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. 2021 May 15;280:114028. doi: 10.1016/j.socscimed.2021.114028

Dynamic relationships between different types of conspiracy theories about COVID-19 and protective behaviour: A four-wave panel study in Poland

Tomasz Oleksy a,∗, Anna Wnuk b, Małgorzata Gambin a, Agnieszka Łyś a
PMCID: PMC9755974  PMID: 34023709

Abstract

Rationale

Conspiracy theories about COVID-19 pose a serious threat to public health by providing false information and undermining official health recommendations. However, existing studies rarely employed longitudinal designs, precluding the determination of the directionality between endorsement of conspiracy theories and its societal consequences. Also, relatively little research examined whether the association between protective health behaviour and the endorsement of conspiracy theories is affected by the content of a given theory.

Methods

A four-wave longitudinal panel survey on the association between belief in a wide range of conspiracy theories about COVID-19 and protective behaviour was carried out on a representative sample of Polish citizens (T1 = 1130, T2 = 971, T3 = 818, T4 = 688). Analyses were performed using Random Intercept Cross-Lagged Panel Models.

Results

The results showed a reciprocal, bidirectional association between conspiracy mentality and protective behaviour. The same effect was also observed between protective behaviour and threat of authoritarianism. We did not find evidence that specific COVID-19 related conspiracy theories directly (and differently) predict within-person changes in protective behaviour over time.

Conclusions

Our results showed that the association between various conspiracy-related variables and anti-pandemic COVID-19 variables differs at within- and between-person levels. Changes in the adherence to pro-health measures were negatively predicted by conspiracy mentality and a feeling of threat that the solutions introduced by the government may limit civil rights. Specific conspiracy beliefs were significantly related to protective behaviour only at the between-person level.

Keywords: Conspiracy beliefs, Conspiracy mentality, COVID-19, Protective behaviour, Public health, Random-intercept cross-lagged panel models, Coronavirus, Threat of authoritarianism

1. Introduction

The COVID-19 pandemic has forced entire societies to change daily life. Rigorous preventive measures, such as increased hygienic behaviour and social distancing, were recommended as crucial in preventing the spread of coronavirus (CDC, 2020; WHO, 2020a). The effectiveness of these measures depends on compliance with the recommendations by as large a proportion of the population as possible (Capraro and Barcelo, 2020). One of the important psychological factors influencing adherence to official guidelines is belief in conspiracy theories about COVID-19 (Allington and Dhavan, 2020; Pennycook et al., 2020). During the outbreak, COVID-19 conspiracy theories flourished to such an extent that the WHO stated, “we are not just fighting an epidemic; we're fighting an infodemic” (WHO, 2020b; see also Depoux et al., 2020; Kouzy et al., 2020). There have been rumours about the existence of a vaccine hidden by a conspiracy of pharmaceutical companies and available only to certain people. Some theories have alleged that the coronavirus was developed in a laboratory as a biological weapon. Others take aim at governments, accusing them of concealing facts about the pandemic and using the situation for their own purposes (van Mulukom et al., 2020). By increasing uncertainty about the appropriate methods of proceeding and reducing trust in official recommendations, conspiracy theories can pose a serious threat to collective efforts to combat the pandemic (see, e.g., Pennycook et al., 2020).

Given the social importance of this issue, it is not surprising that several studies have already examined the effects of endorsing conspiracy beliefs on preventive behaviours during a pandemic (see van Mulukom et al., 2020 for a review; Romer and Jamieson, 2020). Most of these studies were correlational, thus precluding the determination of the directionality between variables or changes in the prevalence of conspiracy theories. Additionally, they rarely focused on the content of specific conspiracy theories. To address these limitations, we conducted a four-wave representative panel study to investigate the association between preventive behaviour and various conspiracy beliefs related to COVID-19. To establish information about directionality, we employed an advanced statistical technique, random-intercept cross-lagged panel models.

1.1. Conspiracy theories and their role in predicting preventive behaviour

Numerous research projects have found an association between conspiracy beliefs and risky health behaviour and the rejection of scientifically proven health recommendations. Oliver and Wood (2014) showed that various variants of medical conspiracy theories were not only known to most people but also enjoyed considerable support (for example, nearly 40% of those surveyed agreed that the government agencies intentionally suppress research on natural cures for cancer). Moreover, belief in conspiracy theories was associated with the increased use of alternative medicine and decreased adherence to official medical recommendations, such as getting influenza vaccinations or annual check-ups (Oliver and Wood, 2014). Quinn et al. (2017) also found that believers in conspiracy theories had fewer positive attitudes towards vaccination and preferred to use natural medicines rather than being vaccinated (see also Eicher et al., 2014; Lohiniva et al., 2014; Setbon and Raude, 2010). In addition to anti-vaccine views, belief in conspiracy theories is associated with other risky health behaviours, such as reduced contraceptive use (Grebe and Nattrass, 2012; Thorburn and Bogart, 2005) or refusing antiretroviral treatment (Bogart et al., 2010). The negative association between healthy behaviours and conspiracy beliefs may arise from generally reduced trust in science and thus in medicine (Galliford and Furnham, 2017; Imhoff and Bruder, 2014, Imhoff and Lamberty, 2020, Imhoff et al., 2018).

Regarding the COVID-19 pandemic, existing research has shown mixed results. On one hand, research has demonstrated a link between endorsing unfounded beliefs about COVID-19 and decreased compliance with public health recommendations (Allington et al., 2020; Bierwiaczonek et al., 2020; Erceg et al., 2020; Sternisko et al., 2020; Swami and Barron, 2020). A conspiracy mentality—perceiving the world as full of hidden conspiracies—is related to non-normative prevention behaviours and, to a lesser extent, complying with government-driven behaviours (Imhoff and Bruder, 2014, Imhoff and Lamberty, 2020, Imhoff et al., 2018). On the other hand, some studies find no significant association between conspiracy theories and adherence to preventive measures (Alper et al., 2020; Čavojova et al., 2020; Díaz and Cova, 2020; Plohl and Musil, 2020). Inconsistent results can be caused by many factors such as size or representativeness of samples, intercultural differences, and instruments of assessment (Hornik et al., 2021). In our study, we examined whether such inconsistencies can be explained to some extent by the particular content of endorsed conspiracy theory.

1.2. Content of conspiracy theories: is it important in research on COVID-19-related conspiracy theories?

Despite the growing concern about the societal effects of the prevalence of conspiracy theories, relatively little research has examined whether the consequences of endorsing them may differ depending on the content of the theory (Imhoff and Bruder, 2014, Imhoff and Lamberty, 2020, Imhoff et al., 2018; Oleksy et al., 2020; van Mulukom et al., 2020). People can believe to similar degrees even in logically contradictory conspiracy theories, which makes a strong argument for the existence of a generalised conspiracy mindset, a source of various conspiratory beliefs (e.g., Imhoff and Lamberty, 2020; Miller, 2020; Sutton and Douglas, 2020). However, the variety of conspiracy theories associated with COVID-19 has led to an increased interest in how the different descriptions of pandemic reality presented in a given theory are related to its popularity and social consequences, both behavioural and attitudinal (Enders et al., 2020). For example, Enders et al. (2020) concluded that more abstract conspiracy theories (e.g., ‘The number of deaths related to the coronavirus has been exaggerated’) receive a higher amount of endorsement than the more specific ones (e.g., ‘Bill Gates is behind the coronavirus pandemic’). According to Enders et al., the general conspiracy theories may be more popular because they can be relatively easily filled with details compatible with individuals' existing belief systems. Moreover, people vary in being susceptible to particular conspiracy theories, depending on their political view (Enders et al., 2020; Uscinski et al., 2020), type of national identification (Sternisko et al., 2020), or gender (Imhoff and Bruder, 2014, Imhoff and Lamberty, 2020, Imhoff et al., 2018).

The association between the content of COVID-19-related conspiracy theories and their consequences, such as complying with pro-health guidelines, has received increasing research attention. For example, Oleksy et al. (2020) indicated negative associations between believing in conspiratorial governments (e.g., ‘the government is using the pandemic to limit citizens’ freedom’) and using prevention methods, such as social distancing and handwashing, less frequently. Endorsing more general conspiracy theories had no association with adherence to such guidelines. Similarly, Imhoff and Lamberty (2020) mentioned that the belief that COVID-19 is a hoax was related to fewer preventive behaviours and the belief that coronavirus is a biological weapon was related to self-centred prepping behaviour.

The above studies provide a theoretical and empirical rationale for considering the role of the content of conspiracy theories to better understand their prevalence and societal impact, but most of these studies were correlational, and more advanced methods (e.g., longitudinal studies) are required to confirm their findings.

1.3. Coronavirus risk and specific vs non-specific groups in the content of COVID-19 conspiracy theories

We propose that popular conspiracy theories about COVID-19 be categorised along two dimensions: 1) those emphasizing the threat of the pandemic vs. theories suggesting no threat and 2) those related to unspecified vs. specified groups exploiting the pandemic for their own purposes. According to the first dimension, theories emphasizing the danger of COVID-19 include beliefs that the coronavirus was created as a biological weapon or the belief that authorities are hiding the true number of victims from the public. We assume that people endorsing threat-related theories exhibit more frequent preventive behaviours to reduce the possibility of a potentially deadly infection. At the other extreme are conspiracy theories that question the very existence of the threat. Such theories indicate, for example, that the pandemic is a 'plandemic'—a hoax planned by elites to give them more power in the world. Another theory of this type is the belief that coronavirus is completely harmless, or at least no more dangerous than typical seasonal diseases, such as flu (Koon et al., 2021; Uscinski et al., 2020). Promoted by some populist politicians (e.g., Donald Trump or Jair Bolsonaro), these theories seem to have an increasing impact and have become one of the slogans propagated by a growing number of movements protesting COVID-19 restrictions.

COVID-19-related conspiracy theories also differ in the exactness of identifying the group that gains from the development of pandemic. Theories emphasizing the existence of unspecified groups (such as ‘global elites’) using COVID-19 are closer to classic conspiratory mentality (see e.g., Bruder et al., 2013). By contrast, group-specific theories indicate specific groups that can be blamed for developments during a pandemic. Some of these theories focus, for example, on stigmatizing the countries where the coronavirus was first observed (Douglas, 2020), while others take a suspicious look at representatives of their own group, particularly governments (Oleksy et al., 2020). According to some research, ingroup and outgroup conspiracy beliefs may result in different social consequences (Bertin et al., 2020; Cichocka et al., 2016; Oleksy et al., 2020). The effects of both ‘threat’ and ‘not a threat’ conspiracy theories may be exacerbated in cases when own governments are suspected of malevolent intentions, because the governments' decisions affect citizens directly. Therefore, belief in theories such as ‘the government is hiding the true number of victims from people may reinforce a sense of particularly imminent danger and, consequently, a greater willingness to protect oneself and one's loved ones. Similarly, the belief that the government wants to achieve its own goals under the pretext of fighting a pandemic (e.g., limit civil rights and democracy) may arouse even greater resistance to complying with official recommendations than when the unspecified group is to blame. Indeed, existing research on the role of trust in adhering to governmental decisions has indicated that citizens are more willing to comply if they perceive the authorities as acting for the common good (Dalton, 2004; see also Douglas, 2020). In the context of the COVID-19 pandemic, Karić and Međedović (2020) stated that perceiving coronavirus as harmless was related to lower adherence to pro-health behaviour due to decreased political trust (see also Latkin et al., 2021). Distrust in governments was also a mediator between political COVID-19 conspiracy beliefs and complying with guidelines in Germany (Bruder and Kunert, 2021) and Croatia (Imhoff and Bruder, 2014, Imhoff and Lamberty, 2020, Imhoff et al., 2018).

1.4. Study overview and hypotheses

To address the limitations of previous studies, we employed a four-wave longitudinal panel design to examine the dynamics of preventive behaviour during eight months of the pandemic in Poland and their association to the endorsement of a wide range of conspiracy theories. We examined the role of general conspiracy mentality which is known to be a common ground for other more specific theories (see e.g., Sutton and Douglas, 2020) as well as five specific conspiracy beliefs: COVID-19 is a weapon, 2) COVID-19 is a hoax, and 3) the government underestimates or conceals the true scale of the pandemic, 4) some unidentified groups are secretly benefiting from the pandemic, 5) threat of authoritarianism. To our knowledge, this is the first study examining the association between the specific content of conspiracy theories and preventive behaviours that change dynamically with the changing context of the pandemic.

We hypothesize that the beliefs that COVID-19 is a weapon and that the government hides the real number of COVID-19 cases will positively predict maintaining preventive behaviour because such behaviour is then necessary to counteract a serious threat (Hypothesis 1). In contrast, the other four beliefs should be related to a decrease in preventive behaviour because of the perception that these behaviours are unnecessary or recommended by ill-intentioned groups (Hypothesis 2).

2. Methods

The studies were approved by the Scientific Research Ethics Committee of the Faculty of Psychology at the University of Warsaw. The findings presented in this article are part of a larger research project on psychological aspects of the COVID-19 pandemic in the Polish population.

2.1. Participants

A total of 1179 adults participated in Wave 1 of the online study, conducted between 4th-7th May. Data were collected from Polish adults via Internet research panel sampled from a poll of 150,000 verified panelists using the computer-assisted web interviewing method. The random-quota sample was nationally representative in terms of age, gender, and place of residence. To ensure the quality of the data, 49 outliers were removed: 24 participants using only the highest or lowest scale levels in the whole survey, 25 participants using only the midpoint of the scale. Finally, data from 1130 participants were analysed. The vast majority (99%, n = 1123) of participants declared that Poland was their country of origin. The sample included 569 females (50.4%) and 561 males (49.6%), in the age range from 18 to 85 (M = 44.53, SD = 15.83). Over one third (37%) of participants lived in a village, 12.1% lived in a small town (up to 20,000 residents), 21.3% lived in a medium town (20000–99000 residents), 17.4% lived in a big town (100,000–500000 residents), and 11.7% lived in a big city (over 500,000 residents). Wave 2 occurred between 4th and 17th of June among 971 participants from the previous wave (473 women, 498 men; age ranged from 18 to 85 years, M = 45.35, SD = 15.42). Wave 3 was conducted 7th-17th July among 818 participants (387 women, 431 men; age ranged from 18 to 85 years, M = 46.27, SD = 15.07). And, Wave 4 took place 3–22 December among 688 participants (315 women and 373 men, aged ranges from 18 to 85 years, M = 47.30, SD = 14.88).

2.2. The pandemic situation in Poland

The study was conducted in four waves taking place between 4th May and December 23, 2020. Wave 1 occurred between the 4th and the 7th of May, two months after the detection of the first case of coronavirus infection in Poland. At the very beginning of the COVID-19 outbreak in Poland, the Polish government implemented strong restrictions and lockdowns. Since 20th April, the most restrictive recommendations were gradually lifted (Krzysztofik et al., 2020; Włodarczyk, 2020). Presidential elections were planned for 10th May, and until the very end, the government tried to convince society that it is possible to conduct the elections with all-postal voting.

Wave 2 occurred between 4th and 17th June. At this time, the situation worsened in several voivodeships, and there were large outbreaks of infections (in mines, nursing homes, and hospitals), but the government continued the gradual lifting of restrictions. The Polish Prime Minister assured that ‘Poland is emerging victorious in the fight against the epidemic.’ However, some Poles (especially scientists) raised critical voices concerning the Polish government's decisions and emphasized the inconsistency between drastic restrictions implemented in the beginning and then the very fast pace of lifting of the restrictions irrespective of the epidemic situation in Poland. Suspicions were raised that the content of messages presented by the Polish government and implemented strategies changed with the approaching of presidential elections (Włodarczyk, 2020). Additionally, the high rate of positive COVID-19 cases among miners, their mass testing, and the analysis of these data raised the question of how big the discrepancy is between the official number of those infected and the number actually infected. Experts and commentators suspected that the discrepancy could be up to 20 times as large (Krzysztofik et al., 2020).

Wave 3 occurred between 7 and 17 July. Outbreaks of infections further occurred in individual hospitals, workplaces, weddings or funerals, and holiday centres. The daily number of new cases in Poland was still between 200 and 400. The second round of presidential elections took place at this time in Poland. The Prime Minister assured that the situation related to the coronavirus is stabilizing and that the virus is in retreat, as well as encouraged all Poles (even older people) to vote during the elections (Włodarczyk, 2020).

Wave 4 occurred between 3rd and 22nd December. The number of people infected with coronavirus approached 1,028,000, the number of fatalities exceeded 18,800, and about 640,000 people recovered. For almost four weeks, the new restrictions (remote learning in schools, closure of cultural and sports facilities and restaurants, ban on mass events) were implemented due to high increases in the number of COVID-19 cases at the end of October and the beginning of November in Poland. After the increase in infections, approximately 20,000 new cases daily, the number of infections decreased at the time of Wave 4 since the Polish Ministry of Health has reduced the number of tests and decided to test only people who already have symptoms of COVID-19, which is not in line with the recommendations of WHO. Moreover, according to the data collected by local authorities, the number of infected people was higher than that specified by the Polish government.

2.3. Measures

Preventive Behaviour was measured with seven items, e.g., ‘I wash my hands after being outside” or “I socialize with people outside my household during the epidemic (e.g., family, friends)” (reverse coded; see full scale is given in the online supplement). Participants responded on a scale from 1 (‘I strongly disagree’) to 5 (‘I strongly agree’). The scale had good reliability, T1: α = 0.70; T2: α = 0.76; T3: α = 0.76; T4: α = 0.75.

Conspiracy mentality was measured with five-item scale of Bruder et al. (2013), e.g., “I think that many very important things happen in the world, which the public is never informed about” (for the full scale see the online supplement). The scale had a very good reliability, T1: α = 0.83; T2: α = 0.86; T3: α = 0.86; T4: α = 0.83. Participants responded on a scale from 1 (‘I strongly disagree’) to 5 (‘I strongly agree’)

Conspiracy theory about groups benefiting from COVID-19 was measured with two items, “I think that the development of the pandemic may be beneficial to certain groups whose interests we are unaware of” and “I think there are groups interested in exaggerating the panic over COVID-19 to achieve their own goals” (T1: r = 0.71, T2: r = 0.74, T3: r = 79; T4: r = 0.80).

Specific conspiracy theories about COVID-19 were measured with one item each:

COVID-19 as a weapon: “I think that the coronavirus was created in the laboratory as a biological weapon.”

COVID-19 as a hoax: “I wouldn't be surprised if after some time, it turned out that the coronavirus doesn't exist.”

Governmental conspiracy: “I believe that the authorities are hiding the true scale of the victims of the pandemic from society.”

Threat of authoritarianism was measured with three items, “I am concerned that politicians during a pandemic are free to change the law as they wish because no one has time to control their actions”, “I am afraid that the authorities may, under the pretext of fighting the pandemic, seek to permanently restrict the rights and freedoms of citizens”, “Even after the pandemic, I fear, the authorities will control us more than before it happened”. The scale had an excellent reliability, T1: α = 0.93; T2: α = 0.94; T3: α = 0.94; T4: α = 0.94. If not stated otherwise, all conspiracy-related items were completed on a scale ranging from 1 (‘I strongly disagree’) to 7 (‘I strongly agree’).

2.4. Analytical strategy

We applied the random-intercept cross-lagged panel model (RI-CLPM; Hamaker et al., 2015), which allows for more accurate estimations of directionality than standard cross-lagged panel models (CLPM) (Hamaker et al., 2015). The CLPM method, although still frequently used for analysing panel data, is ineffective in distinguishing between-person stability of variables and within-person change (Mund and Nestler, 2019), which may lead to biased interpretation of estimates (see Berry and Willoughby, 2017; Hamaker et al., 2015; Osborne and Sibley, 2020). In turn, the RI-CLPM allows the decomposition of observed variables into two parts: 1) time-invariant, trait-like, ‘between-person’ factors and 2) more state-like, time-varying, or ‘within-person’ factors (Hamaker et al., 2015). In this type of model, a random intercept for each variable is used to extract its time-invariant characteristics, so the remaining cross-lagged paths can be directly interpreted as reflecting within-person dynamics over time. Thus, RI-CLMP enabled us to investigate whether a person's deviation from their expected score of one variable predicts their future deviations in the other variable; for example, whether different from the expected belief in one conspiracy theory, Time 2, predicts similar deviations from individuals' preventive behaviour in Time 3, after adjustment for autoregression effects.

We modelled six RI-CLPMs, one for each variable related to conspiratory thinking (see an example in Fig. 1 ). This approach could be justified by a high complexity of RI-CLPM models and potential convergence issues, particularly when more than two constructs are analysed simultaneously (see also Golec de Zavala et al., 2020a, Golec de Zavala et al., 2020b, 2020b; Meagher and Cheadle, 2020; Schwaba and Bleidorn, 2020). To increase model parsimony, we held direct paths between specific state constructs to be equal over time (Hamaker et al., 2015). Thus, for example, the prediction of acceptance of preventive behaviour at Time 4 by conspiracy mentality at Time 3 was constrained to be equal to the prediction from Time 3 to Time 2 and Time 2 to Time 1 among the same variables. We also controlled for demographic variables, such as age, sex, and educational level. All analyses were computed using the R-package ‘lavaan’ (Rosseel, 2012).

Fig. 1.

Fig. 1

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Random intercept cross-lagged panel model (RI-CLPM) for the estimation of the directionality between conspiracy mentality (CM) and protective behaviour (PT) for four-wave panel data. Each observed score is divided into two parts: a within-person part and a between-person part. The wCM and wPT factors represent the within-person part. The two random intercepts capture the between-person part.

2.5. Attrition analysis

To examine systematic patterns of attrition, we compared incomplete responders (n = 1130) to complete responders (n = 688) on key demographic variables and main variables used in the models. Complete responders were more likely to be men than women, χ2(1) = 14.69, p < .001, and were older than incomplete responders, t(1128) = −7.52, p < .001. When other variables were considered, complete responders had lower levels of conspiracy mentality t(1128) = −2.42, p = .02, beliefs in government hiding number of victims, t(1128) = −2.54, p = .01, general conspiracy beliefs about the COVID-19 pandemic, t(1128) = 4.15, p < .001, and beliefs that the pandemic is a hoax, t(1128) = 3.80, p < .001. Then, we used a binary logistic regression model to examine whether being a complete or incomplete respondent is predicted by demographic variables and variables related to conspiracy theories. The model explained R2 Cox-and-Snell = 0.08 (8%) of the variance in attrition over time. Age [odds ratio (OR) = 1.03, p < .001] and gender (OR = 1.52, p = .001) significantly predicted attrition. None of the variables related to conspiracy theories significantly predicted the attrition panel except for general conspiracy beliefs about COVID-19 (OR = 0.85, p = .003). Thus, we assumed that, when demographic variables are included in the model, missing data in our variables can be treated as missing at random (MAR; see Young and Johnson, 2015). Accordingly, for handling missing data, we used full information maximum likelihood, providing unbiased parameter estimates when data were MAR (Enders and Bandalos, 2001).

3. Results

3.1. Descriptive statistics

Table 1 presents the percentage of participants that agreed with each type of conspiracy belief within four waves. Most participants (over 70%) across all four waves endorsed conspiracy mentality and threat of authoritarianism. Endorsement of the conspiracy theory about groups benefiting from COVID-19, governmental conspiracy, and belief that COVID-19 is a weapon gradually decreased throughout the four waves. Belief that COVID-19 does not exist received the lower endorsement of all statements.

Table 1.

Percentage of participants that agreed with each type of conspiracy beliefs within four waves (values higher than midpoint of the response scale were aggregated).

Conspiracy beliefs Wave 1 Wave 2 Wave 3 Wave 4
Conspiracy mentality 76.5% 73.5% 72.6% 71.7%
Conspiracy about groups benefiting from the pandemic 68.3% 67.8% 60.4% 56.1%
COVID-19 as a weapon 51.8% 44.9% 42.8% 40.7%
COVID-19 as a hoax 31.9% 29.6% 29.3% 26.3%
Government that hiding true scale of the pandemic 63.6% 58.6% 53.4% 53.2%
Threat of authoritarianism 75% 71.3% 68.7% 72.7%
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3.2. Zero-order correlations

Both the hoax and general COVID-19 conspiracy theories, which fit in with thinking about the COVID-19 outbreak as a ‘plandemic’, correlated negatively with preventive behaviour while belief that the government conceals the real number of COVID-19 cases correlated positively with protective measures. General conspiracy mentality and threat of authoritarianism were positively related to preventive measures in the first wave. And conspiracy theory about ‘COVID-19 as a weapon’ was not associated with preventive behaviour. The full correlation matrix among study variables across the four waves is provided in the online supplement (T6).

3.3. Random intercept cross lagged model analyses

To address hypotheses 1–2 we used a RI-CLPM to examine the influence of all types of conspiracy theories on the preventive behaviours. We conducted the analyses with robust maximum likelihood estimation (MLR) to account for non-normally distributed data. We used the maximum likelihood procedure (FIML) to deal with missing values. All models showed good fit to the data (see Table 2 ). The results showed the bidirectional within-subject relations between conspiracy mentality and threat of authoritarianism, and preventive behavior (see Table 3 ). The within-subject effects of remaining conspiracy beliefs were insignificant.

Table 2.

RI-CLPM model parameters.

Model χ2 Df p CFI RMSEA SRMR
CM PREV 64.60 23 <.001 .99 .04 .02
CGB PREV 90.37 23 <.001 .96 .05 .03
W PREV 64.93 23 <.001 .98 .04 .03
H PREV 74.76 23 <.001 .99 .05 .02
GOV PREV 65.89 23 <.001 .99 .04 .02
AUT PREV 60.78 23 <.001 .99 .04 .03
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Note. PREV - Preventive behavior, CM - Conspiracy mentality, CGB - Conspiracy about groups benefiting from the pandemic, H - COVID-19 as a hoax, W - COVID-19 as a weapon, GOV - Government that hiding true scale of the pandemic, AUT - threat of authoritarianism.

Table 3.

Results of random-intercept cross-lagged panel models.

Parameters B SE p
RI-CLPM 1: CM PREV
Autoregressive Paths
CM .035 .048 .465
PREV .339 .070 <.001
Cross-Lagged Path
CM PREV -.106 .042 .011
PB CT -.100 .045 .025
4-waves between subject correlation .017 .013 .215
RI-CLPM 2: CGB PREV
Autoregressive Paths
CGB .111 .052 .03
PREV .343 .080 <.001
Cross-Lagged Path
CGB PREV -.017 .019 .353
PREV CGB -.118 .135 .382
4-waves between subject correlation -.061 .027 .017
RI-CLPM 3: W PREV
Autoregressive Paths
W .129 .043 .002
PREV .324 .082 <.001
Cross-Lagged Path
W PREV -.003 .016 .861
PREV W .006 .105 .953
4-waves between subject correlation .018 .031 .567
RI-CLPM 4: H PREV
Autoregressive Paths
H .130 .045 .004
PREV .320 .078 <.001
Cross-Lagged Path
H PREV -.024 .015 .107
PREV H -.081 .123 .509
4-waves between subject correlation -.130 .037 <.001
RI-CLPM 4: GOV PREV
Autoregressive Paths
GOV .065 .045 .149
PREV .317 .083 <.001
Cross-Lagged Path
GOV PREV .003 .013 .822
PREV GOV .118 .103 .251
4-waves between subject correlation .029 .028 .305
RI-CLPM 4: AUT PREV
Autoregressive Paths
AUT .114 .053 .031
PREV .339 .064 <.001
Cross-Lagged Path
AUT PREV -.074 .020 <.001
PREV AUT -.235 .085 .006
4-waves between subject correlation .003 .027 .922
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Note. PREV - Preventive behavior, CM - Conspiracy mentality, CGB - Conspiracy about groups benefiting from the pandemic, H - COVID-19 as a hoax, W - COVID-19 as a weapon, GOV - Government that hiding true scale of the pandemic, AUT - threat of authoritarianism.

Additionally, because the lag for the fourth wave was much longer than between the three previous waves, we analysed six additional models in which the final lag differs from the others in its path weight. Models including conspiracy theories related to COVID-19 perceived as a weapon, government hiding the true scale of the pandemic, threat of authoritarianism, and general conspiracy mentality did not differ significantly from the fully constrained models. In the case of perceiving COVID-19 as a hoax, non-constrained model was significantly better than constrained (Δχ2(4) = 11.075, p = .03), but we still did not observe any significant cross-lagged effects between T3 and T4. In the case of conspiracy theory about groups benefiting from COVID-19, non-constrained model was also significantly better than constrained (Δχ2(4) = 10.377, p = .04), and we observed significant cross-lagged path between T3 and T4, and a higher preventive behaviour at T3 predicted a lower belief in this theory at T4 (B = 0.28, SE = 0.17, p = .004). We also checked RI-CLPMs based on factor analysis (see online supplement).

4. Discussion

One of the most serious issues accompanying the coronavirus outbreak is the spread of conspiracy theories, providing the public with false information about the causes and course of the pandemic, resulting in an ‘infodemic’ (Bruder and Kunert, 2021; Pennycook et al., 2020). Our study indicated that in line with research by Enders et al. (2020), different conspiracy beliefs were endorsed differently throughout the time of the pandemic (see Table 1). The more general (i.e., conspiracy mentality) was shared by more than 70% of participants and the more specific (i.e., COVID-19 seen as a weapon or a hoax) by 26%–51%, depending on the wave. Moreover, similar to the conspiracy mentality, threat of authoritarianism was endorsed by approximately 70% of participants throughout the whole period of data collection. Thus, a more personal (related to one's own fear) belief was a highly socially shared view.

Endorsement of conspiracy theories causes a reduction in the tendency to engage in healthy behaviour recommended by the authorities (e.g., Jolley and Douglas, 2014; Oliver and Wood, 2014; Quinn et al., 2017), which in the case of the COVID-19 pandemic, may lead to particularly negative consequences (for review see e.g., van Mulukom et al., 2020). However, these studies were mainly correlational and thus precluded the determination of the directionality between endorsement of conspiracies and preventive behaviour. Additionally, these studies rarely consider one potentially critical issue: the content of a given conspiracy theory (Larsen, Donaldson and Mohanty, 2020; Oleksy et al., 2020). In a longitudinal four-wave online survey of a representative sample of Poles, we used advanced RI-CLPM models to examine whether particular types of conspiracy beliefs predict preventive behaviours.

A reciprocal, bidirectional association was observed between conspiracy mentality and preventive behaviour (i.e., within-person changes in conspiracy mentality preceded within-person changes in preventive behaviour and vice versa), see Table 3. A similar effect was also observed between preventive behaviour and threat of authoritarianism (see Table 3). By using robust longitudinal methods, this finding contributes to the vast extent of research claiming that conspiracy beliefs can indeed drive pro-health action (Oliver and Wood, 2014), which was also shown in correlational studies in the context of the COVID-19 pandemic (e.g., Meagher and Cheadle, 2020, Miller, 2020, Mund and Nestler, 2019). Studies on conspiracy mentality have revealed its connection to distrust in official science and medical recommendations. For example, Imhoff et al. (2020) demonstrated that conspiracy mentality lowers the tendency to engage in normative actions related to politics, such as voting (and increases a preference for non-normative activities). Other studies have indicated that a prerequisite for complying with authorities' recommendations is that they are perceived as acting for the common good (Dalton, 2004; Douglas, 2020; see also Bruder and Kunert, 2021; Pavela Banei et al., 2020). As preventive behaviour can be taken as a strict government recommendation, a growing conspiracy mentality and a greater threat of authoritarianism being gradually introduced by the government may be both associated with future growing resistance to following ‘suspicious’ guidelines.

The use of RI-CLPM models also allowed us to observe the effect in the opposite direction: within-person increase of preventive behaviour predicted within-person decreases in conspiracy mentality as well as the threat of authoritarianism. The results seem to be explainable if adherence to preventive guidelines is, in fact, a marker of more general trust in both government and medical guidelines—the increasing willingness to follow official advice would translate into a recognition that conspiracy mentality and suspicion of one's own government is not an adequate way of thinking in times of pandemic. That within-person changes could also be understood from the perspective of the classical process of rationalization, defined as performing a given action and then adjusting one's beliefs to make the action rational (Cushman, 2020; Festinger, 1962; Webster and Kruglanski, 1994). In terms of rationalization, even if a conspiratory believer started to follow the recommended rules without deliberation (e.g., under social pressure), he or she could then, to maintain consistency between their behaviour and beliefs, have considered preventive behaviour as fully rational and rejected alternative views offered by conspiracies. The result we obtained seems particularly interesting because it shows that a specific action (preventive behaviour) in the previous time of measurement is related to a decrease in the general conspiracy mentality in the next. Thus, one can hypothesize that behaviour inconsistent with conspiracy theories could potentially translate into a reduction of other negative actions or attitudes stemming from conspiracy mentality (e.g., negative intergroup attitudes, see INSERT CITATION) via the decrease of the latter. In a world where conspiracy theories are becoming an increasingly serious social problem, future research should explore whether persuading people to particular behavior which contradicts advice given by conspiracy theories can counteract other related consequences. Such behavioural ‘inoculation’ against conspiracy theories could be a potential complement to the so-called pre-emptive debunking (e.g., Roozenbeek and van der Linden, 2020; van der Linden et al., 2020), which depends on weakening the effect of misinformation via providing individuals with warnings against manipulations and reliable facts.

Contrary to our hypotheses, the results of the other four RI-CLPM models did not show significant cross-lagged effects, except T3-T4 association from preventive behaviour to the belief that some secret groups benefit from COVID-19 (when T3-T4 paths were unconstrained), see Table 3. In other words, we did not find evidence for the fact that specific COVID-19-related conspiracy theories directly (and differently) predict within-person changes in preventive behaviour over time. Why did conspiracy and the threat of authoritarianism prove to be stronger predictors of such changes than other conspiracy-related variables? Perhaps conspiracy mentality is a more stable measure than beliefs in specific conspiracy theories, which are often strongly related to unique contexts (Bruder et al., 2013; Swami et al., 2016; see also Lazarević et al., 2020). In a dynamically changing pandemic situation, more fixed cognitive predispositions that include conspiracy mentality may have been more important in shaping behaviour than explanations offered by more specific conspiracy theories, which may become less relevant more quickly. In addition, it is important to mention that generalised conspiracy mentality is often perceived as a precursor of various conspiratory beliefs (e.g., Imhoff and Lamberty, 2020; Sutton and Douglas, 2020). There are indications that a generalised conspiracy mentality may also be the basis on which more specific conspiracy theories about COVID-19 grow. In numerous research studies on COVID-19 conspiracy theories, specific theories tended to be correlated, with most people believing more than one of them at a given time (see e.g., Imhoff and Lamberty, 2020; Miller, 2020; van Mulukom et al., 2020). This finding was also the case in the study presented. It is possible that a belief in a given specific conspiracy theory may have significant consequences in a particular time, while the factor that predicts changes in respondents’ behaviours over time is their tendency toward conspiracy thinking.

Additionally, conspiracy mentality was found in studies related to paranoia, another construct characterized by lack of trust and suspecting others of malevolent intentions, but more focused on the sense of individual threat (Barron et al., 2014; Darwin et al., 2011; Swami et al., 2016). In some studies, done in the context of COVID-19, paranoia-like beliefs were also associated with less adherence to medical guidelines (e.g., Kowalski et al., 2020; Larsen, Donaldson, Mohanty, 2020), and these beliefs may overlap more with a more general conspiracy mentality than with specific conspiracy theories.

The role of the threat of authoritarianism in predicting preventive behaviour can also be attributed to the salience of this issue during the whole time of measurement. Together with the conspiracy mentality, the threat of authoritarianism was the only conspiracy-related variable for which support remained above 70% in all four waves. Over the past year, the discourse around pandemic restrictions in Poland has focused on the compatibility of the introduced changes with the rule of law (e.g., Civic Development Forum, 2020); thus, the threat of authoritarianism could shape ‘defiance’ against government's recommendations to a greater extent than other conspiratory beliefs. Notably, the questions about authoritarianism differed from the other questions about conspiratorial beliefs as we directly asked about the personal attitude towards the given issue: e.g., ‘I fear that the government uses the pandemic to … ’ compared with asking about a mere opinion, e.g., ‘Coronavirus does not exist’. Presumably, this way of question formulation is more accurate in capturing the real meaning attributed by individuals to a particular issue. Future research on the societal consequences of conspiracy theories should consider the extent to which individuals are concerned by the subjectively perceived truth of a given conspiracy.

4.1. Association between content of conspiracy theories and preventive behaviour at the cross-sectional level

Although we focused on examining longitudinal associations between variables, to compare our results with studies on conspiracy theories during pandemics, it is also worth conducting a cross-sectional analysis. The correlations at the level of separate waves of measurement indicate that not every conspiracy theory was related to an unwillingness to follow the official pro-health guidelines (see correlation matrix in the online supplement), similar to studies on the relevance of conspiracy theory content (see Imhoff and Lamberty, 2020; Oleksy et al., 2020). Notably, longitudinal measurement enabled us to test this association at different times during the pandemic, showing the potential role of not only the content of the conspiracy theory but also of the current context.

The belief that the coronavirus does not exist correlated with a reduced tendency towards healthy behaviour at every time point measured. A similar association was observed in the case of a general conspiracy theory on COVID-19, assuming that the pandemic is used by unidentified groups to reach their hidden goals. This type of theory correlated negatively with preventive behaviour at T2, T3, and T4. Both the hoax and general COVID-19 conspiracy theories fit in with thinking about the COVID-19 outbreak as a ‘plandemic’ – a conspiracy of elites using the virus and a potential vaccine to gain power. In turn, the belief that the government conceals the real number of COVID-19 cases correlated positively with preventive behaviour, consistent with the prediction that this type of conspiracy theory points to COVID-19 as a real threat to health and life. This correlation was observed only in the first two and fourth points of measurement. In contrast to Imhoff and Lamberty (2020), the association between endorsing ‘COVID-19 as a weapon’ theory was not related to preventive behaviour at any level of measurement. One possibility is that our study was conducted at a later stage of the pandemic, when ‘weapon’ theory may be considered less likely (and therefore, meaningful) than at the beginning of the outbreak. The threat of authoritarianism and conspiracy mentality was weakly correlated with the tendency to preventive behaviour only at the beginning of the pandemic.

4.2. Limitations

This study has some limitations. First, the survey, although a longitudinal representative survey, was limited to only one country. Nevertheless, other studies (e.g., Imhoff and Lamberty, 2020) have stated that the conspiracy theories mentioned in the article are among the most common in other countries as well. In addition, the evolution of the pandemic in most European countries has been relatively similar, from high uncertainty and sudden restrictions at the beginning to the gradual easing of restrictions and the formation of the so-called new normal in subsequent months. However, in some countries (e.g., Italy and Spain), Wave 1 of COVID-19 had a more severe impact on the population than in others (e.g., Poland). Thus, our conclusions may be generalisable, but it is worth comparing them with reports from other countries.

For the same reason, our results for the prevalence of a belief in conspiracy theories may be more representative of countries with a similar political situation than Poland. Our results show that the proportion of people agreeing with some conspiracy theories was high (although it must be considered that we classified participants as agreeing with a given theory if their score was above the middle of the response scale. For this reason, there are more or less extreme people among them). One factor that helps explain the popularity of conspiracy theories in a given country is whether it is governed by populist vs non-populist parties. Given the fact that a belief in conspiracy theories and populist ideology are often linked (Plenta, 2020; Silva, Vegetti and Littvay, 2017; van Prooijen et al., 2018), it could be argued that the prevalence of conspiracy theories may be proportional to the percentage of voters of populist parties. The association between populism and conspiracy beliefs was also confirmed in the context of believing in COVID-19-related conspiracy theories (Stecula and Pickup, 2021). Thus, the high degree of agreement with various conspiracy theories in Poland may be related to the fact that the current ruling, right-wing populist party Law and Justice still has the highest, though steadily declining, support among all Polish political parties. In addition, the popularity of conspiracy theories may be also related to the degree of political polarisation as conspiracy theories affect ideological intergroup dynamics by postulating radical opinions about sides in a political dispute (Sutton and Douglas, 2020). Although populist voters are still in the majority, Poland now seems to be a country with very strong political polarisation (Tworzecki, 2019), which can be evidenced, for example, by the outcome of the last presidential election in which the opposition candidate lost by a small number of votes to the candidate of the ruling party. The high political polarisation in Poland may explain why opponents of the current government may fear that the consequence of the government's anti-pandemic actions would be the introduction of an authoritarian system. It is worth comparing our results regarding the popularity of conspiracy theories with results from countries with a different political configuration.

In our study, we did not consider the very beginning of the pandemic. Oleksy et al. (2020) reported that the content of the endorsed conspiracy theory was essential for preventive behaviours even at the beginning of the outbreak. Also, in the case of measuring specific conspiracy beliefs, we used single-item measures, which may limit their predictive value. This limitation was caused by the unprecedented pandemic situation and no existing tools to measure COVID-19-related beliefs. Future research should include validated multi-item measures. Additionally, participants who completed all four waves had significantly lower levels of beliefs in any type of conspiracy theory. This finding suggests that people who believe in different types of conspiracy theories may be more reluctant to participate in research studies or may be suspicious of the consequences of participating in the research. Nevertheless, we demonstrated that when demographic variables were included in the model, the impact of conspiracy beliefs on attrition was reduced.

5. Conclusions

Few studies on the societal implications of conspiracy theories have considered longitudinal analyses. Our research demonstrates the importance of using advanced statistical methods, such as RI-CLPM, to gain a better understanding of the role conspiracy theories play in shaping negative attitudes and behaviours in society. Our results showed that the association between various conspiracy-related variables and anti-pandemic COVID-19 variables differs at within- and between-person levels. Specific conspiracy beliefs, which were significantly related to preventive behaviour at the cross-sectional level, did not predict within-person changes in such behaviours throughout the pandemic. Instead, wave-to-wave changes in the adherence to pro-health measures were negatively predicted by conspiracy mentality and a feeling of threat that the solutions introduced by the government may limit civil rights.

Credit author statement

Tomasz Oleksy (Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Visualization; Writing – original draft; Writing – review & editing), Anna Wnuk (Conceptualization; Formal analysis; Investigation; Methodology; Writing – original draft; Writing – review & editing), Małgorzata Gambin (Investigation; Methodology; Writing – original draft; Writing – review & editing), Agnieszka Łyś; (Investigation; Methodology; Writing – original draft; Writing – review & editing).

Acknowledgements

The research and the publication is financed by the funds from the Faculty of Psychology at the University of Warsaw awarded by the Polish Ministry of Science and Higher Education in the form of a subvention for maintaining and developing research potential in 2020.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.socscimed.2021.114028.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

Multimedia component 1
mmc1.docx (66.8KB, docx)

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