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Psychological Medicine
cambridge.org/psm
Original Article
Cite this article: Freeman D et al (2020).
Coronavirus conspiracy beliefs, mistrust, and
compliance with government guidelines in
England. Psychological Medicine 1–13. https://
doi.org/10.1017/S0033291720001890
Received: 19 May 2020
Accepted: 19 May 2020
Key words:
conspiracy beliefs; mistrust; paranoia; public
health; vaccination hesitancy
Author for correspondence:
Daniel Freeman,
E-mail: daniel.freeman@psych.ox.ac.uk
© The Author(s) 2020. Published by Cambridge
University Press. This is an Open Access article,
distributed under the terms of the Creative
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non-commercial re-use, distribution, and
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Press must be obtained for commercial re-use.
Coronavirus conspiracy beliefs, mistrust, and
compliance with government guidelines in
England
Daniel Freeman1,2 , Felicity Waite1,2, Laina Rosebrock1,2, Ariane Petit1,2,
Chiara Causier1,2, Anna East1,2, Lucy Jenner1,2, Ashley-Louise Teale1,2,
Lydia Carr1,2, Sophie Mulhall1,2, Emily Bold1, 2 and Sinéad Lambe1,2
1
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK and
2
Oxford Health NHS
Foundation Trust, Oxford, UK
Abstract
Background. An invisible threat has visibly altered the world. Governments and key institu-
tions have had to implement decisive responses to the danger posed by the coronavirus pan-
demic. Imposed change will increase the likelihood that alternative explanations take hold. In
a proportion of the general population there may be strong scepticism, fear of being misled,
and false conspiracy theories. Our objectives were to estimate the prevalence of conspiracy
thinking about the pandemic and test associations with reduced adherence to government
guidelines.
Methods. A non-probability online survey with 2501 adults in England, quota sampled to
match the population for age, gender, income, and region.
Results. Approximately 50% of this population showed little evidence of conspiracy thinking,
25% showed a degree of endorsement, 15% showed a consistent pattern of endorsement, and
10% had very high levels of endorsement. Higher levels of coronavirus conspiracy thinking
were associated with less adherence to all government guidelines and less willingness to
take diagnostic or antibody tests or to be vaccinated. Such ideas were also associated with
paranoia, general vaccination conspiracy beliefs, climate change conspiracy belief, a conspiracy
mentality, and distrust in institutions and professions. Holding coronavirus conspiracy beliefs
was also associated with being more likely to share opinions.
Conclusions. In England there is appreciable endorsement of conspiracy beliefs about corona-
virus. Such ideas do not appear confined to the fringes. The conspiracy beliefs connect to
other forms of mistrust and are associated with less compliance with government guidelines
and greater unwillingness to take up future tests and treatment.
Introduction
In times of national crisis, individual differences in explanatory beliefs may affect the degree of
adherence to necessary collective responses. Accurate beliefs foster helpful behaviours; errone-
ous beliefs foster unhelpful behaviours. In the current coronavirus pandemic, we focus on the
potential influence of false conspiracy theories (Sunstein & Vermeule, 2009) on the English
population’s response. Conspiracy theories typically have four common characteristics
(Freeman & Bentall, 2017): the world or an event is held to be not as it seems; there is believed
to be a cover-up by powerful others; the theory is accepted only by a minority; and the theory
is unsupported by evidence. There are likely to be varying degrees of such mistrust, from exces-
sive scepticism to detailed ideas concerning perpetrators, motivations, and modi operandi.
This mistrust can be conceptualised as a conspiracy mentality (Brotherton, French, &
Pickering, 2013; Goertzel, 1994; Imhoff & Bruder, 2014): a way of seeing the world that is
marked by antipathy to official or mainstream accounts or to those in higher status positions.
This conspiracy mind-set can be seen in evidence that holding one conspiracy belief raises the
likelihood of unrelated conspiracy beliefs (Swami, Chamorro-Premuzic, & Furnham, 2010)
and that individuals can simultaneously endorse mutually incompatible conspiracy beliefs
(Wood, Douglas, & Sutton, 2012). Conspiracy beliefs are unlikely to be benign. For instance,
parental belief in anti-vaccine conspiracy theories is associated with lower intent to vaccinate a
child (Jolley & Douglas, 2014), while such theories are cited by parents who do not vaccinate
their children (Attwell, Leask, Meyer, Rokkas, & Ward, 2017; Luthy, Beckstrand, Callister, &
Cahoon, 2012). In our view multiple features of the current pandemic make conspiracy beliefs
likely to develop and propagate. Such erroneous beliefs will weaken collective actions necessary
to minimise harm to the population.
Our perspective on conspiracy beliefs is rooted in the psychology of mistrust. Conspiracy
theories are attempts to explain world events that are threatening or inconsistent with
personal expectations. The acceptance of conspiracy explana-
tions is much more likely when an individual tends to mistrust.
A mistrusting mind-set –a defensive response of wariness –will
occur when there is perceived vulnerability and a sense of assail-
ment. Perceptions of vulnerability and attack can be linked to
low self-esteem, poorer psychological well-being, powerlessness,
and anger. Mistrust of authority or higher status groups is more
likely when there is a perception of (real or subjective) social
marginalisation. When emotion is heightened by perceived dan-
ger, individuals are likely to accept the explanations, however
unlikely, that conform to preconceptions. The more cognitively
taxing process of carefully weighing up the evidence for
and against different explanations is unlikely to be adopted.
Conspiracy beliefs are likely to bring short-term benefits, such
as a reduction in uncertainty and increase in control; access
(often online) to like-minded people; and a sense of having pri-
vileged information. It has been argued that the benefits can be
categorised as epistemic (e.g. understanding), existential (e.g.
control), and social (e.g. positive self-image) (Douglas et al.,
2019). Conspiracy beliefs and paranoia are associated (Goreis
& Voracek, 2019) but the shared nature of conspiracy beliefs is
most likely less unhealthy in comparison to paranoia, in which
the individual alone is the target. Empirical evidence has linked
conspiracy beliefs to perceptions of threat from societal
change (Federico, Williams, & Vitriol, 2018), uncertainty (van
Prooijen & Jostmann, 2013), powerlessness (Abalakina-Paap,
Stephan, Craig, & Gregory, 1999), lack of socio-political control
(Bruder, Haffke, Neave, Nouripanah, & Imhoff, 2013), percep-
tions of lower social status (Freeman & Bentall, 2017), less ana-
lytic thinking (Swami, Voracek, Stieger, Tran, & Furnham,
2014), lower levels of education and income (Douglas, Sutton,
Callan, Dawtry, & Harvey, 2016;Freeman&Bentall,2017),
and being a member of a disadvantaged social group (Davis,
Wetherell, & Henry, 2018). Political extremes (left or right)
are most associated with the endorsement of conspiracy beliefs
(Krouwel, Kutiyski, van Prooijen, Martinsson, & Markstedt,
2017; van Prooijen, Krouwel, & Pollet, 2015).
The coronavirus pandemic and associated countermeasures
have created conditions in which conspiracy beliefs are likely to
develop. Such conditions include the sense of vulnerability trig-
gered by the sustained threat to physical health, psychological
well-being, and financial security. Uncertainty about the future
is widespread. Expectations about everyday life have changed
rapidly and dramatically, with top-down imposition of explana-
tions and required responses, enforceable by law. Normal routines
and plans have been thwarted. The effects of the countermeasures
are likely to have been greatest in those in lower socio-economic
circumstances. There is much talk of medical tests and vaccina-
tions, while many individuals have greater time to themselves,
in isolation, and with the Internet to hand. We hypothesise
that: a significant minority of the population hold excessively
sceptical views, including clear false conspiracy beliefs, of official
explanations of the coronavirus pandemic; these ideas connect
with pre-existing conspiracy theories, especially about vaccina-
tions; and conspiracy ideas are associated with less compliance
with government guidance such as social distancing and less will-
ingness to take up future tests and vaccinations. We would expect
conspiracy beliefs to be more likely to be held by those who are
more marginalised, reflected by lower levels of psychological well-
being, education, and income. We also took the opportunity to
survey individuals’appraisals of positive outcomes in the response
to the pandemic.
Methods
Participants
An online survey with a quota sampled participant group was con-
ducted by Lucid (https://luc.id/) from 4th May 2020 to the 11th May
2020. The quotas used were based upon UK Office for National
Statistics (ONS) population estimate data. The quotas were for gen-
der (males = 49.35%, females = 50.65%), age (<18 = 21.30%, 18–24
= 9.4%, 25–34 = 13.4%, 35–44 = 14.00%, 45–54 = 13.7%, 55–64 =
11.70%, 65–99 = 16.50%), region (South East = 16.33%, North
West= 13.04%, East = 11.09%, West Midlands= 10.55%, South
West= 9.94%, East Midlands = 8.58%, North East = 4.76%,
London = 15.92%, Yorkshire and the Humber = 9.79%), and income
(<£ 15 000 = 17.06%, 15 000–19 999 = 9.11%, 20 000–29 999 =
18.63%, 30 000–39 999 = 15.32%, 40 000–49 999 = 11.81%, 50 000–
59 999 = 7.51%, 60 000–69 999 = 5.58%, 70 000–99 999 = 8.58%,
100 000–149 000 = 4.15%, 150 000 + = 2.25%). Lucid’s platform
serves as a centralised source for survey responses, working with
over 250 survey suppliers, all of whom adhere to the ESOMAR
Guidelines (https://www.esomar.org/what-we-do/code-guidelines).
Lucid operates a marketplace in which they advertise the survey to
suppliers, who provide individual participants, with sampling by
Lucid from this pool. The advantage of using multiple survey sources
is substantially less reliant on any particular demographic or segment
of the population. Respondents will have been sourced from: ads and
promotions across digital networks, search, word of mouth and
membership referrals, social networks, online and mobile games,
affiliate marketing, banner ads, offerwalls, TV and radio ads, and off-
line recruitment with mail campaigns. Participants have opted in to
being a panel member for the supplier as well as providing informed
consent to this particular survey. Individuals are not included if they
have responded to allquestions in the same way or have a completion
time that is less than one-third of the median.
The Oxford Coronavirus Explanations, Attitudes, and
Narratives Survey (OCEANS) was approved by the University of
Oxford Central University Research Ethics Committee (R
69510/RE001) and all participants provided informed consent.
Participants were given the following rationale for OCEANS:
‘Coronavirus has been a shock and lives have changed dramatic-
ally. At times of crisis, people may think of lots of different expla-
nations for what is occurring. We are interested in how common
different views may be and how they influence responses to the
crisis. It may inform the extent to which people follow current
lockdown guidance and take-up future treatments…A wide-
range of views are asked –some have a lot of evidence supporting
them, others have no evidence supporting them. You may agree
or disagree with explanations provided’.
Assessments
We collected demographic data, information on how the pan-
demic had affected each participant, and where they obtained
information about the virus. On seven-point scales, participants
rated religiosity (0 = not all religious, 6 = strongly religious) and
political viewpoint (0 = strongly left wing, 6 = strongly right
wing). They were also asked how they viewed the importance of
voting in general elections.
Conspiracy mentality questionnaire (CMQ) (Bruder et al., 2013)
This five-item scale assesses a non-content specific tendency to
see secretive forces behind events (e.g. ‘there are secret organiza-
tions that greatly influence political decisions’). Each item is rated
2 Daniel Freeman et al.
Table 1. Demographic information
Mean (S.D.)/n
(%)
Age (years) 46.6 (17.3)
Gender: male; female; other 1213; 1285; 3
Ethnicity:
White
English/Welsh/Scottish/Northern Irish/British 2009 (80.3)
Irish 24 (1.0)
Gypsy or Irish Traveller 10 (0.4)
Any other White background 117 (4.7)
Mixed/Multiple ethnic groups
White and Black Caribbean 11 (0.4)
White and Black African 16 (0.6)
White and Asian 24 (1.0)
Any other Mixed/Multiple ethnic background 34 (1.4)
Asian/Asian British
Indian 51 (2.0)
Pakistani 37 (1.5)
Bangladeshi 16 (0.6)
Chinese 35 (1.4)
Any other Asian background 30 (1.2)
Black/African/Caribbean/Black British
African 40 (1.6)
Caribbean 25 (1.0)
Any other Black/African/Caribbean background 5 (0.2)
Other ethnic group
Arab 11 (0.4)
Any other ethnic group 6 (0.2)
Marital status
Single 712 (28.5)
Cohabiting 327 (13.1)
Married or civil partnership 1157 (46.3)
Divorced or separated 207 (8.3)
Widowed 98 (3.9)
Highest level of education
No qualifications 119 (4.8)
GCSEs grades A*–C (or equivalent) 619 (24.8)
AS levels (or equivalent) 98 (3.9)
A levels (or equivalent) 599 (24.0)
Certificate of higher education (e.g. BA, BSc, or
equivalent)
763 (30.5)
Post-graduate qualifications (e.g. MA, MSc, PhD,
DPhil)
303 (12.1)
Total household income
Less than £ 15 000 428 (17.1)
(Continued)
Table 1. (Continued.)
Mean (S.D.)/n
(%)
£ 15 000–£ 19 999 237 (9.5)
£ 20 000–£ 29 999 481 (19.2)
£ 30 000–£ 39 999 393 (15.7)
£ 40 000–£ 49 999 307 (12.3)
£ 50 000–£ 59 999 195 (7.8)
£ 60 000–£ 69 999 137 (5.5)
£ 70 000–£ 99 999 203 (8.1)
£ 100 000–£ 149 999 81 (3.2)
£ 150 000 and above 39 (1.6)
Housing situation
Rented from council 377 (15.1)
Rented from private landlord 561 (22.4)
Homeowner 1460 (58.4)
Other 103 (4.1)
Living situation
Living alone (no children) 522 (20.9)
Living alone with children 174 (7.0)
Living with husband/wife (no children) 545 (21.8)
Living with husband/wife with children 472 (18.9)
Living together as a couple 260 (10.4)
Living together as a couple (with children) 190 (7.6)
Living with parents 236 (9.4)
Living with other relatives 46 (1.8)
Living with others 56 (2.2)
Region
South East 421 (16.8)
North West 331 (13.2)
East 252 (10.1)
West Midlands 262 (10.5)
South West 250 (10.0)
East Midlands 218 (8.7)
North East 115 (4.6)
London 411 (16.4)
Yorkshire and the Humber 241 (9.6)
Pre-coronavirus employment status
Unemployed 203 (8.1)
Employed full-time 1043 (41.7)
Employed part-time 349 (14.0)
Self-employed 186 (7.4)
Retired 510 (20.4)
Student 90 (3.6)
Housewife/husband 120 (4.8)
(Continued)
Psychological Medicine 3
on an 11-point scale from 0% (certainly not) to 100% (certain)
scale. Higher scores indicate a greater degree of conspiracy men-
tality. Cronbach’sαin the current study was 0.88.
Coronavirus conspiracy explanations
We asked participants to rate the extent to which they agreed with
48 conspiracy statements. Each item is rated on a five-point scale:
do not agree (1), agree a little (2), agree moderately (3), agree a
lot (4), agree completely (5). A higher score indicates greater
endorsement of a statement. The list of statements comprised: scep-
ticism about the government’s response (n=3)(e.g. ‘I’msceptical
about the official explanation about the cause of the virus’), general
conspiracy views on the cause of the virus (n=3)(e.g.‘The virus is
ahoax’), general conspiracy views about the spread of the virus
(n=7) (e.g. ‘The spread of the virus is a deliberate attempt to
reduce the size of the global population’), general conspiracy
views about the reasons for lockdown (n=5) (e.g.‘The real reason
for the lockdown is to impose mass surveillance’), and then specific
conspiracy beliefs (n= 30) (e.g. ‘The elite have created the virus in
order to establish a one-world government’). The statements were
generated from searching the internet in the preceding weeks of
the lockdown, looking at both mainstream and alternative sites,
which produced an initial list of 99 conspiracy statements. The
selection of items tried to balance out possibly opposing political
and religious views on causes and motivations. We also assessed
agreement with four official explanations (e.g. ‘The virus is most
likely to have originated from bats’).
Following of UK government coronavirus guidance
Participants were asked to rate how often they followed six key
aspects of government guidance on a five-point scale (not at all,
occasionally, some of the time, most of the time, all of the
time). Higher scores indicate greater levels of following the guid-
ance. Participants were also asked to rate on the same scale two
general items assessing how much they follow the guidance now
and how much they will in the future.
Future medical tests and treatment
Participants were asked to rate on a five-point scale (definitely,
probably, possibly, probably not, definitely not) how likely it
was that they would accept diagnostic tests and vaccination for
coronavirus, and whether they would wear a facemask outside if
advised. Higher scores indicate lower potential engagement.
Sharing coronavirus information
Participants were asked two questions concerning the degree to
which they shared with other information or opinions about the
coronavirus. Each was rated on a five-point scale (not at all, occa-
sionally, some of the time, most of the time, all of the time).
Higher scores indicate greater sharing.
Vaccine conspiracy beliefs scale (Shapiro, Holding, Perez, Amsel,
& Rosberger, 2016)
This seven-item questionnaire asks participants how much they
agree on a seven-point scale (strongly disagree, disagree, some-
what disagree, neutral, somewhat agree, agree, strongly agree)
with vaccine conspiracy statements (e.g. ‘Vaccine safety data is
often fabricated’). Higher scores indicate greater endorsement of
vaccine conspiracy statements. Cronbach’sαin the current
study was 0.95.
Climate change conspiracy belief (Bolsen & Druckman, 2018)
Participants were asked to rate on a seven-point scale (strongly
disagree, disagree, somewhat disagree, neither agree nor disagree,
somewhat agree, agree) how much they agreed with the statement
‘The idea that climate change is primarily due to human activities
is a hoax or a conspiracy’. Higher scores indicate greater belief in
the conspiracy.
Trust barometer (Edelman, 2020)
Items were constructed, based on the barometer, to assess levels of
trust in a number of institutions and professions. Each item is
rated on a five-point scale (1 never trust, 2 rarely trust, 3 some-
times trust, 4 often trust, 5 always trust).
Revised Green et al. paranoid thoughts scale –part B (R-GPTS)
(Freeman et al., 2019)
This 10-item questionnaire assesses persecutory ideation over the
past fortnight. Each item (e.g. ‘Certain individuals have had it in
for me’.) is rated on a 0 (not at all) to 4 (totally) scale. Higher
scores indicate higher levels of paranoia. Cronbach’sαin the cur-
rent study was 0.97.
Warwick−Edinburgh mental well-being scale (WEMWBS)
(Tennant et al., 2007)
The WEMWBS is a 14-item scale assessing psychological well-
being over the past fortnight. Each item (e.g. ‘I’ve been feeling
optimistic about the future’) is rated on a 1 (none of the time)
to 5 (all of the time) scale. Higher scores indicate a greater level
of well-being. Cronbach’sαin the current study was 0.93.
Positive experiences of the pandemic
At the end of the survey participants were asked to rate on a five-
point scale (do not agree, agree a little, agree moderately, agree a
Table 1. (Continued.)
Mean (S.D.)/n
(%)
Employment change due to coronavirus
None 1135 (45.4)
None, but working from a different location (e.g.
work from home)
373 (14.9)
Working hours have reduced 295 (11.8)
Working hours have increased 83 (3.3)
Furlough 468 (18.7)
Newly unemployed 118 (4.7)
Newly employed (full-time) 17 (0.7)
Newly employed (part-time) 12 (0.5)
Had COVID-19
Yes 98 (3.9)
No 2165 (86.6)
Maybe 238 (9.5)
High risk for severe COVID-19 course
Not high risk 1681 (67.2)
High risk 658 (26.3)
Very high risk 162 (6.5)
4 Daniel Freeman et al.
Table 2. Endorsement of general and specific coronavirus conspiracy beliefs and official explanations
Do not agree Agree a little Agree moderately Agree a lot Agree completely
Statements n
%
95% CI n
%
95% CI n
%
95% CI n
%
95% CI n
%
95% CI
Scepticism
The government is misleading the public about the
cause of the virus.
1024 40.9
39.0–42.9
496 19.8
18.2–21.4
506 20.2
18.7–21.6
264 10.6
9.4–11.8
211 8.4
7.4–9.6
I’m sceptical about the official explanation about the
cause of the virus.
642 25.7
24.1–27.4
624 25.0
23.3–26.6
528 21.1
19.6–22.7
399 16.0
14.4–17.4
308 12.3
11.1–13.6
I don’t trust the information about the virus from
scientific experts.
1091 43.6
41.7–45.7
505 20.2
18.6–21.7
470 18.8
17.2–20.3
259 10.4
9.2–11.5
176 7.0
6.1–8.2
Conspiracy cause of the virus
The virus is a hoax. 1977 79.0
77.5–80.7
179 7.2
6.2–8.1
202 8.1
7.0–9.1
88 3.5
2.8–4.2
55 2.2
1.6–2.7
The virus is manmade. 944 37.7
35.9–39.7
596 23.8
22.2–25.6
416 16.6
15.1–18.2
312 12.5
11.2–13.8
233 9.3
8.2–10.5
The virus is produced by powerful organisations (e.g.
government, military).
1278 51.1
49.2–53.1
471 18.8
17.2–20.5
348 13.9
12.6–15.3
242 9.7
8.6–11.0
162 6.5
5.5–7.5
The spread of the virus is a deliberate attempt
To reduce the size of the global population. 1441 57.6
55.7–59.5
398 15.9
14.5–17.4
310 12.4
11.1–13.8
192 7.7
6.7–8.7
160 6.4
5.4–7.4
By governments to gain political control. 1460 58.4
56.6–60.4
360 14.4
13.0–15.9
305 12.2
10.9–13.6
237 9.5
8.3–10.6
139 5.6
4.7–6.5
By a group of powerful people to make money. 1528 61.1
59.3–63.0
337 13.5
12.2–14.9
279 11.2
9.9–12.4
222 8.9
7.8–10.0
135 5.4
4.5–6.4
By a group of powerful people to gain control. 1457 58.3
56.4–60.1
384 15.4
13.9–16.8
279 11.2
9.8–12.3
231 9.2
8.1–10.4
150 6.0
5.1–7.0
By one nation to destabilise another. 1336 53.4
51.6–55.4
476 19.0
17.4–20.6
302 12.1
10.8–13.4
229 9.2
8.0–10.2
158 6.3
5.3–7.3
By global companies to take control. 1610 64.4
62.5–66.2
329 13.2
11.8–14.5
260 10.4
9.2–11.6
176 7.0
6.0–8.0
126 5.0
4.2–5.8
By activists to stop climate change. 1866 74.6
73.1–76.3
211 8.4
7.3–9.5
201 8.0
7.0–9.1
138 5.5
4.6–6.4
85 3.4
2.7–4.1
Conspiracy reasons for lockdown
Stop immigration. 1897 75.8
74.2–77.5
220 8.8
7.6–9.9
200 8.0
6.9–9.1
109 4.4
3.6–5.2
75 3.0
2.4–3.7
Control every aspect of our lives. 1527 61.1
59.1–62.9
378 15.1
13.8–16.6
250 10.0
8.9–11.1
212 8.5
7.4–9.6
134 5.4
4.5–6.2
Impose mass surveillance. 1557 62.3
60.5–64.1
351 14.0
12.6–15.4
261 10.4
9.2–11.7
203 8.1
7.0–9.2
129 5.2
4.3–6.0
(Continued)
Psychological Medicine 5
Table 2. (Continued.)
Do not agree Agree a little Agree moderately Agree a lot Agree completely
Statements n
%
95% CI n
%
95% CI n
%
95% CI n
%
95% CI n
%
95% CI
Destabilise the nation for political gain. 1686 67.4
65.7–69.3
273 10.9
9.6–12.2
246 9.8
8.7–11.0
184 7.4
6.4–8.4
112 4.5
3.7–5.3
Destabilise the economy for financial gain. 1671 66.8
65.0–68.7
291 11.6
10.4–13.0
241 9.6
8.4–10.8
189 7.6
6.5–8.6
109 4.4
3.6–5.2
Specific conspiracy beliefs
Coronavirus is a bioweapon developed by China to
destroy the West.
1366 54.6
52.7–56.5
505 20.2
18.6–21.7
292 11.7
10.5–13.1
201 8.0
7.0–9.2
137 5.5
4.6–6.4
The virus is a biological weapon manufactured by the
United States.
1792 71.7
69.9–73.3
267 10.7
9.5–11.9
229 9.2
8.0–10.3
136 5.4
4.6–6.3
77 3.1
2.4–3.8
The virus is a scaremongering tactic to prevent Brexit. 1942 77.6
76.2–79.2
173 6.9
5.9–7.9
196 7.8
6.8–8.9
132 5.3
4.5–6.2
58 2.3
1.7–2.9
Coronavirus is being used by the elite to stop Brexit. 1898 75.9
74.3–77.4
190 7.6
6.6–8.8
208 8.3
7.3–9.3
138 5.5
4.6–6.4
67 2.7
2.1–3.3
The UN and WHO have manufactured the virus to take
global control.
1895 75.8
74.1–77.4
217 8.7
7.6–9.7
214 8.6
7.5–9.7
101 4.0
3.3–4.8
74 3.0
2.3–3.7
Jews have created the virus to collapse the economy for
financial gain.
2022 80.8
79.3–82.3
133 5.3
4.4–6.2
170 6.8
5.8–7.7
116 4.6
3.8–5.5
60 2.4
1.8–3.0
Muslims are spreading the virus as an attack on Western
values.
2004 80.1
78.7–81.6
148 5.9
5.0–6.9
176 7.0
6.0–8.0
114 4.6
3.8–5.4
59 2.4
1.8–3.0
The elite have created the virus in order to establish a
one-world government.
1859 74.3
72.6–76.0
207 8.3
7.2–9.4
206 8.2
7.2–9.3
146 5.8
5.0–6.8
83 3.3
2.7–4.0
Bill Gates has created the virus in order to reduce the
world population.
1976 79.0
77.3–80.5
159 6.4
5.5–7.4
164 6.6
5.6–7.6
127 5.1
4.3–6.0
75 3.0
2.4–3.7
Big Pharma created coronavirus to profit from the
vaccines.
1885 75.4
73.7–76.9
194 7.8
6.8–8.8
221 8.8
7.8–9.9
132 5.3
4.4–6.2
69 2.8
2.2–3.5
Coronavirus is being used by the government to
implement a police state.
1789 71.5
69.8–73.3
279 11.2
10.0–12.3
215 8.6
7.5–9.7
137 5.5
4.6–6.4
81 3.2
2.6–3.9
Coronavirus is caused by 5 G and is a form of radiation
poisoning transmitted through radio waves.
1968 78.7
77.1–80.2
188 7.5
6.5–8.6
188 7.5
6.5–8.6
111 4.4
3.6–5.3
46 1.8
1.4–2.4
Coronavirus is an alien weapon to destroy humanity. 1976 79.0
77.5–80.6
167 6.7
6.1–8.0
176 7.0
6.1–8.0
119 4.8
3.9–5.7
63 2.5
1.69–3.2
The virus is a smokescreen for a global conspiracy that
swapped the real world with a simulation.
1956 78.2
76.6–79.8
186 7.4
6.4–8.5
190 7.6
6.6–8.8
111 4.4
3.7–5.3
58 2.3
1.8–2.9
The virus is a front to implement measures to destroy
our privacy.
1813 72.5
70.7–74.2
235 9.4
8.3–10.5
205 8.2
7.2–9.3
152 6.1
5.2–7.1
96 3.8
3.0–4.6
Companies are being deliberately put out of business to
hide the effects of Brexit.
1880 75.2
73.6–76.8
230 9.2
8.1–10.5
203 8.1
7.1–9.1
118 4.7
3.9–5.5
70 2.8
2.2–3.4
6 Daniel Freeman et al.
Lockdown is a way to terrify, isolate, and demoralise a
society as a whole in order to reshape society to fit
specific interests.
1750 70.0
68.3–71.7
313 12.5
11.2–13.8
208 8.3
7.3–9.4
140 5.6
4.6–6.6
90 3.6
2.9–4.4
Coronavirus is a plot by globalists to destroy religion by
banning gatherings.
1956 78.2
76.6–79.8
160 6.4
5.4–7.4
189 7.6
6.6–8.6
132 5.3
4.4–6.2
64 2.6
2.0–3.2
The intention of lockdown is to force people to rely on
big corporations rather than their local businesses.
1846 73.8
72.1–75.4
242 9.7
8.5–10.9
208 8.3
7.2–9.4
126 5.0
4.2–6.0
79 3.2
2.5–3.8
Lockdown is a plot by environmental activists to control
the rest of us.
1951 78.0
76.4–79.6
156 6.2
5.3–7.2
189 7.6
6.6–8.6
136 5.4
4.6–6.4
69 2.8
2.2–3.4
The coronavirus vaccine will contain microchips to
control the people.
1898 75.9
74.63–77.6
182 7.3
6.3–8.3
199 8.0
7.0–8.9
135 5.4
4.6–6.3
87 3.5
2.8–4.2
Coronavirus was created to force everyone to get
vaccinated.
1857 74.3
72.6–75.9
195 7.8
6.8–9.0
201 8.0
7.0–9.2
154 6.2
5.3–7.1
94 3.8
3.0–4.5
The vaccine will be used to carry out mass sterilisation. 1906 76.2
74.6–77.8
173 6.9
5.9–7.9
192 7.7
6.8–8.8
148 5.9
5.0–6.8
82 3.3
2.6–4.0
The coronavirus is bait to scare the whole globe into
accepting a vaccine that will introduce the ‘real’deadly
virus.
1956 78.2
76.6–79.7
182 7.3
6.3–8.3
173 6.9
6.0–7.9
122 4.9
4.0–5.7
68 2.7
2.1–3.4
The WHO already has a vaccine and are withholding it. 1773 70.9
69.2–72.6
265 10.6
9.4–11.8
233 9.3
8.2–10.5
135 5.4
4.5–6.3
95 3.8
3.1–4.6
Antibody testing is a plot to harvest our DNA. 1852 74.1
72.5–75.8
208 8.3
7.2–9.4
198 7.9
6.9–9.0
159 6.4
5.5–7.3
84 3.4
2.6–4.1
Celebrities are being paid to say they have coronavirus. 1864 74.5
72.8–76.3
213 8.5
7.4–9.6
198 7.9
6.9–9.0
140 5.6
4.7–6.4
86 3.4
2.8–4.2
Politicians (e.g. Boris Johnson) have faked having
coronavirus.
1837 73.5
71.7–75.0
230 9.2
8.0–10.3
203 8.1
7.0–9.2
142 5.7
4.8–6.6
89 3.6
2.9–4.3
The mainstream media is deliberately feeding us
misinformation about the virus and lockdown.
1394 55.7
53.7–57.7
517 20.7
19.2–22.3
275 11.0
9.8–12.3
183 7.3
6.4–8.3
132 5.3
4.5–6.2
Coronavirus cannot be passed from person to person,
you can only get it if someone deliberately infects you
with it (e.g. being injected or poisoned).
2012 80.4
78.9–82.0
174 7.0
6.0–8.0
145 5.8
4.9–6.7
112 4.5
3.7–5.3
58 2.3
1.8–3.0
Official explanations
Social distancing reduces the likelihood of spreading the
virus from person to person.
59 2.4
1.8–3.0
250 10.0
8.8–11.2
280 11.2
10.0–12.4
587 23.5
21.9–25.2
1325 53.0
51.1–55.1
The virus is most likely to have originated from bats. 483 19.3
17.7–21.0
478 19.1
17.6–20.7
714 28.5
26.8–30.4
532 21.3
19.7–22.9
294 11.8
10.4–13.0
The virus is most likely to have started at a wet market
(marketplace selling fresh meat, fish, produce, and other
perishable goods) in China.
338 13.5
12.2–15.0
517 20.7
19.0–22.3
631 25.2
23.4–26.9
622 24.9
23.2–17.2
393 15.7
14.2–17.2
The virus is naturally occurring. 557 22.3
20.6–23.9
587 23.5
21.7–25.2
511 20.4
19.0–22.0
507 20.3
18.7–22.0
339 13.6
12.1–15.0
Psychological Medicine 7
Table 3. Following of government coronavirus guidance and willingness to accept future diagnostics and vaccination
Statements Not at all Occasionally Some of the time Most of the time All of the time
Overall following government guidance n% 95% CI n% 95% CI n% 95% CI n% 95% CI n% 95% CI
Overall how much do you follow guidance from
the government about coronavirus?
11 0.4
0.2–0.7
34 1.4
0.9–1.8
194 7.8
6.7–8.8
984 39.3
37.5–41.2
1278 51.1
49.3–53.1
How much will you follow future guidance from
the government about coronavirus?
15 0.6
0.3–0.9
56 2.2
1.7–2.8
253 10.1
8.9–11.4
1005 40.2
38.2–42.1
1172 46.9
44.9–48.8
Following government guidelines Not at all Occasionally Some of the time Most of the time All of the time
Staying home and only leaving your house for
essential journeys
69 2.8
2.1–3.4
151 6
5.0–7.0
208 8.3
7.2–9.4
575 23
32.4–24.6
1498 59.9
58.0–61.9
Not meeting with people outside your household
even friends and family
98 3.9
3.2–4.6
112 4.5
3.7–5.3
157 6.3
5.4–7.2
425 17
15.5–18.5
1709 68.3
66.6–70.1
No more than one form of exercise a day outside,
alone or with members of your household
91 3.6
2.9–4.4
119 4.8
4.0–5.6
234 9.4
8.2–10.5
417 16.7
15.2–18.2
1640 65.6
63.7–67.5
If you do go out staying 2 m apart from other
people at all times
46 1.8
1.3–2.4
89 3.6
2.9–4.3
177 7.1
6.2–8.1
544 21.8
20–23.3
1645 65.8
64–67.7
Wash your hands with soap and water often for
at least 20 s
36 1.4
1–2
119 4.8
3.9–5.6
254 10.2
8.49–11.3
484 19.4
17.8–21.0
1608 64.3
62.5–66.3
Not going to work unless you absolutely have to 130 5.2
4.3–6.2
77 3.1
2.4–3.7
185 7.4
6.4–8.4
228 9.1
8.0–10.2
1881 75.2
73.5–76.9
Not touching your eyes nose or mouth if your
hands are not clean
69 2.8
2.1–3.4
179 7.2
6.1–8.1
471 18.8
17.4–20.5
783 31.3
29.5–33.1
999 39.9
38.0–41.9
Follow medical testing/treatment Definitely Probably Possibly Probably not Definitely not
Take a diagnostic test if offered 1138 45.5
43.6–47.5
634 25.3
23.6–27
482 19.3
17.7–20.9
159 6.4
5.4–7.4
88 3.5
2.8–4.3
Take a COVID, 19 antibody test if offered 1190 47.6
45.7–49.4
598 23.9
22.2–25.6
449 18
16.5–19.6
179 7.2
6.1–8.2
85 3.4
2.7–4.1
Take a COVID, 19 vaccine if offered 1188 47.5
45.5–49.5
552 22.1
20.4–23.7
459 18.4
16.9–20
183 7.3
6.3–8.4
119 4.8
3.9–5.6
Try to stop family and friends from getting the
vaccine
274 11.0
9.6–12.2
182 7.3
6.2–8.3
265 10.6
9.3–11.8
467 18.7
17.2–20.4
1313 52.5
50.4–54.3
Download and use a contact tracing app 683 27.3
25.6–29.1
517 20.7
29–22.3
606 24.2
22.5–26.1
339 13.6
12.2–14.9
356 14.2
12.9–15.7
If advised by the government, wear a facemask
outside
1065 42.6
40.6–44.6
662 26.5
24.7–28.1
505 20.2
18.6–21.8
164 6.6
5.6–7.5
105 4.2
3.5–5.0
8 Daniel Freeman et al.
lot, agree completely) 17 potential positive aspects of the pan-
demic (e.g. ‘The coronavirus pandemic has brought communities
closer together’). Higher scores indicate greater endorsement of
positive aspects of the crisis.
Analysis
The first main reporting was descriptive, providing the prevalence
of endorsement of items. 95% confidence intervals (CI) for preva-
lence percentages were estimated using bootstrapping with 1000
samples. Data reduction, using principal components analyses,
was carried out separately for the 18 general coronavirus conspir-
acy theory items and the 30 specific coronavirus conspiracy items.
The primary principal component factors (without rotation) that
explained 61.3% and 69.4% of the variance respectively, were used
to test associations with the other variables. No attempt was made
to fit formal measurement models (e.g. via confirmatory factor
analysis), since this is unnecessary for the data simplification pro-
cess (see Freeman et al., 2015). Associations were then tested
using Pearson’s correlations, ttests, ANOVAs, and chi-square
tests. There were no missing data. All statistical testing was two-
tailed. The analyses were carried out using SPSS Version
25.0.0.1 (IBM, 2017).
Results
A summary of demographic information about the participant
group is provided in Table 1. The group is consistent with the
quota sampling targets for age, gender, income, and region.
In Table 2, a summary is provided of the frequency of endorse-
ment of each general and specific coronavirus conspiracy belief.
The mean total specific coronavirus conspiracy score was 46.1,
S.D. = 26.0 (minimum = 30, maximum = 150, 25th percentile = 30,
50th percentile = 32, 75th percentile = 48, 90th percentile = 91),
the mean total generic coronavirus conspiracy score was 34.1
(S.D. = 17.0) (minimum = 18, maximum = 90, 25th percentile = 20,
50th percentile = 27, 75th percentile = 45, 90th percentile = 60),
and the mean total score for the four official explanations was
12.9, S.D. = 3.4 (minimum = 4, maximum = 20, 25th percentile =
10, 50th percentile = 13, 75th percentile = 15). Endorsement scores
for all specific conspiracy items significantly positively correlated
with one another, and similarly all generic conspiracy items
Table 4. Associations of coronavirus conspiracy beliefs with following government guidelines
Specific coronavirus
conspiracy beliefs
Pearson’s correlation, pvalue
General coronavirus
conspiracy beliefs
Pearson’s correlation, pvalue
Overall following government guidance
Overall, how much do you follow guidance from the government about
coronavirus?
−0.32
p< 0.001
−0.27
p< 0.001
How much will you follow future guidance from the government about
coronavirus?
−0.34
p< 0.001
−0.31
p< 0.001
Following government guidelines
Staying home and only leaving your house for essential journeys −0.44
p< 0.001
−0.35
p< 0.001
Not meeting with people outside your household, even friends and family −0.39
p< 0.001
−0.32
p< 0.001
No more than one form of exercise a day outside, alone or with members of
your household
−0.38
p< 0.001
−0.32
p< 0.001
If you do go out, staying 2 m apart from other people at all times −0.42
p< 0.001
−0.32
p< 0.001
Wash your hands with soap and water often, for at least 20 s −0.38
p< 0.001
−0.27
p< 0.001
Not going to work unless you absolutely have to −0.38
p< 0.001
−0.31
p< 0.001
Follow medical testing/treatment
Take a diagnostic test if offered 0.33
p< 0.001
0.29
p< 0.001
Take a COVID-19 antibody test if offered 0.36
p< 0.001
0.34
p< 0.001
Accept a COVID-19 vaccine if offered 0.35
p< 0.001
0.37
p< 0.001
Try to stop family and friends from getting the vaccine −0.47
p< 0.001
−0.42
p< 0.001
Download and use a contact tracing app 0.11
p< 0.001
0.15
p< 0.001
If advised by the government, wear a facemask outside 0.23
p< 0.001
0.21
p< 0.001
Psychological Medicine 9
significantly positively correlated with one another. The correlation
between the specific and generic coronavirus conspiracy principal
component scores was high, r=0.84,p<0.001.Specific conspiracy
beliefs, r=−0.101, p< 0.001, and generic conspiracy beliefs, r=
−0.21, p< 0.001, were both negatively associated with the total
endorsement score for the official explanations.
There were no significant differences in levels of specific, t(df =
2451.5) = 1.89, p= 0.056, or general, t(df = 2466.3) = 0.69, p= 0.491,
coronavirus conspiracy beliefs by gender. Younger participants
held higher levels of both specific, r=−0.42, p< 0.001, and general,
r=−0.35, p< 0.001, coronavirus conspiracy beliefs. There were
lower levels of both specific, df = 407.0, t=−9.44, p< 0.001, and
general, df = 426.8, t=−8.21, p< 0.001, coronavirus conspiracy con-
cerns in those of white ethnicity (n= 2160) compared to individuals
of other ethnicities (n= 341). There were no significant associations
of specific, r= 0.02, p= 0.25, or general, −0.02, p= 0.418, corona-
virus conspiracy concerns with household income. General conspir-
acy, r=−0.06, p= 0.002, but not specific, r=−0.01, p= 0.526,
coronavirus conspiracy concerns, were associated with lower levels
of education. Specific and general coronavirus conspiracy beliefs
were significantly higher in those who thought it not worth voting
in a general election (n= 195) compared with individuals who
Table 6. Associations of coronavirus conspiracy concerns and general mistrust
Specific coronavirus conspiracy
beliefs
Pearson’s correlation, pvalue
General coronavirus conspiracy
beliefs
Pearson’s correlation, pvalue
Religious belief 0.32
p< 0.001
0.28
p< 0.001
Political belief 0.14
p< 0.001
0.15
p< 0.001
How much do you share information about coronavirus with others 0.20
p< 0.001
0.20
p< 0.001
How much do you share your own opinions about coronavirus on online
sites
0.49
p< 0.001
0.46
p< 0.001
Psychological well-being −0.02
p= 0.306
−0.06
p= 0.005
Table 5. Associations of coronavirus conspiracy concerns and general mistrust
Specific coronavirus conspiracy beliefs
Pearson’s correlation, pvalue
General coronavirus conspiracy beliefs
Pearson’s correlation, pvalue
Conspiracy mentality 0.16
p< 0.001
0.35
p< 0.001
General vaccination conspiracy beliefs 0.60
p< 0.001
0.65
p< 0.001
Climate change conspiracy belief 0.51
p< 0.001
0.47
p< 0.001
Paranoia 0.72
p< 0.001
0.61
p< 0.001
Trust in UK government −0.12
p< 0.001
−0.17
p< 0.001
Trust in UK military −0.16
p< 0.001
−0.17
p< 0.001
Trust in mainstream media 0.13
p< 0.001
0.03
p= 0.179
Trust in doctors −0.30
p< 0.001
−0.29
p< 0.001
Trust in scientists −0.20
p< 0.001
−0.25
p< 0.001
Trust in World Health Organisation −0.17
p< 0.001
−0.24
p< 0.001
Trust in United Nations −0.08
p< 0.001
−0.17
p< 0.001
Trust in European Union −0.07
p= 0.001
−0.03
p= 0.127
10 Daniel Freeman et al.
Table 7. Positive experiences of the coronavirus pandemic
Do not agree Agree a little Agree moderately Agree a lot Agree completely
n
%
95% CI n
%
95% CI n
%
95% CI n
%
95% CI n
%
95% CI
The coronavirus pandemic has brought communities closer
together.
214 8.6
7.5–9.8
621 24.8
23.1–26.6
756 30.2
28.2–32.1
603 24.1
22.5–25.8
307 12.3
11.0–13.6
The pandemic has generally brought out the best in people. 232 9.3
8.3–10.5
570 22.8
21.2–24.4
731 29.2
27.5–31.0
691 27.6
25.9–29.3
277 11.1
9.8–12.4
The pandemic has made people more appreciative of the
NHS and its workforce.
67 2.7
2.0–3.3
221 8.8
7.7–9.9
394 15.8
14.3–17.2
676 27.0
25.4–28.7
1143 45.7
43.7–47.5
Since the pandemic, people have become more appreciative
of essential workers (e.g. delivery drivers, shop staff).
74 3.0
2.3–3.6
247 9.9
8.8–11.0
503 20.1
18.6–21.8
817 32.7
30.9–34.5
860 34.4
32.6–36.2
People have become more thoughtful of their relationship
with the planet.
276 11.0
9.9–12.4
522 20.9
19.2–22.5
757 30.3
28.5–32.0
592 23.7
22.0–25.4
354 14.2
12.8–15.5
I feel more connected to neighbours and people in my local
area.
546 21.8
20.4–23.5
618 24.7
23.0–26.5
722 28.9
27.0–30.5
431 17.2
15.8–18.7
184 7.4
6.4–8.4
I have felt more connected to family and friends. 394 15.8
14.4–17.2
469 18.8
17.3–20.4
662 26.5
24.7–28.2
614 24.6
22.8–26.3
362 14.5
13.2–15.8
I learned a great deal about how wonderful people are. 340 13.6
12.2–14.9
569 22.8
21.2–24.4
734 29.3
27.6–31.1
594 23.8
22.2–25.4
264 10.6
9.4–11.8
I have been more able to engage with activities and hobbies
that I enjoy.
484 19.4
17.8–21.0
501 20.0
18.5–21.6
727 29.1
27.3–30.7
517 20.7
19.2–22.4
272 10.9
9.7–12.2
I have been able to do more regular exercise. 740 29.6
27.8–31.3
482 19.3
17.8–20.8
606 24.2
22.4–25.9
403 16.1
14.8–17.6
270 10.8
9.6–12.1
I have had more time to reflect on what matters to me. 291 11.6
10.4–12.8
534 21.4
19.7–23.0
671 26.8
25.0–28.5
648 25.9
24.2–27.7
357 14.3
12.9–15.7
I have appreciated taking time for myself. 308 12.3
11.1–13.6
476 19.0
17.6–20.6
706 28.2
26.5–30.0
612 24.5
22.8–26.1
399 16.0
14.6–17.4
I discovered that I’m stronger than I thought I was. 451 18.0
16.5–19.6
473 18.9
17.4–20.4
730 29.2
27.3–30.9
524 21.0
19.3–22.6
323 12.9
11.6–14.2
I have a greater appreciation for the value of my own life. 295 11.8
10.5–13.0
408 16.3
14.8–17.8
662 26.5
24.8–28.1
655 26.2
24.6–27.7
481 19.2
17.8–20.8
I established a new path for my life. 891 35.6
33.7–37.5
462 18.5
17.0–20.1
632 25.3
23.4–27.0
317 12.7
11.4–14.0
199 8.0
7.0–9.0
I have a better understanding of spiritual matters. 1142 45.7
43.8–47.6
366 14.6
13.2–16.1
503 20.1
18.5–21.7
288 11.5
10.2–12.8
202 8.1
7.0–9.2
I have a stronger religious faith. 1364 54.5
52.7–56.6
301 12.0
10.8–13.4
422 16.9
15.4–18.4
235 9.4
8.2–10.6
179 7.2
6.2–8.2
Psychological Medicine 11
thought you should only vote if you care who wins (n= 512), with
the latter scoring significantly higher for coronavirus conspiracy
beliefs than individuals who consider it everyone’s duty to vote
(n= 1794). Individuals (n= 1825) who obtained most of their infor-
mation about coronavirus from the BBC had lower levels of specific,
df = 934.8, t= 11.91, p< 0.001, and general, df = 1058.2, t= 12.09,
p< 0.001 coronavirus beliefs compared with those who did not
(n= 676). Whereas individuals (n= 453) who obtained most of
their information about coronavirus from friends had higher levels
of specific, df = 602.6, t=−5.77, p< 0.001, and general, df = 618.61,
t=−6.24, p< 0.001 coronavirus beliefs compared with those who
did not (n= 2048). Similarly, individuals (n= 808) who obtained
most of their information about coronavirus from social media
had higher levels of specific, df = 1263.6, t=−12.27, p< 0.001, and
general, df = 1345.61, t=−12.73, p< 0.001 coronavirus beliefs com-
pared with those who did not (n= 1693). Individuals (n= 382) who
obtained most of their information about coronavirus from
YouTube had higher levels of specific, df = 470.73, t=−10.39,
p< 0.001, and general, df = 494.11, t=−11.06, p< 0.001 coronavirus
beliefs compared with those who did not (n= 2119).
The degree to which participants adhere to government cor-
onavirus guidance and willingness to accept future diagnostics
and vaccination is summarised in Table 3. Generally, rates of
adhering to the guidelines were high, though approximately
20% adhered to a lower extent.
Endorsement of specific or generic coronavirus conspiracy
beliefs is significantly associated with less self-reported adher-
ence to each government recommendation (Table 4).
Conspiracy beliefs were also associated with less likelihood to
accept future diagnostic tests or a vaccination. As illustrations
of these associations, respondents who endorsed to any degree
that ‘Coronavirus is a bioweapon developed by China to destroy
the West’were much more likely to also not adhere (defined as
less than most of the time) to the guidance to stay at home, odds
ratio (OR) 4.57, 95% CI 3.62–5.79, and endorsing to any degree
that ‘Jews have created the virus to collapse the economy
for financial gain’was highly associated with not adhering to
the guidance to stay at home, OR 14.34, 95% CI 11.26–18.25.
Respondents were more likely to report that they would
not accept a COVID-19 vaccine (possibly not, definitely not)
if they endorsed the bioweapon belief, OR 2.11, 95% CI
1.65–2.70, or the belief about Jewish people, OR 2.70, 95%
CI 2.08–3.50.
Coronavirus conspiracy concerns were associated with all
other forms of mistrust, notably paranoia, general vaccination
conspiracy beliefs and climate change conspiracy belief (Table 5).
Holding specific or general coronavirus conspiracy beliefs was
associated with higher levels of religiosity, slightly more right
wing political orientation, and being more likely to share informa-
tion and opinions about coronavirus (Table 6). Although there is
a small association of coronavirus conspiracy beliefs with degree
of right wing views, there was also evidence for a quadratic rela-
tionship, with those who rated themselves as at the extreme ends
of either left or right holding higher levels of conspiracy thinking.
A hierarchical regression showed that both the linear political
item, B=−0.28, standard error = 0.05, t=−5.92, p< 0.001, and
a quadratic term (the political item squared), B= 0.064, standard
error = 0.01, t= 8.63, p< 0.001 were significant predictors of spe-
cific coronavirus conspiracy scores. A similar finding was found
for holding general coronavirus conspiracy beliefs. There was little
indication of an association of coronavirus conspiracy beliefs with
psychological well-being.
The endorsement of positive experiences from the pandemic is
summarised in Table 7. These show that at a personal and local
level there have been positive aspects appraised by most people.
Higher levels of specific coronavirus conspiracy beliefs, r= 0.20,
p< 0.001, and general coronavirus conspiracy beliefs, r= 0.21,
p< 0.001, were associated with higher levels of endorsement of
the positive statements.
Discussion
The results are illuminating but dispiriting: a substantial minority of
the population endorses unequivocally false ideas about the pan-
demic. Only half the population showed little evidence of conspiracy
thinking. The idea that the current crisis may be especially fertile
ground for conspiracy beliefs may well be correct. The coronavirus
conspiracy ideas ascribe malevolent intent to individuals, groups,
and organisations based on what are likely to be long-standing pre-
judices. For instance, almost half of participants endorsed to some
degree the idea that ‘Coronavirus is a bioweapon developed by
China to destroy the West’andaroundone-fifthendorsedto
some degree that ‘Jews have created the virus to collapse the econ-
omy for financial gain’. The conspiracy beliefs were connected to a
number of markers of excessive mistrust: paranoia, endorsement of
other conspiracy beliefs, mistrust in institutions and experts, and a
conspiracy mentality. Conspiracy beliefs are likely to be both indexes
and drivers of societal corrosion. They matter in this context
because they may well have reduced compliance with government
social distancing guidelines, thereby contributing to the spread of
the disease. One consequence of this national crisis may be to reveal
fully the harmful effects of mistrust and misinformation.
A public health information crisis may be observable.
Misinformation and misguided –often malign –views look to
be highly prevalent. Fringe beliefs may now be mainstream. A
previously defining element that the beliefs are typically only
held by a minority may require revision. The numerous different
conspiracy statements, often contradictory in detail, were all sig-
nificantly associated. The detailed content of the statements
may matter less than the respondents’tendency to believe that
institutions, officials, and experts may be deliberately misleading.
This is consistent with previous research that shows mutually
incompatible conspiracy beliefs can be endorsed (Wood et al.,
2012) and with the noticeably high associations in this study of
coronavirus conspiracy beliefs with paranoia (i.e. the idea that
others intend harm to the individual) and conspiracy beliefs con-
cerning vaccination and climate change. Healthy scepticism may
have tipped over into a breakdown of trust. There may also be
a simple attraction of discussing, holding, and sharing conspiracy
theories, especially in youth. Interestingly, those holding conspir-
acy beliefs could also see greater personal benefits arising from the
crisis. There were indications that the coronavirus conspiracy
beliefs are more likely to be held by those who perceive themselves
as marginalised, but these relationships do not appear as strong as
in previous studies (e.g. Freeman & Bentall, 2017). This weaken-
ing may reflect a cross-over of distrust of mainstream accounts
into the mainstream itself. Replications of the survey are required
to confirm whether the high prevalence of conspiracy beliefs is
accurate. Comparative studies across countries could be extremely
informative in establishing the social causes.
There are significant limitations to the survey. Foremost, we
used a non-probability online quota sampling method. This will
have introduced bias into who was approached to take part.
Probability sampling, in which members of the population have
12 Daniel Freeman et al.
an equal chance of participating, produces better estimates. All
that we know in this survey is that as a whole the respondents
were broadly representative of the adult general population on a
number of basic demographic features but not that individual
respondents were representative of the general population. The
views of those who are not online were not assessed, the level
of non-responses to the survey invitation is unknown, and, specif-
ically, it is unknown whether the degree to which conspiracy
beliefs are endorsed influenced the decision to take part. The
prevalence estimates in this survey need to be treated with cau-
tion. It is also unknown whether important coronavirus conspir-
acy beliefs were overlooked in the item pool or the degree to
which self-report of attitudes to coronavirus guidelines is accurate.
The cross-sectional nature of the design precludes causal infer-
ence. Arguably, the coronavirus concerns could be post hoc ratio-
nalisations of not following socially accepted lockdown
behaviours. However, we believe it is more likely that conspiracy
beliefs drive behaviour or at the very least remove barriers to car-
rying out unhelpful behaviours. In our view the urgent question
now is how can the prevalence and impact of conspiracy beliefs
and general mistrust be reduced both in the short and long term?
Acknowledgements. DF is supported by an NIHR Research Professorship
(NIHR-RP-2014-05-003). The study was supported by the NHS National
Institute of Health Research (NIHR) invention for innovation (i4i) programme
(Project II-C7-0117-20001) and the NIHR Oxford Health Biomedical Research
Centre (BRC-1215-20005). The views expressed are those of the authors and
not necessarily those of the National Health Service, NIHR, or the
Department of Health.
Author contributions.
DF was the chief investigator and wrote the paper. All authors contributed to the study
design. DF and SL carried out the analyses. All authors commented on the paper.
Conflict of interest. Daniel Freeman has written popular science, self-help,
and academic books about paranoia with several publishers for which royalties
are received. DF reports grants on the topic of paranoia from National Institute
for Health Research, Medical Research Council, and Wellcome Trust. Other
authors report no competing interests.
References
Abalakina-Paap, M., Stephan, W. G., Craig, T., & Gregory, W. L. (1999). Beliefs
in conspiracies. Political Psychology,20, 637–647.
Attwell, K., Leask, J., Meyer, S.B., Rokkas, P., & Ward, P. (2017). Vaccine
rejecting parents’engagement with expert systems that inform vaccination
programs. Journal of Bioethical Inquiry,14,65–76.
Bolsen, T., & Druckman, J. N. (2018). Validating conspiracy beliefs and effect-
ively communicating scientific consensus. Weather, Climate, and Society,
10, 453–458.
Brotherton, R., French, C., & Pickering, A. (2013). Measuring belief in conspir-
acy theories: The generic conspiracist beliefs scale. Frontiers in Psychology,
4, 279.
Bruder, M., Haffke, P., Neave, N., Nouripanah, N., & Imhoff, R. (2013).
Measuring individual differences in generic beliefs in conspiracy theories
across cultures: Conspiracy mentality questionnaire. Frontiers in
Psychology,4, 225.
Davis, J., Wetherell, G., & Henry, P. J. (2018). Social devaluation of African
Americans and race-related conspiracy theories. European Journal of
Social Psychology,48, 999–1010.
Douglas, K. M., Sutton, R. M., Callan, M. J., Dawtry, R. J., & Harvey, A. J.
(2016). Someone is pulling the strings: Hypersensitive agency detection
and belief in conspiracy theories. Thinking & Reasoning,22,57–77.
Douglas, K. M., Uscinski, J. E., Sutton, R. M., Cichocka, A., Nefes, T., Ang, C.
S., & Deravi, F. (2019). Understanding conspiracy theories. Advances in
Political Psychology,40(Suppl 1), 3–35.
Edelman (2020) 2020 Edelman trust barometer. London: Edelman. [online]
Available at: https://www.edelman.com/trustbarometer.
Federico, C. M., Williams, A. L., & Vitriol, J. A. (2018). The role of system
identity threat in conspiracy theory endorsement. European Journal of
Social Psychology,48, 927–938.
Freeman, D., & Bentall, R. (2017). The concomitants of conspiracy concerns.
Social Psychiatry and Psychiatric Epidemiology,52, 595–604.
Freeman, D., Dunn, G., Murray, R., Evans, N., Lister, R., Antley, A., …
Morrison, P. (2015). How cannabis causes paranoia: Using the intraven-
ous administration of Δ9-tetrahydrocannabinol (THC) to identify key
cognitive mechanisms leading to paranoia. Schizophrenia Bulletin,41,
391–399.
Freeman, D., Loe, B.S., Kingdon, D., Startup, H., Molodynski, A.,
Rosebrock, L., …Bird, J.C. (2019). The revised Green et al., paranoid
thoughts scale (R-GPTS): Psychometric properties, severity ranges,
and clinical cut-offs. Psychological Medicine,1–10. doi:10.1017/
S0033291719003155.
Goertzel,T.(1994).Beliefinconspiracytheories.Political Psychology,15,
731–742.
Goreis, A., & Voracek, M. (2019). A systematic review and meta-analysis of
psychological research on conspiracy beliefs: Field characteristics, measure-
ment instruments, and associations with personality traits. Frontiers in
Psychology,10, 205.
IBM (2017). SPSS Statistics version 25. Release 25.0.0.1. Armonk, NY: IBM
Corporation.
Imhoff, R., & Bruder, M. (2014). Speaking (un-)truth to power: Conspiracy
mentality as a generalized political attitude. European Journal of
Personality,28,25–43.
Jolley, D., & Douglas, K. (2014). The effects of anti-vaccine conspiracy theories
on vaccination intentions. PLoS One,9(2): e89177.
Krouwel, A., Kutiyski, Y., van Prooijen, J. W., Martinsson, J., & Markstedt, E.
(2017). Does extreme political ideology predict conspiracy beliefs, economic
evaluations and political trust? Evidence from Sweden. Journal of Social and
Political Psychology,5(2), 435–462.
Luthy, K.E., Beckstrand, R.L., Callister, L.C., & Cahoon, S. (2012). Reasons par-
ents exempt children from receiving immunizations. Journal of School
Nursing,28, 153–160.
Shapiro, G.K., Holding, A., Perez, S., Amsel, R., & Rosberger, Z. (2016)
Validation of the vaccine conspiracy beliefs scale. Papillomavirus
Research,2, 167–172.
Sunstein, C., & Vermeule, A. (2009). Conspiracy theories. Journal of Political
Philosophy,17, 202–227.
Swami, V., Chamorro-Premuzic, T., & Furnham, A. (2010). Unanswered ques-
tions: A preliminary investigation of personality and individual difference
predictors of 9/11 conspiracist beliefs. Applied Cognitive Psychology,24,
749–761.
Swami V., Voracek M., Stieger S., Tran U. S., & Furnham A. (2014).
Analytic thinking reduces belief in conspiracy theories. Cognition,133,
572–585.
Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., …
Stewart-Brown, S. L. (2007). The Warwick−Edinburgh mental well-being
scale (WEMWBS): Development and UK validation. Health and Quality
of Life Outcomes,5, 63.
van Prooijen, J.-W., & Jostmann, N. B. (2013). Belief in conspiracy theories:
The influence of uncertainty and perceived morality. European Journal of
Social Psychology,43(1), 109–115.
van Prooijen, J.-W., Krouwel, A. P. M., & Pollet, T. (2015). Political extremism
predicts belief in conspiracy theories. Social Psychological and Personality
Science,6, 570–578.
Wood, M. J., Douglas, K. M., & Sutton, R. M. (2012). Dead and alive: Beliefs in
contradictory conspiracy theories. Social Psychological and Personality
Science,3, 767–773.
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