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https://doi.org/10.1057/s41599-025-04774-3
OPEN
Are COVID-19 conspiracy theories for losers?
Probing the interactive effect of voting choice and
emotional distress on anti-vaccine conspiracy
beliefs
1234567890():,;
Fen Lin1, Xiang Meng2 ✉ & Pei Zhi1
As the COVID-19 pandemic has increasingly become intertwined with politics, emerging
studies have identified political orientations as essential drivers behind public endorsement of
COVID-19 conspiracy theories. Yet little is known about the relationship between individuals’
voting choices and their conspiracy beliefs, as well as the psychological mechanism behind
them. By introducing affective intelligence theory (AIT) into the conspiracy theory literature,
this study examines the moderating role of emotional distress as the underlying mechanism
that conditions the relationship between voting choice and the public’s anti-vaccine conspiracy beliefs. A cross-national online survey of adults (aged 18 or above; n = 2208) was
fielded in Singapore, Hong Kong, Japan, and the US in June 2021. The results show that
individuals who voted for the losing party in the previous election are more susceptible to
anti-vaccine conspiracy theories, indicating a “losing effect.” Additionally, those experiencing
greater emotional distress are more vulnerable to those conspiratorial statements. Moreover,
the aforementioned losing effect of voting choice is weaker among individuals who experienced greater emotional distress during the pandemic. These findings enhance our understanding of the socio-psychological mechanism behind conspiracy beliefs.
1 Department of Media and Communication, City University of Hong Kong, Hong Kong, China. 2 Department of English and Communication, The Hong Kong
Polytechnic University, Hong Kong, China. ✉email:
[email protected]
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Introduction
he assertion that science is often utilized or distorted to
advance political agendas is not novel. However, the politicisation of the COVID-19 pandemic, including the proliferation of various COVID-19 conspiracy theories, has been
particularly concerning given the scale and intensity of the crisis.
Recent evidence shows that belief in anti-vaccine conspiracy
theories reduces vaccination willingness and uptake (Chen et al.
2022a; Đorđević et al. 2021; Lin et al. 2022; Seddig et al. 2022),
thereby threatening individual health and the efficacy of public
health policies. More concerning, public attitudes toward antivaccine conspiracy theories are found to be intertwined with
political orientations, such as political ideology (Jiang et al. 2021),
suggesting a pressing threat to public health from the turbulent
political landscape. Therefore, understanding how political factors influence public beliefs in anti-vaccine conspiracy theories
has become crucial for individual health and the health of the
social system.
This study focuses on the effect of an individual’s voting choice
on his or her anti-vaccine conspiracy beliefs, as well as the psychological mechanism underlying this effect. Unlike prior
research that has concentrated on political ideology, this study
emphasises the role of voting—a crucial means for citizens to
engage in politics and a key process in the distribution of power
in modern society. Previous studies have suggested that individuals on the losing side of an election are more susceptible to
political conspiracy theories, because conspiratorial narratives
disparaging their opponents can help these “losers” cope with the
increased threat of losing power and justify their own political
choices (Douglas et al. 2019; Uscinski and Parent, 2014). However, little is currently known about how voting choice influences
attitudes toward COVID-19 conspiracy theories.
Apart from its substantial role in shaping political behaviours,
emotion is also found to be a crucial antecedent for individual
endorsement of COVID-19 conspiracy theories (Kim and Kim
2021; van Mulukom et al. 2022). This study focuses on emotional
distress, a prominent mental state during the pandemic (Twenge
and Joiner 2020; Zhao et al. 2020). In recent decades, advances in
neuroscience and political psychology—especially research on
affective intelligence theory—have refuted the conventional idea
that emotional experience or affective processes must follow
cognitive processes (Adolphs 2008; Davidson and Irwin 1999;
Mintz et al. 2021; Straube et al. 2010; Zajonc 1980). Emotional
experience can occur preconsciously, and thus can serve as “the
foundation of all information processing, decision-making, and
behavior” (Marcus et al. 2019, p. 114). This theorization implies
that emotions (including distress) may act as a conditional factor
(i.e., moderator) that can alter the impact of political factors
(herein one’s voting choice) on individuals’ conspiracy beliefs.
Yet, existing scholarship on conspiracy theories often centres on
the isolated effects of various antecedents, neglecting the potential
interactive dynamics between them. By introducing affective
intelligence theory (AIT) to the literature on conspiracy theories,
this study fills the above research gaps by probing the following
questions: How does voting choice influence individuals’ antivaccine conspiracy beliefs? Does feeling distressed affect this
voting choice effect? And if so, how?
For empirical investigation, this study incorporates data from a
cross-national survey covering Singapore, Hong Kong, Japan, and
the US (n = 2208) conducted in June 2021. Those four jurisdictions were selected because they have similar timelines regarding
exposure to the first few waves of the pandemic. Also, by the time
of our survey, all four jurisdictions had launched their official
vaccination programs, and were suffering from vaccine-related
conspiracy theories (Lee 2021; Letters 2021; Mainichi Japan 2021;
Tandoc et al. 2021). Additionally, the three East Asian
T
2
jurisdictions share cultural proximity (such as Confucianism) to
the epicentre of the pandemic (i.e., China) while differing in
terms of their political systems. Including the US provides a
Western counterpart featuring a democratic system. These similarities and differences enable us to check and compare our
models and findings across contexts, and thus help generate
deeper insight into the psychological mechanism that drives the
public’s anti-vaccine conspiracy beliefs.
Defining conspiracy theories and conspiracy beliefs. Conspiracy
theories, by their very nature, are social and political. They often
attempt “to explain the ultimate causes of significant social and
political events and circumstances with claims of secret plots by
two or more powerful actors” (Douglas et al. 2019, p. 4). Typically, these “secret plots” promote the interests of a handful of
actors, “the conspirators,” at the expense of public interest or the
common good (Uscinski et al. 2016). This conceptualization of
conspiracy theory distinguishes this concept from rumours and
misinformation which are not characterized by malicious intent
on the part of actors (De Coninck et al. 2021; Hong et al. 2021).
Moreover, though not necessarily addressing the government, the
actors of conspiracy theories usually refer to powerful persons or
groups (Douglas et al. 2019; Goertzel 1994). Grounded on the
above conceptualization, conspiracy beliefs are construed as
“belief[s] in a specific conspiracy theory, or set of conspiracy
theories” (Douglas et al. 2019, p. 4).
Recent evidence highlights the importance of differentiating
conspiracy beliefs from conspiracy mentality, especially when
examining related antecedents of conspiracy beliefs. Conspiracy
mentality, also referred to as “conspiracy predispositions”
(Uscinski and Parent 2014), “conspiracy thinking” (Walter and
Drochon 2022) and “conspiracy mindset” (Sutton and Douglas
2020), “describes the general propensity to subscribe to theories
blaming a conspiracy of ill-intending individuals or groups for
important societal phenomena” (Bruder et al. 2013, p. 2). Results
from a meta-analysis (Stojanov and Halberstadt 2020) have
shown that, compared to beliefs in specific conspiratorial
statements, conspiracy mentality is less likely to be influenced
by a perceived lack of control. A recent overview (Imhoff,
Bertlich, Frenken 2022) has demonstrated that conspiracy
mentality is “probably a relatively pure measure of accepting
the existence of conspiracies” (p. 4), highlighting its stability as a
disposition and robustness as a predictor of specific conspiracy
beliefs. Moreover, scholars have identified a significant linkage
between political orientation and conspiracy mentality (Imhoff,
Zimmer, Klein et al. 2022), suggesting a possible confounding
effect of the latter on the relationship between voting choice and
conspiracy beliefs. Therefore, our analysis includes conspiracy
mentality as an important control variable.
Voting for opposition parties and anti-vaccine conspiracy
beliefs. Social motive, specifically “the desire to belong and to
maintain a positive image of the self and the in-group,” is a major
driving force facilitating conspiracy beliefs (Douglas et al. 2017, p.
540). When such a social need arises, conspiracy theories implicating the competing out-groups gain appeal as they help people
valorise the images of themselves and their in-groups (Douglas
et al. 2017). This is particularly the case for individuals on the
losing side of a political process like an election (Douglas et al.
2019; Edelson et al. 2017). Moreover, scholars have also argued
that conspiracy theories can serve as an important measure to
cope with perceived dangers for vulnerable groups, especially outof-power groups after an election (Uscinski and Parent 2014).
This is because losing an election means becoming disadvantaged
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in the distribution process of power and resources, thus making
conspiracy theories which demonize the opponent attractive and
resonant among the out-of-power groups (Uscinski and Parent
2014).
Prior studies have found empirical evidence supporting the
above theorization. Based on a long-term content analysis of
letters to the editor of the New York Times, scholars found that
during the terms of Republican presidents, most conspiracy
theories targeted the right and capitalists, whereas when a
Democrat took office, most conspiracy theories targeted the left
and communists (Uscinski and Parent 2014). Using longitudinal
data collected before and after the 2012 US election, Edelson et al.
(2017) determined that electoral losers are more likely than
winners to believe there has been election fraud.
Extending this line of research to the context of COVID-19
conspiracy theories, we contend that the anti-vaccine conspiracy
theories could also serve the need of electoral losers to validate
themselves by painting the incumbent (or the ruling parties) in a
negative light. Moreover, we argue that the above “validating role”
of conspiracy theories could even be applied to conspiratorial
claim that does not directly involve the incumbent (e.g., “the only
reason the COVID-19 vaccine is being developed is to make
money for pharmaceutical companies”). Specifically, considering
that all of these vaccines have been approved by their respective
governments and even included in official vaccination programs,1
conspiratorial claim about the vaccines could be deemed implicit
accusations against the incumbent, thereby serving to help
uphold the in-group and self-image of individuals who supported
the losing parties in the former election.
That said, some may suspect that the impact of losing the
election could be temporary. Yet, a recent study of the 2010
Swedish general election demonstrated that the experience of
losing an election is not “a temporary disappointment with the
election outcome but rather a relatively long-lasting aspect of how
voters regard the functioning of the democratic system”
(Dahlberg and Linde 2017, p. 638). In fact, this “losing effect”
has been found to last for nearly the entire electoral cycle
(Dahlberg and Linde 2017). This finding suggests that the
distance between the latest election and the prevalence of antivaccine conspiracy theories may have little impact on the relation
between voting choice and conspiracy beliefs. As such, we
hypothesize that:
Hypothesis 1: People voting for opposition parties will be more
likely to believe in anti-vaccine conspiracy theories.
Emotional distress and anti-vaccine conspiracy beliefs. Past
experimental studies demonstrated that conspiracy beliefs are
emotional-driven (e.g., van Prooijen and Jostmann 2013; Whitson
et al. 2015). The “dual-process models” (Evans 2008) posit that
the human mind processes information about the environment
with two functional systems, with one system operating rapidly
by relying on intuitions and emotions (System 1) and the other
operating slow with its reliance on analytical thinking and
rational deliberation (System 2). A recent overview of the socialcognitive processes of conspiracy beliefs concluded that those
beliefs derive from System 1 thinking, as empirical studies have
consistently identified intuitive thinking and uncertainty-related
emotions as key predictors (van Prooijen et al. 2020). For
instance, utilizing two experimental studies, van Prooijen and
Jostmann (2013) have recognized a positive effect of experiencing
anxious uncertainty on conspiracy beliefs.
Grounded on these findings, we hypothesize that experiencing
emotional distress can also induce one’s beliefs in conspiracy
theories, especially those about COVID-19 vaccines. Emotional
distress, or “psychological distress,” is “a state of emotional
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suffering typically characterized by symptoms of depression and
anxiety” (Arvidsdotter et al. 2016). Scholars (van Prooijen and
Douglas 2017, 2018) have noted that conspiracy theories flourish
after the occurrence of distressing and anxiety-provoking events,
“such as a fire, a disease epidemic, a war, a plane crash, or a
terrorist strike” (van Prooijen and Douglas 2017, p. 326),
suggesting a link between distress and conspiracy beliefs. Drawing
on a series of experiments, Whitson et al. (2015) found that
experiencing uncertain emotions like anxiety, a key component of
distress, increases one’s belief in conspiracy theories. This is
because those conspiratorial discourses can help people “regain a
sense of perceived control over the uncertain landscape” by
offering a simplified explanation of the current events (Whitson
et al. 2015, p. 89). More pertinent to our study, recent surveys of
COVID-19 conspiracy theories have documented a positive
correlation between distress and conspiracy beliefs (De Coninck
et al. 2021; Simione et al. 2021). The above discussion generally
implies a positive association between emotional distress and
endorsement of anti-vaccine conspiracy theories. Therefore, we
propose that:
Hypothesis 2: People with more intense emotional distress will
be more likely to believe in anti-vaccine conspiracy theories.
Emotional distress as a moderator of voting choice. Guided by
affective intelligence theory, we further scrutinize the potential role
of emotional distress in the relationship between voting choice and
anti-vaccine conspiracy beliefs. Affective intelligence theory,
drawing on insights from neuroscience, suggests that affective
appraisal occurs preconsciously. This positions an individual’s
emotional experience as the basis for all consciousness-based
information processing, decision-making, and behaviours (Marcus
et al. 2019). This argument suggests that emotion can serve as a
condition that determines how the cognitive process functions.
More specifically, in the literature on AIT, uncertainty-related
emotions such as distress, anxiety, and fear have garnered
substantial scholarly attention. These emotions have been found
to make individuals less reliant on their existing stances or habits
when managing affairs or responding to the environment
(Gervais 2019; MacKuen et al. 2007; Marcus et al. 2000, 2019).
It is because these emotions often arise when individuals
encounter a novel threat with an uncertain cause, leading to a
sense of lack of control (Lerner and Keltner 2001). To alleviate
this feeling of uncertainty, emotionally triggered individuals tend
to seek out additional information, even from sources that
contradict their political beliefs (Albertson and Gadarian 2015;
Valentino et al. 2008). The acquisition of novel and diverse
information can lead to opinion changes, particularly among
anxious individuals, thereby diminishing the influence of their
existing political standpoints on their responses to the surroundings (MacKuen et al. 2007; Marcus et al. 2000).
Empirical evidence has lent support to this theorization. For
instance, Marcus et al. (2019), utilizing three survey studies,
demonstrated that fear reduces the likelihood of voting for a farright party (Front National), especially among centre-right and
far-right party identifiers; also, they found that fear can increase
acceptance of authoritarian policies (i.e., stricter security
measures), particularly among left-leaning who typically oppose
such measures. Similarly, a recent study using cross-national
panel data revealed that higher levels of fear and governmental
trust are associated with greater public support for libertyrestricting public health measures, such as curfews and mobile
phone surveillance. However, the positive relationship between
governmental trust and support for liberty-restricting measures
weakens among individuals with greater fear over the COVID-19
pandemic (Vasilopoulos et al. 2022).
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Although prior research on AIT has primarily focused on
public attitudes and decision-making processes in political
context, this study extends the theory to the realm of conspiracy
beliefs. As discussed above, conspiracy theories are inherently
political, often implicating powerful figures and groups as
conspirators. Therefore, based on this line of reasoning, we
hypothesize that:
Hypothesis 3: Feelings of distress will attenuate the relationship
between voting choice and anti-vaccine conspiracy beliefs.
Methods
Data. This study relies on cross-national survey data collected in
Singapore, Hong Kong, Japan, and the US between June 11 and
30, 2021, a time period when the pandemic in each region turned
relatively stable. Though, as noted earlier, the influence of losing
an election has been shown to persist throughout the entire
electoral cycle (Dahlberg and Linde 2017), our data collection
spans four jurisdictions with varying intervals between their most
recent elections and the time of data collection, allowing us to
make comparisons based on the length of the intervals. Specifically, Singapore and Hong Kong held their general and legislative
elections on 10 July 2020 and 4 September 2016, respectively.
Japan conducted its general election on 22 October 2017, while
the United States completed its presidential election on 3
November 2020.
The survey was administered by a global data company,
Dynata. For the four regions examined, the company-owned
online panels comprised 56,000 to 2,350,000 registered users,
among whom our samples were obtained via opt-in online
surveys. Data collection based on online panels can be conducted
quickly for time-sensitive projects (Callegaro et al. 2014; Wright
2005), such as studies on the COVID-19 pandemic.
Our surveys targeted adult residents (18 and over) in each
jurisdiction. Quota sampling method was employed to recruit
participants with characteristics that approximated the general
population. The data company sent email invitations to registered
panel members, inviting them to log into the survey platform to
complete the questionnaire via computers or mobile phones. This
recruiting procedure was continued until the pre-determined
quota was met. To increase the response rate, upon completing
the surveys, participants were rewarded with credits to redeem for
cash or goods. The response rates of the four jurisdictions ranged
from 15% to 30%. The questionnaire was prepared in English,
Chinese, and Japanese. After removing cases with incomplete
information, a sample of 2,208 respondents was obtained.
Regarding the demographics of the sample, less than half of the
respondents were aged under 40 (44.4%), and there were slightly
more male respondents (57%) than female respondents in the
sample. Additionally, most respondents had obtained a tertiary
degree or above (79.3%). Nearly half of the respondents perceived
themselves as middle class (47.9%), while only 20.2% of the
respondents perceived their status as upper middle or upper class.
To save space, detailed characteristics of the sample from each
jurisdiction are presented in Supplementary Table S1.
Measures
Anti-vaccine conspiracy beliefs. Anti-vaccine conspiracy beliefs
were measured by two items originating from prior research
(Duffy et al. 2020). Both items were measured by asking the same
question (“Please evaluate how much you disagree or agree with
the following statements”) on a seven-point scale (1 = “strongly
disagree”; 7 = “strongly agree”). The first statement (Conspiracy
Theory 1) was “The real purpose of a mass vaccination program
against COVID-19 is to track and control the population,” while
the second (Conspiracy Theory 2) was “The only reason the
4
COVID-19 vaccine is being developed is to make money for
pharmaceutical companies.” We then aggregated these two items
into an index of anti-vaccine conspiracy beliefs (Pooled data:
M = 3.98, S.D. = 1.73, Spearman-Brown coefficient = 0.82).
Higher scores indicated stronger belief in anti-vaccine conspiracy
theories.
Voting choice. Voting choice was measured by asking which party
the respondents voted for in the previous general/legislative
election. Voting for opposition/losing parties was coded as 1, and
voting for the ruling/winning party was coded as 0. Particularly,
in Singapore, voting for People’s Action Party was coded as 0
while choosing other parties was coded as 1.2 In Hong Kong,
though the political leader (i.e., Chief Executive) is not popularly
elected and the party system was fragmented, the legislative
election is based on universal suffrage within a political landscape
characterized by a clear cleavage between the pro-establishment/
pro-Beijing camp and the opposition camp (Wong et al. 2018).
Therefore, scholars usually analysed people’s voting choice in
terms of the political camp they choose (Tang and Lee 2018;
Wong et al. 2018). Given that the pro-Beijing camp had won a
majority in the 2016 Hong Kong legislative election, those voting
for parties of the opposition camp were coded as 1, and those
voting for pro-Beijing parties were coded as 0.3 For Japanese
respondents, since the ruling coalition of LDP (Liberal Democratic Party)–Komeito had retained supermajority in the 2017
general election (Liff and Maeda 2019; Wakatsuki et al. 2017),
voting for LDP and Komeito were coded as 0, while voting for
other parties were coded as 1.4 For the US survey, voting for the
Democratic Party was coded as 0, and voting for the Republican
Party or other parties was coded as 1. Abstaining from voting in
the previous election or “I don’t remember/No response” was
treated as a missing value.
Emotional distress. Following prior research (Chen et al. 2022b;
Weathers et al. 2013), emotional distress was measured by five
items. Specifically, respondents were asked to rate on a sevenpoint scale (1 = “not at all”; 7 = “very much”) the extent to which
they have been in the following five situations over the past
month: “stressed about leaving home”; “having repeated and
disturbing thoughts or dreams about what is happening”; “having
difficulty concentrating”; “having trouble falling or staying
asleep”; “feeling irritable or having anger outburst.” Then, these
five indicators were aggregated into an index of emotional distress
(Pooled data: M = 3.87, S.D. = 1.77, Cronbach’s α = 0.93).
Control variables. To achieve more accurate estimations of the
focal relationships, a set of variables were included in our analysis
as potential confounders. As elaborated in the second section,
conspiracy mentality was controlled for and measured by five
questions adapted from Bruder et al. (2013). Also, to minimize
the possible confounding effect of partisanship, we included trust
in government as a proxy measure due to the lack of direct
measurement in our dataset. Past studies showed that trust in
government was significantly linked to partisanship during the
COVID-19 pandemic (Kerr et al. 2021; Nielsen and Lindvall
2021; Pickup et al. 2020; Robinson et al. 2021). Additionally,
authoritarianism, news use of media, perceived threat, and feeling
of hope were also controlled according to prior literature (Jolley
et al. 2018; Min 2021; Peitz et al. 2021; Richey 2017; Wood and
Gray 2019). We also included gender, age (1 = “18-29”; 2 = “3039”; 3 = “40-49”; 4 = “50-59”; 5 = “60 or above”), education level
(1 = “secondary or below”; 2 = “tertiary or above”), and social
class (1 = “lower or lower middle class”; 2 = “middle class”; 3 =
“upper middle or upper class”) as control variables. Country
dummy variables were included when we conducted model fitting
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Table 1 OLS regression predicting anti-vaccine conspiracy beliefs using pooled data.
Voting for opposition parties
Emotional distress
Voting for opposition parties * Emotional
distress
Trust in government
Conspiracy mentality
Authoritarianism
News use of social media
News use of traditional media
Feeling of hope
Perceived threat
Observations
R2
Anti-Vaccine Conspiracy Beliefs
(Combined)
Tracking and Controlling the
Making Money for
Population (Conspiracy Theory 1) Pharmaceutical Companies
(Conspiracy Theory 2)
Model 1
0.077***
0.312***
Model 2
0.081***
0.362***
−0.075***
Model 3
0.073***
0.275***
Model 4
0.077***
0.327***
−0.078***
Model 5
0.071***
0.297***
Model 6
0.074***
0.335***
−0.057*
−0.084***
0.302***
0.238***
0.067***
−0.009
0.004
−0.063***
2147
0.491
−0.078***
0.295***
0.241***
0.062**
−0.007
-0.001
−0.058***
2147
0.494
−0.054*
0.262***
0.212***
0.086***
−0.004
−0.008
−0.068***
2176
0.426
−0.047*
0.254***
0.216***
0.081***
−0.001
−0.013
−0.063***
2176
0.429
−0.099***
0.298***
0.231***
0.033
−0.019
0.022
−0.045*
2161
0.421
−0.095***
0.292***
0.234***
0.029
−0.017
0.018
−0.041*
2161
0.423
Entries are standardized coefficients. Emotional distress was centred by local means before it was used to create the interaction term. Gender, age, education, social class, and country dummy variables
were controlled.
*p < 0.05, **p < 0.01, ***p < 0.001
with the pooled data. Singapore was assigned as the reference
group. Descriptives and complete measures of all control variables
were
provided
in
Supplementary
Table
S1 and Supplementary Note.
Results
Before model testing, multicollinearity diagnostics were checked
for the pooled and regional data. Variance inflation factors (VIF)
ranged from 1.03 to 3.46, which was acceptable according to
O’brien (2007) who suggested VIF should be less than 5.
Ordinary least squares (OLS) regressions were applied to the
model fitting.
Hypothesis 1 posited a positive relationship between voting for
opposition parties in the former election and belief in antivaccine conspiracy theories. As shown in Table 1, all other conditions being equal, compared to respondents voting for the
incumbent party, people who voted for the opposition parties
were more likely to believe the anti-vaccine conspiracy theories
(β = 0.077, p < 0.001, in Model 1 Table 1). This result was consistent across the three jurisdictions (Hong Kong: β = 0.141,
p < 0.001, in Model 13 Table 3; Japan: β = 0.1, p = 0.008, in
Model 19 Table 4; the US: β = 0.058, p = 0.027, in Model 25
Table 5) but not in Singapore (β = 0.006, p = 0.86, in Model 7
Table 2). Furthermore, analyses using each conspiracy theory as
the dependent variable also generated similar results patterns,
except for Singapore and Japan (in Japan, voting choice was only
positively related to beliefs in Conspiracy Theory 1). Hence,
Hypothesis 1 was at least partly supported.
Hypothesis 2 presumed a positive relationship between one’s
emotional distress and belief in anti-vaccine conspiracy theories.
The findings presented in Model 1 in Table 1 demonstrated that
distress had a significant positive association with the anti-vaccine
conspiracy belief index (β = 0.312, p < 0.001). Moreover, this relationship was consistent across the four regions (Singapore: β = 0.28,
p < 0.001, in Model 7 Table 2; Hong Kong: β = 0.439, p < 0.001, in
Model 13 Table 3; Japan: β = 0.166, p < 0.001, in Model 19 Table 4;
the US: β = 0.341, p < 0.001, in Model 25 Table 5). Analyses using
each conspiratorial statement as the dependent variable also showed
the same result. Thus, Hypothesis 2 was supported.
Hypothesis 3 presumed a negative moderating effect of emotional distress on the association proposed in H1. Results from
Model 2 in Table 1 showed that the positive relationship between
voting for the opposition parties and conspiracy beliefs was
attenuated by emotional distress (β = −0.075, p < 0.001, also see
Fig. 1), which supported H3. Specifically, as illustrated in Fig. 2,
individuals voting for opposition parties exhibited significantly
stronger beliefs in anti-vaccine conspiracy theories compared to
those voting for the ruling parties when experiencing moderate or
low levels of emotional distress (moderate level: B = 0.28,
S.E. = 0.06, p < 0.001; low level: B = 0.48, S.E. = 0.08, p < 0.001).
However, when individuals experienced extreme emotional distress, their voting choice in the previous election no longer differentiated their beliefs; under such conditions, they consistently
expressed strong beliefs in these conspiracy theories regardless of
their voting behaviour (B = 0.09, S.E. = 0.08, p = 0.254).
Furthermore, regional analyses showed that such a negative
moderating effect of distress was statistically significant in both
Hong Kong (β = −0.149, p = 0.014, in Model 14 Table 3) and the
US (β = −0.111, p < 0.001, in Model 26 Table 5), but not in
Singapore (β = −0.028, p = 0.513, in Model 8 Table 2) or Japan
(β = 0.02, p = 0.668, in Model 20 Table 4). Additionally, in both
Hong Kong and the US, individuals voting for the opposition
parties expressed significantly stronger conspiracy beliefs compared to those voting for ruling parties, particularly when they
experienced low to moderate levels of distress. However, this
difference diminished when individuals experienced high levels of
distress, as shown in Figs. 3 and 4. Moreover, when using each
conspiracy theory as the dependent variable, this interactive
relationship between voting choice and emotional distress still
held in Hong Kong, the US, and the pooled data. Hence,
Hypothesis 3 was partly supported.
Discussion
Relying on cross-national survey data, we have scrutinized the
role of voting choice and emotional distress, and their interactive
dynamics in shaping individual beliefs about anti-vaccine conspiracy theories. In summary, all our hypotheses have been at
least partly supported: people voting for the opposition parties in
the former election (Hypothesis 1) and those experiencing greater
emotional distress (Hypothesis 2) are more tilted toward conspiratorial statements against the COVID-19 vaccines; this positive relationship between voting choice and conspiracy beliefs
turns weaker when people experience more emotional distress
(Hypothesis 3).
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Table 2 OLS regression predicting anti-vaccine conspiracy beliefs in Singapore.
Voting for opposition parties
Emotional distress
Voting for opposition parties * Emotional
distress
Trust in government
Conspiracy mentality
Authoritarianism
News use of social media
News use of traditional media
Feeling of hope
Perceived threat
Observations
R2
Anti-Vaccine Conspiracy
Beliefs (Combined)
Tracking and Controlling the
Population (Conspiracy
Theory 1)
Making Money for
Pharmaceutical Companies
(Conspiracy Theory 2)
Model 7
0.006
0.28***
Model 8
0.008
0.296***
−0.028
Model 9
−0.019
0.23***
Model 10
-0.018
0.239***
−0.016
Model 11
0.037
0.269***
Model 12
0.040
0.295***
−0.045
−0.124**
0.367***
0.221***
−0.028
−0.002
0.047
−0.077*
541
0.453
−0.125**
0.366***
0.224***
−0.03
−0.001
0.046
−0.078*
541
0.454
−0.093*
0.284***
0.219***
0.01
−0.007
0.029
−0.04
544
0.341
−0.093*
0.283***
0.220***
0.009
−0.006
0.028
−0.04
544
0.341
−0.13**
0.377***
0.187***
−0.065+
−0.002
0.059+
−0.095**
547
0.426
−0.132**
0.375***
0.191***
−0.068+
0.001
0.056
−0.095**
547
0.427
Entries are standardized coefficients. Emotional distress was centred by local means before it was used to create the interaction term. Gender, age, education, and social class were controlled.
+p < 0.1, *p < 0.05. **p < 0.01. ***p < 0.001
Table 3 OLS regression predicting anti-vaccine conspiracy beliefs in Hong Kong.
Voting for opposition parties
Emotional distress
Voting for opposition parties * Emotional
distress
Trust in government
Conspiracy mentality
Authoritarianism
News use of social media
News use of traditional media
Feeling of hope
Perceived threat
Observations
R2
Anti-Vaccine Conspiracy
Beliefs (Combined)
Tracking and Controlling the
Making Money for
Population (Conspiracy Theory 1) Pharmaceutical Companies
(Conspiracy Theory 2)
Model 13
0.141***
0.439***
Model 14
0.145***
0.549***
−0.149*
Model 15
0.109*
0.387***
Model 16
0.112*
0.481***
−0.126+
Model 17
0.142**
0.394***
Model 18
0.146**
0.498***
−0.142*
−0.032
0.304***
0.035
−0.01
0.006
−0.1**
−0.112**
484
0.463
-0.027
0.305***
0.063
−0.013
0.013
-0.101**
−0.102**
484
0.47
−0.026
0.279***
−0.035
0.017
−0.019
−0.087*
−0.162***
491
0.380
0.028
0.279***
−0.011
0.014
−0.012
−0.088*
−0.154***
491
0.385
−0.075
0.266***
0.122*
−0.041
0.019
−0.086*
−0.034
486
0.375
−0.069
0.267***
0.149**
−0.044
0.026
−0.086*
−0.024
486
0.381
Entries are standardized coefficients. Emotional distress was centred by local means before it was used to create the interaction term. Gender, age, education, and social class were controlled.
+p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001
Our finding on voting choice and anti-vaccine conspiracy
beliefs resonates with the conventional wisdom that “conspiracy
theories are for losers” (Uscinski and Parent 2014, p. 130). For
people voting for the losing parties in an election, conspiracy
theories implicating the incumbent are particularly attractive
because they can justify individuals’ political choices and uphold
a positive image of themselves and their in-groups. This finding
remains robust even after controlling for conspiracy mentality,
which rules out the possibility that individuals are equally likely
to believe any conspiracy theory about an out-group. Additionally, we include governmental trust as a proxy measure for partisanship, a potential confounder that could influence the
relationship between voting choice and conspiracy beliefs.
Moreover, as expected, this finding even extends to anti-vaccine
conspiracy theories that do not directly involve the incumbent.
Specifically, the explicit actor in Conspiracy Theory 2 is pharmaceutical company. Yet, our analysis shows that the effect size of
voting choice in the case of Conspiracy Theory 2 is comparable to
that in the case of Conspiracy Theory 1. This result suggests that
conspiracy beliefs driven by political bias tend to be pervasive, as
long as the conspiratorial claims help justify individuals’ political
6
choices, either directly or indirectly. Due to this political bias,
official efforts to debunk vaccine-related conspiracy theories may
be ineffective, especially among citizens supporting the losing
parties in the most recent election. Thus, the roles of other actors
(i.e., other than the current administration, such as the media,
opposition parties, and NGOs) in fighting conspiratorial information on vaccines should be further valued, by both policymakers and practitioners.
Our findings also revealed additional nuances based on
regional variation. In both Hong Kong and the US, the relationship between voting choice and anti-vaccine conspiracy
beliefs is particularly salient and consistent across the two conspiratorial claims (compared to that in Japan and Singapore).
This pattern is probably due to the growing political polarisation
in Hong Kong and the US in recent years (Chan and Fu 2017;
Ding and Lin 2021; Jahani et al. 2022; Lee 2016). As politics
become more contentious and polarised, issues surrounding
COVID-19 vaccines, including related conspiratorial narratives,
may be increasingly weaponised as tools for political contestation,
thereby amplifying the role of voting choice in shaping conspiracy
beliefs.
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Table 4 OLS regression predicting anti-vaccine conspiracy beliefs in Japan.
Voting for opposition parties
Emotional distress
Voting for opposition parties * Emotional
distress
Trust in government
Conspiracy mentality
Authoritarianism
News use of social media
News use of traditional media
Feeling of hope
Perceived threat
Observations
R2
Anti-Vaccine Conspiracy
Beliefs (Combined)
Tracking and Controlling the
Population (Conspiracy
Theory 1)
Making Money for
Pharmaceutical Companies
(Conspiracy Theory 2)
Model 19
0.1**
0.166***
Model 20
0.1**
0.153**
0.02
Model 21
0.118**
0.183***
Model 22
0.118**
0.185***
−0.003
Model 23
0.057
0.112**
Model 24
0.065
0.069
0.066
0.063
0.299***
0.359***
0.077*
−0.028
−0.053
−0.041
498
0.411
0.061
0.3***
0.359***
0.077*
−0.028
−0.053
−0.041
498
0.411
0.041
0.209***
0.323***
0.094*
−0.021
−0.05
−0.02
512
0.344
0.041
0.209***
0.323***
0.094*
−0.021
−0.05
−0.02
512
0.344
0.061
0.342***
0.314***
0.049
−0.031
−0.034
−0.04
498
0.345
0.056
0.344***
0.314***
0.05
−0.029
−0.033
−0.041
498
0.348
Entries are standardized coefficients. Emotional distress was centred by local means before it was used to create the interaction term. Gender, age, education, and social class were controlled.
*p < 0.05, **p < 0.01, ***p < 0.001.
Table 5 OLS regression predicting anti-vaccine conspiracy beliefs in the United States.
Voting for opposition parties
Emotional distress
Voting for opposition parties * Emotional
distress
Trust in government
Conspiracy mentality
Authoritarianism
News use of social media
News use of traditional media
Feeling of hope
Perceived threat
Observations
R2
Anti-Vaccine Conspiracy
Beliefs (Combined)
Tracking and Controlling the
Population (Conspiracy
Theory 1)
Making Money for
Pharmaceutical Companies
(Conspiracy Theory 2)
Model 25
0.058*
0.341***
Model 26
0.07**
0.416***
−0.111**
Model 27
0.06*
0.298***
Model 28
0.071*
0.371***
−0.11**
Model 29
0.056+
0.354***
Model 30
0.066*
0.42***
−0.1**
−0.138***
0.212***
0.295***
0.142***
−0.014
0.048+
−0.042
624
0.628
−0.124***
0.193***
0.292***
0.132***
-0.004
0.037
−0.032
624
0.634
−0.094**
0.199***
0.322***
0.124**
0.012
0.036
−0.061*
629
0.596
−0.08*
0.182***
0.318***
0.113**
0.023
0.025
−0.051+
629
0.602
−0.156***
0.223***
0.237***
0.138**
−0.051
0.059*
−0.025
630
0.557
−0.143***
0.206***
0.235***
0.129**
−0.042
0.048+
−0.016
630
0.562
Entries are standardized coefficients. Emotional distress was centred by local means before it was used to create the interaction term. Gender, age, education, and social class were controlled.
+p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001.
In Japan, voting for the losing party was found to correlate with
beliefs in Conspiracy Theory 1 but not Conspiracy Theory 2, the
latter of which does not explicitly implicate the incumbent. This
suggests that the connection between voting choice and conspiracy beliefs may depend on the extent to which the conspiratorial claim targets the ruling party. Notably, the varied
intervals between the most recent elections and our data collection (Hong Kong: 57 months; Japan: 44 months; US: 8 months)
suggest that the “losing effect” tends to persist over time, aligning
with prior research (Dahlberg and Linde 2017). However, this
effect is absent in Singapore, which is somewhat expected given
its lack of competitive elections and ruling party alternation. The
absence of a counterfactual condition in elections may diminish
the predictive power of voting choice for conspiracy beliefs in this
context. Taken together, our regional findings indicate that while
the persistence of the losing effect is not sensitive to the time
elapsed since an election, its strength is influenced by the level of
political competitiveness within the region.
Our investigation of emotional distress reaffirms the emotional
roots of conspiracy beliefs (van Prooijen et al. 2020). Consistent
with recent evidence (Simione et al. 2021), our finding shows that
individuals experiencing higher levels of distress are more vulnerable to COVID-19 conspiracy theories. This finding indicates
that when encountering a novel threat like the COVID-19 pandemic, uncertainty-related emotion like distress would drive
individuals’ judgment on pandemic-related conspiracy theories,
since the latter could mitigate one’s feeling of uncertainty and loss
of control by providing a simplified explanation of the situation at
hand (Whitson et al. 2015). This finding implies that emotional
distress may endanger individual health and paralyse public
health initiatives as it can raise anti-vaccine conspiracy beliefs
that are found to impair vaccination intentions (Chen et al.
2022a; Đorđević et al. 2021). More concerning is that the effect of
distress is quite robust across the four jurisdictions examined,
with the magnitude of the effect even comparable to that of
conspiracy mentality. The effect of emotional distress is also
consistently stronger than that of voting choice, authoritarianism,
media use, and socioeconomic factors. This indicates that individuals’ anti-vaccine conspiracy beliefs are primarily emotiondriven.
Furthermore, by extending affective intelligence theory to the
context of conspiracy theories, we have identified a moderating
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Fig. 1 Comparing model coefficients of key independent variables predicting beliefs in anti-vaccine conspiracy theories (pooled data).
Fig. 2 Conditional effects of voting choice on conspiracy beliefs varied by distress (pooled data).
effect of emotional distress that mitigates the association between
voting choice and anti-vaccine conspiracy beliefs. This finding
corresponds with the AIT theorization that when facing a novel
external threat like COVID-19, experiencing uncertain emotions
like distress reduces individuals’ reliance on their current political
stance, in their attitude formation and decision-making processes
(Vasilopoulos et al. 2018). Nonetheless, distress itself could be
harmful to personal health and the execution of public health
policies, regardless of its role in restraining the politicisation of
vaccine-related conspiracy theories. This finding also implies that
8
as people are normalized to the pandemic and their emotional
distress start to wane, the weight of political stance in shaping
conspiracy beliefs will increase. This means that, to more effectively counter conspiracy beliefs, stakeholders should consider
reallocating resources among various actors (both official and
unofficial) responsible for addressing vaccine-related conspiracy
theories, based on the different stages of the pandemic.
This study expands our understanding of the sociopsychological mechanism underpinning conspiracy beliefs. As
one of the pioneering studies examining the role of voting choice
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Fig. 3 Conditional effects of voting choice on conspiracy beliefs varied by distress (Hong Kong).
Fig. 4 Conditional effects of voting choice on conspiracy beliefs varied by distress (United States).
in the context of conspiracy theories, it reveals that past political
behaviours, such as voting, can influence individual’s attitudes
toward conspiratorial statements about health issues like COVID19 vaccines. Furthermore, by introducing AIT into conspiracy
theory research, this study elucidates the fundamental role of
emotion in shaping individual conspiracy beliefs: uncertaintyrelated emotions such as distress not only directly influence
conspiracy beliefs but also modify the impact of political factors
like voting choice.
This study is admittedly limited in several respects. First, by
utilizing cross-sectional data, we could not discern the causality
behind the relationships examined, especially for the effects of
emotional distress. Therefore, future research is needed to retest
those relationships with longitudinal data. Second, we have
examined the moderating role of only one negative emotion (i.e.,
distress) through the lens of AIT, leaving other emotions, such as
anger, unexamined. Future research is needed to compare the
roles of different types of emotions in shaping conspiracy beliefs.
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Third, it is sensitive to ask about respondents’ voting choices,
especially in non-democratic societies like Singapore and Hong
Kong, since people may face more political risk when overtly
expressing support for opposition parties. To address this issue,
we first checked the vote percentages for both the ruling party
and the opposition parties in our data, which generally reflected
the actual voting results in each jurisdiction. Also, for each region,
we performed a correlation analysis using authoritarianism and
voting for opposition parties which was pertaining to one’s
political ideology. The results show that the correlation coefficient
in Singapore (r = −0.111, p < 0.01) is comparable to those in
Japan (r = −0.125, p < 0.001) and the US (r = −0.085, p < 0.01),
suggesting there is no systematic bias in our measurement of
voting choice. Yet, surprisingly, the negative correlation was
particularly pronounced in Hong Kong (r = −0.336, p < 0.001).
This is probably due to the series of pro-democracy social
movements and protests triggered by the “Anti-Extradition Bill
Movement” in 2019, which has garnered extensive support across
demographics (Fong 2022). Conceivably, after those movements,
people still voting for the incumbent (or the so-called “proestablishment camp”) would be more likely to tilt toward
authoritarianism. Fourth, while we use a single-item measure of
governmental trust as a proxy for partisanship, its validity may
differ between bi-party (e.g., the US and Hong Kong) and multiparty (e.g., Japan) systems. Future study should include direct and
contextualized measures of partisanship to improve the estimation. Lastly, using dummy variables to control the regional
influence, we were unable to examine the potential mechanisms
underlying the regional difference. For instance, as discussed
above, the divergent effects of voting choice on conspiracy beliefs
detected in the four jurisdictions may depend on the extent of
political polarisation in each society. However, empirical examination of this assumption would require a larger dataset covering
more societies. Therefore, we encourage future study to explore
the possible influence of contextual-level factors, and to reexamine our model by checking for potential interactions
between contextual-level and individual-level factors in shaping
conspiracy beliefs.
Data availability
The datasets generated during and/or analysed during the current
study are available from the corresponding author on reasonable
request.
Received: 17 June 2024; Accepted: 17 March 2025;
Notes
1 For detailed information on official permission for the vaccines used in vaccination
programs in the four jurisdictions, see Centers for Disease Control and Prevention
(2022), Government of Singapore (2022), Ministry of Health, Labor and Welfare
(2022), and the Government of Hong Kong Special Administrative Region (2022).
2 For Singaporean respondents, voting for Workers’ Party, Singapore People’s Party,
Singapore Democratic Party, National Solidarity Party, Singapore Democratic
Alliance, Reform Party, Singaporeans First, People’s Power Party, or other opposition
parties were coded as 1.
3 For Hong Kong respondents, voting for Civic Party, CP–PPI–HKRO, the Democratic
Party, Demosisto, Hong Kong Association for Democracy and People’s Livelihood,
Labour Party, League of Social Democrats, People Power, or other opposition parties
were coded as 1; voting for Business and Professionals Alliance for Hong Kong,
Democratic Alliance for the Betterment and Progress of Hong Kong, Hong Kong
Federation of Trade Unions, Liberal Party, New People’s Party, or other proestablishment/pro-Beijing parties were coded as 0
4 For Japanese respondents, voting for Constitutional Democratic Party, Democratic
Party for the People, Japanese Communist Party, Japan Innovation Party, Social
10
Democratic Party, Reiwa Shinsengumi, NHK Party, or other opposition parties were
coded as 1
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Author contributions
Conceptualization: Xiang MENG, Fen LIN; Methodology: Xiang MENG, Fen LIN, Pei
ZHI; Formal analysis and investigation: Xiang MENG; Writing—original draft preparation: Xiang MENG; Writing—review and editing: Xiang MENG, Fen LIN, Pei ZHI;
Funding acquisition: Fen LIN.
Funding
at the top of the first survey page. Participants were told the length of the time of the
survey, the purpose of the study, and the contact information of the project coordinators.
They were also explicitly informed that their participation was voluntary and that their
responses would be treated with complete confidentiality and anonymity. In addition,
this study intentionally avoided collecting any identifying information, such as names,
addresses, or affiliations.
Additional information
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1057/s41599-025-04774-3.
Correspondence and requests for materials should be addressed to Xiang Meng.
Reprints and permission information is available at http://www.nature.com/reprints
This work was supported by the Strategic Research Project of City University of Hong
Kong [grant number 7005823]; and the Knowledge Transfer Earmarked Fund from
Hong Kong University Grants Committee [grant number 6354048]. The funders had no
role in the design of the study; the collection, analysis, and interpretation of the data; the
writing of the manuscript; or the decision to submit the manuscript for publication.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
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the copyright holder. To view a copy of this licence, visit http://creativecommons.org/
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Before initiating the data collection process via online survey, the authors obtained
written informed consent from all participants. The informed consent section was shown
© The Author(s) 2025
Competing interests
The authors declare no competing interests.
Ethical approval
Ethical approvalEthical approval was obtained from the Human Subject Ethics Committee of the City University of Hong Kong (Ref No: 8-2020-04-E295-18). The procedures used in this study adhere to the tenets of the Declaration of Helsinki.
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HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS | (2025)12:470 | https://doi.org/10.1057/s41599-025-04774-3