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The effects of corrective information about disease epidemics and outbreaks: Evidence from Zika and yellow fever in Brazil

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Disease epidemics and outbreaks often generate conspiracy theories and misperceptions that mislead people about the risks they face and how best to protect themselves. We investigate the effectiveness of interventions aimed at combating false and unsupported information about the Zika epidemic and subsequent yellow fever outbreak in Brazil. Results from a nationally representative survey show that conspiracy theories and other misperceptions about Zika are widely believed. Moreover, results from three preregistered survey experiments suggest that efforts to counter misperceptions about diseases during epidemics and outbreaks may not always be effective. We find that corrective information not only fails to reduce targeted Zika misperceptions but also reduces the accuracy of other beliefs about the disease. In addition, although corrective information about the better-known threat from yellow fever was more effective, none of these corrections affected support for vector control policies or intentions to engage in preventive behavior.
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SCIENCE ADVANCES | RESEARCH ARTICLE
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SOCIAL SCIENCES
The effects of corrective information about disease
epidemics and outbreaks: Evidence from Zika
and yellow fever in Brazil
John M. Carey1, Victoria Chi2, D. J. Flynn3, Brendan Nyhan4*, Thomas Zeitzoff5
Disease epidemics and outbreaks often generate conspiracy theories and misperceptions that mislead people
about the risks they face and how best to protect themselves. We investigate the effectiveness of interventions
aimed at combating false and unsupported information about the Zika epidemic and subsequent yellow fever
outbreak in Brazil. Results from a nationally representative survey show that conspiracy theories and other
misperceptions about Zika are widely believed. Moreover, results from three preregistered survey experiments
suggest that efforts to counter misperceptions about diseases during epidemics and outbreaks may not always
be effective. We find that corrective information not only fails to reduce targeted Zika misperceptions but also
reduces the accuracy of other beliefs about the disease. In addition, although corrective information about the
better-known threat from yellow fever was more effective, none of these corrections affected support for vector
control policies or intentions to engage in preventive behavior.
INTRODUCTION
Public health officials struggle to counter false or unsupported claims
about health, medicine, and science. These false claims can gain ad-
herents and circulate in public discourse and through social networks
despite a lack of scientific evidence to support them (1). This problem
is especially acute during disease epidemics and outbreaks, when
governments must often work to dispel misinformation and build
public knowledge around disease control and prevention in the face
of a surge of misinformation (2,3).
Unfortunately, efforts to counter misinformation can have mixed
or unintended effects. Although corrective information is often some-
what effective at changing beliefs (4), these effects can vary substan-
tially (5) and, in some cases, may be counterproductive for beliefs or
behavior (6). Assessing the effectiveness of efforts to combat misin-
formation about disease epidemics and outbreaks is thus crucial for
public health. There is some evidence that corrective information
can reduce false beliefs about diseases under these circumstances,
but studies conducted to date often rely on fictional scenarios and/
or participants from unaffected countries (7,8).
A particular challenge in this context is that many public health
misperceptions are rooted in conspiracy theories, which attribute
events to the secret actions of malevolent, powerful forces that attempt
to conceal their role (9). These narratives are particularly common
during public crises like disease epidemics. For instance, conspiracy
beliefs and other forms of misinformation have been a major concern
during Ebola outbreaks in West Africa (10,11), the Zika outbreak in
Brazil (12), and the recent yellow fever crisis in Brazil (13). Conspiracy
beliefs often proliferate after unexpected or tragic events like these
because they help people explain away or diminish feelings of lack
of control, chaos, or uncontrolled risks (14). Such effects could be
detrimental—exposure to conspiracy theories has been found to re-
duce people’s intentions to take action to protect themselves from
communicable disease (15). Conspiracy beliefs are thus potentially
dangerous during health emergencies if they discourage people from
taking preventive action and/or reduce support for policies designed
to contain epidemics.
The epidemic of Zika in 2015 and 2016 and subsequent outbreak
of yellow fever in 2018in Brazil illustrate how conspiracy theories
about disease can spread despite attempts by governments to cor-
rect misinformation. False information circulated widely in the
country about the causes of both diseases, the reasons for their
spread, and the consequences they could have for human health.
Public health officials struggled to combat these claims, which, in
some cases, motivated counterproductive policies. For instance,
health officials in parts of Brazil banned a pesticide that helped
control mosquitoes because it was incorrectly believed to cause
microcephaly (16).
We examine the prevalence and persistence of misperceptions
and conspiracy beliefs during the Zika epidemic and yellow fever
outbreak in Brazil. The goal of our study is to see if giving corrective
information of the kind that public health campaigns provide to
citizens can improve the accuracy of people’s beliefs or have other
beneficial effects on public attitudes and behavioral intentions. We
report two principal findings. First, results from a nationally repre-
sentative survey demonstrate that Zika misperceptions and conspiracy
beliefs were prevalent in Brazil during the epidemic. Second, results
from survey experiments conducted there indicate that exposure to
corrective information adapted from World Health Organization
(WHO) failed to measurably decrease beliefs in targeted myths about
Zika, while it unexpectedly decreased the accuracy of other Zika
beliefs. Corrective information was more effective in reducing mis-
perceptions about the better-known threat from yellow fever, but
it did not measurably increase support for vector control policies
or intentions to engage in preventive behavior against mosquitoes
for either disease. These results suggest that current approaches to
combating conspiracy theories and misperceptions may not be ef-
fective and can, in some cases, undermine public understanding of
epidemics. Public health officials and other communicators should
1Department of Government, Dartmouth College, Hanover, NH, USA. 2School of
Medicine, University of California, San Francisco, San Francisco, CA, USA. 3School
of International Relations, IE University, Segovia, Spain. 4Department of Government,
Dartmouth College, Hanover, NH, USA. 5School of Public Affairs, American University,
Washington, DC, USA.
*Corresponding author. Email: nyhan@dartmouth.edu
Copyright © 2020
The Authors, some
rights reserved;
exclusive licensee
American Association
for the Advancement
of Science. No claim to
original U.S. Government
Works. Distributed
under a Creative
Commons Attribution
NonCommercial
License 4.0 (CC BY-NC).
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therefore conduct experimental trials to ensure that information
campaigns are not counterproductive.
METHODS/OVERVIEW
This article proceeds in two parts. We first report the results of a
nationally representative face-to-face survey conducted in Brazil in
April and May 2017 to measure the prevalence of Zika misperceptions
and conspiracy beliefs. Our results, which were collected while Zika
disease transmission was still ongoing and additional Zika-related cases
of microcephaly and Guillain-Barre syndrome were being reported
(17), indicate that most Brazilians understood the role of mosquitoes in
spreading Zika and that the virus was not spread by casual contact.
However, a distressing number of people endorsed misperceptions that
had previously circulated widely in Brazil (often as part of conspiracy
theories) blaming the spread of the disease on genetically modified
mosquitoes and attributing the surge in microcephaly cases to the use
of larvicides in drinking water and to prenatal vaccines (12,18,19).
Second, we report the results of three preregistered survey ex-
periments conducted in 2017 and 2018 on large online samples of
Brazilian adults to test the efficacy of public health messages intended
to reduce conspiracy theories and misperceptions about Zika (both
years) and yellow fever (2018 only). The 2017 Zika experiment ex-
amined the effectiveness of public health communications during
a disease epidemic in which misinformation was spreading widely.
The 2018 Zika experiment was conducted to replicate and extend
our initial findings with a broader set of knowledge items, while the
2018 yellow fever study was conducted to determine whether these
findings would hold in the context of an outbreak of a better-known
disease (see table S1 for an overview of all studies).
The survey and experiments followed all institutional review board
guidelines with respect to human subjects and were reviewed by
Dartmouth College’s Committee for the Protection of Human Subjects
(STUDY00029828; approved 19 September 2016, and modified
30 April 2018).
NATIONALLY REPRESENTATIVE SURVEY
Materials and methods
To measure Brazilians’ beliefs about Zika, we fielded a module as
part of the nationally representative 2017 AmericasBarometer survey.
The survey was coordinated and supervised by the Latin American
Public Opinion Project, which conducts biannual surveys in 29 coun-
tries in the Western Hemisphere. The AmericasBarometer survey
drew from a nationally representative sample of voting age adults
in Brazil that was stratified by major regions of the country, size of
municipality, and urban and rural areas within municipalities. In-
terviews were conducted face to face at respondent residences by
enumerators who used tablet devices to record responses. In total,
surveys were conducted with 1532 respondents from 5 April to
11 May 2017. Table S2 summarizes respondent demographics. Our
module included questions about the causes and consequences of
the Zika outbreak, beliefs in Zika conspiracy theories and misper-
ceptions, support for Zika control policies, preventive behavioral
intentions, and perceived threats posed by Zika. To avoid potential
social desirability effects, none of these claims were referred to as
“conspiracy theories” or “misperceptions” in the survey, which pre-
sented them in a neutral fashion (see the Supplementary Materials
for exact wording).
Results
Brazilians regarded Zika as a serious threat in 2017—8in 10 rated
the threat it posed to health in Brazil as “high” or “very high.” However,
the accuracy of their beliefs about the virus varied substantially.
We first measure beliefs about Zika transmission by asking respon-
dents to evaluate the accuracy of three statements—that Zika can be
transmitted by mosquitoes (true) and by sexual contact (true) and that
it can be transmitted by casual contact (false)—on a four-point scale
ranging from “not at all accurate” to “very accurate.” Figure1A summa-
rizes the percentage of respondents who rated each of the three state-
ments as “very accurate” or “somewhat accurate.” Our data indicate
that 92% of Brazilians endorse the true statement that Zika is spread
by mosquitoes, the dominant mode of infection to date. Moreover,
83% of Brazilians know that Zika is not spread by casual contact—
only 17% endorsed this false claim as accurate. However, just 40%
correctly recognize that Zika can also be spread by sexual contact, a less
frequent vector but one that could pose an increased threat to public
health once rates of infection are established in the population.
The data also indicate that many Brazilians endorse conspiracy
theories and misperceptions regarding Zika that could hinder public
health efforts to raise Zika awareness and encourage prevention.
More than 63% of respondents indicated that it was “very accurate”
or “somewhat accurate” that GMO (genetically modified organism)
mosquitoes spread Zika. Slightly more than half also incorrectly
endorsed claims attributing the increased prevalence of microcephaly
to larvicides and the Tdap vaccine, respectively.
Last, we examine the correlates of these beliefs. Table1 presents
ordinary least squares regression (OLS) models examining the rela-
tionship between demographic characteristics (education, income,
sex, age, urban residence, and region) and the Zika outcome measures
considered earlier: beliefs about possible Zika vectors (columns 1 to 3)
and a composite measure of Zika misperception belief (column 4)
from items measuring belief that Zika is spread by GMO mosquitoes
and that larvicides or the Tdap vaccine caused the increase in
microcephaly ( = 0.57).
Although most of the estimated effects are small and the variance
in Zika-related beliefs accounted for by these factors is limited, we
note the following correlations. First, respondents with more years
of schooling are less likely to believe that Zika is spread through casual
contact and less likely to endorse misperceptions about Zika based
on conspiracy theories (P < 0.005 in both cases). However, more
educated respondents are also less likely to believe that Zika can
be transmitted via sexual contact (P < 0.005). We also find that re-
spondents from urban areas are less likely to believe, incorrectly,
that Zika can be contracted via casual contact (P < 0.005). Last, there
are also regional differences in responses across Brazil. Perhaps most
concerning, in the northeast and southeast—the regions with the
highest numbers of documented Zika infections—respondents are
more likely to be misinformed about transmission via casual contact
(P < 0.005 in both cases) and marginally more likely to endorse
Zika-related misperceptions (P < 0.10 in both cases).
ONLINE SURVEY EXPERIMENTS
To investigate how to counter public health misperceptions and
conspiracy theories, we conducted three preregistered, randomized
online survey experiments on large samples of Brazilian adults in
2017 and 2018. Specifically, we conducted two experiments exam-
ining the effects of corrective information about Zika (in 2017 and
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2018) and one experiment examining the effects of a similar correction
about yellow fever (2018). Both the Zika and yellow fever experiments
randomized exposure to disease-specific corrective information adapted
from WHO materials. In each experiment, we estimated the effect of
exposure to corrective information (relative to a placebo condition)
on endorsement of the Zika/yellow fever misperceptions that were
specifically debunked in our treatments, on belief in other claims
(some factually correct, some incorrect) about Zika/yellow fever, on
support for public policies that could prevent the spread of the disease,
and on self-reported intention to take steps to protect oneself from
the disease. Question wording for all outcome measures is provided
in the Supplementary Materials.
Although corrective information can reduce false beliefs, there
are also reasons for concern. First, corrections can spur directionally
motivated reasoning among people with a predisposition to endorse
conspiracy theories (20) or among people who believe in the specific
misperceptions that are being debunked; for these people, corrections
may fail to reduce misperceptions (21). Similarly, exposure to false
information may, in some cases, produce a so-called continued in-
fluence or belief perseverance effect even after the misinformation
is definitively corrected (22). Introducing false information can in-
crease the familiarity of a false claim and thereby cause it to seem
more plausible, especially over time as memory for the truth value
of the claims fades (23).
Last, unexpected results of the 2017 Zika experiment (discussed
below) led us to consider whether corrective messages could under-
mine people’s confidence in other disease-specific beliefs or in their
ability to understand scientific issues more generally. Research on
meta-cognition demonstrates that people’s confidence in the validity
of their beliefs affects their openness to persuasion (24). These judg-
ments may not always be applied accurately. Research on the so-called
tainted truth effect finds that people who are warned about misin-
formation may overcorrect and become less likely to believe or recall
accurate event details (25). In addition, efforts to intervene to warn
people about the presence of false information can have spillover
effects on belief in accurate claims (26). (Throughout the article, we
use the term “spillover effects” to refer to any impact of corrective
interventions on beliefs that are unrelated to the specific corrective
information delivered.)
Hypotheses
On the basis of the research discussed above, we test the following
hypotheses, which were preregistered in the Evidence in Governance
and Politics (EGAP) archive before researcher access to outcome
data. All deviations from the preregistered study plan are noted below
(URLs omitted for peer review).
First, we test the hypothesis that corrective information about
the disease in question will reduce beliefs in targeted myths about the
disease and increase the accuracy of respondents’ beliefs about these
causes and consequences of the disease both immediately (H1a) and
after a delay (H1b). If these myths undermine support for policies to
prevent the disease in question and reduce behavioral intentions to
protect oneself, then corrective information should increase support
for policies intended to reduce the spread of the Aedes aegypti
mosquito (H2), the primary vector for the disease, and increase
respondents’ intention to protect themselves from mosquito bites
(H3). In addition, we test whether the effects of corrective infor-
m ation on belief in myths about the disease in question vary by re-
spondents’ pretreatment level of trust in governmental and health
institutions (H4a), a factor for which previous studies find differing
results (27,28), and their predisposition to believe in conspiracy
theories (H4b).
To evaluate our interpretation of the results of the 2017 Zika ex-
periment, we preregistered additional hypotheses that were formally
tested only in the 2018 Zika and yellow fever experiments. These
predicted that the myths correction treatment will decrease respondents’
belief in factual claims about the disease that are unrelated to the
content of the treatment (H5a) and respondents’ confidence in their
ability to find the truth behind medical and health disputes (H5b).
We also investigate the following research questions for which
we have weaker theoretical priors and therefore did not preregister
directional hypotheses. First, we consider how a myths correction
treatment affects respondents’ policy opinions and intended behavior
after a delay (RQ1). Second, we examine how the effects of a myths
correction treatment on policy opinions and intended behavior vary
by respondents’ levels of trust and conspiratorial predispositions both
immediately and after a delay (RQ2).
Materials and methods
In the 2017 and 2018 Zika experiments and the 2018 yellow fever
experiment, we randomized participants into a myths correction
treatment condition or into a placebo condition representing the
no-information baseline. Using this between-subjects design, we
tested the effects of corrective information debunking myths about
Zika or yellow fever on the following outcome variables: belief in
the myths targeted by corrective information, other disease-related
AB
0%
20%
40%
60%
80%
100%
Spread by
mosquitoes (T)
Spread by
sexual contact (T)
Spread by
casual contact (F)
0%
20%
40%
60%
80%
100%
GMO mosquitoes
spread Zika (F)
Larvicides increased
microcephaly (F)
Va
ccines increased
microcephaly (F)
Fig. 1. Zika disease beliefs and conspiracy theory endorsement (representative survey). Means and 95% confidence intervals from the Brazil wave of the 2016 and
2017 AmericasBarometer survey (n = 1532; 5 April to 11 May 2017). “T” and “F” indicate true and false, respectively, for the outcome measures.
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beliefs, support for policies to prevent the spread of the disease, and in-
tention to engage in preventive behaviors to protect one’s self from it.
Our treatments reflect how the WHO and other public health
entities communicate information about disease epidemics to af-
fected populations (see the Supplementary Materials for the word-
ing used in the study instruments). The myths correction treatment
used in our Zika experiments was adapted from a report issued by
the WHO titled “Dispelling rumours around Zika and complications”
(http://archive.is/HXd3J). Similarly, the mosquito information and
preventive behavior treatments in our Zika experiments were adapted
from communication materials released by the Pan American Health
Organization for use with the public (http://archive.is/xZpLd and
http://archive.is/osYRl). For the 2018 yellow fever experiment, the
myths correction information was adapted from reports from the
Brazilian Ministry of Health and the fact-checking website AOS Fatos
(http://archive.is/cwJoD and http://archive.is/OYI0F).
Last, the 2017 Zika experiment also tested two alternate public
health messages that were used by the WHO in Brazil: providing
accurate information about the Aedes aegypti mosquito, the main
carrier of Zika, and describing steps people can take to reduce
mosquito breeding in and around their home. Results from these
conditions are described in the Supplementary Materials.
Sample composition
The 2017 Zika experiment and the 2018 Zika and yellow fever ex-
periments were administered online to separate convenience samples
Table 1. Correlates of Zika beliefs and misperceptions (survey data). *P < 0.05, **P < 0.01, ***P < 0.005 (two-sided); OLS models estimated using survey
weights. Data from the Brazil wave of the 2016 and 2017 AmericasBarometer survey (n = 1532; 5 April to 11 May 2017). Outcome variables are measures of
factual belief about Zika and a composite measure indicating greater misperceptions about Zika, respectively (see the Supplementary Materials for wording).
Respondents ages 16 to 30 are the reference category for age, and the north is the excluded category for region.
Spreads via mosquito Spreads via sex Spread via casual contact Misperception beliefs
(mean)
Years of schooling 0.01 −0.05*** −0.05*** −0.08***
(0.01) (0.01) (0.01) (0.01)
Moderate income −0.04 −0.22* −0.15 −0.05
(quartile 2) (0.05) (0.10) (0.08) (0.07)
Medium income −0.01 −0.17 −0.17 −0.16*
(quartile 3) (0.06) (0.13) (0.09) (0.08)
High income 0.01 −0.25* −0.14 −0.14
(quartile 4) (0.06) (0.11) (0.08) (0.08)
Male 0.06 0.00 0.02 −0.13*
(0.04) (0.08) (0.06) (0.05)
Age 31–45 0.08 −0.07 −0.06 0.03
(0.04) (0.08) (0.06) (0.06)
Age 46–60 0.00 −0.16 −0.08 −0.09
(0.06) (0.11) (0.07) (0.08)
Age 61 or older −0.05 0.07 0.24* 0.05
(0.08) (0.14) (0.11) (0.09)
Urban 0.06 −0.08 −0.20*** −0.05
(0.07) (0.09) (0.07) (0.07)
Northeast region 0.03 0.07 0.18*** 0.14
(0.08) (0.11) (0.06) (0.08)
Center-west region −0.05 0.14 0.16 0.05
(0.09) (0.13) (0.10) (0.10)
Southeast region 0.02 0.26* 0.20*** 0.15
(0.06) (0.10) (0.06) (0.08)
South region −0.01 −0.08 0.11 0.03
(0.08) (0.13) (0.07) (0.09)
Constant 3.53*** 2.75*** 2.07*** 3.31***
(0.10) (0.18) (0.11) (0.12)
R20.01 0.05 0.07 0.14
n1402 1331 1391 1284
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of Brazilian adults recruited by an opt-in panel of participants
maintained by online survey vendor Survey Sampling International.
In the 2017 Zika experiment, data collection occurred in two waves.
The first wave, which included our experimental treatments, was
fielded from 12 to 24 April 2017 and included 1283 respondents in
the myths correction and placebo conditions (n = 616 and n = 667,
respectively). These respondents were then recontacted and invited
to participate in a second wave of the study, which was fielded from
1 to 30 May 2017 and included the same outcome measures as wave 1.
The median interval between responses to waves 1 and 2 among
those who participated in both was 17 days. In total, 899 respondents
participated in the second wave (recontact rate, 70.6%). Attrition
did not vary systematically between conditions (P = 0.16), although
wave 2 respondents were significantly older and more educated and
more likely to self-identify as white (see table S2 for descriptive
statistics on the wave 1 and 2 samples).
The 2018 Zika and yellow fever experiments were conducted from
17 to 31 May 2018. A total of 2173 respondents were randomly as-
signed to either the Zika experiment or the yellow fever experiment
(n = 1081 and n = 1092, respectively). Respondents in each experi-
ment were then randomly assigned to a disease-specific myths cor-
rection condition (n = 547 for Zika, n = 501 for yellow fever) or to a
placebo condition (n = 534 for Zika, n = 591 for yellow fever).
We note that these experiments were conducted at different points
in the life cycles of the two diseases. Zika was a new disease to Brazil
when it began to spread in late 2015. Cases of Zika and Google Trends
data on searches for information about the disease peaked in Brazil
during the first few months of 2016, just over 1 year before our
2017 Zika experiment and 2 years before our 2018 Zika experiment
(29,30). By contrast, yellow fever was a more familiar disease in Brazil
but the outbreak was also a more recent experience for participants
in our 2018 yellow fever experiment—cases of and search interest in
the disease peaked in January and February 2018, just a few months
before our study (31). The expected effects of these differences in
timing on our experiments are not obvious. If beliefs are more firm
when an issue is at peak salience, then we might expect our corrective
treatments to have less effect on beliefs about yellow fever compared
with Zika. Alternatively, if beliefs take root over time, then the relative
impact of corrective information might be reversed.
Consistent with other opt-in internet samples, participants in these
studies are more white, educated, and wealthy than the Brazilian
population (see table S2, which compares the characteristics of the
online samples with our representative face-to-face survey sample).
However, online convenience samples such as these have been shown
to generate experimental treatment effect estimates that closely cor-
respond to those obtained from representative samples (32,33).
Balance tests indicate the experimental randomizations were successful
(details available upon request).
Outcome measures
We collected four types of outcome measures in each of our ex-
periments (the exact wording of all questions is provided in the
Supplementary Materials). These measures capture belief in mis-
perceptions that were targeted by the corrective information treatment,
other beliefs related to the disease or its effects, support for policies
intended to reduce the spread of the disease, and self-reported in-
tention to engage in preventive behaviors.
The misperceptions targeted by the myths correction treatment
were the same in both the 2017 and 2018 Zika experiments: the be-
liefs that GMO mosquitoes caused the outbreak and that larvicides
or vaccines cause microcephaly. In the yellow fever experiment, the
myths correction treatment instead targeted beliefs that the yellow
fever vaccine had been rendered ineffective by genetic mutations in
the virus, that the vaccine has life-threatening side effects, and that
an alternative remedy based on a propolis made by bees provides
effective protection against infection. No nationally representative
data exist on the prevalence of these myths that is analogous to our
Zika survey, but Brazilian and international news sources reported
that the misperceptions about yellow fever we tested were being
widely circulated online in early 2018 (13,34,35).
As noted above, we also measured other disease-related beliefs
that were not targeted by the myths correction treatment. The 2017
Zika experiment measured people’s beliefs that Zika can be contracted
via mosquito bite (true), by sex (true), and by casual contact (false),
and that Zika has potential neurological effects (true). The 2018 Zika
experiment not only included these items but also measured beliefs
in additional true statements about potential transmission of the virus
in utero and via blood transfusion and its connection to microcephaly,
as well as false statements about microcephaly causing paralysis and
vulnerability to Zika among people with weakened immune systems.
The 2018 yellow fever experiment included a similar set of disease-
related belief questions. These included belief in true statements that
the disease spreads via mosquito bite, that it is spread by the same
mosquito as Zika, that its symptoms include fever and vomiting, that
the disease can be fatal, that it is now present in cities, and that the
government recommends all Brazilians be immunized, as well as belief
in incorrect statements that there is no effective vaccine for yellow
fever, that the vaccine can cause damage to the immune system, and
that the vaccine is a fraud perpetrated by drug companies.
The third set of outcomes measured support for policies intended
to reduce the spread of the disease. These were the same in both
Zika experiments, which asked respondents about their support for
government policies of releasing GMO mosquitoes to limit disease
spread, treating water with larvicides, authorizing health officials to
enter properties to prevent mosquito-breeding conditions, and rec-
ommending the Tdap vaccine. In the yellow fever experiment, we
included the first three of these policies and support for fining citizens
who do not get vaccinated against yellow fever and for requiring the
vaccine for children attending public schools.
The fourth category, preventive intentions, was identical in each
experiment. Respondents were asked about their use of long-sleeved
shirts and pants, mosquito spray/repellent, and screens or closed
windows to keep mosquitoes out.
The items measuring beliefs targeted by the myths correction
treatment and other disease-related beliefs are measured on a four-
point Likert scale from “not at all accurate” to “very accurate.” The
policy response items are scored on a 1 (strongly disapprove) to 10
(strongly approve) scale. The behavioral measures are scored on a
five-point scale from never (1) to always (5).
Following our preregistration, we conducted principal components
factor analysis to examine the extent to which the relevant questions
from each set described above constitute reliable scales of targeted
misperceptions, other disease-related beliefs, policy support, and pre-
ventive intentions. In the first, third, and fourth sets, we found that
the items load onto a single factor. In those cases, we create com-
posite indices based on all the items in the group. The questions on
other disease-related beliefs, however, do not load onto a single factor,
and we therefore analyze responses to each of them separately.
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Last, the 2018 Zika and yellow fever experiments measure re-
spondents’ beliefs that they can discern the truth about health and
science issues, which was adapted from previous research (36). The
exact wording is provided in the Supplementary Appendix.
Results: 2017 and 2018 Zika experiments
We first present the results of the 2017 and 2018 Zika experiments.
Both studies (which use identical designs) estimate the effects of
exposure to our myths correction message in a series of OLS re-
gression models with robust standard errors (all reported P values are
two-sided). However, all results in the main text from the 2017 and
2018 Zika experiments and the 2018 yellow fever experiment are
substantively identical when estimated using ordered probit models
(see the Supplementary Materials).
We begin by examining the effect of corrective information on
endorsement of Zika misperceptions. Table2 summarizes the effects
of the myths correction treatment on the Zika-related misperceptions
targeted in both the 2017 and 2018 experiments. The treatment failed
to reduce mean belief in these myths significantly in either experi-
ment. In the 2017 experiment, the myths correction treatment had
no measurable effect on any of the three mistaken or unsupported
claims compared to the placebo condition. Similarly, the 2018 study
found that the myths correction treatment had no measurable effect
on misperceptions beliefs overall or in specific beliefs that larvicides
cause Zika or that vaccines cause microcephaly in the 2018 experi-
ment, although beliefs in GMO mosquito transmission did decline
significantly (P = 0.002). These findings are precisely estimated; the
95% confidence intervals for the myths correction treatment effects
in the experiments exclude even small positive effects on the four-point
misperceptions index (2017, −0.08, 0.08; 2018, −0.14, 0.04). H1a is
thus not supported.
Exploratory analyses suggest that these null results are not at-
tributable to a lack of respondent attention to the experimental stimuli.
The median time respondents spent viewing the information of in-
terest was quite high for an online survey: 54.7 s (2017) and 54.8 s
(2018) for the placebo conditions and 57.9 s (2017) and 53.8 s (2018)
for the myths correction treatments.
Additional analyses reveal that corrective information is similarly
ineffective among respondents who may have differing levels of
pretreatment motivation to endorse conspiracy theories. In particular,
there is no consistent evidence in either study that the effects of
the myths correction treatment vary by respondents’ conspiratorial
predispositions or trust in governmental and health institutions
(H4a and H4b, respectively; see the Supplementary Materials).
Apart from its effects on targeted misperceptions, corrective
information might affect other beliefs that respondents hold about
the disease in question. Table3A and fig. S1B indicate that the
myths correction treatment unexpectedly reduced the accuracy of
respondent’s beliefs about two of three true factual claims in the
2017 Zika experiment. Specifically, the perceived accuracy of state-
ments about Zika’s neurological effects and the role of mosquitoes
in spreading the disease declined (P < 0.005in both cases), although
the treatment had no measurable effect on beliefs about Zika being
transmitted through sexual contact (P = 0.60). In addition, the myths
correction treatment decreased the incorrect belief that Zika can be
transmitted by casual contact such as a handshake (P = 0.002), sug-
gesting that the treatment reduced the perceived accuracy of claims
about Zika regardless of whether they are true or untrue. These ef-
fects are also jointly significant in an exploratory F test of the null
hypothesis of no effect on respondent beliefs across these four out-
come variables (P < 0.005).
In the 2018 Zika experiment, we therefore tested the hypothesis
that the myths correction treatment undermines belief in factual
claims about the disease more generally (H5a). Our results again
indicated that people became less likely to believe in statements
about Zika after exposure to the myths correction treatment. These
effects were particularly concentrated among accurate statements—
exposure to the treatment reduced the accuracy of beliefs about four
of six true factual claims but did not move beliefs significantly for
any of the three false claims tested. An exploratory F test again finds
Table 2. Correction effects on targeted Zika misperceptions. *P < 0.05, **P < 0.01, ***P < 0.005 (two-sided); OLS models with robust standard errors.
Respondents are separate samples from Survey Sampling International’s online panel in Brazil. For each outcome measure, higher values indicate greater belief
in the claim or claims in question [measured on a Likert scale ranging from “not at all accurate” (1) to “very accurate” (4); see the Supplementary Materials for
wording]. All outcome measures are false.
Misperception beliefs
(mean)
GMO mosquitoes caused
outbreak
Larvicides responsible for
microcephaly
Vaccines responsible for
microcephaly
A. 2017 Zika experiment
Myths correction −0.00 −0.08 0.02 0.07
(0.04) (0.06) (0.05) (0.05)
Constant 1.69*** 1.92*** 1.63*** 1.53***
(0.03) (0.04) (0.04) (0.04)
n1249 1260 1254 1255
B. 2018 Zika experiment
Myths correction −0.06 −0.19*** 0.01 0.01
(0.05) (0.06) (0.06) (0.06)
Constant (placebo) 1.68*** 1.89*** 1.62*** 1.55***
(0.03) (0.05) (0.04) (0.04)
n1049 1059 1062 1058
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that we can reject the null hypothesis of no treatment effect across
the nine outcome variables (P < 0.005).
Overall, across two Zika experiments, the myths correction treat-
ment measurably decreased belief in 7 of 13 statements about Zika,
including 6 of the 9 accurate statements that were tested. All seven
remain significant at the P < 0.05 level in an exploratory analysis
using the Benjamini-Hochberg procedure to control the false dis-
covery rate. Although the magnitude of these effects is modest
(Cohen’s d, 0.15 to 0.27; median, 0.19), the results paradoxically
suggest that attempts to rebut misperceptions and conspiracy theo-
ries with corrective information actually reduced the accuracy of
people’s beliefs about the true causes and consequences of Zika.
One interpretation of these results is that people became con-
fused or less certain about what they knew as a result of exposure
to the myths correction treatments. Across both Zika experiments,
negative spillover effects on respondent knowledge were highly
negatively correlated with baseline beliefs. This effect was observed
for true statements (r = − 0.55) but not false ones (r = − 0.03), a
finding that does not appear to be the result of a floor effect.
Why would such an effect occur? Treated respondents do not
self-report feeling they are less able to discern the truth about com-
plex health and science issues (H5b; see tables S21 and S29 for results
from both the 2018 Zika and yellow fever experiments). Similarly,
exploratory analyses also provide no consistent evidence that these
effects vary by education or science knowledge (see tables S11 and
S20), suggesting that the problem is more complex than a lack of
understanding of the scientific information respondents were pro-
vided. Another possible interpretation is that respondents who skim
the materials learn the gist (that some information about Zika is false)
and apply it indiscriminately to other Zika-related beliefs. However,
we find no consistent evidence of larger negative spillover effects on
respondent knowledge among respondents who completed the pre-
treatment portion of the survey more quickly or who read the ex-
perimental materials more quickly in additional exploratory analyses
(see tables S30 and S31).
Our results are instead consistent with a tainted truth effect in
which a warning that specific information acquired previously is
unreliable can diminish beliefs on related information not addressed
in the warning (25). Corrections, like warnings, may increase skep-
ticism generally, creating collateral damage to belief in accurate claims
and information (26). Still, more research is needed to understand
the mechanism by which corrective information decreases agreement
with true claims, a question we address further in Discussion.
We also examined the effect of the myths correction treatment
on respondents’ support for public policies intended to prevent Zika
(H2) and respondents’ intentions to engage in preventive behavior
(H3). As table S4 indicates, the treatment failed to significantly affect
these outcome measures.
Last, to assess the durability of the effects of the myths correction
treatment, the 2017 Zika experiment also surveyed participants after
a delay and again measured our outcome variables. While commu-
nication effects generally decay over time, one potential concern with
informational treatments such as ours is “illusion of truth” effects,
which refer to people’s tendency to incorrectly remember previously
discredited information as true at later points in time (23). For in-
stance, while the myths and facts treatment did not have immediate
effects on targeted misperceptions, it is possible that this message could
have increased familiarity with the targeted claims and therefore
Table 3. Correction effects on other Zika beliefs. *P < 0.05, **P < 0.01, ***P < 0.005 (two-sided); OLS models with robust standard errors. Respondents are
members of Survey Sampling International’s online panel in Brazil. For each outcome measure, higher values indicate greater belief in the claim or claims in
question [measured on a Likert scale ranging from “not at all accurate” (1) to “very accurate” (4); see the Supplementary Materials for wording]. “T” and “F”
indicate true and false, respectively, for the outcome measures.
(A) 2017 Zika experiment
Causes neurological
problems (T)
Spreads
via
mosquito
bite (T)
Spreads via sexual
contact (T) Spread via casual contact (F)
Myths correction −0.22*** −0.09*** −0.03 −0.10***
(0.06) (0.03) (0.07) (0.03)
Constant (placebo) 3.01*** 3.85*** 1.98*** 1.25***
(0.04) (0.02) (0.05) (0.03)
n1259 1261 1260 1261
(B) 2018 Zika experiment
Causes
neurological
problems (T)
Spreads
via
mosquito
bite (T)
Spreads
via sexual
contact (T)
Spread via
casual
contact (F)
Weak
immune more
vulnerable (F)
Transmit
Zika in
utero (T)
Zika increases
microcephaly (T)
Get Zika
from
donated
blood (T)
Microcephaly
causes
paralysis (F)
Myths
correction
−0.20*** −0.13*** −0.04 −0.04 −0.04 −0.15* −0.19*** −0.12 −0.10
(0.06) (0.04) (0.07) (0.04) (0.07) (0.06) (0.04) (0.07) (0.06)
Constant
(placebo)
3.00*** 3.83*** 1.86*** 1.26*** 2.71*** 3.37*** 3.69*** 2.54*** 2.82***
(0.04) (0.02) (0.05) (0.03) (0.05) (0.04) (0.03) (0.05) (0.04)
n1059 1061 1053 1061 1057 1056 1056 1059 1062
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increased their credibility at a later point in time. To examine this
possibility (H1b), we recontacted respondents in the myths correction
and placebo conditions after a delay and measured our outcome
variables again. We find that the immediate effect of the myths and
facts treatment on factual beliefs disappears after a delay (see table
S12). Moreover, we find no significant differences in belief in tar-
geted misperceptions, policy opinions, or behavioral intentions
between these groups after a delay. Mirroring the results from wave 1,
we also find no evidence that the effect of the myths correction
treatment varies with respondents’ conspiratorial predispositions
or trust in government and health institutions.
Results: 2018 yellow fever experiment
Experimental evaluation of a myths correction treatment on beliefs
about yellow fever provided more encouraging results than those
obtained for Zika. Table4 shows the effects of a myths correction
treatment on targeted misperceptions (Table4A) and on factual
claims unrelated to those addressed in the treatment (Table4B).
The treatment diminished beliefs in two of the three targeted mis-
perceptions (on the side effects of the vaccine and on the effects of
propolis) and reduced overall misperceptions, providing support
for H1a. The effect of the myths correction treatment on belief in
other factual claims about the disease was weaker and less consistent
than observed in the 2017 and 2018 Zika experiments. The yellow
fever myths correction treatment increased belief in one of six true
claims about the disease—that yellow fever is spread by the same
mosquito as Zika—and diminished belief slightly in another—that
yellow fever can be fatal. The treatment also diminished belief in
one of three false claims—that the vaccine can damage the immune
system. Beliefs in six of the nine claims unrelated to the treatment
were unaffected. We thus do not find support for H5a. As noted
above, H5b was also unsupported (see the Supplementary Materials).
The myths correction treatment had no effect on support for
policies intended to reduce the spread of the disease, although in-
tentions to engage in behaviors to protect oneself from yellow fever
did increase significantly (P < 0.05; see the Supplementary Materials).
Last, as in the 2017 and 2018 Zika experiments, we found no evi-
dence that these experimental effects varied by trust in governmental
and health institutions or respondents’ predisposition to believe in
conspiracy theories (H4a/H4b; see the Supplementary Materials).
DISCUSSION
During disease epidemics and outbreaks, public health officials fre-
quently struggle to counter conspiracy theories and misperceptions
that discourage citizens from taking preventive action and reduce
support for policies designed to contain the spread of disease. This
article examines the prevalence and persistence of misperceptions
and conspiracy theories in Brazil and reports results from preregistered
experiments examining the effectiveness of current approaches to
combating false beliefs during the Zika epidemic and subsequent yellow
fever outbreak in the country.
Nationally representative survey results from Brazil indicate that
the public is only partially informed about Zika and is vulnerable to
false or unsupported beliefs. On a more positive note, Brazilians are
well informed about whether Zika can be transmitted via mosquito
bites and casual contact. However, they have less accurate beliefs
about the risks of sexual contact, a less widely discussed mode of
transmission. In addition, more than 63% of respondents falsely
endorse the myth that GMO mosquitoes spread Zika when asked
Table 4. 2018 yellow fever experiment results. *P < 0.05, **P < .01, ***P < .005 (two-sided); OLS models with robust standard errors. Respondents are members
of Survey Sampling International’s online panel in Brazil. For each outcome measure, higher values indicate greater belief in the claim or claims in question
[measured on a Likert scale ranging from “not at all accurate” (1) to “very accurate” (4); see the Supplementary Materials for wording]. “Misperception belief” is a
composite measure calculated as the mean of the three items listed. All misperception measures are false. “T” and “F” indicate true and false, respectively, for the
other outcome measures.
(A) Correction effects on targeted yellow fever misperceptions
Misperception beliefs
(mean)
Yellow fever vaccine
ineffective
Life-threatening
side effects Propolis protects from yellow fever
Myths correction −0.20*** −0.03 −0.20*** −0.38***
(0.04) (0.06) (0.06) (0.06)
Constant (placebo) 1.98*** 1.82*** 2.00*** 2.13***
(0.03) (0.04) (0.04) (0.04)
n1063 1072 1072 1075
(B) Correction effects on other yellow fever beliefs
Spreads
via
mosquito
bite (T)
No
effective
vaccine (F)
Same
mosquito as
Zika (T)
Symptoms
include
fever,
vomiting (T)
Disease
can be
fatal (T)
Government
recommends
vaccine (T)
Yellow fever
in cities (T)
Vaccine
causes
immune
damage (F)
Hoax by
drug
companies (F)
Myths
correction
0.04 0.01 0.36*** 0.02 −0.07* 0.11 0.03 −0.14* 0.03
(0.04) (0.05) (0.06) (0.04) (0.04) (0.06) (0.04) (0.06) (0.05)
Constant
(placebo)
3.77*** 1.55*** 3.10*** 3.68*** 3.82*** 3.09*** 3.51*** 2.01*** 1.45***
(0.03) (0.03) (0.05) (0.02) (0.02) (0.04) (0.03) (0.04) (0.03)
n1068 1077 1070 1075 1073 1073 1073 1074 1068
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and more than half incorrectly state that larvicides in water and pre-
natal vaccines cause microcephaly.
Perhaps most concerning, we find that current approaches to
combating misinformation and conspiracy theories about disease
epidemics and outbreaks may be ineffective or even counterproductive.
In separate experiments in 2017 and 2018, we found that a myths
correction message fails to reduce overall belief in the Zika-related
misperceptions it targeted. This failure was widespread and occurred
among respondents with both high and low motivation to endorse
conspiracies. We also found unexpected evidence that the myths
correction approach causes collateral damage by reducing belief in
other factual claims about Zika that are actually true. The myths
correction treatment significantly reduced the perceived accuracy
of 7 of 13 factual claims tested in the 2017 and 2018 experiments that
were not targeted by the myths correction treatment. In particular,
belief in six of nine scientifically accurate facts that we tested declined
significantly.
In a separate experiment conducted in 2018 on beliefs related to
yellow fever, a myths correction treatment was more effective, de-
creasing false beliefs overall and for two of three misperceptions that
the message debunked. This treatment also inflicted less collateral
damage on the accuracy of people’s beliefs about the outbreak than
the one used in the Zika experiments.
One potential explanation for these differing results is that general
knowledge about yellow fever is better established among Brazilians.
The disease has been present in the Americas for over a century and
has been a longstanding target of public health efforts. By contrast,
Zika’s first confirmed case in Brazil occurred in 2015. As such,
Zika-related beliefs may be less firmly rooted and more vulnerable
to spillover effects. This interpretation suggests that the risk of cor-
rective information reducing the accuracy of other disease-related
beliefs is lower in situations where baseline knowledge is well estab-
lished (as with yellow fever in Brazil). By contrast, where public
knowledge is less firm, as with Zika (and perhaps other recent ep-
idemics like Ebola), the risk of collateral damage from corrective
information to other knowledge may be higher. This distinction is
consistent with the differing results from our yellow fever and Zika
experiments, but should be tested further in future research, including
other contexts besides Brazil.
Our research does have limitations. First, it is possible that social
desirability concerns affected responses to our survey measures of
misperception belief. We sought to reduce these concerns by avoiding
the use of potentially stigmatizing language and conducting our
experiment online. Moreover, our findings are not obviously con-
sistent with such an account. Most notably, we found widespread
expression of conspiracy belief in our face-to-face survey, where social
desirability pressures are likely to be greatest. Nonetheless, future
research should consider using experimental designs intended to test
for such effects. Second, the linkage between factual beliefs and public
policy attitudes is complex and should be explored further. Other
values or considerations may be more important determinants of
opinion toward policies intended to reduce the spread of Zika and
yellow fever. Third, it would be desirable to verify that our experi-
mental results replicate among a representative sample of Brazilians.
Last, future research should test whether these results vary with dif-
ferent information sources or formats. We chose not to test such
variations because they could reduce our power to detect main effects
and also potentially induce heterogeneous treatment effects based
on source trust and literacy that are even more difficult to test with
appropriate statistical power. Still, source and information format
effects should be investigated further in this context.
Despite these limitations, we contribute to the broader literature
on misperceptions and conspiracy theory belief in two important
respects. First, our findings echo other research showing that efforts
to warn people about the presence of false information can have
unexpected spillover effects on their belief in other claims (26,37).
In particular, a general warning about the presence of fake news has
been found to decrease belief in the accuracy of both false and legit-
imate news headlines (26). Second, these findings demonstrate further
evidence that providing accurate factual information does not always
have the expected effect on public support for related policies or
leaders (21).
The knowledge spillover effects we find underscore the need for
further randomized controlled trials testing the effects of health mes-
sages on attitudinal and behavioral outcomes. Although the Zika ep-
idemic has ended, the study of misperceptions and how to address
them has implications for numerous regions and diseases around the
world. To prepare for future disease outbreaks, we must know more
about the prevalence of conspiracy theories and misperceptions, which
types of citizens endorse them, and how to effectively combat them.
Until more is known, however, public health professionals should
have realistic expectations about the effectiveness of efforts to pro-
vide corrective information during disease outbreaks. It may be more
effective to instead pursue alternative strategies that do not involve
direct debunking such as educational programs to encourage parents
and children to engage with public health information (38), partic-
ipatory approaches that enlist local medical practitioners to dissem-
inate information about disease vectors (39), and encouragement of
publicly visible prevention and protection measures that might en-
courage emulation through peer pressure (40). In some cases, the best
way to defeat misperceptions may be to avoid challenging them directly.
SUPPLEMENTARY MATERIALS
Supplementary material for this article is available at http://advances.sciencemag.org/cgi/
content/full/6/5/eaaw7449/DC1
Survey instruments
Additional results
Fig. S1. Beliefs about Zika (experimental data).
Table S1. Study summaries.
Table S2. Sample statistics.
Table S3. Treatment effects on Zika beliefs (experimental data).
Table S4. Treatment effects on Zika attitudes and behavioral intentions.
Table S5. Correction effects in 2017 Zika experiment (ordered probit).
Table S6. Treatment effects on Zika beliefs and attitudes (conspiracy predispositions).
Table S7. Treatment effects on Zika beliefs and attitudes (confidence in government).
Table S8. Treatment effects on Zika beliefs and attitudes (confidence in Ministry of Health).
Table S9. Treatment effects on Zika beliefs and attitudes (confidence in medicine).
Table S10. Treatment effects on Zika beliefs and attitudes (confidence in scientists).
Table S11. Correction effects on other Zika beliefs in 2017 Zika experiment.
Table S12. Correction effects on Zika beliefs and attitudes after delay.
Table S13. Treatment effects on Zika attitudes and behavioral intentions.
Table S14. Correction effects in 2018 Zika experiment (ordered probit).
Table S15. Treatment effects on Zika beliefs and attitudes (conspiracy predispositions).
Table S16. Treatment effects on Zika beliefs and attitudes (confidence in government).
Table S17. Treatment effects on Zika beliefs and attitudes (confidence in Ministry of Health).
Table S18. Treatment effects on Zika beliefs and attitudes (confidence in medicine).
Table S19. Treatment effects on Zika beliefs and attitudes (confidence in scientists).
Table S20. Correction effects on other Zika beliefs in 2018 Zika experiment.
Table S21. Treatment effect on perceived ability to discern truth about health/science.
Table S22. Treatment effects on yellow fever attitudes and behavioral intentions.
Table S23. Correction effects in 2018 yellow fever experiment (ordered probit).
Table S24. Treatment effects on yellow fever beliefs and attitudes (conspiracy predispositions).
Table S25. Treatment effects on yellow fever beliefs and attitudes (confidence in government).
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Table S26. Treatment effects on yellow fever beliefs and attitudes (confidence in Ministry of
Health).
Table S27. Treatment effects on yellow fever beliefs and attitudes (confidence in medicine).
Table S28. Treatment effects on yellow fever beliefs and attitudes (confidence in scientists).
Table S29. Treatment effect on perceived ability to discern truth about health/science.
Table S30. Correction effects on other Zika beliefs by pre-experiment response time.
Table S31. Correction effects on other Zika beliefs by experimental response time.
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Acknowledgments: We thank S. Clifford, T. Lahey, N. Lee, A. Ozer, B. Simas, and participants in
seminars at Harvard University, the Political Misperceptions Conference at the University of
Houston, and the Evidence in Governance and Politics conference at Yale University for helpful
comments; C. D. L. E. Silva for translation assistance; J. Davidson, J. Fidalgo, E. Morgan, and
M. Sandhu for research assistance; and M. J. Cohen and E. Zechmeister of the Latin American
Public Opinion Project for assistance with the administration of our AmericasBarometer survey
module. Funding: This study was supported by the Decision, Risk and Management Sciences
program at the NSF (award 1659128) and the Global Health Initiative of the John Sloan Dickey
Center for International Understanding at Dartmouth College. Author contributions: All
authors designed the study and wrote the original manuscript. J.M.C., B.N., and T.Z. revised the
manuscript. B.N. and D.J.F. analyzed the data. Competing interests: The authors declare that
they have no competing interests. Data and materials availability: All data needed to
evaluate the conclusions in the paper are present in the paper and/or the Supplementary
Materials. Replication data and Stata code for all our findings will be made available upon
publication in the Dataverse archive with the identifier (https://doi.org/10.7910/DVN/86M3S1).
Additional data related to this paper may be requested from the authors.
Submitted 21 January 2019
Accepted 20 November 2019
Published 29 January 2020
10.1126/sciadv.aaw7449
Citation: J. M. Carey, V. Chi, D. J. Flynn, B. Nyhan, T. Zeitzoff, The effects of corrective information
about disease epidemics and outbreaks: Evidence from Zika and yellow fever in Brazil. Sci. Adv.
6, eaaw7449 (2020).
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... Embora a eficácia dessas medidas e seu impacto no bem-estar da população mundial continuem sendo discutidas (Van Prooijen & Van Vugt, 2018), as evidências disponíveis (e.g., Carey, Chi, Flynn, Nyhan, & Zeitzoff, 2020;Torales, O'Higgins, Castaldelli-Maia, & Ventriglio, 2020), elas indicam que a capacidade individual e a vontade de cumprir ações de isolamento social estão associadas a uma série de fatores de natureza econômica, política e psicológica. A alta carga de informações transmitidas simultaneamente por variados veículos de comunicação e mídia (e.g., redes sociais, internet, TV), os quais nem sempre permitem avaliar sua procedência e pertinência, impacta em diferentes esferas da estrutura social, interferindo, inclusive, em dimensões psicológicas e sociais. ...
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... Comme mentionné précédemment, la mentalité conspirationniste a été particulièrement utilisée pour théoriser une forme d'idéologie politique conspirationniste (Imhoff & Bruder, 2014). Il a également été suggéré que l'adhésion aux théories du complot politique s'inscrive dans le système de croyance monologique, en étant corrélée à d'autres théories du complot spécifiques comme les théories du complot médicales (Galliford & Furnham, 2017 Swami, 2012), au Moyen-Orient (e.g., Sallam et al., 2021), en Afrique (e.g., Olatunji et al., 2020) ou encore en Amérique du Sud (e.g., Carey et al., 2020). ...
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The study reports on a meta-analysis of attempts to correct misinformation (k = 65). Results indicate that corrective messages have a moderate influence on belief in misinformation (r = .35); however, it is more difficult to correct for misinformation in the context of politics (r = .15) and marketing (r = .18) than health (r = .27). Correction of real-world misinformation is more challenging (r = .14), as opposed to constructed misinformation (r = .48). Rebuttals (r = .38) are more effective than forewarnings (r = .16), and appeals to coherence (r = .55) outperform fact-checking (r = .25), and appeals to credibility (r = .14).
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To what extent do survey experimental treatment effect estimates generalize to other populations and contexts? Survey experiments conducted on convenience samples have often been criticized on the grounds that subjects are sufficiently different from the public at large to render the results of such experiments uninformative more broadly. In the presence of moderate treatment effect heterogeneity, however, such concerns may be allayed. I provide evidence from a series of 15 replication experiments that results derived from convenience samples like Amazon’s Mechanical Turk are similar to those obtained from national samples. Either the treatments deployed in these experiments cause similar responses for many subject types or convenience and national samples do not differ much with respect to treatment effect moderators. Using evidence of limited within-experiment heterogeneity, I show that the former is likely to be the case. Despite a wide diversity of background characteristics across samples, the effects uncovered in these experiments appear to be relatively homogeneous.