economist/YouGov poll
to more directly relate our findings to their survey results. Participants were
also asked to report the extent to which they had been practicing social-
distancing in the past week in response to the COVID-19 epidemic (1 ¼ not
at all, 6 ¼ a lot) and the extent to which they had been washing their hands
with soap and water in the past week in response to the COVID-19 pan-
demic (1 ¼ not at all, 6 ¼ a lot). Participants were also asked to list possible
solutions to the COVID-19 pandemic and to list the specific ways in which
they had helped in response to the COVID-19 pandemic in the past week;
the maximum number of solutions and helping behaviors that participants
could list was six.

Demographics and political questions

Participants were asked to report their age, gender, and level of education
(1 ¼ did not complete high school, 2 ¼ high school degree or equivalent,
3 ¼ Associate’s degree, 4 ¼ Bachelor’s degree, 5 ¼ Graduate or Professional
degree), after which they responded to questions about their politics.
Specifically, participants were asked to indicate how liberal or conservative
they are on social issues (1 ¼ very liberal, 7 ¼ very conservative) and on eco-
nomic issues (1 ¼ very liberal, 7 ¼ very conservative).

Procedure
After providing informed consent, participants first completed the seven-
item CRT, with the order of seven questions randomized across participants.
Then, for the COVID-19 questions, participants first listed possible solutions
to the pandemic and helping behaviors that they had engaged in over the
prior week. Using sliding scales, participants then responded to the hoax
item, and after that, the social-distancing and hand-washing questions (the
order of these two questions were randomized across participants). After
responding to all COVID-19 questions, participants completed the demo-
graphics and political questions.
 THINKING & REASONING 469

Table 1. Means, SDs, and correlation coefficients.

Issue Mean SD (1) (2) (3) (4)
(1)CRT performance .63 .31 –
(2)Hoax 1.89 1.53 -.46 –
(3)Social-distancing 5.49 .81 .14 -.24 –
(4)Hand-washing 5.49 .88 .14 -.29 .45 –
(5)Count of helping behaviors 2.92 1.69 -.06 .04 .10 .22
Note: p < .001, p < .01, p < .05.

At the end of the study, participants were presented with an attention

check question that has been used in published research (e.g., Stanley
et al., 2019). Only those participants who reported paying attention were
included in the analyses (see pre-registration for details).

Results
Table 1 provides descriptive statistics and correlation coefficients for the
primary variables of interest (Supplemental Information contains descriptive
statistics and correlation coefficients for additional demographics and polit-
ical variables). We hypothesized that those individuals who perform worse
on the CRT (i.e., individuals less willing to engage effortful, deliberative, and
reflective cognitive processes) would be more likely to believe the COVID-
19 pandemic is a hoax and less likely to have engaged in helpful behaviors
over the prior week. To address these hypotheses, we computed bivariate
correlations between average CRT performance, beliefs about the COVID-19
pandemic being a hoax, and measures of helping behaviors (social-distanc-
ing, hand-washing, and the reported quantity of helping behaviors in the
past week).
Corroborating our hypotheses, participants who performed worse on the
CRT were indeed more likely to believe that the pandemic is a hoax (r(276)
¼ .46, p < .001); participants who performed worse on the CRT were also
less likely to have engaged in social-distancing (r(276) ¼ .14, p ¼ .02) and
hand-washing with soap and water (r(276) ¼ .14, p ¼ .02) over the previous
week.1 However, there was no significant relationship between CRT per-
formance and participants’ reported quantity of helping behaviors (r(276) ¼
.06, p ¼ .28). So, while CRT performance did not predict the quantity of
helpful behaviors related to the COVID-19 pandemic, it did predict the
extent to which participants have engaged in those helpful behaviors. See
Supplemental Information for partial correlations.

1
Non-parametric correlations (Spearman’s rank-order) showed the same pattern of results:
Participants who performed worse on the CRT were more likely to believe that the coronavirus
pandemic is a hoax (r(276) ¼ -.45, p < .001); participants who performed worse on the CRT were
also less likely to have engaged in social-distancing (r(276) ¼ .15, p ¼ .01) and hand-washing with
soap and water (r(276) ¼ .16, p ¼ .007) in the previous week.
470 M. L. STANLEY ET AL.

We next tested our hypothesis that CRT performance would be indirectly

related to engagement in helping behaviors via beliefs about the COVID-19
being a hoax. To address this hypothesis, we used the PROCESS macro in
SPSS from Hayes (2016) with 5,000 bootstrap resamples. The results from
these analyses corroborate our hypothesis: There were significant indirect
effects of CRT performance on social-distancing (b ¼ .27, boot SE ¼ .07,
95% CI [.13, .42]) and hand-washing (b ¼ .37, boot SE ¼ .10, 95% CI [.20,
.57]) through beliefs about the COVID-19 pandemic being a hoax. The dir-
ect effects of CRT performance on social-distancing (b ¼ .09, SE ¼ .17, t ¼
.52, p ¼ .60, 95% CI [-.25, .43]) and hand-washing (b ¼ .03, SE ¼ .18, t ¼ .17,
p ¼ .86, 95% CI [-.33, .40]) behaviors were non-significant in the models.
We also sought to ensure that these indirect effects persist after statistic-
ally controlling for several demographics (age, education level) and political
(social and economic conservatism) variables. Our results indicate that,
even after statistically accounting for age, education level, social conserva-
tism, and economic conservatism, there remained significant indirect effects
of CRT performance on social-distancing (b ¼ .18, boot SE ¼ .06, 95% CI
[.07, .31]) and hand-washing (b ¼ .29, boot SE ¼ .08, 95% CI [.15, .46])
behaviors through beliefs about the COVID-19 pandemic being a hoax. The
direct effects of CRT performance on social-distancing (b ¼ .03, SE ¼ .18, t
¼ .18, p ¼ .86, 95% CI [-.31, .38]) and hand-washing (b ¼ .03, SE ¼ .19, t ¼
.18, p ¼ .86, 95% CI [-.34, .41]) behaviors were non-significant in
the models.

Discussion
We conducted this study when the rate of confirmed COVID-19 cases ini-
tially began to skyrocket in the United States, and we found evidence that
individuals less willing to engage effortful, deliberative, and reflective cogni-
tive processes were more likely to believe that the pandemic was a hoax
and less likely to have recently engaged in social-distancing and hand-
washing behaviors. Subsequent analyses were consistent with the hypoth-
esis that participants less willing to engage these effortful, deliberative, and
reflective cognitive processes were less likely to engage in helpful behav-
iors, perhaps because they believed the pandemic to be a hoax. These find-
ings contribute to a growing literature on insights from social and
behavioral sciences critical for understanding human responses to the pan-
demic, and hopefully, optimizing the response to the pandemic (Van Bavel
et al., in press).
The current investigation yielded theoretically-important findings that
are generally consistent with prior findings on the relations between dispo-
sitional analytic-thinking, epistemically-suspect beliefs, and conspiracist
 THINKING & REASONING 471

ideation (Pennycook, Cheyne, et al., 2015). Our results extend these prior
findings to hoax beliefs about a serious, contemporary problem at a critical
time during the course of the crisis. Our study links analytic thinking and
hoax beliefs to behaviors that have the potential to mitigate harm to indi-
viduals and society at-large, offering a novel contribution to the empirical
research on prosociality and morality. Other research has examined associa-
tions between analytic thinking and the judgments and decisions made
about carefully designed, but hypothetical, vignettes involving moral issues
(e.g., Baron et al., 2015; Patel et al., 2019; Pennycook et al., 2014). There are
two noteworthy differences between our project and this prior research.
First, the content of the hypothetical vignettes commonly employed in
these studies does not match the kinds of judgments, decisions, and behav-
iors that people encounter and experience in the world (Hofmann et al.,
2014). Second, recent empirical evidence (e.g., Bostyn et al., 2018;
FeldmanHall et al., 2012) suggests that the judgments and decisions that
people make in hypothetical vignettes often do not map on to their real-
life behaviors. Although we certainly believe that this prior research is
valuable and informative, our contribution is distinct in that we investigate
real-world helpful behaviors that have the potential to mitigate future
harm, and most Americans have had to make judgments and decisions
about hand-washing and social-distancing throughout the course of
this pandemic.
Our findings might also inform efforts to craft communications and
implement interventions to inspire behavioral change for the sake of public
safety. For one, given the relatively high prevalence of respondents who
were willing to entertain the possibility that COVID-19 is a hoax—both
within our sample and other polls (e.g. The Economist/YouGov poll)—and
given that this hoax beliefs strongly predict prosocial behavior, efforts to
inspire behavior change might attempt to directly combat hoax beliefs
head-on (going forward, it would also be valuable to better understand the
details of these hoax beliefs). Researchers recently identified several effect-
ive ways of correcting misinformation that could be implemented on a
national scale (Lorenz-Spreen et al., 2020).
It remains unclear, however, whether effective public messaging and
other interventions aimed at eliminating hoax beliefs will work or meaning-
fully shift behavior. In looking to copious evidence from the field of behav-
ioral economics, it is difficult to create interventions that establish
consistent and prolonged behavior change. Simon (1997) argued that
humans are boundedly rational, limited by both time and mental energy,
often leading us to make sub-optimal decisions, even when we know bet-
ter. Given mounting evidence on the importance of individual differences
in analytic-thinking style in predicting epistemic beliefs (Pennycook,
472 M. L. STANLEY ET AL.

Cheyne, et al., 2015), with the rationality of some bounded more than
others, it stands to reason that those individuals low in analyticity might be
less responsive to information-based appeals that require reasoned shifts to
behavioral change. Other kinds of persuasive techniques might be better-
suited to changing the beliefs and behaviors of those who are disposition-
ally less willing to engage in effortful, deliberative, and reflecting thinking.
This is particularly important given that Pennycook et al. (in press) recently
found that people who score lower on analytic-thinking tend to be less dis-
cerning in their sharing of COVID-19 news.
At the same time, however, it might not be the case that we can simply
aim System 2 information-rich messaging at one audience, and System 1
messaging at another. System 1 strategies might be ineffective (or even
backfire) with those individuals who approach the CRT with fast but flawed
reasoning. The rejection of the COVID-19 information presented by public
health experts could potentially be countered with deeper causal explana-
tions of the mechanisms of the pandemic accessible to the layperson.
McPhetres et al. (2019) found that increasing knowledge about genetically
modified foods can increase positive attitudes about such foods.
Analogously, in the case of the COVID-19 pandemic, some people might be
persuaded by genetics research showing the lineage of the COVID-19
pathogen and, in turn, benefit from more comprehensive biological explan-
ations of our lack of resistance to it. As with climate change, sometimes
denial is the result of feeling overwhelmed by the problem (Haltinner &
Sarathchandra, 2018). A nuanced, multi-faceted approach to gaining con-
sensus on the challenge is likely required to get alignment on the solutions.
In the same way that Ignaz Semmelweis’s contemporaries rejected his the-
ory that they caused patients’ deaths and that hand-washing was the solu-
tion, many people might not currently have the mental models to
understand, accept, and react appropriately to the science of infectious dis-
ease epidemiology.
After the initial submission of this manuscript, several other researchers
published pre-prints examining relationships between analytic thinking,
conspiratorial/hoax beliefs, and compliance with different COVID-19 guide-
lines at different time-points over the course of the pandemic and in sev-
eral different countries. We discuss three of these pre-prints, in turn, as they
relate to our findings. First, with a sample of 407 participants whose data
were collected in mid-April, Teovanovic et al. (under review) found that
those who performed worse on the CRT were more likely to hold conspira-
torial/hoax beliefs about the COVID-19 pandemic and less likely to have fol-
lowed COVID-19 guidelines (e.g., social-distancing, hand-washing) over the
previous two weeks. Overall, these findings closely accord with our results.
Second, with a sample of 783 participants whose data were collected in
 THINKING & REASONING 473


mid-March, Cavojov a et al. (under review) also found that those who per-
formed worse on the CRT were more likely to hold conspiratorial beliefs
about the COVID-19 pandemic; better performers on the CRT were also
somewhat less likely to have engaged in many different preventive behav-
iors, but this relationship just missed the threshold for statistical signifi-
cance. However, the items comprising this composite were binary
responses indicating whether or not participants had engaged in each of
the preventive behaviors (yes vs. no), not the extent to which they had
engaged in these behaviors. Our results indicate that CRT performance only
predicted the extent to which participants had engaged in these helpful
behaviors, not in the number of helpful behaviors they had performed. So,

our findings are largely consistent with those from Cavojov a et al. (under
review). Third, with several large samples collected in the U.S., U.K., and
Canada, Pennycook et al. (under review) also found that those who per-
formed worse on the CRT were more likely to hold misconceptions about
the COVID-19 pandemic, but CRT performance was not statistically signifi-
cantly related to intentions to change behavior in helpful ways (e.g., by
social-distancing). Whereas Pennycook et al. (under review) measured inten-
tions to change behavior, our study measured self-reported engagement in
helpful behaviors over the past week. As such, our findings and those from
Pennycook et al. (under review) are not necessarily at odds with each other,
especially given the large corpus of work showing that intentions are often
poor predictors of actual behavior (Ajzen & Fishbein, 2005; Fazio & Zanna,
1981; Fishbein, 1966; Sheeran, 2002; Sheeran & Webb, 2016). In sum, while
it is clear across studies that dispositional analytic thinking is a strong, con-
sistent predictor of hoax beliefs, conspiratorial beliefs, and misconceptions
about COVID-19, the relationships between analytic thinking, intentions,
and behavior are more nuanced. Whereas analytic thinking seems to pre-
dict the extent to which people have engaged in helpful behaviors in
response to the pandemic, analytic thinking may not predict the number of
helpful behaviors people have performed or intentions to change behavior.
There are three limitations to our study worth noting. First, we intention-
ally adopted the “hoax” language from the The Economist/YouGov poll to
more directly relate our findings to those survey results. However, there
could be ambiguity in what it means for the pandemic to be a hoax. Some
variation in reported hoax beliefs might reflect people’s beliefs about the
seriousness of the pandemic, as opposed to whether COVID-19 or the pan-
demic exist at all. Second, we administered the CRT before asking questions
about COVID-19, but some evidence suggests that administering the CRT
first can influence subsequent judgments (Finley et al., 2015). So, some
researchers have recommended that the CRT be administered at the end of
a study. Third, because all variables were measured instead of manipulated,
474 M. L. STANLEY ET AL.

we cannot draw strong causal conclusions about mediation effects. Our

results are consistent with the model that people who are less willing to
engage these effortful, deliberative, and reflective cognitive processes were
less likely to engage in helpful behaviors, because they believed the pan-
demic to be a hoax. However, our results do not provide strong causal sup-
port for the links in the model.
After this study was conducted on March 21, 2020, many states issued
mandatory social-distancing measures. However, the public was divided on
the value and necessity of these measures (Rosenfeld, Rothgerber, &
Wilson, under review). In some cases, social-distancing mandates were met
with backlash from citizens, with protests popping up in many states. In
May 2020, some states began the process of reducing or lifting social-dis-
tancing mandates, giving more agency and decision-making power to citi-
zens. The process of re-opening increases the likelihood of severe
subsequent waves of the virus. We hope that our research will provide a
better understanding of people’s beliefs about COVID-19, why certain peo-
ple are more likely to social-distance than others, and even how certain
people will react to the process of re-opening.

Open practices statement

The study reported here was formally pre-registered. De-identified data are
publicly available on OSF (https://osf.io/f9evs/). All materials for all studies
are provided in the main text or in the pre-registration.

Disclosure statment
The authors declared that they have no competing interests with respect to
the publication of this article.

References
Ajzen, I., & Fishbein, M. (2005). The influence of attitudes on behavior. In D.
Albarracın, B. T. Johnson, & M. P. Zanna (Eds.), The handbook of attitudes (p.
173–221). Lawrence Erlbaum Associates Publishers.
Baron, J., Scott, S., Fincher, K., & Metz, S. E. (2015). Why does the Cognitive Reflection
Test (sometimes) predict utilitarian moral judgment (and other things)? Journal of
Applied Research in Memory and Cognition, 4(3), 265–284. https://doi.org/10.1016/
j.jarmac.2014.09.003
Bialek, M., & Pennycook, G. (2018). The cognitive reflection test is robust to multiple
exposures. Behavior Research Methods, 50(5), 1953–1959. https://doi.org/10.3758/
s13428-017-0963-x
Bostyn, D. H., Sevenhant, S., & Roets, A. (2018). Of mice, men, and trolleys: hypothet-
ical judgment versus real-life behavior in trolley-style moral dilemmas.
 THINKING & REASONING 475

Psychological Science, 29(7), 1084–1093. https://doi.org/10.1177/

0956797617752640
Bronstein, M. V., Pennycook, G., Bear, A., Rand, D. G., & Cannon, T. D. (2019). Belief in
fake news is associated with delusionality, dogmatism, religious fundamentalism,
and reduced analytic-thinking. Journal of Applied Research in Memory and
Cognition, 8(1), 108–117. https://doi.org/10.1016/j.jarmac.2018.09.005

Cavojov a, V., Srol, J., Mikuskova, E. B. (under review). Scientific reasoning as a pre-
dictor of healthrelated beliefs and behaviors in the time of COVID-19. https://doi.
org/10.31234/osf.io/tfy5q
Cokely, E. T., & Kelley, C. M. (2009). Cognitive abilities and superior decision making
under risk: A protocol analysis and process model evaluation. Judgment and
Decision Making, 4, 20–33.
De Neys, W. (2012). Bias and conflict: A case for logical intuitions. Perspectives on
Psychological Science : a Journal of the Association for Psychological Science, 7(1),
28–38. https://doi.org/10.1177/1745691611429354
Evans, J. S. B., & Stanovich, K. E. (2013). Dual-process theories of higher cognition:
Advancing the debate. Perspectives on Psychological Science : a Journal of the
Association for Psychological Science, 8(3), 223–241. https://doi.org/10.1177/
1745691612460685
Fazio, R. H., & Zanna, M. P. (1981). Direct experience and attitude-behavior consist-
ency. In Advances in Experimental Social Psychology (pp. 161–202). Academic
Press.
FeldmanHall, O., Mobbs, D., Evans, D., Hiscox, L., Navrady, L., & Dalgleish, T. (2012).
What we say and what we do: The relationship between real and hypothetical
moral choices. Cognition, 123(3), 434–441. https://doi.org/10.1016/j.cognition.
2012.02.001
Finley, A. J., Tang, D., & Schmeichel, B. J. (2015). Revisiting the relationship between
individual differences in analytic thinking and religious belief: Evidence that meas-
urement order moderates their inverse correlation. PloS One, 10(9),
e0138922https://doi.org/10.1371/journal.pone.0138922
Fishbein, M. (1966). The relationship between beliefs, attitudes, and behavior. In S.
Feldman (Ed.), Cognitive Consistency. Academic Press.
Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic
Perspectives, 19(4), 25–42. https://doi.org/10.1257/089533005775196732
Frenkel, S., Alba, D., Zhong, R. (2020, March 8). Surge of virus misinformation stumps
Facebook and Twitter. The New York Times. https://www.nytimes.com/2020/03/08/
technology/coronavirus-misinformation-socialmedia.html
Haltinner, K., & Sarathchandra, D. (2018). Climate change skepticism as a psycho-
logical coping strategy. Sociology Compass, 12(6), e12586. https://doi.org/10.1111/
soc4.12586
Hayes, A. F. (2016). The PROCESS Macro for SPSS and SAS, http://www.processmacro.
org/
Hofmann, W., Wisneski, D. C., Brandt, M. J., & Skitka, L. J. (2014). Morality in everyday
life. Science (New York, N.Y.), 345(6202), 1340–1343. https://doi.org/10.1126/sci-
ence.1251560
Jacobo, J. (2020, March 18). The frustration millennials have with older people not
taking coronavirus precautions seriously. https://abcnews.go.com/Health/frustra-
tion-millennials-older-people-taking-coronavirusprecautions/story?id=69618912
Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
476 M. L. STANLEY ET AL.

Lorenz-Spreen, P., Lewandowsky, S., Sunstein, C. R., & Hertwig, R. (2020). How behav-
ioural sciences can promote truth, autonomy and democratic discourse online.
Nature Human Behaviour.
McPhetres, J., Rutjens, B. T., Weinstein, N., & Brisson, J. A. (2019). Modifying attitudes
about modified foods: Increased knowledge leads to more positive attitudes.
Journal of Environmental Psychology, 64, 21–29. https://doi.org/10.1016/j.jenvp.
2019.04.012
Meyer, A., Zhou, E., & Shane, F. (2018). The non-effects of repeated exposure to the
Cognitive Reflection Test. Judgment and Decision Making, 13(3), 246–259.
Oechssler, J., Roider, A., & Schmitz, P. W. (2009). Cognitive abilities and behavioral
biases. Journal of Economic Behavior & Organization, 72(1), 147–152. https://doi.
org/10.1016/j.jebo.2009.04.018
Patel, N., Baker, S. G., & Scherer, L. D. (2019). Evaluating the cognitive reflection test
as a measure of intuition/reflection, numeracy, and insight problem solving, and
the implications for understanding real-world judgments and beliefs. Journal of
Experimental Psychology: General, 148(12), 2129–2153. https://doi.org/10.1037/
xge0000592
Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J., & Fugelsang, J. A. (2014). The
role of analytic thinking in moral judgements and values. Thinking & Reasoning,
20(2), 188–214. https://doi.org/10.1080/13546783.2013.865000
Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J., & Fugelsang, J. A. (2015). On the
reception and detection of pseudo-profound bullshit. Judgment and Decision
Making, 10(6), 549–563.
Pennycook, G., Cheyne, J. A., Seli, P., Koehler, D. J., & Fugelsang, J. A. (2012). Analytic
cognitive style predicts religious and paranormal belief. Cognition, 123(3),
335–346. https://doi.org/10.1016/j.cognition.2012.03.003
Pennycook, G., Fugelsang, J. A., & Koehler, D. J. (2015). Everyday consequences of
analytic-thinking. Current Directions in Psychological Science, 24(6), 425–432.
https://doi.org/10.1177/0963721415604610
Pennycook, G., McPhetres, J., Zhang, Y., Rand, D. (in press). Fighting COVID-19 misin-
formation on social media: Experimental evidence for a scalable accuracy nudge
intervention. Psychological Science. https://psyarxiv.com/uhbk9/
Pennycook, G., & Rand, D. G. (2019). Lazy, not biased: Susceptibility to partisan fake
news is better explained by lack of reasoning than by motivated reasoning.
Cognition, 188, 39–50. https://doi.org/10.1016/j.cognition.2018.06.011
Pennycook, G., & Rand, D. G. (2020). Who falls for fake news? The roles of bullshit
receptivity, overclaiming, familiarity, and analytic-thinking. Journal of Personality,
88(2), 185–200. https://doi.org/10.1111/jopy.12476
Rothgerber, H., Wilson, T., Whaley, D., Rosenberg, D. L., Humphrey, M., Moore, A., &
Bihl, A. (under review). Politicizing the COVID-19 pandemic: Ideological differences
in adherence to social-distancing. https://psyarxiv.com/k23cv/
Russonello, G. (2020, March 13). Afraid of coronavirus? That might say something
about your politics. The New York Times. https://www.nytimes.com/2020/03/13/
us/politics/coronavirus-trump-polling.html
Schnell, L. (2020, March 16). Coronavirus and social distancing: Why people won’t
avoid each other. https://www.usatoday.com/story/news/nation/2020/03/16/cor-
onavirus-social-distancingwhy-people-wont-avoid-each-other/5065228002/
Sheeran, P. (2002). Intention—behavior relations: A conceptual and empirical review.
European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/
14792772143000003
 THINKING & REASONING 477

Sheeran, P., & Webb, T. L. (2016). The intention–behavior gap. Social and Personality
Psychology Compass, 10(9), 503–518. https://doi.org/10.1111/spc3.12265
Simon, H. A. (1997). Models of bounded rationality: Empirically grounded economic
reason. (Vol. 3). MIT Press.
Stagnaro, M. N., Pennycook, G., & Rand, D. G. (2018). Performance on the Cognitive
Reflection Test is stable across time. Judgment and Decision Making, 13(3),
260–267.
Stanley, M. L., Yin, S., & Sinnott-Armstrong, W. (2019). A reason-based explanation
for moral dumbfounding. Judgment and Decision Making, 14(2), 120–129.
Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications
for the rationality debate? The Behavioral and Brain Sciences, 23(5), 645–665.
https://doi.org/10.1017/S0140525X00003435
Swami, V., Voracek, M., Stieger, S., Tran, U. S., & Furnham, A. (2014). Analytic thinking
reduces belief in conspiracy theories . Cognition, 133(3), 572–585. https://doi.org/
10.1016/j.cognition.2014.08.006
Teovanovic, P., Lukic, P., Zupan, Z., Lazic, A., Ninkovic, M., Zezelj, I. (under review).
Irrational beliefs differentially predict adherence to guidelines and pseudoscien-
tific practices during the COVID-19 pandemic. https://psyarxiv.com/gefhn/
Thomson, K. S., & Oppenheimer, D. M. (2016). Investigating an alternate form of the
cognitive reflection test. Judgment and Decision Making, 11(1), 99–113.
Toplak, M. E., West, R. F., & Stanovich, K. E. (2011). The Cognitive Reflection Test as a
predictor of performance on heuristics-and-biases tasks. Memory & Cognition,
39(7), 1275–1289. https://doi.org/10.3758/s13421-011-0104-1
Toplak, M. E., West, R. F., & Stanovich, K. E. (2014). Assessing miserly information
processing: An expansion of the Cognitive Reflection Test. Thinking & Reasoning,
20(2), 147–168. https://doi.org/10.1080/13546783.2013.844729
Van Bavel, J., et al. (in press). Using social and behavioural science to support
COVID-19 pandemic response. Nature Human Behavior. https://psyarxiv.com/
y38m9