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There has been increasing concern with the growing infusion of misinformation, or “fake news”, into public discourse and politics in many western democracies. Our article first briefly reviews the current state of the literature on conventional countermeasures to misinformation. We then explore proactive measures to prevent misinformation from finding traction in the first place that is based on the psychological theory of “inoculation”. Inoculation rests on the idea that if people are forewarned that they might be misinformed and are exposed to weakened examples of the ways in which they might be misled, they will become more immune to misinformation. We review a number of techniques that can boost people’s resilience to misinformation, ranging from general warnings to more specific instructions about misleading (rhetorical) techniques. We show that based on the available evidence, inoculation appears to be a promising avenue to help protect people from misinformation and “fake news”.
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European Review of Social Psychology
ISSN: (Print) (Online) Journal homepage:
Countering Misinformation and Fake News
Through Inoculation and Prebunking
Stephan Lewandowsky & Sander van der Linden
To cite this article: Stephan Lewandowsky & Sander van der Linden (2021): Countering
Misinformation and Fake News Through Inoculation and Prebunking, European Review of Social
Psychology, DOI: 10.1080/10463283.2021.1876983
To link to this article:
Published online: 22 Feb 2021.
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Countering Misinformation and Fake News Through
Inoculation and Prebunking
Stephan Lewandowsky
and Sander van der Linden
School of Psychological Science, University of Bristol and University of Western, Crawley, WA,
Department of Psychology, University of Cambridge, Cambridge
There has been increasing concern with the growing infusion of misinforma-
tion, or “fake news”, into public discourse and politics in many western democ-
racies. Our article rst briey reviews the current state of the literature on
conventional countermeasures to misinformation. We then explore proactive
measures to prevent misinformation from nding traction in the rst place that
is based on the psychological theory of “inoculation”. Inoculation rests on the
idea that if people are forewarned that they might be misinformed and are
exposed to weakened examples of the ways in which they might be misled,
they will become more immune to misinformation. We review a number of
techniques that can boost people’s resilience to misinformation, ranging from
general warnings to more specic instructions about misleading (rhetorical)
techniques. We show that based on the available evidence, inoculation appears
to be a promising avenue to help protect people from misinformation and “fake
KEYWORDS Fake News; Misinformation; Inoculation Theory; Prebunking
Countering Misinformation and Fake News Through Inoculation and
“We can develop belief resistance in people as we develop disease resis-
tance in a biologically overprotected man or animal: by exposing the person
to a weak dose of the attacking material, strong enough to stimulate his [or
her] defenses, but not strong enough to overwhelm them.” (McGuire,
1970, p. 37)
“Just remember, what you’re seeing and what you’re reading is not what’s
happening.” (U.S. President Donald Trump, 24 July 2018)
“Post-truth” was nominated word of the year by Oxford dictionaries in
2016, to describe “circumstances in which objective facts are less influential
in shaping public opinion than appeals to emotion and personal belief”
CONTACT Stephan Lewandowsky School of Psychological
Science, University of Bristol, 12A Priory Road, Bristol BS8 1TU, Australia
Author note
Both authors contributed equally.
© 2021 European Association of Social Psychology
(OED, 2016). Two political events in 2016 triggered the concern with truth–
or rather its absence: The Brexit referendum in the UK and the election of
Donald Trump in the U.S. During the Brexit referendum, the public’s
“epistemic rights”—that is, their right to be adequately informed—were
serially violated by the British tabloids (Watson, 2018), and during the
U.S. presidential campaign, independent fact checkers judged 70% of all
statements by Donald Trump to be false or mostly false.
This situation invites at least two questions: First, can “fact-checking”
provide a solution to “post-truth” politics? Second, instead of solely relying
on fact-checking, could the public be given the skills and tools required to
manage an environment in which political misinformation abounds?
Misinformation and Society
Misinformation sticks. Erasing “fake news” from one’s memory is
a challenging task, even under the best of circumstances; that is, in the
psychological laboratory when participants are motivated to be accurate
and are free from distraction (for a review, see Lewandowsky et al., 2012).
In the cardinal misinformation experiment, people are presented with
a fictitious scripted story (e.g., about a warehouse fire). In one condition,
information that was presented early on (e.g., that oil paint had been found
in a wiring cabinet) is explicitly corrected later in the script (e.g., the wiring
cabinet was actually empty). In a control condition, the script never contains
a correction and the wiring cabinet is presented as empty from the outset
(e.g., Ecker et al., 2011; Johnson & Seifert, 1994; Wilkes & Leatherbarrow,
1988). Although most participants can recall the correction, when present,
after they have finished processing the script, they continue to rely on the
original misinformation on an inference test. That is, when asked to explain
why there was “so much black smoke”, participants might refer to oil paint in
the wiring cabinet. This “continued influence effect” of misinformation has
been demonstrated repeatedly (for reviews, see Chan et al., 2017;
Lewandowsky et al., 2012; Swire & Ecker, 2017).
Continued inuence of political misinformation
When circumstances are less controlled than in the laboratory, as in most
real-life political events involving complex and messy situations, false mem-
ories for non-existent events can be strikingly frequent. For example,
Murphy et al. (2019) presented participants in Ireland with true and false
news stories relating to the referendum on abortion in the Republic of
Ireland. Participants correctly recognized the true stories 56% of the time,
but they also reported a distinct memory for one of the fabricated stories
(invented by the experimenters) 37% of the time. Qualitative responses
suggested that some participants reported rich and detailed false memories
for one of the fabricated events. It is therefore perhaps unsurprising that the
persistence of political misinformation can take on epic proportions. To
illustrate, consider the mythical Weapons of Mass Destruction (WMDs)
that were alleged to be in Iraq and that were cited as the reason for the
invasion of 2003. The constant drumbeat of “WMD, WMD, WMD” in the
media and among politicians in the lead-up to the invasion, followed by
innumerable media reports of “preliminary tests” that tested positive for
chemical weapons during the early stages of the conflict—but ultimately were
never confirmed by more thorough follow-up tests—created a strong
impression that those weapons had been discovered. This impression was
so powerful that notable segments of the American public continued to
believe, up until at least 2014, that either the U.S. had found WMDs in
Iraq or that Iraq had hidden the weapons so well that they escaped detection.
Jacobson (2010) reviewed polling data from 2006 through 2009 and found
that around 60% of Republicans (and around 20% of Democrats) believed in
the existence of Iraqi WMDs, with little evidence of a decline of those false
beliefs over time. A poll from December 2014 pegged erroneous beliefs in
WMDs at 51% for Republicans and 32% for Democrats (http://publicmind., confirming the longevity of those false beliefs. Mistaken
beliefs in WMD thus persisted for around a decade after the absence of
WMDs in Iraq had become the official U.S. position with the Duelfer report
(September 2004;
Persistent false beliefs in war-related information were also observed with
specific events during the initial stages of the invasion of Iraq. In a study
conducted before the Marines reached Baghdad, Lewandowsky et al. (2005)
presented participants with specific war-related items from the news media,
some of which had been subsequently corrected. Participants were asked to
indicate their belief in the items, as well as their recollection of the original
information and memory for its correction. Among U.S. participants, even
those individuals who were certain that the information had been retracted,
continued to believe it to be true (Lewandowsky et al., 2005). The ironic co-
existence of acknowledgement of a correction (“I know that X is false”) and
continued belief (“I believe X to be true”) or reliance (“I act like I believe X”)
on discredited information are hallmarks of the cognitive fallout from mis-
information in the political arena. This fallout can manifest itself in a number
of different ways.
Corrections of falsehoods but not feelings
There are repeated demonstrations that people can update their specific
factual beliefs in response to corrections, but that those changes in belief
have no politically relevant downstream consequences, such as affecting
voting intentions and favorability ratings of a candidate. In an experi-
ment conducted during the U.S. primary campaign in 2016, Swire et al.
(2017) presented more than 2,000 online participants with statements
made by Donald Trump on the campaign trail. Half the statements
shown to participants were true (e.g., “the U.S. spent $2 trillion on the
war in Iraq”) and the other half consisted of false claims (e.g., “vaccines
cause autism”). Participants rated their belief in those statements (from
“definitely false” to “definitely true”). Participants were then presented
with corrections of the false statements and affirmations of the correct
statements. On a subsequent test, belief ratings changed according to the
experimental intervention: All participants, including Trump supporters,
believed statements less after they were identified as false, and they
believed them more after they were affirmed as being correct. However,
for Trump supporters there was no association between the extent to
which they shifted their belief when a statement was corrected and their
feelings for Trump or their intention to vote for him. Thus, it seems that
Trump’s false claims did not matter to his supporters—at least they did
not matter sufficiently to alter their feelings or voting intentions.
The same result was obtained in a study by Nyhan et al. (2019) using
a different methodology. They presented participants with a single incorrect
claim made by Donald Trump (about crime rates), which was followed by
various types of correction and a single belief rating. Trump supporters again
showed that they were sensitive to the corrections, in comparison to a no-
correction control condition. However, just as in the study by Swire et al.
(2017), the correction had no effect on participants’ favorability ratings of
Donald Trump.
The basic pattern of results was replicated by Swire-Thompson et al. (2020)
in a study that also included supporters of Bernie Sanders and statements by
Sanders (in addition to Trump supporters and statements by Trump).
Supporters of both politicians adjusted beliefs in statements after being told
they were false (or true), but those corrections typically did not affect their
support for their favoured candidate. It was only when there were four times
as many false statements as true statements attributed to Trump or Sanders,
that a statistically significant decline in support for the candidate was
observed, although the effect size was small. (There were also small differences
between supporters of Sanders and Trump but they are not relevant here.)
The persistent support for a politician even after he has been shown to
make numerous false claims meshes well with public-opinion data about
partisans’ perceptions of President Trump. An NBC poll conducted in
April 2018 revealed that 76% of Republicans thought that President Trump
tells the truth “all or most of the time” (Arenge et al., 2018). By contrast, only
5% of Democrats held that view. Essentially the same pattern was obtained by
a Quinnipiac University poll in November 2018 (Quinnipiac, 2018).
The fallout from misinformation
It takes little imagination to realize that misinformed individuals are unlikely
to make optimal decisions, and that even putting aside one’s political pre-
ferences, this can have adverse consequences for society as a whole. For
example, following the unsubstantiated—and now thoroughly debunked
(DeStefano & Thompson, 2004; Godlee et al., 2011)—claim of a link between
childhood vaccinations and autism, numerous parents (largely in the UK)
decided not to immunize their children. These misinformation-driven
choices led to a marked increase in vaccine-preventable diseases, and sub-
stantial effort and expenditure were required to resolve this public-health
crisis (Larson et al., 2011; Poland & Spier, 2010).
Misinformation has also become associated with acts of violence or
vandalism. In Myanmar, the military orchestrated a propaganda campaign
on Facebook that targeted the country’s Muslim Rohingya minority group.
The ensuing violence forced 700,000 people to flee the country (Mozur,
2018). Violence can also arise without a directed campaign: In India, false
rumours about child kidnappers shared via WhatsApp incited at least 16
mob lynchings in 2018, leading to the deaths of 29 innocent people (Dixit &
Mac, 2018).
And at the time of this writing, the worldwide COVID-19 pandemic has
given rise to multiple conspiracy theories and misleading news stories that
have found considerable traction, with adverse consequences for society (van
der Linden, Roozenbeek, et al., 2020). For example, 29% of Americans
believe that COVID-19 was created in a laboratory (Schaeffer, 2020). In the
UK the belief that 5G mobile technology is associated with COVID-19 has
led to vandalism of infrastructure, with numerous cellphone masts being set
alight by arsonists (Lewandowsky & Cook, 2020). About one quarter of the
British public consistently endorses some form of conspiracy related to
COVID-19 (Freeman, Waite, et al., 2020; see also Brennen et al., 2020;
Roozenbeek et al., 2020a). There is currently widespread concern among
public-health officials that disinformation campaigns may curtail uptake of
a COVID-19 vaccine, which at the time of this writing is being rolled out in
the UK (Peretti-Watel et al., 2020). Although acceptance of the new vaccine
is high in the UK. as of November 2020 (Freeman, Loe, et al., 2020), the trend
in acceptance in many countries at the end of 2020 has been downward
(Babalola et al., 2020). Belief in COVID-19-related misinformation has in
fact been linked to reduced compliance with public health guidelines and
lower reported willingness to take the vaccine and recommend it to others
(Roozenbeek et al., 2020a).
The toxic fallout from misinformation is not limited to those direct
consequences. Other more insidious fallouts may involve people’s reluctance
to believe in facts altogether. There have been numerous demonstrations that
the presence of misinformation undermines the effects of accurate informa-
tion. In one study, van der Linden, Leiserowitz, et al. (2017) showed that
when participants were presented with both a persuasive fact and a related
piece of misinformation, belief overall was unaffected—the misinformation
cancelled out the fact. McCright et al. (2016) found that the presence of
a contrarian counter frame cancelled out valid climate information, and the
same effect was also observed by Cook et al. (2017).
Misinformation does not just misinform. It also undermines democracy
by calling into question the knowability of information altogether. And
without knowable information deliberative democratic discourse becomes
impossible (for an elaboration of those concerns, see Lewandowsky et al.,
2017a, 2017b). Fortunately, we are not entirely powerless in confronting the
“post-truth” malaise.
Confronting the “post-truth” world
Debunking of misinformation
Although the effectiveness of corrections in general is often debated, there is
broad agreement in the literature that corrections of misinformation are
more likely to be successful if the correction is accompanied by an alternative
explanation, or if suspicion is aroused over the initial source of the mis-
information (e.g., Lewandowsky et al., 2012). That is, telling people that
negligence was not a factor in a story about a fictitious warehouse fire (i.e.,
stating that a wiring cabinet was empty after negligence was first implied by
claiming it contained oil paint) is insufficient for participants to dismiss that
information. Telling people instead that arson, rather than negligence, was to
blame for the fire (by referring to petrol-soaked rags that were found at the
scene), successfully eliminates reliance on the initial misinformation (e.g.,
Ecker et al., 2015, 2010; Johnson & Seifert, 1994).
If a clear causal alternative is not available—as, for example, when
attempting to rebut conspiracy theories about the disappearance of
Malaysian Airlines flight MH370 over the Indian Ocean (MacLeod et al.,
2014)—arousing suspicion about the source of misinformation may be
another technique to achieve debunking. For example, when mock jurors
are admonished to disregard tainted evidence presented when reaching
a verdict during a mock trial, they demonstrably continue to rely on that
tainted evidence, similar to the way in which the oil paint in the wiring
cabinet continues to affect participants’ reasoning even when the cabinet was
actually empty. Reliance on tainted evidence disappears only when jurors are
made suspicious of the motives underlying the dissemination of the tainted
evidence in the first place, for example because it may have been planted by
the prosecutor’s office (Fein et al., 1997).
Although the success of these routes to debunking has been repeatedly
established in the laboratory, their applicability outside the laboratory “in the
wild” encounters at least three distinct problems. First, a causal alternative
can only be effective to the extent that it exists or that it is accepted. There are
many situations in which an alternative explanation may be unknown even
though it is clear that the original information is false. For example, the claim
that Malaysian Airlines flight MH370 was abducted by space aliens can be
confidently identified as false; however, no well-established causal alternative
exists that could be used to replace that claim.
Turning to the second problem, in other circumstances a causal alternative
may exist, but it may come with ideological or political baggage that prevents
some people from accepting it. The same problem also arises when scepticism of
the source of misinformation is advisable: even though there may be good
reasons to question the motives or credibility of a source, these reasons may
not necessarily be accepted by the target audience. This problem can be illu-
strated with a study by Lewandowsky et al. (2005), which probed the public’s
knowledge and belief in war-related events during the early stages of the invasion
of Iraq in 2003. Participants were presented with news items that had either been
corrected by official sources after they were published or were thought to be true
at the time. Participants were first asked for their belief in the items and whether
they had heard of them previously, before being presented with a correction
(where it existed) and a second set of belief ratings. Lewandowsky et al. (2005)
found that people who accepted as true the official casus belli, namely the
elimination of Weapons of Mass Destruction (WMD) thought to be hidden in
Iraq, were likely to believe in news reports that they knew had been corrected.
Those participants thus exhibited the quintessential ironic attribute of the
continued influence effect: knowledge that a piece of information is false accom-
panied by continued belief. By contrast, people who were sceptical of the official
reason for the war, and who thought it was initiated over something other than
WMD, were better able to dismiss false information and accept true statements.
On the one hand these results affirm the importance of scepticism and its
benefits to processing of information about contested events. On the other
hand, given the highly partisan landscape of public opinion surrounding Iraq,
with many Republicans—and considerably fewer Democrats—continuing to
(mistakenly) believe that Iraq possessed WMDs in 2003 (e.g., Jacobson, 2010;
Kull, Stephens, Weber, Lewis, & Hadfield, 2006), and with that belief being
strongly associated with endorsement of the war (Kull et al., 2006), it is unlikely
that provision of an alternative cause of the war would have been accepted by
partisan supporters of the Bush administration’s decision to invade. Indeed,
Nyhan and Reifler (2010) showed that under certain circumstances a corrective
message about WMDs can lead to an ironic further entrenchment of
Republicans’ false beliefs.
The same problem continues to affect contemporary American public
discourse. In light of repeated surveys showing that Republicans consider
President Trump to be honest, the extensive archive of his misleading and
false statements that are being accumulated by the Washington Post’s fact-
checker database is unlikely to convince supporters that Donald Trump’s
trustworthiness may be questionable. Conversely, Trump supporters may
well question the accuracy of mainstream media such as the Washington Post
that Trump is consistently dismissing as sources of “fake news” or even
“enemies of the people”. Under those circumstances, scepticism is likely to
be driven more by partisan motivations than concern about the relevant
evidence. In support, a recent study by van der Linden, Panagopoulos, et al.
(2020) found that the first media association that comes to mind for
Republicans when they hear the phrase “fake news” is “CNN”. CNN has
been a frequent target of the President’s ire. Under these circumstances, it is
not entirely surprising that corrections fail to alter people’s feelings about
their preferred candidate (Swire et al., 2017; Swire-Thompson et al., 2020).
A final problem with debunking is that it is often forced to adapt
a disadvantageous framing at a disadvantageous time. One often unavoidable
attribute of corrections is that they tacitly accept someone else’s rhetorical
framing, thereby permitting the actor who promulgated the original false-
hood to set the agenda. For example, a government official who announces
that there are “no plans for a carbon tax” in response to a newspaper article
falsely hinting at a tax may achieve a reduction in the specific belief that
a carbon tax is imminent. However, the correction is keeping the concept of
a “carbon tax” in the public realm, possibly deflecting public attention away
from the government’s actual agenda. The continued mention of a “carbon
tax” may have additional fallout, for example by making people who oppose
new taxes think about climate change mitigation as a greater threat than
climate change itself—notwithstanding the fact that the climate crisis is now
considered an acute emergency by many scientists (e.g., Gills & Morgan,
2020) and politicians (e.g., Gunia & The U.K. has officially declared a climate
“emergency”, 2019). The framing problem is compounded by the fact that
a correction necessarily follows dissemination of a falsehood. This temporal
sequencing is problematic in light of evidence that misinformation spreads
faster and further online than true information (Vosoughi et al., 2018).
The “backfire” effect reported by Nyhan and Reifler (2010) has been found to be less common than
initially thought (Guess & Coppock, 2018; Wood & Porter, 2018). We are therefore reluctant to expect
backfire effects generally; however, the exact replication of Nyhan and Reifler (2010) reported by Wood
and Porter (2018) (their Figure 5) are visually identical to those reported by Nyhan and Reifler (2010).
When corrections challenge worldviews, we should therefore still be sensitive to the possibility of
a backfire effect even though we should not routinely expect it.
Corrections therefore inevitably play a catch-up game with misinformation
and the corrections may be outpaced by falsehoods. Recent projections based
on models of contemporary discourse on Facebook have raised the alarming
possibility that anti-vaccination rhetoric may dominate the online landscape
within a decade (Johnson et al., 2020).
It turns out that all these difficulties that beset even potentially successful
debunking techniques can be circumvented by avoiding debunking alto-
gether. Aside from debunking, we should also explore prebunking—that is,
making people aware of potential misinformation before it is presented.
This idea, known as inoculation, has a long history that has recently
culminated in research that has yielded actionable knowledge for
Concern about people’s general vulnerability to political indoctrination goes
back many decades (McGuire, 1961), arising at the time from disquietude
about persuasive techniques employed by totalitarian states. The larger
question of how to go about developing attitudinal “resistance” against
unwanted persuasion attempts ultimately led McGuire to develop “inocula-
tion theory”, which, for a popular audience, he described as a “vaccine for
brainwash” (McGuire, 1970); see Figure 1.
Inoculation theory (Anderson & McGuire, 1965; McGuire, 1961, 1964,
1970; McGuire & Papageorgis, 1962) closely follows the biomedical analogy.
Just as vaccines are weakened versions of a pathogen that trigger the produc-
tion of antibodies when they enter the body to help confer immunity against
future infection, inoculation theory postulates that the same can be achieved
Figure 1. A Vaccine for Brainwash. From the original article by McGuire (1970) in
Psychology Today. Copyright held by an unknown person.
with information: by preemptively exposing people to a sufficiently wea-
kened version of a persuasive attack, a cognitive-motivational process is
triggered that is analogous to the production of “mental antibodies”, render-
ing the individual more immune to persuasion (Compton, 2013; McGuire,
1961; Pfau, 1997).
Specifically, the psychological inoculation process consists of two core
elements, including: 1) a warning to help activate threat in message recipients
(to motivate resistance), and 2) refutational preemption (or prebunking).
These two components are assumed to work together in the following
fashion: forewarning people that they are about to be exposed to challenging
content is thought to elicit threat to motivate the protection of existing
beliefs. In turn, two-sided refutational messages, which involve the threaten-
ing information, serve to both teach and inform people as they model the
counterarguing process and provide specific content that can be used to
resist persuasive attacks (Compton, 2013; McGuire, 1970). Over the last 50
years, a large body of evidence across domains—from health to political
campaigning—has revealed that inoculation messages can be effective at
conferring resistance to persuasion. A meta-analysis by Banas and Rains
(2010) that considered 40 studies with more than 10,000 participants alto-
gether established an effect size of inoculation interventions of about d¼
0:43 (conventionally considered to be “medium” in magnitude). Yet,
although a handful of dedicated scholars have continued to publish on the
theory (see Compton & Pfau, 2005; Pfau, 1997), interest among social
psychologists has dwindled over the years.
As Eagly and Chaiken (1993) summarize in their landmark text on the
psychology of attitudes, “although the analogy is admittedly clever and valid
the theory has not seen much development for many years and many of the
questions it raised remain unresolved” (p. 568). Following Eagly and
Chaiken’s call that inoculation theory deserves renewed interest in the con-
text of contemporary social psychological research, we outline our research
program bringing inoculation theory into the 21st century. Importantly,
although McGuire formulated his theories long before the rise of the inter-
net, we now know that the propagation of misinformation through online
social networks closely resembles the spread of a virus: rapidly transmitting
highly infectious information from one host to another but without the need
for physical contact (Budak et al., 2011; Kucharski, 2016). It must be of
particular concern that false news on Twitter spreads faster, deeper, and
broader than does truth (Vosoughi et al., 2018). Fake news appears to press
several psychological hot buttons. One is negative emotions and how people
express them online. For instance, Vosoughi et al. (2018) found that false
stories were likely to inspire fear, disgust, and surprise; true stories, in
contrast, triggered anticipation, sadness, joy, and trust. People are generally
more likely to share messages featuring moral–emotional language (Brady
et al., 2017), and this tendency may be amplified by people’s negativity bias,
that is the human proclivity to attend more to negative than to positive
things (Soroka et al., 2019). The ability of false news to trigger negative
emotions may thus give it an edge in the competition for human attention,
and digital media may, as Crockett (2017) argued, promote the expression of
negative emotions such as moral outrage “by inflating its triggering stimuli,
reducing some of its costs and amplifying many of its personal benefits” (p.
769). Whether by design or coincidence, false online content appears to
exploit these psychological factors.
The inoculation metaphor is therefore perhaps more relevant now than it
was ever before, given that the natural antidote to a virus is the creation of
a scalable vaccine. Accordingly, we outline three fundamental recent devel-
opments in inoculation theory scholarship that have pushed the theoretical
boundaries of the original theory forward, namely; 1) a move away from
a near-exclusive focus on “cultural truisms” towards inoculation against
more contested issues, including fake news and misinformation, 2) a shift
in focus from inoculation against specific arguments (narrow-spectrum) to
the techniques that underlie manipulation and persuasion more generally
(broad-spectrum), and 3) revisiting the potential of “active” vs. “passive”
inoculation defenses. Our research program has enabled the vaccine meta-
phor to be scaled widely to address the real-world challenge of inoculating
people against fake news and misinformation.
From cultural truisms to highly contested issues
There is a common (mis)perception that inoculation theory can only be
applied to what McGuire (1970) referred to as “cultural truism” or “beliefs so
generally accepted that most individuals are unaware of attacking argu-
ments” (p. 37). Examples he gave included “the value of frequent tooth
brushing” and “annual medical check-ups”. Because student surveys indi-
cated little polarization on these issues, uniformly favourable attitudes could
therefore be strengthened against persuasive attacks through the process of
inoculation. After all, if people had been exposed to attitude dissonant
information before on a topic, would this still constitute “preemptive”
refutation? The overarching concern for McGuire was research on selective
exposure: people tend to seek out information that will confirm their pre-
existing view of the world and avoid information that conflicts with what
they already believe. McGuire reasoned that if this is true, then people
maintain their beliefs in what he called a “germ-free ideological” environ-
ment (i.e., they avoid contact with arguments that challenge their beliefs on
controversial issues) and so inoculation would still apply. However, McGuire
concluded that as a psychological mechanism, the literature on selective bias
has a “questionable empirical status” (Anderson & McGuire, 1965, p. 46) as
people do regularly seek out information that challenges their worldview and
so it felt risky and premature to announce that inoculation would simply
apply to all beliefs (McGuire, 1970).
Nonetheless, it is interesting that the focus of inoculation research—by
and large—has remained with cultural truisms (Pfau et al., 2001), as this rigid
interpretation of the initial metaphor hampers theory development. For
example, consider that the threat element of the analogy has received intense
debate, as it was unclear whether threat was meant to be elicited implicitly
through exposure to a weakened attack (sending a warning signal to the
mind, sort of speak, to help motivate antibody production) or whether it was
meant to be implemented as an explicit forewarning. At any rate, McGuire
initially did not test the threat component explicitly and it fits less clearly
with the biological analogy (Compton, 2009). Yet, McGuire himself did
actively encourage further pursuit of the medical analogy (McGuire &
Papageorgis, 1962, p. 34). The consensus interpretation is therefore that
the analogy is meant to be instructive rather than restrictive (Compton,
2019) to encourage further theoretical development and innovation. In
fact, some 20 years after McGuire’s initial experiments, Pryor and Steinfatt
(1978) already noted that McGuire was incorrect about the fact that inocula-
tion cannot be applied to issues where people have differing prior beliefs,
which has led to a call to rethink the boundary conditions of the analogy
more generally (Wood, 2007). Research by van der Linden, Leiserowitz, et al.
(2017) and Cook et al. (2017) addresses this directly. Both research teams
showed that inoculation can be applied to one of the most contested issues in
the United States today: global warming (Ballew et al., 2019).
Misinformation about climate change is rampant on the internet (e.g.,
Lewandowsky et al., 2019a). One potent online climate misinformation
campaign is the “Global Warming Petition Project” (Cook et al., 2018).
The petition engendered a viral misinformation story on social media in
2016 claiming that “tens of thousands of scientists have declared global
warming a hoax” (Readfearn, 2016). In actuality, the petition was mean-
ingless. The list contains no affiliations, making verification of signatories
problematic (e.g., Charles Darwin and the Spice Girls were among the
signatories; van der Linden, Leiserowitz, et al., 2017). Fewer than 1% of the
signatories have any expertise in climate science revealing the petition to be
an instance of the “fake-experts” strategy that was pioneered by the tobacco
industry in the 1970s and 1980s (Cook et al., 2017; Oreskes & Conway, 2010).
Although the petition has been debunked repeatedly, it continues to sow
confusion. In a national probability sample of the United States population,
van der Linden, Leiserowitz, et al. (2017) found that amongst a wide range of
fake claims, Americans were most persuaded by the debunked Oregon
petition. Accordingly, in a subsequent experiment van der Linden,
Leiserowitz, et al. (2017) evaluated whether (a) such misinformation is
actually harmful to public opinion formation and (b) if so, whether people
can be inoculated against such specific falsehoods. In their online experiment
(N=2167), participants were randomly assigned to one of five conditions.
Figure 2 presents the data from the experiment and guides explanation of the
The conditions were formed by presenting misinformation or factual
information either alone or in combination. The factual information
focused on the scientific consensus, namely the fact that over “97% of
climate scientists have concluded that human-caused global warming is
happening”. Acceptance of that consensus had been identified by related
research as a “gateway” for attitude change (S. L. van der Linden et al., 2015;
Lewandowsky et al., 2013; van der Linden et al., 2019). The misinformation
was a screenshot of the Global Warming Petition Project stating that “over
31,000 scientists have signed a petition that there is no scientific evidence
for human-caused global warming”. In the experiment, participants were
either exposed to just the scientific consensus (Figure 2A, “consensus”), just
the misinformation by itself (Figure 2A, “misinformation”), a condition in
which participants were first exposed to the scientific consensus before
being exposed to the misinformation (Figure 2A, “false-balance”) and two
separate inoculation conditions. In the brief inoculation condition,
Figure 2. Inoculating against misinformation, adapted from van der Linden, Leiserowitz,
et al. (2017). Note: Error bars represent 95% confidence intervals. The three attitudinal
groups were created based on answers to the pre-test questions, such that those who
answered that they believe that climate change is happening and human-caused were
classified as “positive”, those who stated that they do not believe that climate change is
happening at all were classified as “negative” and the remainder of the sample were
classified as “neutral”. The same patterns emerged for political party ID (Republican,
Democrat, Independent).
participants were simply forewarned that politically motivated groups use
misleading tactics to try to convince the public that there is a lot of
disagreement between scientists (Figure 2A, “inoculation-W”) whereas in
the more detailed inoculation condition, the warning was accompanied by
a traditional preemptive refutation of the petition by noting that many of
the signatories are clearly fake (e.g. Charles Darwin), that although 31,000
may sound big, it only comprises 0.3% of US science graduates, and that
most of the signatories have no real expertise in climate science (Figure 2A,
The results showed that when participants were exposed to the full
“dose” of the misinformation at the end of the experiment (i.e., the
website of the petition), both inoculation conditions were effective in
conferring attitudinal immunity against misinformation. In particular,
although the misinformation itself proved potent—decreasing people’s
judgments about the scientific consensus in the absence of any inocula-
tion (d¼0:48)—both the forewarning (d¼0:33) and full inoculation
(d¼0:75) were effective in conferring resistance against the persuasive
attack (maintaining about 1/3
and 2/3
of the effect of the factual
message). Although these results mainly speak the danger of misinfor-
mation and the efficacy of inoculation, strikingly, nearly the exact same
patterns emerged regardless of people’s prior attitude towards climate
change (Figure 2B). In other words, the inoculation treatments equally
protected against misinformation (and boosted belief in the scientific
consensus) for those with positive, neutral, and negative prior attitudes
toward the issue.
Although these results are not the first demonstration that inocula-
tion works in the context of differing prior attitudes (e.g., see also Pryor
& Steinfatt, 1978; Wood, 2007), or for an issue that is not a cultural
truism (e.g., Banas & Miller, 2013; Jolley & Douglas, 2017), the highly
politicized nature of the climate change debate pushes the boundary
conditions of inoculation theory beyond what was previously thought
There have been several additional recent extensions of the inoculation
paradigm into contested arenas. For example, Zerback et al. (2020) explored
the effects of “astroturfed” comments launched by Russian “bots” on social
media. Astroturfing refers to the manipulative use of media to create an
artificial impression of grassroots support for an issue where no such support
actually exists (McNutt & Boland, 2007). There is considerable evidence that
Russian state-sponsored actors are engaged in astroturfing on social media
(e.g., by amplifying public division in the context of vaccinations;
Broniatowski et al., 2018). The primary astroturfing technique involves
manufacturing of comments on social media that masquerade as authentic
citizen voices. Zerback et al. (2020) showed in a large-scale experiment
involving the German public that pro-Russian comments under a news
article eroded people’s belief that Russia was responsible for the Skripal
poisoning in the UK. This erosion of belief was preventable through inocu-
lation, but only if the inoculation message anticipated the exact arguments to
which participants were subsequently exposed—that is, the inoculation effect
was specific rather than constituting a “broad spectrum” vaccine. Zerback
et al. (2020) also showed that the inoculation effect wore off after a two-week
delay (a similar wearing off of inoculation was reported by Niederdeppe
et al., 2014).
Into the rabbit hole and beyond
A particularly concerning manifestation of misinformation comprises
conspiracy theories, which are often a gateway to extremism and
radicalization. For example, the QAnon conspiracy theory,
a contemporary instantiation of a “cabal theory” which holds that
a single sinister group directs nearly all events in the world (Harari,
2020), has been identified as a security risk and domestic terror threat
in the U.S. (Amarasingam & Argentino, 2020). A conspiracy theory
that links the 5G cellphone network to the emergence of COVID-19
has been associated with widespread vandalism of telecommunications
installations in the UK in 2020. People who endorse this theory have
been found to be willing to also endorse violence (Jolley & Paterson,
It is therefore encouraging that inoculation has been repeatedly found
to be successful against conspiracy theories. Jolley and Douglas (2017)
demonstrated the success of inoculation in an experiment involving peo-
ple’s attitudes towards vaccinations. In the inoculation condition, people
were first exposed to anti-conspiratorial information which foreshadowed
the arguments that conspiracy theorists might make against vaccinations,
before being exposed to the conspiratorial material itself. In another
condition, the order was reversed. Jolley and Douglas (2017) found that
when people were inoculated by first receiving anti-conspiratorial mate-
rial, they were no longer adversely affected by subsequent conspiratorial
rhetoric. By contrast, if the conspiratorial material was presented first, the
countering material was less effective. Similarly, Banas and Miller (2013)
used both fact-based and logic-based inoculation material against a 9/11
conspiracy (the Loose Change film). Both approaches were found to be
Inoculation has also been found to be successful against potential
radicalization by online extremists. Braddock (2019) presented partici-
pants with pamphlets by rightwing and leftwing extremist groups which,
in the experimental conditions, were preceded by an inoculation
treatment. The inoculation succeeded in making the extremist material
unattractive in comparison to a no-treatment control condition. In
a recent, as yet unpublished study by Muhsin Yesilada and the first
author, inoculation was also found to be successful against Islamist
and Islamophobic material. Participants who watched a brief training
video that explained rhetorical techniques used by extremists were less
likely to endorse subsequent radicalizing videos than people in the
control condition who received no training. Similarly, in a recent
study, Saleh et al. (2021) found that participants who were exposed to
weakened doses of the strategies used in extremist recruitment—as part
of the interactive inoculation game Radicalize—were more resistant and
better able to identify manipulative social media messages when com-
pared to a control condition.
In summary, recent research suggests that McGuire might have been
surprised to learn that his initial reservations about the scope of inocu-
lation theory were, in fact, conservative. There is now growing evidence
that even controversial issues may be within the purview of the bene-
ficial effects of inoculation. The shift toward contested issues has led
scholars to rethink the original inoculation analogy by distinguishing
between therapeutic and prophylactic inoculations (Compton, 2019).
This distinction helped resolve a debate about whether inoculation in
a contested domain still counts as “inoculation”, given that most people
may have been exposed to arguments about climate change, online
extremism, or high-profile events such as Russian responsibility for the
poisoning of Sergei Skripal, a former Russian agent in the UK (Urban,
2019). In consequence, inoculation “in the wild” can hardly ever be truly
preemptive (Basol, Roozenbeek & van der Linden, 2020). From an out-
come perspective this does not seem to matter much: Attitudes are
protected from harmful information. From our perspective, the real-
world inoculation process need not be inconsistent with the biomedical
analogy. For example, consider that the incubation period for viral
infections is highly variable, ranging from a couple of days up to a few
years, without a vaccine necessarily losing its effectiveness. The same
could apply to how individuals become “infected” with misleading
information. Moreover, developments of the psychological analogy can
parallel those in medicine. Recent advances in medicine have found that
therapeutic vaccines (which are administered after infection) can still
reduce the effects of the disease by boosting immune response, for
example in the context of HPV, hepatitis, and rabies (Autran et al.,
2004). As such, the distinction between prophylactic vs. therapeutic
vaccines still allows for inoculation to occur within the context of
differing prior attitudes and has opened up a completely new area of
research (Compton, 2019).
From specic issues to broad-spectrum immunity
One issue that has remained slightly unclear is the specificity of inoculation:
Is it limited to the specific arguments that people might encounter later
(Zerback et al., 2020), or might a cognitive “vaccine” provide “broad-
spectrum” immunity; that is, might an inoculation message generalize to
other arguments not previously encountered? Recent research increasingly
supports the latter alternative.
Using the exact same misinformation as van der Linden, Leiserowitz,
et al. (2017), Cook et al. (2017) conducted a similar inoculation study
with national samples of the U.S. population (N¼1;092 and N¼400 in
studies 1 and 2, respectively) with equally promising results. Cook et al.
(2017) presented participants with (1) a warning that attempts are made
to cast doubt on the scientific consensus on climate change for political
reasons, and (2) an explanation that one disinformation technique
involves appeals to dissenting “fake experts” to feign a lack of scientific
consensus. Cook and colleagues illustrated the “fake-expert” approach by
drawing attention to the historical attempts of the tobacco industry to
undermine the medical consensus about the health risks from smoking
with advertising claims such as “20,679 Physicians say ‘Luckies are less
irritating’”. Figure 3 shows the photo that accompanied the inoculation
text in their experiment.
By exposing the fake-expert disinformation strategy at the outset, the sub-
sequent misinformation (in this case, the feigned lack of scientific consensus
on climate change) was defanged and people’s responses to various climate-
related test items did not differ from a control condition that received no
misinformation. By contrast, in the absence of inoculation, the misinformation
involving “fake experts” had a discernible detrimental effect. An important
further result of Cook et al. (2017) involves the role of political ideology, shown
in Figure 4. On its own, misinformation had a polarizing effect such that
Conservatives lowered their perception of the scientific consensus whereas
Liberals’ perception remained unchanged (Figure 4, orange line). Because
Liberals correctly estimated the consensus to be high, this implies that they
were unaffected by the misinformation whereas conservatives were susceptible
to misinformation. There have been several recent reports that susceptibility to
misinformation is greater on the populist right and among strong conserva-
tives than the political left (Grinberg et al., 2019; Guess, Nyhan, et al., 2020;
Guess et al., 2019; Guess, Lockett, et al., 2020; Ognyanova et al., 2020; van der
Linden, Panagopoulos, Azevedo, & Jost, 2020). The inoculation message
administered before participants were exposed to the misinformation (Figure
4, blue line) completely neutralized its effect, thereby also eliminating the effect
of participants’ political ideology. This replicated the effect observed by van der
Linden, Leiserowitz, et al. (2017).
Figure 3. Stimulus used by Cook et al. (2017) to explain the disinformation strategy used
by the tobacco industry to undermine the scientific consensus about the health risks
from smoking. Reproduced from Cook et al. (2017) (Creative Commons, no permission
Figure 4. The effects of ideology on receptivity to misinformation (orange line) and its
elimination by inoculation. Data were replotted by the authors from Cook et al. (2017).
Note: political ideology was assessed with a measure of free-market support.
There is, however, an important difference between the procedures of
van der Linden, Leiserowitz, et al. (2017) and Cook et al. (2017). The
procedure used by Cook and colleagues was not in the classical “refuta-
tional-same” format. In fact, their intervention did not mention the
Global Warming Petition Project at all. Instead, their treatment inocu-
lated participants by explaining a common manipulation technique: the
promotion of fake experts. Cook et al. (2017) define the fake expert
technique as “the use of spokespeople who convey the impression of
expertise without possessing any relevant scientific expertise” (p. 11).
This technique is not limited to the tobacco industry or climate denial.
On the contrary, the technique is itself is widespread, for example,
consider self-professed health experts advocating for homegrown cures
against the coronavirus (such as gargling with lemon juice). The impor-
tant result of Cook et al. (2017) is that exposing this technique in one
context (medicine) inoculated individuals against the same technique in
another context (climate change). This finding is crucial because it
suggests the vaccine metaphor could be scaled by focusing less on
specific issues and more on broader persuasion techniques. These find-
ings accord with an emerging literature on “cross-protection” or the idea
that an inoculation message can function as a “blanket of protection” by
also conferring resistance to related yet untreated attitudes (Parker et al.,
2016). For example, Parker et al. (2012) showed that if young people
were successfully inoculated against one health-adverse behaviour
(unprotected sex), the inoculation transferred to another risky behaviour
(binge drinking).
In the context of misinformation, it seems neither practical nor
feasible to produce inoculations out of a weakened strain of a specific
dose of fake news. Indeed, because fake news stories change and evolve
on a frequent basis, this strategy would appear inefficient if applied at
scale. In contrast, if a single inoculation treatment could offer wide-
spread protection against a whole range of fake news, this would allow
the analogy to be scaled and implemented more easily. This notion of
“generalized” resistance or a “broad-spectrum” vaccine was further
developed in a series of studies in the first author’s laboratory and by
Roozenbeek and van der Linden (Roozenbeek & van der Linden Linden,
2018, 2019; Roozenbeek et al., 2020; van der Linden & Roozenbeek,
2020). Both lines of research suggest that rather than focusing on
specific content, the public should be inoculated against the broader
manipulation techniques that underlie the production of most misinfor-
mation. We turn to both lines of research in turn.
Inoculation by detecting awed argumentation
Researchers have compiled several inventories of flawed argumentation that
are used to disinform, for example by populist politicians (Blassnig et al.,
2019), anti-vaccination activists (Jacobson et al., 2007), or by people who
spread conspiracy theories (Lewandowsky et al., 2015, 2018). The underlying
rationale for those inventories is that, by and large, human cognition is
a truth-tracking device. In many circumstances, cognition is found to be
optimal by a Bayesian gold standard of rationality (e.g., Lewandowsky et al.,
2009). Cognition that jettisons those normative standards is therefore likely
to be less suited as a reality-tracking device, and its role in conspiracy
theorizing and disinforming rhetoric is therefore unsurprising.
In the present context, it follows that if people can be trained to detect
flawed argumentation, those skills might inoculate them against being mis-
informed in a fairly general “broad spectrum” manner. A stream of as-yet
unpublished studies by the authors (in collaboration with Jon Roozenbeek
and Google Jigsaw) has explored the use of brief (2-3 minute) inoculation
videos to train people in the detection of flawed arguments. In all studies,
participants in the inoculation condition were exposed to an argumentation-
detection video that focused on a single misleading technique, whereas in the
control condition they watched a video about an unrelated issue (e.g., freezer
burn). The template of each video consisted of both a forewarning as well as
a weakened dose of the “virus” (i.e., a prebunk of the manipulation techni-
que). In all studies, the inoculation improved participants’ ability to detect
misleading information, which in turn generally reduced their intention to
share misleading material and increased discernment between trustworthy
and untrustworthy material.
To illustrate, one of the techniques examined in our studies was incoher-
ence. Incoherence is a frequent attribute of conspiracy theories (e.g.,
“Princess Diana was killed by MI5 and faked her own death”; Wood et al.,
2012) as well as climate denial (e.g., “Global temperatures cannot be mea-
sured accurately but we shouldn’t worry because it has been cooling for the
last 5 years”; Lewandowsky et al., 2016). Incoherent arguments are, by
definition, suspect and should be dismissed. Other techniques involved
false dichotomies (“Either you are with us, or you are with the terrorists”;
George W. Bush, 21 September 2001), scapegoating, ad hominem argumen-
tation, and emotional manipulation (e.g., fearmongering).
In a slightly different context, Merpert et al. (2018) showed that members
of the public can be readily trained to identify statements in a politician’s
speech that could, in principle, be subject to fact checking. This is an
important skill because opinions, by definition, are not subject to fact
checking, and differentiation of opinions from factual assertions is therefore
a necessary first step before fact-checking of suitable items can commence.
From passive to active inoculation: learning by doing
McGuire initially hypothesized that compared to “passive” inoculation
(where participants are simply provided with refutations to a particular
argument), the inoculation process might be more effective when people
are tasked with actively generating their own defenses or counter-arguments.
This is relevant because inoculation messages are known to change the
structure of associative memory networks, boosting nodes (e.g., counter-
arguments) as well as the number of linkages between nodes, which helps
strengthen people’s ability to resist persuasion (Pfau et al., 2005).
Roozenbeek and van der Linden (2018, 2019) designed a real-world active
inoculation simulation in the form of a free online “fake news game” called
Bad News ( The intervention simulates a social
media feed and players are encouraged to step into the shoes of a fake
news producer and over the course of 15 minutes gain as many followers
as they can without losing credibility. The purpose of the game is to inoculate
people against the techniques used in the production of fake news by letting
them actively generate their own content in the simulation engine (see Figure
5). Roozenbeek and van der Linden identified six common manipulation
techniques that are routinely involved in the production of fake news;
impersonating people online (including experts), using emotional language
(e.g., outrage), group polarization, floating conspiracy theories, discrediting
opponents, and online trolling.
The game shows players a meme or headline to which they can react in
a number of ways. Progress in the game is measured through a “followers”
and “credibility” meter (Figure 5B). Selecting an option that is consistent
with what a “real” producer of disinformation would do earns players more
followers and credibility. By contrast, if their strategy is too obvious or too
much in line with journalistic best practice, the game either takes followers
away or lowers players’ credibility score. In the game, players start off by
Figure 5. Screenshot of landing page (A) and gameplay (B). For further details visit www.
posting a tweet about something that frustrates them, which could be any-
thing from the government, to the mainstream media, or the Flat Earth
Society. Players then progress through six badges (or levels), each of which
illustrates one of the manipulation techniques mentioned earlier; imperso-
nation, emotion, polarization, conspiracy, discrediting, and trolling (for
a detailed review of these techniques see Roozenbeek & van der Linden,
2019a; van der Linden & Roozenbeek, 2020). The scenarios in which these
techniques are defanged also make use of other popular concepts such as
echo chambers and false amplification of a message. Players start the game by
impersonating an official account, they can choose from various options such
as impersonating Donald Trump (who declares war on North Korea) or
NASA (which announces that a massive meteorite is about to hit earth). The
game is fully interactive and players are shown (simulated) reactions from
other users and followers after they produce content. The game subsequently
prompts the player to go professional and start their own news site by
selecting a website name and slogan. The game was designed in collaboration
with the Dutch media collective “DROG” and design studio Gusmanson.
The game is based on full-cycle social psychology research (Mortensen &
Cialdini, 2010), moving continuously from the lab to the field and back.
The game incorporates both elements of the inoculation process; (a) the
game forewarns people that they are about to be exposed to challenging
content and (b) the game exposes the player to severely weakened doses of
the strategies that are used in the production of fake news. The doses are
severely weakened through the use of ridicule and humour: they activate the
immune system (getting the point across) but without actually overwhelming
it (i.e., the content does not actually dupe people). The Bad News game has
been played by about a million people worldwide (Roozenbeek et al., 2020b).
The game features a research component where players are quizzed before
and after gameplay on the reliability of fake and credible headlines using
7-point scales. Importantly, the test items are not featured in the game itself
to help evaluate to what extent people can identify manipulation techniques
in a range of “new” headlines. Although the test items are mirrored after real-
world fake news, they are fictional for two important reasons: (1) to exclude
memory and familiarity confounds (people may simply know a headline is
real or fake because they have seen it before) and (2) to have sufficient
experimental control over isolating and embedding the specific manipula-
tion techniques in each of the test items. An example item for the conspiracy
badge asked players to judge the reliability of the headline “The Bitcoin
exchange rate is being manipulated by a small group of rich bankers”
(which uses the conspiracy technique) or “New study shows that right-
wing people lie far more than left-wing people” (which uses the polarization
technique). An example of a credible real item that does not make use of any
of these techniques included; “Brexit, the United Kingdom’s exit from the
European Union, will officially happen in 2019”. (The study was conducted
before the UK formally exited the EU, at a time when the exit date was
thought to be in 2019. The UK ultimately departed on 31 January 2020.)
Roozenbeek and van der Linden (2019b) initially evaluated the game
using a within-subject design with a sample of roughly N¼15;000 people.
The results are shown in Figure 6. For the real news items, people did not
change their reliability ratings between a pre- and a post-test
(d¼0:03 0:04, Figure 6D). For the fake news items, by contrast, people
significantly downgraded reliability overall (d¼0:52) as well as for each
technique separately (d ranges from 0.16 to 0.35, Figure 6A-C)
Given that
many elections are decided on small margins (e.g., half of U.S. presidential
elections were decided by margins under 7.6% (Epstein & Robertson, 2015)
and the 2016 election was decided by razor-thin margins in a few swing
states), these effects can be considered meaningful when scaled (Funder &
Ozer, 2019) and commensurate with effect sizes in persuasion research
(Banas & Rains, 2010; Walter & Murphy, 2018). Importantly, although
Roozenbeek and van der Linden (2019) found some small variation in the
inoculation effect across age and ideology, such that older people and
Figure 6. Pre and post scores for fake items that use manipulation techniques (panels
A-C) as well as the mean score for the control items (panel D). Note: Error bars represent
95% confidence intervals. Adopted from Roozenbeek and van der Linden (2019).
Conservatives were slightly more susceptible to fake news on the pre-test
(which is consistent with other recent work, e.g., Grinberg et al., 2019; Guess
et al., 2019, 2020; for a review see Brashier & Schacter, 2020), the inoculation
effect was significant across all subgroups.
Basol et al. (2020) replicated these findings in a randomized experiment
with a treatment and a control group (the latter involved participants
playing Tetris for 15 minutes). The results were very similar for the overall
effect-size (d¼0:60) as well the range per technique (d¼0:14 to 0:45).
Importantly, Basol et al. (2020) also included a measure of how much
confidence players had in their judgments. Confidence plays a key role in
the inoculation process (Tormala & Petty, 2004), as people who are con-
fident in their beliefs are both more willing and able to defend them against
persuasion attempts. Basol et al. (2020) found that the game significantly
boosted people’s confidence in their judgments about the reliability of the
fake items when those judgments were accurate (d¼0:52). Boosting of
confidence is important because confidence in one’s own beliefs is critical
to being able to resist unwanted attempts to persuade and manipulate
(Compton & Pfau, 2005).
The game has seen several spin-offs and real-world adaptations. For
example, in collaboration with the UK government, the Bad News game
has been translated worldwide into more than 20 languages to allow for
larger-scale testing. Roozenbeek et al. (2020) were able to conduct
a cross-cultural replication of the game in Sweden, Germany, Greece,
and Poland. Although some cultural heterogeneity was observed, the
principal effects of the intervention replicated overall across cultures.
In 2020, Roozenbeek and van der Linden launched GoViral!, a game
focused on prebunking COVID-19 misinformation specifically in colla-
boration with the UK Cabinet office with support from the WHO and
UN (Reader, 2020), as well as Harmony Square, a game focused on
inoculating against political misinformation during elections in colla-
boration with the Department of Homeland Security in the United
States (Roozenbeek & van der Linden, 2020).
From a vaccine to herd immunity
Many interesting questions remain, including how long the inoculation
effect lasts. Inoculation treatments are typically observed to decay over
a number of weeks (Banas & Rains, 2010; Niederdeppe et al., 2014;
Zerback et al., 2020), much in line with the forgetting of conventional
rebuttal efforts (Swire et al., 2017). Recent research has suggested that
For a detailed methodological overview of item and testing effects using the Bad News paradigm we
refer the reader to Roozenbeek et al. (2020b).
occasional booster doses can extend retention of inoculation (Ivanov et al.,
2018; Maertens, Anseel, et al., 2020). In the study by Maertens et al. (2020),
the benefits of playing the “Bad News” game were found to wear off after 2
months without further interventions, but the benefits retained intact for 3
months if the retention interval included a potential booster shot in the form
of repeated testing.
Another open question is whether inoculation interacts with psycholo-
gical reactance (though see Miller et al., 2013). Reactance refers to the
motivational state that arises when people feel that their behavioural free-
dom has been threatened or taken away (Brehm & Brehm, 1981). When
this occurs, individuals may act contrary to a prescribed action in order to
protect or restore their feeling of freedom and control. It is unclear
whether people who are high in trait reactance (e.g., Quick et al., 2011)
are less receptive to inoculation messages. Attempts to inoculate against
reactance (i.e., seeking to reduce the freedom threat of directive messages
by inoculation) have been met with mixed success (Richards & Banas,
2015, 2015).
Although these questions open exciting and important avenues for future
research, perhaps the most important question of all is how to translate
a cognitive vaccine that boosts individual immune responses into societal
level “herd immunity”. Undoubtedly, the most powerful aspect of the inocu-
lation metaphor was left relatively unexplored by McGuire; namely, the
social nature of the theory (van der Linden, Maibach, et al., 2017). If enough
individuals in a population are vaccinated, the informational virus has no
opportunity to take hold and spread. Importantly, the metaphor implies that
not every single individual needs to be vaccinated, as herd immunity offers
protection to those who are unable or unwilling to receive the vaccine.
Accordingly, what is important about the newer (e.g., gamified) inoculation
approaches is its ability to scale: the game can be shared interpersonally as
well as on social media. In addition, the intervention is flexible and adaptive,
and so scenarios can easily be changed and updated in response to new
threats (e.g., deepfakes) to remain preemptive. In other words, just like
misinformation, the vaccine can spread too, either because other people
are enticed to play the game (or watch a video) or because people engage
in something known as “post-inoculation talk”. Recent research has started
to evaluate how interpersonal discussions following an inoculation interven-
tion can strengthen attitude resistance through enhanced confidence and
advocacy (Dillingham & Ivanov, 2016).
The potential for the social diffusion of inoculation content in social
networks raises many exciting questions about how best to model its spread.
For example, agent-based simulations are shedding light on how evidence-
resistant minorities can delay consensus formation and undermine public
opinion (Lewandowsky et al., 2019b). We expect that the future of
inoculation theory scholarship will be best served by focusing on social
psychological theories of how inoculation spreads from one person to
another to be able to offer realistic predictions about the potential for
attitudinal herd immunity against the increasing spread of fake news and
Inoculating against manipulative personalization
We conclude by turning attention to another arena of political communica-
tion that has been highly contested, namely “micro-targeting” of persuasive
messages via Facebook or other social media. Micro-targeted political adver-
tising exploits the unprecedented amounts of personal data that are harvested
by platforms such as Facebook to reach its targets. There is evidence that
knowledge of 300 Facebook “likes” is sufficient to infer a user’s personality
with greater accuracy than their spouse (Youyou et al., 2015). Micro-targeting
erupted onto the public scene with the Cambridge Analytica scandal after the
Brexit referendum in the UK, when it transpired that the company had used
profiles from 87 million Facebook users to target individuals with highly
specific messages (Heawood, 2018). A British Parliamentary committee that
investigated the scandal concluded that relentless targeting that plays “to the
fears and the prejudices of people, in order to alter their voting plans” is “more
invasive than obviously false information” and contributes to a “democratic
crisis” (Digital, Culture, Media and Sport Committee, 2019). Although
Facebook has curtailed data access in response, advertisers can continue to
select audiences on the basis of attributes that are now known to be predictive
of personality. Content delivery can therefore continue to exploit, without
users’ awareness, sensitive details about their lives.
Although the impact of Cambridge Analytica is difficult to quantify,
experimental evidence suggests that ads that are targeted at a person’s
personality are more effective than other ads. In a large-scale “real life”
experiment on Facebook, Matz et al. (2017) showed that cosmetic ads that
were designed to appeal either to introverts or to extraverts (Figure 7A, top
and bottom, respectively) elicited more click-throughs and purchases when
recipients’ personality matched than when it did not.
Although advertisements for cosmetics are unlikely to alter the course of
history, they nonetheless open a window into the power of algorithmic
targeting on social media. It is therefore important to ask whether people
might be protected against targeted manipulation by “boosting” their detec-
tion skills: might the provision of information about their personality inocu-
late a person against inadvertently being particularly receptive to a targeted
The study by Matz et al. (2017) has been subjected to critiques (Eckles et al., 2018; Sharp et al., 2018)
which were (in our view) convincingly rebutted by the authors (Matz et al., 2018a, 2018b).
ad? An as-yet unpublished experiment involving the first author (Lorenz-
Spreen, Hertwig, Lewandowsky, & Herzog, in preparation) showed that this
is indeed possible. In the experimental “boosting” condition, participants
were provided with information about their introversion-extraversion score
(Figure 7B) together with a brief explanation of the characteristics of the two
personality types. During a subsequent classification task, in which partici-
pants had to decide for each ad whether or not it matched their personality,
performance was considerably better in the boosting condition than in
a control condition involving feedback about an unrelated personal attribute.
We live in an environment that is drenched in misinformation, “fake news”,
and propaganda not because of an unavoidable accident but because it has
been created by political actors in pursuit of political and economic objec-
tives (Lewandowsky, 2020; Lewandowsky et al., 2017b). We therefore do not
face a natural disaster but a political problem. On the positive side, this
implies that, unlike for earthquakes or tsunamis, a solution is likely to exist
and ought to be achievable. On the negative side, it means that the solution is
unlikely to involve more (or better) communication alone. As Brulle et al.
(2012) noted in the context of climate change, “introducing new messages or
information into an otherwise unchanged socioeconomic system will accom-
plish little” (p. 185). Instead, we need to pursue multiple avenues—many of
them political—to contain misinformation and redesign the information
architecture that facilitates its dissemination (Kozyreva et al., 2020; Lorenz-
Figure 7. (A) Advertisements designed by Matz et al. (2017) that target introverts (top)
and extraverts. (B) Feeback provided to participants in the experiment by Lorenz-Spreen
and colleagues.
Spreen et al., 2020). van der Linden (2019) postulated several such beha-
vioural avenues, starting with prebunking or inoculation, which is followed
where necessary by real-time rebuttal or fact-checking and then debunking if
inoculation fails. Lorenz-Spreen et al. (2020) additionally provided an ana-
lysis of how online architectures contribute to the spread of misinformation
and how they could be redesigned to facilitate accurate democratic delibera-
tion. In short, future work would be well-served by adopting a multi-layered
response to misinformation, including the techniques that we have reviewed
It is encouraging that inoculation techniques have been successful in the
“real world” outside the laboratory. For example, during a mumps epidemic
in Iowa in 2006, the Department of Public Health posted a primer for the
media online. The primer provided explanations and rebuttals to anticipated
arguments by anti-vaccine activists. This enabled the media to understand
and defang those contrarian arguments (Jacobson et al., 2007). In arguably
the largest real-world inoculation experiment to date, Twitter recently fore-
warned all of its U.S. users about false information concerning voting by mail
that they may encounter during the 2020 U.S. Presidential election (Ingram,
20202020). We invite psychologists of all stripes to consider the benefits of
inoculation in curtailing the spread of misinformation.
Stephan Lewandowsky
Sander van der Linden
Amarasingam, A., & Argentino, M.-A. (2020). The QAnon conspiracy theory:
A security threat in the making?. CTC Sentinel, 13(7), 37–44.
Anderson, L. R., & McGuire, W. J. (1965). Prior reassurance of group consensus as
a factor in producing resistance to persuasion. Sociometry, 28(1), 44–56. https://
Arenge, A., Lapinski, J., & Tallevi, A. (2018, May). Poll: Republicans who think
Trump is untruthful still approve of him. NBC News.
Autran, B., Carcelain, G., Combadiere, B., & Debre, P. (2004). Therapeutic vaccines
for chronic infections. Science, 305(5681), 205–208.
Babalola, S., Krenn, S., Rimal, R., Serlemitsos, E., Shaivitz, M., Shattuck, D., &
Storey, D. (2020). KAP COVID dashboard. Johns Hopkins Center for
Communication Programs, Massachusetts Institute of Technology, Global
Outbreak Alert; Response Network, Facebook Data for Good. https://ccp.jhu.
Ballew, M. T., Goldberg, M. H., Rosenthal, S. A., Gustafson, A., & Leiserowitz, A.
(2019). Systems thinking as a pathway to global warming beliefs and attitudes
through an ecological worldview. Proceedings of the National Academy of Sciences,
116(17), 8214–8219.
Banas, J. A., & Miller, G. (2013). Inducing resistance to conspiracy theory propa-
ganda: Testing inoculation and metainoculation strategies. Human communica-
tion research, 39(2), 184–207.
Banas, J. A., & Rains, S. A. (2010). A meta-analysis of research on inoculation theory.
Communication monographs, 77(3), 281–311. doi: 10.1080/03637751003758193
Basol, M., Roozenbeek, J., & Linden, S. V. D. (2020). Good news about bad news:
Gamified inoculation boosts confidence and cognitive immunity against fake
news. Journal of Cognition, 3(1), 1–9. doi: 10.5334/joc.91
Blassnig, S., Büchel, F., Ernst, N., & Engesser, S. (2019). Populism and informal
fallacies: An analysis of right-wing populist rhetoric in election campaigns.
Argumentation, 33(1), 107–136.
Braddock, K. (2019). Vaccinating against hate: Using attitudinal inoculation to
confer resistance to persuasion by extremist propaganda. Terrorism and Political
Violence, 1–23.
Brady, W. J., Wills, J. A., Jost, J. T., Tucker, J. A., & Van Bavel, J. J. (2017).
Emotion shapes the diffusion of moralized content in social networks.
Proceedings of the National Academy of Sciences, 114(28), 7313–7318.
Brashier, N. M., & Schacter, D. L. (2020). Aging in an Era of Fake News. Current
directions in psychological science, 29(3), 316–323. doi: 10.1177/0963721420915872
Brehm, S. S., & Brehm, J. W. (1981). Psychological reactance: A theory of freedom and
control. Academic Press.
Brennen, J. S., Simon, F. M., Howard, P. N., & Nielsen, R. K. (2020). Types, sources,
and claims of COVID-19 misinformation. Reuters Institute.
Broniatowski, D. A., Jamison, A. M., Qi, S., AlKulaib, L., Chen, T., Benton, A., &
Dredze, M. (2018). Weaponized health communication: Twitter bots and Russian
trolls amplify the vaccine debate. American Journal of Public Health, 108(10),
Brulle, R. J., Carmichael, J., & Jenkins, J. C. (2012). Shifting public opinion on climate
change: An empirical assessment of factors influencing concern over climate
change in the U.S., 2002–2010. Climatic change, 114(2), 169–188. https://doi.
Budak, C., Agrawal, D., & El Abbadi, A. (2011). Limiting the spread of misinforma-
tion in social networks. In Proceedings of the 20th international conference on
world wide web - WWW ’11. Hyderabad, India.
Chan, M. P. S., Jones, C. R., Jamieson, K. H., & Albarracín, D. (2017). Debunking: A
meta-analysis of the psychological efficacy of messages countering
misinformation. Psychological science, 28(11), 1531–1546.
Compton, J. (2009). Threat explication: What we know and don’t yet know about
a key component of inoculation theory. STAM Journal, 39, 1–18.
Compton, J. (2013). oculation theory. In J. Dillard & L. Shen (Eds.), The SAGE
handbook of persuasion: Developments in theory and practice. (pp. 220–
236). Thousand Oaks, CA: Sage.
Compton, J. (2019). Prophylactic versus therapeutic inoculation treatments for
resistance to influence. Communication Theory, 30(3), 330-343.
Compton, J., van der Linden, S., Cook, J., & Basol, M. (2019). Inoculation theory and
science communication: Extant findings and new directions. Paper presented at
the 69th conference of the International Communication Association,
Washington, DC, USA.
Compton, J. A., & Pfau, M. (2005). Inoculation theory of resistance to influence at
maturity: Recent progress in theory development and application and suggestions
for future research. Annals of the International Communication Association, 29(1),
Cook, J., Lewandowsky, S., & Ecker, U. K. H. (2017). Neutralizing misinformation
through inoculation: Exposing misleading argumentation techniques reduces
their influence. PLOS ONE, 12(5), e0175799.
Cook, J., Maibach, E., van der Linden, S., & Lewandowsky, S. (2018). The consensus
handbook. George Mason University.
Crockett, M. J. (2017). Moral outrage in the digital age. Nature Human Behaviour, 1
(11), 769–771. doi: 10.1038/s41562-017-0213-3
DeStefano, F., & Thompson, W. W. (2004). MMR vaccine and autism: An update of
the scientific evidence. Expert review of vaccines, 3(1), 19–22.
Digital, Culture, Media, and Sport Committee. (2019). Disinformation and “fake
news”: Final report. House of Commons, U.K. Parliament. https://publications.
Dillingham, L. L., & Ivanov, B. (2016). Using postinoculation talk to strengthen
generated resistance. Communication Research Reports, 33(4), 295–302. https://
Dixit, P., & Mac, R. (2018). How WhatsApp destroyed a village. BuzzFeed News.
Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace
Ecker, U. K. H., Lewandowsky, S., Cheung, C. S. C., & Maybery, M. T. (2015). He did
it! She did it! No, she did not! Multiple causal explanations and the continued
influence of misinformation. Journal of memory and language, 85, 101–115.
Ecker, U. K. H., Lewandowsky, S., Swire, B., & Chang, D. (2011). Correcting false
information in memory: Manipulating the strength of misinformation encoding
and its retraction. Psychonomic bulletin & review, 18(3), 570–578.
Ecker, U. K. H., Lewandowsky, S., & Tang, D. T. W. (2010). Explicit warnings reduce
but do not eliminate the continued influence of misinformation. Memory &
cognition, 38(8), 1087–1100.
Eckles, D., Gordon, B. R., & Johnson, G. A. (2018). Field studies of psychologically
targeted ads face threats to internal validity. Proceedings of the National Academy
of Sciences, 115(23), E5254–E5255.
Epstein, R., & Robertson, R. E. (2015). The search engine manipulation effect
(SEME) and its possible impact on the outcomes of elections. Proceedings of
the National Academy of Sciences, 112(33), E4512–E4521.
Fein, S., McCloskey, A. L., & Tomlinson, T. M. (1997). Can the jury disregard that
information? The use of suspicion to reduce the prejudicial effects of pretrial
publicity and inadmissible testimony. Personality & social psychology bulletin, 23
(11), 1215–1226.
Freeman, D., Loe, B. S., Chadwick, A., Vaccari, C., Waite, F., Rosebrock, L., Jenner,
L., Petit, A., Lewandowsky, S., Vanderslott, S., Innocenti, S., Larkin, M., Giubilini,
A., Yu, L.-M., McShane, H., Pollard, A. J., & Lambe, S. (2020). COVID-19 vaccine
hesitancy in the UK: The Oxford coronavirus explanations, attitudes, and narra-
tives survey (OCEANS) II. Psychological Medicine:1–34.
Freeman, D., Waite, F., Rosebrock, L., Petit, A., Causier, C., East, A., & Lambe, S.
(2020). Coronavirus conspiracy beliefs, mistrust, and compliance with govern-
ment guidelines in England. Psychological Medicine.
Funder, D. C., & Ozer, D. J. (2019). Evaluating effect size in psychological research:
Sense and nonsense. Advances in Methods and Practices in Psychological Science, 2
(2), 156–168.
Gills, B., & Morgan, J. (2020). Global Climate Emergency: After COP24, climate
science, urgency, and the threat to humanity. Globalizations, 17(6), 885–902.
Godlee, F., Smith, J., & Marcovitch, H. (2011). Wakefield’s article linking MMR
vaccine and autism was fraudulent: Clear evidence of falsification of data should
now close the door on this damaging vaccine scare. BMJ: British Medical Journal,
342, 64–66.
Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake
news on Twitter during the 2016 U.S. Presidential election. Science, 363(6425),
Guess, A., & Coppock, A. (2018). Does counter-attitudinal information cause back-
lash? Results from three large survey experiments. British Journal of Political
Science, 50(4), 1497-1515.
Guess, A. M., Nagler, J., & Tucker, J. (2019). Less than you think: Prevalence and
predictors of fake news dissemination on Facebook. Science Advances, 5(1),
Guess, A. M., Nyhan, B., & Reifler, J. (2020). Exposure to untrustworthy websites in
the 2016 U.S. election. Nature Human Behavior, 1(1). (electronic). in press.
Guess, A. M., Nyhan, B., & Reifler, J. (2020). Exposure to untrustworthy websites in
the 2016 U.S. election. Nature Human Behavior, in press.
Gunia, A. (2019). The U.K. has officially declared a climate “emergency”. TIME.
Harari, Y. N. (2020). When the world seems like one big conspiracy. New York
Heawood, J. (2018). Pseudo-public political speech: Democratic implications of the
Cambridge Analytica scandal. Information Polity, 23(4), 429–434.
Ingram, D. (October 26th, 2020). Twitter launches 'pre-bunks' to get ahead of voting
misinformation. NBC News.
Ivanov, B., Parker, K. A., & Dillingham, L. L. (2018). Testing the limits of
inoculation-generated resistance. Western Journal of Communication, 82(5),
Jacobson, G. C. (2010). Perception, memory, and partisan polarization on the iraq
war. Political science quarterly, 125(1), 31–56. doi:10.1002/j.1538-165X.2010.
Jacobson, R. A., Targonski, P. V., & Poland, G. A. (2007). A taxonomy of reasoning
flaws in the anti-vaccine movement. Vaccine, 25(16), 3146–3152. doi:10.1016/j.
Johnson, H. M., & Seifert, C. M. (1994). Sources of the continued influence effect:
When misinformation in memory affects later inferences. Journal of Experimental
Psychology: Learning, Memory and Cognition, 20(6) 1420–1436.
Johnson, N. F., Velásquez, N., Restrepo, N. J., Leahy, R., Gabriel, N., Oud, S. E., &
Lupu, Y. (2020). The online competition between pro- and anti-vaccination views.
Nature, 582(7811), 230–233.
Jolley, D., & Douglas, K. M. (2017). Prevention is better than cure: Addressing
anti-vaccine conspiracy theories. Journal of applied social psychology, 47(8),
Jolley, D., & Paterson, J. L. (2020). Pylons ablaze: Examining the role of 5G
COVID-19 conspiracy beliefs and support for violence. British Journal of Social
Psychology, 59(3), 628–640.
Kozyreva, A., Lewandowsky, S., & Hertwig, R. (2020). Citizens Versus the Internet:
Confronting Digital Challenges With Cognitive Tools. Psychological Science in the
Public Interest, 21(3), 103–156.
Kucharski, A. (2016). Study epidemiology of fake news. Nature, 540(7634), 525.
Kull, C., And Ramsay, S., Stephens, A., Weber, S., Lewis, E., & Hadfield, J. (2006).
Americans on Iraq: Three years on. Program on International Policy Attitudes,
Larson, H. J., Cooper, L. Z., Eskola, J., Katz, S. L., & Ratzan, S. C. (2011). Addressing
the vaccine confidence gap. The Lancet, 378(9790), 526–535.
Lewandowsky, S. (2020). Wilful construction of ignorance: A tale of two ontologies.
In R. Hertwig & C. Engel (Eds.), Deliberate ignorance: Choosing not to know (pp.
101–117). MIT Press.
Lewandowsky, S., & Cook, J. (2020). Coronavirus conspiracy theories are dangerous
—here’s how to stop them spreading. The Conversation. https://theconversation.
Lewandowsky, S., Cook, J., & Ecker, U. K. H. (2017a). Letting the gorilla emerge from
the mist: Getting past post-truth. Journal of applied research in memory and
cognition, 6(4), 418–424.
Lewandowsky, S., Cook, J., Fay, N., & Gignac, G. E. (2019a). Science by social media:
Attitudes towards climate change are mediated by perceived social consensus.
Memory & cognition, 47(8), 1445–1456.
Lewandowsky, S., Cook, J., & Lloyd, E. (2016). The “Alice in Wonderland” mechanics
of the rejection of (climate) science: Simulating coherence by conspiracism.
Synthese, 195(1), 175–196.
Lewandowsky, S., Cook, J., Oberauer, K., Brophy, S., Lloyd, E. A., & Marriott, M.
(2015). Recurrent fury: Conspiratorial discourse in the blogosphere triggered by
research on the role of conspiracist ideation in climate denial. Journal of Social and
Political Psychology, 3(1), 142–178.
Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017b). Beyond misinformation:
Understanding and coping with the post-truth era. Journal of applied research in
memory and cognition, 6(4), 353–369.
Lewandowsky, S., Ecker, U. K. H., Seifert, C., Schwarz, N., & Cook, J. (2012).
Misinformation and its correction: Continued influence and successful
debiasing. Psychological Science in the Public Interest, 13(3), 106–131. https://doi.
Lewandowsky, S., Gignac, G. E., & Vaughan, S. (2013). The pivotal role of perceived
scientific consensus in acceptance of science. Nature climate change, 3(4),
399–404. doi:10.1038/nclimate1720
Lewandowsky, S., Griffiths, T. L., & Kalish, M. L. (2009). The wisdom of individuals:
Exploring people’s knowledge about everyday events using iterated learning.
Cognitive science, 33(6), 969–998.
Lewandowsky, S., Lloyd, E. A., & Brophy, S. (2018). When THUNCing Trumps
thinking: What distant alternative worlds can tell us about the real world.
Argumenta, 3, 217–231.
Lewandowsky, S., Pilditch, T. D., Madsen, J. K., Oreskes, N., & Risbey, J. S. (2019b).
Influence and seepage: An evidence-resistant minority can affect public opinion
and scientific belief formation. Cognition, 188, 124–139.
Lewandowsky, S., Stritzke, W. G. K., Oberauer, K., & Morales, M. (2005). Memory
for fact, fiction, and misinformation: The Iraq War 2003. Psychological science, 16
(3), 190–195.
Lorenz-Spreen, P., Lewandowsky, S., Sunstein, C. R., & Hertwig, R. (2020). How
behavioural sciences can promote truth, autonomy and democratic discourse
online. Nature Human Behaviour, 4(11), 1102–1109.
MacLeod, C., Winter, M., & Gray, A. (2014). Beijing-bound flight from Malaysia
missing. USA Today.
Maertens, R., Anseel, F., & van der Linden, S. (2020). Combatting climate change
misinformation: Evidence for longevity of inoculation and consensus messaging
effects. Journal of Environmental Psychology, 70, 101455.
Maertens, R., Roozenbeek, J., Basol, M., & van der Linden, S. (2020). Long-term
effectiveness of inoculation against misinformation: Three longitudinal experi-
ments. In Journal of Experimental Psychology: Applied. Advance online publica-
Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2017). Psychological targeting as
an effective approach to digital mass persuasion. Proceedings of the National
Academy of Sciences, 114(48), 12714–12719.
Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2018a). Reply to Sharp et al.:
Psychological targeting produces robust effects. Proceedings of the National
Academy of Sciences, 115(34), E7891–E7891.
Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2018b). Reply to Eckles et al.:
facebook’s optimization algorithms are highly unlikely to explain the effects of
psychological targeting. Proceedings of the National Academy of Sciences, 115(23),
McCright, A. M., Charters, M., Dentzman, K., & Dietz, T. (2016). Examining the
effectiveness of climate change frames in the face of a climate change denial
counter-frame. Topics in cognitive science, 8(1), 76–97.
McGuire, W. J. (1961). Resistance to persuasion conferred by active and passive prior
refutation of the same and alternative counterarguments.. The Journal of
Abnormal and Social Psychology, 63(2), 326–332.
McGuire, W. J. (1964). Some contemporary approaches. In Advances in experimental
social psychology (Vol. 1, pp. 191-229). Academic Press.
McGuire, W. J. (1970). Vaccine for brainwash. Psychology today, 3(9), 36–64.
McGuire, W. J., & Papageorgis, D. (1962). Effectiveness of forewarning in developing
resistance to persuasion. Public opinion quarterly, 26(1), 24–34.
McNutt, J., & Boland, K. (2007). Astroturf, technology and the future of community
mobilization: Implications for nonprofit theory. The Journal of Sociology & Social
Welfare, 34(23), 165–178.
Merpert, A., Furman, M., Anauati, M. V., Zommer, L., & Taylor, I. (2018). Is that
even checkable? An experimental study in identifying checkable statements in
political discourse. Communication Research Reports, 35(1), 48–57. https://doi.
Miller, C. H., Ivanov, B., Sims, J., Compton, J., Harrison, K. J., Parker, K. A.,
Parker, J. L., & Averbeck, J. M.. (2013). Boosting the potency of resistance:
Combining the motivational forces of inoculation and psychological reactance.
Human communication research, 39(1), 127–155.
Mortensen, C. R., & Cialdini, R. B. (2010). Full-cycle social psychology for theory and
application. Social and personality psychology compass, 4(1), 53–63. doi:10.1111/
Mozur, P. (2018). A genocide incited on Facebook, with posts from Myanmar’s
military. The New York Times.
Murphy, G., Loftus, E. F., Grady, R. H., Levine, L. J., & Greene, C. M. (2019). False
memories for fake news during Ireland’s abortion referendum. Psychological
science, 30(10), 1449–1459.
Niederdeppe, J., Gollust, S. E., & Barry, C. L. (2014). Inoculation in competitive
framing examining message effects on policy preferences. Public opinion quarterly,
78(3), 634–655.
Nyhan, B., Porter, E., Reifler, J., & Wood, T. J. (2019). Taking fact-checks literally but
not seriously? The effects of journalistic fact-checking on factual beliefs and
candidate favorability. Political Behavior, 42, 939–960.
Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political
misperceptions. Political Behavior, 32(2), 303–330.
OED. (2016). Oxford University Press.
Ognyanova, K., Lazer, D., Robertson, R. E., & Wilson, C. (2020). Misinformation in
action: Fake news exposure is linked to lower trust in media, higher trust in
government when your side is in power. Harvard Kennedy School
Misinformation Review, 1(4).
Oreskes, N., & Conway, E. M. (2010). Merchants of doubt. Bloomsbury Publishing.
Parker, K. A., Ivanov, B., & Compton, J. (2012). Inoculation’s Efficacy With Young
Adults‘ Risky Behaviors: Can Inoculation Confer Cross-Protection Over Related
but Untreated Issues?. Health communication, 27(3), 223–233.
Parker, K. A., Rains, S. A., & Ivanov, B. (2016). Examining the “blanket of protection”
conferred by inoculation: The effects of inoculation messages on the cross-
protection of related attitudes. Communication monographs, 83(1), 49–68.
Peretti-Watel, P., Seror, V., Cortaredona, S., Launay, O., Raude, J., Verger, P.,
Fressard, L., Beck, F., Legleye, S., L’Haridon, O., Léger, D., & Ward, J. K. (2020).
A future vaccination campaign against COVID-19 at risk of vaccine hesitancy and
politicisation. The Lancet infectious diseases, 20(7), 769–770.
Pfau, M. (1997). The inoculation model of resistance to influence. Progress in
Communication Sciences, 13, 133–172.
Pfau, M., Ivanov, B., Houston, B., Haigh, M., Sims, J., Gilchrist, E., Russell, J.,
Wigley, S., Eckstein, J., & Richert, N. (2005). Inoculation and mental processing:
The instrumental role of associative networks in the process of resistance to
counterattitudinal influence. Communication monographs, 72(4), 414–441.
Pfau, M., Szabo, A., Anderson, J., Morrill, J., Zubric, J., & Wan, -H.-H.. (2001). The
role and impact of affect in the process of resistance to persuasion. Human
communication research, 27(2), 216–252.
Poland, G. A., & Spier, R. (2010). Fear, misinformation, and innumerates: How the
Wakefield paper, the press, and advocacy groups damaged the public health.
Vaccine, 28(12), 2361–2362.
Pryor, B., & Steinfatt, T. M. (1978). THE EFFECTS OF INITIAL BELIEF LEVEL ON
munication research, 4(3), 217–230.
Quick, B. L., Scott, A. M., & Ledbetter, A. M. (2011). A close examination of
trait reactance and issue involvement as moderators of psychological reac-
tance theory. Journal of health communication, 16(6), 660–679. https://doi.
Quinnipiac. (2018). U.S. voters give Trump highest grade ever on economy.
Quinnipiac University.
Reader, R. (2020, October 13). This game can stop people from falling for COVID-19
conspiracies. FastCompany.
Readfearn, G. (2016). Revealed: Most popular climate story on social media told half
a million people the science was a hoax. DeSmogBlog. DeSmog. https://www.
Richards, A. S., & Banas, J. A. (2015). Inoculating against reactance to persuasive
health messages. Health communication, 30(5), 451–460.
Roozenbeek, J., Maertens, R., McClanahan, W. P., & van der Linden, S. (2020a).
Disentangling Item and Testing Effects in Inoculation Research on Online
Misinformation: Solomon Revisited. Educational and Psychological
Measurement, 001316442094037.
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L., Recchia, G.,
van der Bles, A. M., & van der Linden, S. (2020b). Susceptibility to misinformation
about COVID-19 around the world. Royal Society Open Science, 7(10), 201199.
Roozenbeek, J., & van der Linden, S. (2019a). The fake news game: Actively inocu-
lating against the risk of misinformation. Journal of risk research, 22(5), 570–580.
Roozenbeek, J., & van der Linden, S. (2019b). Fake news game confers psychological
resistance against online misinformation. Nature Humanities and Social Sciences
Communications, 5(65).
Roozenbeek, J., & van der Linden, S. (2020). Breaking Harmony Square: A game that
“inoculates” against political misinformation. The Harvard Kennedy School
Misinformation Review, 1(8).
Roozenbeek, J., van der Linden, S., & Nygren, T. (2020). Prebunking interventions
based on the psychological theory of “inoculation” can reduce susceptibility to
misinformation across cultures. Harvard Kennedy School Misinformation Review,
Saleh, N., Roozenbeek, J., Makki, F., McClanahan, W.P., & van der Linden, S. (2021).
Active inoculation boosts attitudinal resistance against extremist persuasion tech-
niques: a novel approach towards the prevention of violent extremism.
Behavioural Public Policy, 1–24.
Schaeffer, K. (2020). Nearly three-in-ten Americans believe COVID-19 was made in
a lab. Pew Research Center.
Sharp, B., Danenberg, N., & Bellman, S. (2018). Psychological targeting. Proceedings
of the National Academy of Sciences, 115(34), E7890–E7890.
Soroka, S., Fournier, P., & Nir, L. (2019). Cross-national evidence of a negativity bias
in psychophysiological reactions to news. Proceedings of the National Academy of
Sciences, 116(38), 18888–18892.
Swire, B., & Ecker, U. K. H. (2017). Misinformation and its correction: Cognitive
mechanisms and recommendations for mass communication. In B. Southwell,
E. A. Thorson, & L. Sheble (Eds.), Misinformation and mass audiences. Austin, TX:
University of Texas Press. 195–211.
Swire, B., Berinsky, A. J., Lewandowsky, S., & Ecker, U. K. H. (2017). Processing
political misinformation: Comprehending the Trump phenomenon. Royal Society
Open Science, 4(3), 160802.
Swire-Thompson, B., Ecker, U. K. H., Lewandowsky, S., & Berinsky, A. J. (2020).
They might be a liar but they’re my liar: Source evaluation and the prevalence of
misinformation. Political psychology, 41(1), 21–34.
Tormala, Z. L., & Petty, R. E. (2004). Source credibility and attitude certainty:
A metacognitive analysis of resistance to persuasion. Journal of Consumer
Psychology, 14(4), 427–442.
Urban, M. (2019). Skripal poisoning: Third Russian suspect “commanded attack”.
van der Linden, S. (2019). Countering science denial. Nature Human Behaviour, 3(9),
van der Linden, S., & Roozenbeek, J. (2020). Psychological inoculation against fake
news. In R. Greifeneder, M. Jaffé, E. J. Newman, & N. Schwarz (Eds.), The
psychology of fake news: Accepting, sharing, and correcting misinformation (pp.
147–169). Psychology Press.
van der Linden, S., Leiserowitz, A., & Maibach, E. (2019). The gateway belief model:
A large-scale replication. Journal of Environmental Psychology, 62, 49–58. https://
van der Linden, S., Leiserowitz, A., Rosenthal, S., & Maibach, E. (2017). Inoculating
the public against misinformation about climate change. Global Challenges, 1(2),
van der Linden, S., Maibach, E., Cook, J., Leiserowitz, A., & Lewandowsky, S. (2017).
Inoculating against misinformation.. Science (New York, N.Y.), 358(6367),
van der Linden, S., Panagopoulos, C., & Roozenbeek, J. (2020). You are fake news:
Political bias in perceptions of fake news. Media, Culture & Society, 42(3),
van der Linden, S., Roozenbeek, J., & Compton, J. (2020). Inoculating against fake
news about COVID-19. Frontiers in Psychology, 11, 11, 566790.
van der Linden, S. L., Leiserowitz, A. A., Feinberg, G. D., & Maibach, E. W. (2015).
The scientific consensus on climate change as a gateway belief: Experimental
evidence. PloS One, 114(28), e0118489.
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online.
Science, 359(6380), 1146–1151.
Walter, N., & Murphy, S. T. (2018). How to unring the bell: A meta-analytic
approach to correction of misinformation. Communication monographs, 85(3),
Watson, L. (2018). Systematic epistemic rights violations in the media: A Brexit case
study. Social Epistemology, 32(2), 88–102.
Wilkes, A. L., & Leatherbarrow, M. (1988). Editing episodic memory following the
identification of error. Quarterly Journal of Experimental Psychology: Human
Experimental Psychology, 40(2), 361–387.
Wood, M. J., Douglas, K. M., & Sutton, R. M. (2012). Dead and alive: Beliefs in
contradictory conspiracy theories. Social psychological and personality science, 3
(6), 767–773.
Wood, M. L. M. (2007). Rethinking the inoculation analogy: Effects on subjects with
differing preexisting attitudes. Human communication research, 33(3), 357–378.
Wood, T., & Porter, E. (2018). The elusive backfire effect: Mass attitudes’ steadfast
factual adherence. Political Behavior, 41(1), 135-163.
Youyou, W., Kosinski, M., & Stillwell, D. (2015). Computer-based personality judg-
ments are more accurate than those made by humans. Proceedings of the National
Academy of Sciences, 112(4), 1036–1040.
Zerback, T., Töpfl, F., & Knöpfle, M. (2020). The disconcerting potential of online
disinformation: Persuasive effects of astroturfing comments and three strategies
for inoculation against them. New Media & Society.
... He posits that "just as vaccines trigger the production of antibodies to help confer immunity against future infection, the same can be achieved with information" (p.464). Real-time debunking and misinformation detection techniques are important organizational capabilities, but only after inoculation, that is, prevention measures, have failed (Lewandowsky and van der Linden, 2021). A systematic review by Skafle et al. (2022) revealed that scholarship concerned with COVID-19 related misinformation on social media primarily deals with the types of misinformation (conspiracy claims, medical misinformation, vaccine development) and its effects such as vaccine hesitancy. ...
... Reactive Lewandowsky and van der Linden, 2021;Chan et al., 2017 Existing research heavily focuses on the reactive phases of misinformation containment such as detection (Asr and Taboada, 2019;Shu et al., 2017) and debunking (Chan et al., 2017). According to Lewandowsky and van der Linden (2021) and Ecker et al. (2022), the preventive phase of misinformation is largely overlooked. ...
... Reactive Lewandowsky and van der Linden, 2021;Chan et al., 2017 Existing research heavily focuses on the reactive phases of misinformation containment such as detection (Asr and Taboada, 2019;Shu et al., 2017) and debunking (Chan et al., 2017). According to Lewandowsky and van der Linden (2021) and Ecker et al. (2022), the preventive phase of misinformation is largely overlooked. Research that explains the mechanisms of misinformation prevention, however, could contribute to our understanding of reducing the amount of misinformation that is created in the first place. ...
Purpose – This study investigates the communication behavior of public health organizations on Twitter during the COVID-19 vaccination campaign in Brazil. It contributes to the understanding of the organizational framing of health communication by showcasing several instances of framing devices that borrow from (Brazilian) internet culture. The investigation of this case extends our knowledge by providing a rich description of the organizational framing of health communication to combat misinformation in a politically charged environment. Design/methodology/approach – The authors collected a Twitter dataset of 77,527 tweets and analyzed a purposeful subsample of 536 tweets that contained information provided by Brazilian public health organizations about COVID-19 vaccination campaigns. The data analysis was carried out quantitatively and qualitatively by combining social media analytics techniques and frame analysis. Findings – The analysis showed that Brazilian health organizations used several framing devices that have been identified by previous literature such as hashtags, links, emojis, or images. However, the analysis also unearthed hitherto unknown visual framing devices for misinformation prevention and debunking that borrow from internet culture such as ‘infographics,’ ‘pop culture references,’ and ‘internet-native symbolism.’ Practical implications – The findings inform decision-makers and public health organizations about framing devices that are tailored to internet-native audiences and can guide strategies to carry out information campaigns in misinformation-laden social media environments. Social implications – The findings of this case study expose the often-overlooked cultural peculiarities of framing information campaigns on social media. The report of this study from a country in the Global South helps to contrast several assumptions and strategies that are prevalent in (health) discourses in Western societies and scholarship. Originality/value – This study uncovers unconventional and barely addressed framing devices of health organizations operating in Brazil, which provides a novel perspective to the body of research on misinformation. It contributes to existing knowledge about frame analysis and broadens the understanding of frame devices borrowing from internet culture. It is a call for a frontier in misinformation research that deals with internet culture as part of organizational strategies for successful misinformation combat.
... This provides an explanatory basis for the role of COR. Although there are studies (Banas, 2020;Pryor & Steinfatt, 1978) that have broadened the horizons of the inoculation theory, it has been applied most to explain how individuals resist persuasion through pretraining (Compton & Pfau, 2005;Lewandowsky & van der Linden, 2021). A few studies have used inoculation theory to explain the effect of another type of pretraining (i.e. ...
... (2) This study provides a new perspective on inoculation theory in terms of CBS. Previous inoculation theory studies have focused on how users can be inoculated to resist persuasion (Compton & Pfau, 2005;Lewandowsky & van der Linden, 2021). As there are studies (e.g. ...
Social media provides individuals with tremendous opportunities to follow nearly unlimited influencers online, prompting scholars’ concern about confirmation bias and the need to address it. Based on data from 894 participants, this study explores the positive effect of perceived influence on confirmation bias in social media contexts and the negative moderating effect of civic online reasoning on this relationship. These findings indicate that efforts in public media literacy education for citizens must be enhanced to transform subconscious defense mechanisms into mature coping skills through critical thinking.
... To this, the goal of this paper is not only to evaluate news items, i.e. to understand if the news is real or fake, but also to develop a prebunking system [4], i.e. the process of debunking lies, fake news or sources before they strike, by evaluating the trustworthiness of the news providers. ...
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Technological development combined with the evolution of the Internet has made it possible to reach an increasing number of people over the years and given them the opportunity to access information published on the network. The growth in the number of fake news generated daily, combined with the simplicity with which it is possible to share them, has created such a large phenomenon that it has become immediately uncontrollable. Furthermore, the quality with which malicious content is made is increasingly high so even professional experts, such as journalists, have difficulty recognizing which news is fake and which is real. This paper aims to implement an architecture that provides a service to final users that assures the reliability of news providers and the quality of news based on innovative tools. The proposed models take advantage of several Machine Learning approaches for fake news detection tasks and take into account well-known attacks on trust. Finally, the implemented architecture is tested with a well-known dataset and shows how the proposed models can effectively identify fake news and isolate malicious sources.
... The terms "misinformation" and "disinformation" are both referenced to describe the nature of information being untrue (Shin et al., 2018). While misinformation refers to false or misleading information in general, the motivation for the spread of misinformation is unknown and not necessarily with the intent to manipulate (Lewandowsky and Van Der Linden, 2021). Disinformation, on the other hand, specifically refers to false information being spread with the deliberate intent to manipulate or confuse the public (Institute for Public Relations, 2019). ...
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Purpose This study aims to propose a model that delineated the diffusion process of product-harm misinformation on social media. Drawing on theoretical insights from cue diagnosticity and corporate associations, the proposed model mapped out how consumers' information skepticism and perceived content credibility influence their perceived diagnosticity of the product-harm misinformation and corporate ability (CA) associations with the company being impacted, which in turn influenced their trust toward the company and negative word-of-mouth (NWOM) intention. Design/methodology/approach A survey was conducted with 504 US consumers to empirically test the proposed model. Following the survey, in-depth interviews were conducted with 11 communication professionals regarding the applicability of the model. Findings When exposed to product-harm misinformation on social media, consumers' perceived diagnosticity of misinformation was negatively impacted by their information skepticism and positively impacted by perceived content credibility of misinformation. Perceived diagnosticity of product-harm misinformation negatively impacted consumers' CA associations, which then led to decreased trust and increased NWOM intention. Findings from the interviews further supported the diffusion process and provided insights on strategies to combat product-harm misinformation. Strategies shared by the interviewees included preparedness and social listening, proactive outreach and building strong CA associations as preventative measures. Originality/value This study incorporates the theoretical frameworks of cue diagnosticity and corporate associations into the scholarship of misinformation and specifically addresses the unique diffusion process of product-harm misinformation on social media. This study provides insights and tangible recommendations for communication professionals to combat product-harm misinformation.
... Social media ecosystem is often polluted by false information, extreme partisan messages, financially motivated hoaxes, hate speech, rumor, and satire. To address these issues, different formats of fact-checking -from prebunking (i.e., alerting individuals to the fakeness of incoming information, Lewandowsky and Van Der Linden 2021) to debunking/correction (Chung and Kim 2021; Kligler-Vilenchik 2022) -have been employed to help individuals better assess the veracity of information. ...
... For example, a video deepfake [81] intended to influence public opinion in a certain direction (perhaps by misrepresenting the actions of a political figure) may be unethical because the people who are influenced are not made fully aware of this intention. Had they been aware, they would have assigned less credence to the information contained in the video [74]. See Box 2 for a more general discussion of intent as it relates to the ethics of influence. ...
Agents often exert influence when interacting with humans and non-human agents. However, the ethical status of such influence is often unclear. In this paper, we present the SHAPE framework, which lists reasons why influence may be unethical. We draw on literature from descriptive and moral philosophy and connect it to machine learning to help guide ethical considerations when developing algorithms with potential influence. Lastly, we explore mechanisms for governing algorithmic systems that influence people, inspired by mechanisms used in journalism, human subject research, and advertising.
The COVID-19 pandemic provides a unique opportunity to study science communication and, in particular, the transmission of consensus. In this study, we show how “science communicators,” writ large to include both mainstream science journalists and practiced conspiracy theorists, transform scientific evidence into two dueling consensuses using the effectiveness of masks as a case study. We do this by compiling one of the largest, hand-coded citation datasets of cross-medium science communication, derived from 5 million Twitter posts of people discussing masks. We find that science communicators selectively uplift certain published works while denigrating others to create bodies of evidence that support and oppose masks, respectively. Anti-mask communicators in particular often use selective and deceptive quotation of scientific work and criticize opposing science more than pro-mask communicators. Our findings have implications for scientists, science communicators, and scientific publishers, whose systems of sharing (and correcting) knowledge are highly vulnerable to what we term adversarial science communication.
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Theoretischer Hintergrund: Forschung zu Wissenschaftsvertrauen berichtet den sogenannten “Easiness Effekt” (Scharrer et al., 2012, 2019) und den “Scientificness Effekt” (Bromme et al., 2015; Thomm & Bromme, 2012). Bei ersterem schätzen Leser:innen einen als zugänglich wahrgenommenen Text als vertrauenswürdiger ein und stimmen dessen Aussagen eher zu. Letzterer beschreibt einen ähnlichen Effekt, wenn Informationen in einem wissenschaftlichen Stil (z.B. mittels Referenzen, Methodenbeschreibungen und neutralem Ton) präsentiert werden. Es existiert allerdings wenig Forschung zur Interaktion der Effekte, zum Einfluss von Wissenschaftlichkeitsmerkmalen auf Autor:innen- und Textebene sowie zur Rolle subjektiver Wahrnehmung von Wissenschaftlichkeit durch Leser:innen für diese Prozesse. Fragestellung: Mehrere Fragen werden diskutiert: 1. Lassen sich die genannten Effekte replizieren und zeigen Einfachheit und Wissenschaftlichkeit eine Interaktion mit Blick auf Vertrauen? 2. Führt eine hohe Wissenschaftlichkeit sowohl auf Autor:innen- als auch Textebene zu höherem Vertrauen? 3. Mediiert die subjektive Wahrnehmung von Wissenschaftlichkeit den “Scientificness Effect”? Methode: Die erste Fragestellung wurde mit einer präregstrierten Online-Studie mit N = 1467 Proband:innen aus der deutschsprachigen Allgemeinbevölkerung untersucht. Dabei lasen Proband:innen vier Kurzzusammenfassungen psychologischer Forschung, die systematisch Einfachheit und Wissenschaftlichkeit variierten (hoch vs. niedrig). Nach jeder Zusammenfassung schätzten sie ihr Vertrauen in die Zusammenfassungen selbst (achtstufige Likert-Skala) sowie deren Autorinnen ein (METI, Hendriks et al., 2015). Die Auswertung erfolgte mittels Mixed Model Analysen in R. Für die weiteren Fragestellungen wird ab April/Mai 2023 eine zweite Online-Studie (N = 864) mit einer vergleichbaren Stichprobe durchgeführt. In zwei Kurzzusammenfassungen wird Wissenschaftlichkeit auf Autor:innenebene (akademischer Grad, Affiliation, Bedeutsamkeit der Forschung, Arbeitsweise) sowie Textebene (Referenzen, Methodenbeschreibungen, neutraler Ton) variiert. Für die Vertrauenseinschätzungen werden erneut die oben beschriebenen Maße genutzt, und es wird zunächst eine Pilotstudie durchgeführt. Die Auswertung erfolgt mittels Mediationsanalysen. Ergebnisse: Die Auswertung der ersten Studie ergab einen signifikant positiven Einfluss von Wissenschaftlichkeit auf Vertrauen (β = .142 - .512, SE = .027 - .033, ps < .001, R² = .003 - .037), allerdings keinen Einfluss von Einfachheit (β = -.027 -.032, ps > .343) oder eine Interaktion der Effekte (β = -.009 - -.40, ps >. 285). Die Ergebnisse der zweiten Studie werden im Rahmen des Vortrags vorgestellt. Implikationen für Theorie und Praxis: Die Ergebnisse der ersten Studie lassen, anknüpfend an bestehende Forschung (Tolochko et al., 2019), lediglich geringe Auswirkungen von syntaktischer Einfachheit auf Vertrauen vermuten. Die zweite Studie ermöglicht, die Rolle subjektiver Wahrnehmung von Leser:innen bezüglich Vertrauensurteilen differenzierter zu betrachten. Und schließlich ergeben sich praktische Implikationen für die Gestaltung wissenschaftlicher Texte (z.B. Nutzung von Referenzen und wertender Sprache).
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As legitimate and voluminous as vexations about disinformation are, intended and unintended injury to information integrity—and to individuals consuming compromised content—are not new phenomena on the socio-political landscape. The circulation of exaggeration and lies is an historical reality of human self-organization. Yet the volume, velocity, and variety of contemporary disinformation makes an infodemic diagnosis a reasonable one and the successional levels of disinformed citizenship a legitimate concern for democracy’s preservation. In light of this threat, we trace the salient trajectories and philosophical fault lines related to disinformation and offer diagnostics and present-day mitigation strategies for this hazard.
Background: Promoting COVID-19 vaccination (both the primary series and boosters) remains a priority among healthcare professionals and requires understanding the various sources people trust for acquiring COVID-19 information. Method: From October 2021 to May 2022, we interviewed 150 people who called 2-1-1 helplines in Connecticut and North Carolina about their COVID-19 testing and vaccination experiences in order to (1) better understand where people obtain trusted COVID-19 health information and (2) identify how public health professionals can share emergency health information in the future. We used a mixed methods approach in which semi-structured qualitative interviews and survey data were collected in parallel and analyzed separately. Results: Participants were mostly female (74.0%), Black (43.3%) or White (38.0%), and had a high school degree or higher (88.0%). Most had prior COVID-19 testing experience (88.0%) and were vaccinated (82.7%). A variety of information sources were rated as being very trustworthy including medical professionals and social service organizations. We found that repetition of information from multiple sources increased trust; however, perceived inconsistencies in recommendations over time eroded trust in health communication, especially from government-affiliated information sources. Observations such as seeing long lines for COVID-19 testing or vaccination became internalized trusted information. Conclusions: Public health professionals can leverage the reach and strong community ties of existing, reputable non-government organizations, such as physician groups, schools, and pharmacies, to distribute COVID-19 information about vaccination and testing.
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The Internet is gaining relevance as a platform where extremist organizations seek to recruit new members. For this preregistered study, we developed and tested a novel online game, Radicalise, which aims to combat the effectiveness of online recruitment strategies used by extremist organizations, based on the principles of active psychological inoculation. The game “inoculates” players by exposing them to severely weakened doses of the key techniques and methods used to recruit and radicalize individuals via social media platforms: identifying vulnerable individuals, gaining their trust, isolating them from their community and pressuring them into committing a criminal act in the name of the extremist organization. To test the game’s effectiveness, we conducted a preregistered 2 × 2 mixed (pre–post) randomized controlled experiment (n = 291) with two outcome measures. The first measured participants’ ability and confidence in assessing the manipulativeness of fictitious WhatsApp messages making use of an extremist manipulation technique before and after playing. The second measured participants’ ability to identify what factors make an individual vulnerable to extremist recruitment using 10 profile vignettes, also before and after playing. We find that playing Radicalise significantly improves participants’ ability and confidence in spotting manipulative messages and the characteristics associated with vulnerability.
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The Internet has evolved into a ubiquitous and indispensable digital environment in which people communicate, seek information, and make decisions. Despite offering various benefits, online environments are also replete with smart, highly adaptive choice architectures designed primarily to maximize commercial interests, capture and sustain users’ attention, monetize user data, and predict and influence future behavior. This online landscape holds multiple negative consequences for society, such as a decline in human autonomy, rising incivility in online conversation, the facilitation of political extremism, and the spread of disinformation. Benevolent choice architects working with regulators may curb the worst excesses of manipulative choice architectures, yet the strategic advantages, resources, and data remain with commercial players. One way to address some of this imbalance is with interventions that empower Internet users to gain some control over their digital environments, in part by boosting their information literacy and their cognitive resistance to manipulation. Our goal is to present a conceptual map of interventions that are based on insights from psychological science. We begin by systematically outlining how online and offline environments differ despite being increasingly inextricable. We then identify four major types of challenges that users encounter in online environments: persuasive and manipulative choice architectures, AI-assisted information architectures, false and misleading information, and distracting environments. Next, we turn to how psychological science can inform interventions to counteract these challenges of the digital world. After distinguishing among three types of behavioral and cognitive interventions—nudges, technocognition, and boosts—we focus on boosts, of which we identify two main groups: (a) those aimed at enhancing people’s agency in their digital environments (e.g., self-nudging, deliberate ignorance) and (b) those aimed at boosting competencies of reasoning and resilience to manipulation (e.g., simple decision aids, inoculation). These cognitive tools are designed to foster the civility of online discourse and protect reason and human autonomy against manipulative choice architectures, attention-grabbing techniques, and the spread of false information.
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Background Our aim was to estimate provisional willingness to receive a coronavirus 2019 (COVID-19) vaccine, identify predictive socio-demographic factors, and, principally, determine potential causes in order to guide information provision. Methods A non-probability online survey was conducted (24th September−17th October 2020) with 5,114 UK adults, quota sampled to match the population for age, gender, ethnicity, income, and region. The Oxford COVID-19 vaccine hesitancy scale assessed intent to take an approved vaccine. Structural equation modelling estimated explanatory factor relationships. Results 71.7% (n=3,667) were willing to be vaccinated, 16.6% (n=849) were very unsure, and 11.7% (n=598) were strongly hesitant. An excellent model fit (RMSEA=0.05/CFI=0.97/TLI=0.97), explaining 86% of variance in hesitancy, was provided by beliefs about the collective importance, efficacy, side-effects, and speed of development of a COVID-19 vaccine. A second model, with reasonable fit (RMSEA=0.03/CFI=0.93/TLI=0.92), explaining 32% of variance, highlighted two higher-order explanatory factors: ‘excessive mistrust’ (r=0.51), including conspiracy beliefs, negative views of doctors, and need for chaos, and ‘positive healthcare experiences’ (r=−0.48), including supportive doctor interactions and good NHS care. Hesitancy was associated with younger age, female gender, lower income, and ethnicity, but socio-demographic information explained little variance (9.8%). Hesitancy was associated with lower adherence to social distancing guidelines. Conclusions COVID-19 vaccine hesitancy is relatively evenly spread across the population. Willingness to take a vaccine is closely bound to recognition of the collective importance. Vaccine public information that highlights prosocial benefits may be especially effective. Factors such as conspiracy beliefs that foster mistrust and erode social cohesion will lower vaccine up-take.
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We present Harmony Square, a short, free-to-play online game in which players learn how political misinformation is produced and spread. We find that the game confers psychological resistance against manipulation techniques commonly used in political misinformation: players from around the world find social media content making use of these techniques significantly less reliable after playing, are more confident in their ability to spot such content, and less likely to report sharing it with others in their network.
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The outbreak of the SARS-CoV-2 novel coronavirus (COVID-19) has been accompanied by a large amount of misleading and false information about the virus, especially on social media. In this article, we explore the coronavirus “infodemic” and how behavioral scientists may seek to address this problem. We detail the scope of the problem and discuss the negative influence that COVID-19 misinformation can have on the widespread adoption of health protective behaviors in the population. In response, we explore how insights from the behavioral sciences can be leveraged to manage an effective societal response to curb the spread of misinformation about the virus. In particular, we discuss the theory of psychological inoculation (or prebunking) as an efficient vehicle for conferring large-scale psychological resistance against fake news.