What Explains the Belief in Conspiracy Theories? Composite Concepts as a New Approach to Studying Conspiracy Theories

What Explains the Belief in Conspiracy Theories? 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Composite Concepts as a New Approach to Studying Conspiracy Theories Matouš Pilnáček, Paulína Tabery, Marie Heřmanová, Josef Šlerka, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5682677/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Belief in conspiracy theories (BCT) negatively impacts various aspects of personal and public life, making it a significant subject of research. Previous studies, spanning multiple disciplines, have been predominantly empirical, resulting in considerable fragmentation in both analyses and theoretical foundations. Our paper seeks to systematize research on BCT by introducing a socio-epistemic model (SoEM) and empirically developing this theoretical framework using composite concepts. We introduce three composite concepts: macro-social adhesion, pseudoscientific spirituality, and media consumption orientation, each formed by combining two standard concepts. This approach enhances the analysis of interactions between concepts and nonlinear relationships. Using cross-sectional data from the Czech Republic (N = 3,880), we develop an extended socio-epistemic model (ESoEM) and demonstrate that BCT is significantly explained by a composite concept of institutional trust and anomie, which we term macro-social adhesion. Social science/Sociology Social science/Psychology Social science/Cultural and media studies conspiracy theories trust anomie media consumption Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The prevalence of conspiracy theories in contemporary society has led to a significant increase in research activity within this field over the past decade. The potential negative impact of conspiracy theories on various aspects of society (Bowes et al., 2023; Stasielowicz, 2022; Uscinski et al., 2022), including social, political, and personal domains, has prompted a rigorous examination of these beliefs. The COVID-19 pandemic has further elevated the prominence of this issue within both academic discourse and public debate (Mahl et al., 2023; Mulukom et al., 2022). The content, dissemination, prevalence, and impact of conspiracy theories have been the subject of study in a variety of academic fields, including the social sciences, arts and humanities, law, medicine, and information science (Mahl et al., 2023). Furthermore, it is a field that is highly multidisciplinary and interdisciplinary, as well as one dominated by empirical studies (Mahl et al., 2023). The development of coherent theoretical frameworks that describe the relationship between belief in conspiracy theories (BCT) and a broader set of psychological and social concepts is an ongoing challenge. These frameworks would potentially connect findings from psychology, sociology and other domains of social science into a coherent framework that would enable a comprehensive understanding of the phenomenon. However, they remain underdeveloped and are seldom used (Brandenstein, 2022; Douglas & Sutton, 2023; Mahl et al., 2023; Pilch et al., 2023; van Prooijen & Douglas, 2018). While a large number of expected correlates have been investigated (Biddlestone et al., 2025; Bowes et al., 2023; Mulukom et al., 2022; Stasielowicz, 2022; Uscinski et al., 2022), their categorization in meta-studies tends to vary widely (Bowes et al., 2023; Mulukom et al., 2022). Furthermore, the selection of these correlates across studies is not systematic. The present article responds to long-standing theoretical fragmentation in the study of conspiracy theories by proposing an integrative framework that enables the systematic organization of key correlates. Rather than starting from a single dominant theory, we draw on a diverse body of scholarship, particularly cultural and epistemic approaches, to conceptualize conspiracy theories as alternative interpretations of social reality. This discussion provides the foundation for our adoption of the socio-epistemic model (SoEM), which we expand into the extended socio-epistemic model (ESoEM). The model distinguishes between individual-level and socio-epistemic factors and introduces three composite concepts. The proposed model is empirically explored using cross-sectional survey data from the Czech Republic. A definition of the term 'conspiracy theory' In our study, conspiracy theories are defined as complex explanations comprising a series of statements that interpret social events as the result of secret, malicious activities carried out by a group of people (Birchall, 2006), which is the definition agreed upon by most authors and approaches. However, as Douglas and Sutton (2023) have noted, a more detailed definition of conspiracy theories could facilitate the creation of theoretical models and the systematization of empirical knowledge, a necessity that is increasingly apparent. They offer a more detailed definition of conspiracy theories, adding further characteristics to the aforementioned definition. Firstly, conspiracy theories contradict the official explanation of events. Secondly, they contain elements of malice. Thirdly, they attribute actions to specific individuals or groups rather than to systems or structures. Fourthly, they have an epistemic dimension while being 'epistemically risky'; that is to say, their explanations are improbable. Furthermore, these explanations are social constructs that not only interpret but also create social reality. Conspiracy theories are also characterized by publicness, i.e. a matter of public interest of which the public should be aware (ibid. 2023, p. 282). Another distinguishing characteristic of conspiracy theories is that they generate knowledge (Birchall, 2006; Douglas & Sutton, 2023; Harambam & Aupers, 2015). The extent to which conspiracy theories are successful in this regard is determined by various individual and social factors, which have been extensively studied in recent years. Consequently, in the search for a theoretical model to explain BCT, we sought one that would encompass the production of knowledge and relate it to various characteristics, particularly social ones, given that one of the characteristics of conspiracy theories is their public nature. Theoretical framework The manner in which conspiracy theories have been examined has evolved over time; however, since its inception, two fundamental approaches have been identified. Firstly, a pathologizing approach is employed, with a focus on irrationality and individual and psychological characteristics. Secondly, a cultural and social practices approach (Butter & Knight, 2018). Popper (1972) was the first to characterize 'conspiracy theory of society' as a simplistic and untrue interpretation of the complexity of social events. In the subsequent period, a pathologizing approach prevailed, with individual characteristics such as paranoia, suspiciousness, fear, and feelings of alienation being examined, as well as negative social impacts such as attitudes toward political extremism and undemocratic attitudes. This pathologizing approach has been challenged in recent decades, with the development of cultural approaches (Butter & Knight, 2018) in the fields of analytical philosophy, cultural studies, sociology and social anthropology. This growing body of research focuses on the everyday practices and personal engagement of individuals with conspiracy theories, as well as the theories' social and cultural contexts. It considers conspiracy theories to be an alternative form of knowledge production, in relation to what the actors consider to be mainstream science and institutionalized explanations of the world. Inspired by the term 'conspiracy milieu', coined by (Harambam & Aupers, 2015) to represent the complex social, cultural, and economic relations that conspiracy believers find themselves in, this research strand emphasizes the practical obstacles to establishing definitions and the epistemological impossibility of relating conspiracy theories to established notions of 'truth' or 'reality'. Waisbord (2018) argues with respect to the term 'post-truth', favored by many researchers and a large portion of the media following the 2016 US presidential election, the notions of truth, and consequently post-truth (and related terms such as 'fake news' and 'misinformation'), are always normative. Similarly, Knight and Tsoukas (2019) observe that 'there is no intrinsically accurate language in terms of which to refer to reality' (p. 183). To overcome the issues of inherent normativity and hierarchy in conspiracy theory research, and to avoid pathologization, many authors turn to ethnography and qualitative research methods. These methods allow them to explore the everyday role of conspiracy theories for those who interact with them, and the meaning-making practices constructed around them (Forberg, 2022; Harambam, 2020). For example, Marwick and Partin (2022) propose the notion of 'populist expertise' based on their research inside QAnon-related online communities. They define this as 'the rejection of legacy media accounts, scientific consensus, or elite knowledge in favor of a body of "home-grown" forms of expertise and meaning-making generated by those who may feel disenfranchised from mainstream political participation' (p. 2535). The aforementioned works focus primarily on online communities and rely on qualitative and theoretical research. The present article builds upon these earlier works by employing quantitative research methods and taking into account cultural approaches to conspiracy theories, which treat them as interpretative frameworks. In line with this perspective, conspiracy theories do not exist in isolation but become embedded in a broader, complex socio-epistemic system for interpreting social reality. Based on this understanding, we distinguish between variables that structure the interpretative framework and variables that shape individual predispositions toward adopting conspiracy beliefs. This distinction deviates from the commonly used tripartite classification of existential, epistemic, and social needs (Biddlestone et al., 2025; Douglas et al., 2019). Instead, the focus is on the interconnection of socio-epistemic variables, which, in contrast to individual characteristics, exhibit strong reciprocal reinforcement with BCT. Collectively, these variables form a system of meaning-making. We also argue that, within such a system, many concepts are strongly interconnected through feedback loops. Therefore, we propose merging theoretically related concepts that also exhibit strong empirical relationships into composite concepts. This approach yields a model that is conceptually clearer and analytically more coherent. The creation of composite concepts is also motivated by additional factors. Since studies on BCT usually include a substantial number of correlates, there is a compelling imperative to streamline theoretical models (Healy, 2017) and an analytical necessity to explore interactions and nonlinear relationships within BCT research (Brandenstein, 2022; Sutton & Douglas, 2022). These interactions and nonlinearities have already been the subject of some empirical studies, the results of which have confirmed their existence and importance (Brandenstein, 2022; Jasinskaja-Lahti & Jetten, 2019; Mari et al., 2022). Without limiting the number of variables using composite variables, it is necessary to use machine learning techniques (Brandenstein, 2022; Enders et al., 2023). However, this does not address the requisite streamlining of the theoretical models. Extended socio-epistemic model To address this conceptual framework explicitly, we employ a socio-epistemic model (Pierre 2020, SoEM), which comprises two components: epistemic mistrust and misinformation processing. Mistrust represents a pivotal element in this context, as a deficiency in trust gives rise to an epistemic vacuum that is subsequently occupied by non-authoritative information. Those who distrust the system cease to accept the official interpretation of social events and instead seek alternative explanations. In accordance with the theoretical approaches previously delineated, the SoEM conceptualizes belief in conspiracy theories (BCT) as a re-establishment of the interpretation of social reality. While our approach builds on Pierre’s core insight—that epistemic mistrust leads to the re-establishing of the interpretation of social reality—it introduces two key modifications informed by the preceding theoretical discussion. These adjustments underpin the development of the extended socio-epistemic model (ESoEM), which is illustrated in Figure 1. [FIGURE 1 ABOUT HERE] Firstly, Pierre (2020) proposes several concepts that could influence epistemic mistrust, information processing, and consequently, BCT. However, a significant number of other concepts have been subjected to rigorous examination in numerous studies over recent years. Some of these have been found to exhibit a robust and consistent relationship with BCT, whereas others have demonstrated either a weaker or no association. In general, both personality predispositions to believe in conspiracy theories and the social conditions in which individuals live are examined. The majority of studies concur that strong correlates include, but are not limited to, trust in institutions, science, socio-political control (Brandenstein, 2022), anomie (Biddlestone et al., 2025; Enders et al., 2023), spirituality (Mulukom et al., 2022) dangerous worldviews (Biddlestone et al., 2025), media consumption from specific sources (Strömbäck et al., 2023), and analytical thinking (Gligorić et al., 2021; Pennycook & Rand, 2019). Consequently, we decided to augment Pierre's model by incorporating concepts that, as substantiated by extant literature, exhibit a robust and systematic relation with BCT. These concepts facilitate a more thorough elaboration of the social context of the model. This context is shaped not only by mistrust but also by the related concept of anomie. The social context is also formed by the overall epistemological and interpretative framework, which includes spirituality, pseudoscientific beliefs, and media consumption. With respect to individual characteristics, the study incorporated those that exhibited a strong and systematic relationship with BCT, in addition to characteristics associated with information processing, such as information literacy and cognitive reflection. The ESoEM thus includes the following socio-epsitemic characteristics: institutional trust, operationalized as trust in political institutions (Brandenstein, 2022); mainstream media and scientists (Brandenstein, 2022); anomie (Moulding et al., 2016; Robinson et al., 1991; Srole, 1956); eco-awareness spirituality (Delaney, 2005; Gligorić et al., 2021); pseudoscientific beliefs (Fasce et al., 2021; Stasielowicz, 2022) and consumption of different types of media and information sources (Strömbäck et al., 2023). Additionally, we consider as individual characteristcs, the personal need for structure (Axt et al., 2021; Stehlík, 2017), anxiety (Leibovitz et al., 2021; Spitzer et al., 2006), information literacy (Boh Podgornik et al., 2016; Jones-Jang et al., 2021), and cognitive reflection (Frederick, 2005; Pennycook & Rand, 2019; Stehlík, 2017). As control variables, we also include standard sociodemographic variables. Secondly, Pierre's model is not only extended by new variables, but also by composite concepts, namely macro concepts comprising pre-existing concepts. In our study, we have devised three such concepts: macro-social adhesion (MSA), pseudoscientific spirituality (PS), and media consumption orientation (MCO). Macro-social adhesion (MSA) is comprised of two widely used concepts: institutional trust and anomie. Trust is a pivotal concept within the SoEM framework and the strong relationship between institutional trust and BCT is substantiated by a multitude of empirical studies (Brandenstein, 2022; Mulukom et al., 2022). However, the model employs the term 'epistemic mistrust', thereby raising the question of whether institutional trust, as measured by trust in political institutions, public service media, and scientists, effectively captures the epistemic dimension. These institutions can be regarded as mainstream epistemic authorities within the BCT study, whereby trust in a given institution also encompasses trust in its interpretation of the world. The concept of epistemic authority is characterized by its dualistic nature, encompassing both expertise and trustworthiness (Bartsch et al., 2025). Pierre (2020, p. 620) defines epistemic mistrust as “mistrust of knowledge or, framed within its proper socio-cultural context, mistrust of authoritative informational accounts.” He also acknowledges the dual nature of trust, as trust in information hinges on the perceived expertise and trustworthiness of the source. According to Pierre (2020, p. 626), "trust serves as a 'heuristic for competence,'" so assessing expertise and credibility are often one and the same. However, distrust of institutions plays a role in BCT not only because of the rejection of official interpretations of events but also because of the suspicion of malevolent intentions on the part of institutional representatives (and this attitude is an integral part of BCT). The second strongly corroborated correlate of conspiracy theories is anomie (Biddlestone et al., 2025), a classical sociological concept. Durkheim's (2002 [1897]) seminal definition of anomie posits that significant changes in the social order, whether positive or negative, can lead to the breakdown of social norms, thereby weakening the bonds within society. In defining anomie, Merton focused on the discrepancy between the desirable goals set by society and the impossibility of achieving them by legitimate means (1938). This phenomenon gives rise to various strategies of response to the prevailing system and society, which may include rebellion or retreatism. Alternatively, as specified by Srole (1956), it is a loss of attachment to society. Institutional trust and anomie are two distinct concepts, but they are related. For example, Bornand and Klein (2022) demonstrate that anomie can be conceptualized as a predictor of trust and as a mediating variable between socioeconomic status and trust. Trust and anomie can be seen as complementary concepts because anomie captures a broader perspective of society and a view of norms and alienation, while institutional trust refers to key legitimate and epistemic authorities in society. The composite concept of MSA thus represents both individual and general levels of attachment to society. For the wording and frequency of the questions measuring MSA, see Supplementary Material in Section 1 Tables 5 and 6. Pseudoscientific spirituality (PS) represents a synthesis of two distinct concepts: spirituality and pseudoscientific beliefs. Both of these concepts are strongly and robustly associated with BCT (Gligorić et al., 2021; Mulukom et al., 2022; Stasielowicz, 2022). Pseudoscientific beliefs can be defined as epistemic errors that mimic science. They either take the form of promoting pseudoscience or rejecting science (Fasce et al. 2021).The relationship between spirituality and pseudoscientific beliefs has been extensively investigated, particularly in qualitative research, to the extent that the term “conspirituality” has been directly referenced in the literature (Ward & Voas, 2011). The term conspirituality emphasizes the common aspects of conspiracy thinking and New Age-type spirituality, including a focus on enlightenment (and the subsequent ability to “see the truth”), holistic thinking, and a belief in a paradigm shift in human consciousness, as well as the narrative that a hidden group of elites is attempting to prevent this shift. This type of spirituality is therefore closely aligned with pseudoscientific beliefs. Concurrently, it is also measured in quantitative research under the designation of eco-awareness spirituality, which pertains to a conviction in a higher power and the capacity to draw upon inner strength (Mulukom et al., 2022). For the wording and frequency of questions measuring PS, see Supplementary Material in Section 1 Table 3. Media consumption orientation (MCO) is a measure of media consumption on a continuum that contrasts mainstream media consumption with alternative media consumption. The consumption of media is a multifaceted phenomenon, and the index is designed to quantify this complexity by subtracting the two types of orientation. Consequently, respondents who consume both types of media in equal measure are situated at the midpoint of the continuum. The majority of research on conspiracy theories has focused on social media (Cinelli et al., 2022), with relatively little attention paid to the role of other types of media. Nevertheless, studies that incorporate sources of information beyond social media have demonstrated that the consumption of mainstream or alternative media is a significant factor in the acceptance of conspiracy theories (Strömbäck et al., 2023) or misinformation (Mont’Alverne et al., 2023). The combination of these two orientations into a composite concept allows for a closer alignment with the concept of a mainstream–alternative spectrum, which is a key analytical tool in the study of alternative media more broadly (Steppat et al., 2023). The index is constructed on the basis of survey questions pertaining to the consumption of different types of information sources. The types of sources are classified as alternative or mainstream in accordance with the particular characteristics of the media landscape in the Czech Republic (Štětka et al., 2021). In this instance, it is not assumed that the theoretical division into alternative and mainstream media results in a clear two-factor structure. Consequently, a theoretically based index is employed in lieu of a scale. For the wording and frequency of questions measuring MCO, see Section 1 in Supplementary Material Table 4. In this study, we employ Pierre's model as a foundational framework for the examination of BCT. However, we have not tested the process of creating and filling the epistemic vacuum directly. Instead, we propose an extended socio-epistemic model (ESoEM) with the following characteristics: (1) the distinction between two groups of variables—individual characteristics and the socio-epistemic system; (2) the construction of composite concepts within the socio-epistemic system; and (3) the assumption of a latent dynamic process involving the re-establishment of the interpretation of social reality, which underlies and structures the relationships among the manifest composite concepts. The objective of our research is to investigate the proposed composite concepts, their relationship with BCT, their interactions, and the implications of these findings for the further development of ESoEM. RQ1: Is it empirically justifiable to combine the individual correlates into composite concepts, as we have proposed? RQ2: To what extent do composite concepts explain BCT when controlling for other concepts and sociodemographic variables? RQ3: How do composite concepts interact with each other when explaining BCT? For this purpose, we use representative cross-sectional data from a survey conducted in the Czech Republic (N = 3,880). Methods The materials, anonymized data, and analysis code are available at https://osf.io/rj825/?view_only=53a4d90f18504758acc34e858be0c9c3. Sample The sample was obtained through the administration of a questionnaire survey to an online opt-in panel. The cross-sectional survey is a quota sample representative of the Czech population aged 18–65 with internet access (N = 3,880). The quota variables are defined by gender, age, level of education, region, and size of municipality. Table 1 in the Supplementary Material in Section 2 provides a summary of the quota variables and the extent to which they deviate from the population. The data were collected between March 14, 2023, and April 15, 2023. Informed consent was obtained through online confirmation by the participant. The Czech context The Czech Republic is a standard European liberal democracy (Nord et al., 2024) and ranks relatively high in the Reporters Without Borders Press Freedom Index (RSF, 2024). Additionally, Czech public service media restrain from amplifying conspiracy theories, unlike public service media in other Central and Eastern European countries (Štětka & Mihelj, 2024; Urbániková & Smejkal, 2023). Nevertheless, the specific media and political configuration in the Czech Republic provides important context for the division between conspiracy theories as alternative explanations of social reality and mainstream explanations provided by institutional authorities. A significant portion of commercial media outlets and tabloids maintained ties to political actors and oligarchs at the time of data collection, most notably former Prime Minister and leader of the populist ANO party, Andrej Babiš (Štětka & Mihelj, 2024). Although the 2021 parliamentary elections appeared to slow the momentum of anti-system sentiment, an ecosystem providing fertile ground for the spread of conspiracy theories remains active. This includes a network of disinformation websites that disseminate conspiratorial, pro-Russian, and anti-establishment content (Štětka et al., 2021; Štětka & Mihelj, 2024). Some of these conspiracy outlets sided with Babiš on specific issues, further complicating the boundary between institutional and alternative framings (Syrovátka, 2023). This dual configuration - of formal institutional stability and informal erosion of epistemic authorities makes the Czech Republic an appropriate setting for a case study to investigate ESoEM. The Czech Republic is also a noteworthy case study in terms of the overlaps between religious beliefs, pseudo-science beliefs and BCT. While the link between participating in various forms of institutionalized religion and BCT has been extensively researched (see for example Robertson, 2024), the Czech Republic consistently ranks among the least religious countries worldwide (Furstova et al., 2021). Although the Czech Republic is a specific country in this respect, there are numerous and diverse forms of non-institutionalized alternative spirituality beliefs present in Czech society (Kapusta & Kostićová, 2021). This makes it a fertile ground for researching the links between non-institutionalized spirituality, pseudo-scientific beliefs and BCT. The development, validation, and computation of the BCT scale BCT represents the dependent variable in our study. There are two principal methods of measuring it: 1) by the conspiracy thinking scale or 2) by the set of statements representing the narratives that make up conspiracy theories. We have selected to examine BCT using individual statements representing conspiracy theories. A significant challenge in our selected method of measuring BCT is the process of selecting appropriate statements. The statements representing the conspiracy theories utilized in this study were developed through a quantitative content analysis of Czech conspiracy and disinformation websites, resulting in the identification of four key thematic clusters. Consequently, the selection of statements is grounded in empirical evidence, aiming to assess theories that are currently accessible to Czech audiences, namely content that respondents may encounter in their daily interactions, social media, and online platforms. To ensure that the thematic selection of conspiracy theories clusters was not unduly influenced by the prevalence of COVID-19 pandemic topics, the analysis was based on a content analysis of 21 Czech conspiracy and disinformation websites from 2019. The disinformation and conspiracy websites were selected from a list maintained by the Foundation for Independent Journalism, a resource that has also been utilized in other academic research (Štětka et al., 2021). The last 30 articles from each website were downloaded and coded into categories that reflected the categorization from the book Conspiracy & Populism (Bergmann, 2018). Two additional categories were added to this existing categorization: specifically, Czech conspiracies and pro-Kremlin conspiracies. Exploratory analysis using hierarchical cluster analysis revealed that the theories could be grouped into four thematic clusters: 1. Health and history. This cluster of stories focusing on health issues, alternative healing theories, and reinterpretations of historical events may reflect a common interest in “alternative truths” about the body and the past, leading to a rejection of official explanations and a trust in “hidden” factors affecting health and history. This includes popular historical conspiracies, such as the murder of Princess Diana. 2. Cultural threats to European civilization and migration. This cluster includes theories that focus on culture and demography, often with a belief in a deliberate plan to replace European populations with migrations from non-European countries. Fears of “the great replacement” or “white genocide” are common in these theories, reflecting fears of loss of cultural identity. 3. New World Order. This cluster combines various aspects of New World Order theories, which include ideas of supranational, often secret, forces conspiring to take control of the world. These ideas may include theories of global elites and shadow governments, and may overlap with other conspiratorial motives. 4. Pro-Russian and specific Czech statements. This cluster is specific in that it contains theories and interpretations directly related to the Czech socio-political context and current events, such as the Russian invasion of Ukraine. These theories may include views influenced by Russian propaganda or specific domestic political theories related to national interests and perceptions of international politics. Further details regarding the content analysis can be found in the Supplementary Material, specifically in Section 9. Based on the aforementioned clusters, 20 statements were selected, encompassing all four clusters (for the wording of the conspiracy statements, see Supplementary Material Section 1 Table 2). The selected statements exhibited a range of levels of difficulty and degrees of specificity. The selection of statements was based on the thematic analysis of 27 conspiracy websites, once more from the Foundation for Independent Journalism list, with the inclusion of statements pertaining to current events such as the invasion of Ukraine. In order to avoid the potential for respondents to guess the correct answer (Altay et al., 2023), an explicit “don’t know” option was provided. Additionally, four mainstream statements were included among the conspiracy theories for control purposes. In each case, the respondents were first asked to indicate their level of agreement or disagreement with the statement in question. They were then asked whether they had noticed such statements. The present study focuses exclusively on the level of agreement with the statements included in the BCT scale. In order to test the validity of the BCT scale, the dataset was randomly divided into two parts, which were then subjected to exploratory and confirmatory factor analysis, respectively. In exploratory factor analysis (EFA), the number of factors is determined using optimal parallel analysis (Timmerman & Lorenzo-Seva, 2011) with polychoric correlations. Subsequently, a standard EFA is conducted with oblique oblimin rotation, and McDonald’s omega is calculated to assess the reliability of the scale. The structure of the scale was confirmed by means of a confirmatory factor analysis (CFA) on the second half of the split dataset, employing the WLSMW method. All calculations were conducted (a) for complete observations and (b) with imputed missing values instead of “don’t know” responses. In addition to the original scale, a reduced scale comprising only those statements directly related to the secret plot was employed. The aforementioned methodology was employed to assess the scale. The Pearson correlation between the reduced and unreduced scales of conspiracy theories scales was 0.98, indicating a high degree of correlation between the two sets of data and suggesting that the phenomenon being measured is essentially the same. A second survey was conducted (CAPI, N = 913), in which the conspiracy theories scale was again administered. In the supplementary survey, the conspiracy mentality scale (Bruder et al., 2013) was also administered, which exhibited a Pearson correlation coefficient of 0.57 with the BCT scale. These results imply that the scales assess closely related yet distinct concepts. For detailed results, see Section 7 of the Supplementary Material. Validation and calculation of composite concept scales The concepts of MSA and PS are both constituted by two of the more common concepts. To test the validity of the composite concepts, an identical procedure was employed as that used for the BCT scale. The dataset was randomly divided into two portions for the purposes of EFA and CFA. The optimal number of factors in the exploratory factor analysis (EFA) was determined using parallel analysis with polychoric correlations (Timmerman & Lorenzo-Seva, 2011). The factor structure was examined using EFA with oblique oblimin rotation, and reliability was calculated using McDonald’s omega. The other half of the data was subjected to CFA using the WLSMW method. Given that both composite concepts comprised a mere two factors, an equal loading condition was established for both factors. With regard to MSA, the trust factor was further structured into three sub-factors in accordance with the thematic focus (media, politics, scientists). A graph of the factor structure of MSA is provided in Figure 1 in the Supplementary Material Section 1. All calculations were conducted (a) for complete observations and (b) with imputed missing values instead of “don’t know” responses. For detailed results, see Sections 4 and 6 of the Supplementary Material. In order to evaluate the number of dimensions for MCO, optimal parallel analysis was also employed (Timmerman & Lorenzo-Seva, 2011). In this case, the results indicate the presence of a one-to-three factor solution with respect to the confidence interval. However, none of the solutions derived from EFA align with the conceptualization of the division between mainstream and alternative media observed in the Czech media environment. Consequently, the items were categorized as either alternative or mainstream media in accordance with the extant literature (Štětka et al., 2021). It is therefore evident that MCO is not a standard psychometric scale but, rather, a theoretically constructed index. For a detailed account of the results, see Section 5 of the Supplementary Material. Standard measures A shortened version of the Personal Need for Structure Scale (PNSS) (Neuberg & Newsom, 1993) was employed, based on the results of the validation study conducted in the Czech Republic (Stehlík, 2017). The cognitive reflection test is based on the original version(Frederick, 2005) and its subsequent extensions (Primi et al., 2015; Toplak et al., 2014). The selection of items was based on the validity test in the Czech setting (Stehlík, 2017). Anxiety was measured using the standard GAD-7 scale (Spitzer et al., 2006), and information literacy was measured using a previously developed shortened scale (Jones-Jang et al., 2021) derived from the original information literacy test (Boh Podgornik et al., 2016). McDonald’s omega was calculated for all these scales, and unidimensionality was confirmed by CFA using the WLSMW method. For detailed results, see Section 3 of the Supplementary Material. Table 1 | Overview of all used variables. Variable McDonald’s omega Robust CFI Robust RMSEA Number of items Number of dimensions Dependent variable Belief in conspiracy theories 0.95 0.985 0.046 20 1 Standard concepts Personal need for structure 0.84 0.986 0.052 6 1 Anxiety 0.94 0.998 0.018 7 1 Information literacy 0.75 0.973 0.047 5 1 Cognitive reflection test 0.86 0.997 0.037 4 1 Composite concepts Macro-social adhesion 0.94 0.987 0.046 18 2 Pseudoscientific spirituality 0.96 0.986 0.051 20 2 Media consumption orientation - - - 10 - Socio-demographic variables Education - - - 1 - Age - - - 1 - Gender - - - 1 - Size of municipality - - - 1 - Net personal income - - - 1 - Computation and normalization of measures Scale scores were calculated as the mean of responses to all items. In the case of one-dimensional scales, respondents who did not respond to more than half of the items were excluded from the analysis. For multidimensional scales, respondents who did not respond to more than half of the items in all subscales were excluded from the analysis. All variables were normalized to a range between 0 and 1. Assessment of the strength of the correlates Three measures were used to assess the strength of the relationship with the BCT scale. First, we used Pearson’s correlation coefficient, which measures the strength of the relationship of each correlate separately. In the case of the correlation between gender and the BCT scale, the biserial correlation was used. Second, we adopted a multiple linear regression where all correlates are entered at once (Model 2 in Supplementary Material Section 1 Table 1). B-coefficients are presented, which are comparable due to the normalization of all variables to the range 0–1. The standardized beta coefficients are also presented in Supplementary Material Section 1 Table 1. To provide information on the contribution of composite concepts to the explained variance, a model with only control variables was also estimated (Model 1 in Supplementary Material Section 1 Table 1). Third, the general dominance (Azen & Budescu, 2003) is presented, which expresses the average explained R 2 within all subsets of the regression models. All three measures have bootstrapped confidence intervals that take into account quota sampling (Sturgis et al., 2017) with 2,000 resamples. See Section 8 of the Supplementary Material for detailed results and tests of linear regressions assumptions. Exploring interactions To test for interactions between the composite concepts, we ran two regressions (Model 3 and Model 4 in Supplementary Material Section 1 Table 1). All three possible interactions between composite concepts are included in Model 3. To test whether the interactions were driven by the interaction of other variables, we added terms in Model 4 that were identified using the adaptive LASSO (Beiser-McGrath & Beiser-McGrath, 2020) method at the 99% significance level. Statistical significance was again assessed using bootstrapping to account for quota sampling. We also performed a test for linearity of the interactions (Beiser-McGrath & Beiser-McGrath, 2023). Results As we measured BCT using a set of statements (see Methods for details), it was first necessary to test whether the dependent variable could be considered a scale, using exploratory (EFA) and confirmatory factor analysis (CFA). As a result, conspiracy statements formed a clear one-dimensional scale with very good reliability. We can conclude that there is a latent variable behind the measurement statements and, therefore, they refer to the one phenomenon they measure. The justification for combining the individual correlates into composite concepts was evaluated for all three composite concepts (RQ1). The initial step was to conduct EFA. The two-factor structure observed for macro-social adhesion (MSA) and pseudoscientific spirituality (PS) was consistent with the underlying conceptualization of these constructs. This structure was subsequently confirmed in the CFA, which showed good model fit values (see Table 1). However, in order to obtain good fit values for MSA, it was necessary to split trust into three thematic sub-factors (see Supplementary Material Section 1 Figure 1). Overall, MSA and PS showed clear factor structures and good reliability values, justifying their use as single scales from a psychometric standpoint. The situation was distinct with regard to media consumption orientation (MCO). As anticipated, EFA revealed that MCO did not exhibit a straightforward factor structure. This was predominantly attributable to the impact of media consumption intensity rather than the structure of media consumption itself. Nevertheless, MCO is regarded as a theoretically derived index and can be employed even though it is not a standard scale. The comprehensive results of the factor structure exploration of the composite concepts and the dependent variable are presented in the Supplementary Material Sections 4–6. To find out how the composite concepts relate to BCT (RQ2), we created several models. We first estimated a model in which only control variables (i.e., sociodemographic variables and other expected correlates) were entered (Model 1 in Supplementary Material Section 1 Table 1). This model explains 14% of the variance in the data, and the independent variable with the largest B coefficient is information literacy (B = -0.2). This means that information literacy has the strongest association with BCT in this model, with those who are more information literate less likely to believe in conspiracy theories. In comparison, the model with added composite concepts (Model 2) explains 52% of the variance in the data. Such a high level of explained variance is highly unusual for this type of model (Brandenstein, 2022) and indicates a strong association of the added concepts with BCT. The strength of correlates of Model 2 is summarized in Figure 2. The figure shows in each column (1) Pearson correlations, (2) B coefficients, and (3) general dominance (GD), which reflects additional contributions to explained R 2 of each predictor within all subsets of regression models (Azen & Budescu, 2003). By far the most strongly associated of the three composite concepts with BCT is MSA (r = -0.67, B = -0.7, GD = 0.31). The other two most strongly related variables are MCO (r = 0.41, B = 0.23, GD = 0.07) and PS (r = 0.32, B = 0.23, GD = 0.07)—that is, other composite concepts. These results mean that the higher MSA, the less BCT; the higher the pseudoscientific spirituality, the more BCT. For MCO, if there is a tendency to consume alternative media, there is more BCT. The other correlates explain BCT much less; they are moderately or weakly correlated with BCT and lose most of their substantial association in the regression model. The difference is even more evident in the case of general dominance, where no other variable except the composite concepts exceeds a contribution of 2% of the explained variance. Thus, the studied composite concepts are clearly dominant independent variables compared to the others, indicating their very high interdependence with BCT. Figure 3 in the Supplementary Material Section 1 shows the same analysis of the strength of association of each correlate when the composite concepts are decomposed into pairs of standard correlates. The order of importance of the decomposed correlates in terms of B-coefficients and GD remains the same as for the composite concepts. This result also justifies the validity of merging the correlates into composite concepts and shows that the association with BCT is not realized by only one of its parts. [FIGURE 2 ABOUT HERE] The next step in the analysis was to explore how the composite concepts interact with each other in predicting BCT (RQ3). When using composite concepts, there are only three possible interactions to explore: MSA with PS, MSA with MCO, and PS with MCO. Regression models were used again to test the interactions. All three interactions between composite concepts are included in Model 3 (see Table 1 in the see Supplementary Material Section 1), and two additional terms identified using the adaptive LASSO method are included in Model 4. The only statistically significant interaction in both models is between MSA and MCO. The effect of the interaction between MSA and MCO is shown in Figure 3. At low MSA values, the inclination toward alternative sources of information further increases the already high BCT value. Although the interaction between MSA and PS is statistically significant in Model 3 (p = 0.004), it loses its significance when the terms identified by adaptive LASSO are added. The terms identified by adaptive LASSO are primarily used to check that the interactions under investigation are not an artifact of the influence of other variables (Beiser-McGrath & Beiser-McGrath, 2020). However, they are also of substantive interest as they are additional statistically significant regression terms. The terms identified are the quadratic relationship between PS and BCT (see Figure 4) and the interaction between MSA and age (see Figure 3 in the see Supplementary Material Section 1). In the case of the quadratic relationship between PS and BCT, most of the increase in BCT is realized at higher levels of PS, while the increase is much smaller at lower levels. Regarding the interaction between MSA and age, age is not related to BCT when MSA is high; however, when MSA is low, older people are more likely to believe in conspiracy theories. Detailed results of the regression analysis and assumption tests can be found in Supplementary Material Section 8. [FIGURE 3 ABOUT HERE] [FIGURE 4 ABOUT HERE] Discussion Conspiracy theories are extensively studied, particularly during periods of significant social upheaval, such as migration crises, the COVID-19 pandemic, and shifts in political preferences toward populist or authoritarian parties. Multiple disciplines have examined the tendency to believe in conspiracy theories, resulting in a broad yet theoretically fragmented body of knowledge. It is therefore essential to not only develop theoretical frameworks but also to rigorously test and refine them. In this article, we build upon the socio-epistemic model (SoEM) framework with the aim of providing a thorough explanation of belief in conspiracy theories (BCT) while reducing the number of correlates studied in the models. To accomplish this, we developed and tested composite concepts based on existing correlates. The formation and integration of these concepts into the SoEM is based on the idea that an interpretive framework is a complex system. In such systems, individual entities are characterized by feedback relationships, and emergence can be observed. This implies that larger entities may emerge from the aggregation of smaller original parts (Ladyman et al., 2013 ). In this way, individual correlates, which previously existed in isolation, can be combined into composite concepts based on theoretical assumptions and empirical testing. The utilization of representative survey data from the Czech Republic has demonstrated that the three proposed composite concepts represent a valuable approach for the investigation of BCT. Furthermore, these concepts exhibit a markedly stronger association with BCT in comparison to the other variables included. The model that includes all three composite concepts (Model 2) exhibits an unusually high level of explained variance. First, the most dominant concept, which is most strongly associated with BCT, is macro-social adhesion (MSA). It is not the intention of this study to assume a unidirectional causal relationship between the composite concepts and BCT. Rather, it is proposed that the composite concepts, in conjunction with BCT, constitute a complex system for interpreting social reality. This complex system can be interpreted through the lens of socio-epistemic model (SoEM), which consists of two basic components: epistemic mistrust and information processing. In contrast to SoEM, we extend the concept of epistemic mistrust in traditional authorities to MSA, which includes anomie. Second, in addition to SoEM, we include additional sources for interpreting social reality and information processing, namely pseudoscientific spirituality and media consumption orientation. This substantial extension of the socio-epistemic model (SoEM) is therefore termed the extended socio-epistemic model (ESoEM). The findings of our investigation into the composite concepts that constitute ESoEM are schematically summarized in the black section of Fig. 5 . The association between MSA and BCT is notably robust. The association is strong enough to justify the assertion that MSA is an essential component in explaining BCT. A number of studies have confirmed the strength of the relationship between institutional trust or anomie and BCT (Biddlestone et al., 2025 ; Brandenstein, 2022 ; Mulukom et al., 2022 ). However, to the best of our knowledge, institutional trust and anomie have never been examined in the same study. Our results demonstrate that both components of MSA play an important role in understanding BCT, that they are not mutually substitutable, and that it is justified to combine them into a single composite concept. To some extent, the strength of the association is undoubtedly attributable to the impact of conspiracy theories on MSA, as evidenced by experimental studies examining the influence of conspiracy theories on trust (Invernizzi & Mohamed, 2023 ; Kim & Cao, 2016 ). However, other studies demonstrate that trust in institutions is a remarkably stable phenomenon (Devine & Valgarðsson, 2023 ). Additionally, the roots of distrust in the system are found to originate, at least in part, from early life experiences (Moffitt et al., 2022 ). Furthermore, BCT is influenced by characteristics of the social system, including the level of corruption (Alper, 2023 ). Consequently, a potential strategy for countering the influence of conspiracy theories may lie in a long-term effort to enhance trust in public institutions and foster a sense of attachment to the broader macro-social system (Pierre, 2023 ). The observed interaction between MSA and age is challenging to interpret, as the role of age in this case may be either a consequence of generation or a reflection of the stage of life. With regard to the stage of life rather than generation, it is conceivable that respondents in later life may feel disadvantaged and weakened. An alternative explanation is that the cognitive abilities of older respondents may decline. Nevertheless, cognitive ability is assessed by two additional variables in the model, and the interaction between age and MSA remains statistically significant. No interaction between MSA and either information literacy or the cognitive reflection test was identified. The ESoEM framework permits a second interpretation of this interaction. The interaction between age and MSA could be an effect of time, during which the association between MSA and BCT deepens in a feedback loop. However, this hypothesis would require testing in longitudinal data. It is also possible that this is a situation specific to the country context, and further testing of the model is needed in other countries. The composite concepts of MCO (media consumption orientation) and PS (pseudoscientific spirituality), which serve as sources for interpretation of social reality, exhibit qualitatively distinct relationships with BCT, despite the strength of their linear association being comparable. MCO interact with MSA and reinforce each other in association with BCT. A comparable process has been documented in the context of electoral misinformation (Mont’Alverne et al., 2023 ). It appears that MSA and MCO can engage in a dynamic interplay, which may serve as a basis for changes in the interpretation of social reality. While the association between MSA and BCT is likely to be relatively stable, the relationship with MCO may exhibit greater dynamism. The quadratic relationship between PS and BCT is an intriguing consequence of the investigation into interactions. Lower-level PS is not related to a change in worldview, but higher-level PS is. This outcome suggests the existence of a tipping point at which alternative spirituality could play a larger role in changing the perception of social reality. The observation highlights the importance of addressing the possibility of offering counter-statements to conspiracy theories (Lazić & Žeželj, 2021 ). It would be beneficial to investigate the optimal timing for the dissemination of these counter-statements in future research, as it is plausible that they are more effective when introduced at a time when interpretations of social situations are not yet fully established. The results indicate that cognitive reflection tests, information literacy, anxiety, and sociodemographic variables are moderately correlated with BCT. However, when composite concepts are controlled for, the effect disappears. This does not imply that these variables are irrelevant to BCT; rather, it suggests that they are external to the complex, interrelated system that interprets social reality. Future research could investigate how these external variables influence and condition the gradual formation of the system over time. In addition to ESoEM, there are other theoretical explanations for BCT. The existential threat model (van Prooijen, 2020 ) posits that conspiracy theories emerge and proliferate during periods of crisis, when social events engender a sense of existential threat and prompt a process of sense-making. This aspect is consistent with the ESoEM framework because an unforeseen crisis challenges the MSA and the entire interpretive framework, creating a new situation that requires interpretation. Other theoretical frameworks for explaining BCT include explanations based on evolutionary tendencies to interpret situations conspiratorially (van Prooijen & van Vugt, 2018 ). These explanations are not incompatible with ESoEM. The added value of ESoEM is that it places conspiracy theories in the context of a broader system for interpreting social reality. This allows for the consideration of biological and psychological dispositions as influencing and conditioning factors in the gradual construction of this system. Furthermore, the added value of our theoretical framework compared to these theories is that it can be used to categorize and simplify a larger number of the correlates under investigation. In conclusion, the findings of our study demonstrate that conceptualizing BCT as a constituent part of a comprehensive and intricate system for interpreting reality, simplified by composite concepts, represents a significant and valuable approach. Furthermore, it provides a number of research questions that warrant further investigation in future studies. [FIGURE 5 ABOUT HERE] It is important to acknowledge that this study is subject to several limitations, which may also provide directions for future research. First, it was not feasible to include all the correlates that have been used in previous research on conspiracy theories. To illustrate, narcissism (Stasielowicz, 2022 ), a dangerous worldview (Biddlestone et al., 2025 ), and socio-political control (Brandenstein, 2022 ) are significantly correlated with BCT. Second, the ESoEM approach does not consider the influence of social identity (Van Bavel et al., 2024 ) and intergroup conflict (van Prooijen & Douglas, 2018 ), which may also be integral to a complex system for interpreting social reality. Third, a further avenue for investigation would be to elaborate more theoretically and empirically on MSA. It would be beneficial to examine how the aforementioned variables, which were not included in this study, interact with MSA, as well as to investigate other policy contexts. The concept of MSA encompasses the concept of trust in institutions. Nevertheless, it is not implausible that these very institutions may, in fact, be complicit in the proliferation of conspiracy theories, particularly those of a political nature. Therefore, if institutions disseminate conspiracy theories, it is possible that there may be a positive correlation between high levels of institutional trust and BCT. This indicates that the empirical results may be reversed in different political contexts. It can be concluded that MSA, as proposed in this study, is currently applicable to stable liberal democracies and that further research is required to ascertain its suitability for different political contexts. It is also important to note that the MSA concept includes trust in public service media, which is not a universal phenomenon and may also manifest in various forms across different contexts. While these facts limit the generalizability of our findings, they highlight an important aspect of the social conditioning of BCT. Fourth, some respondents may endorse conspiracy items not because of genuine belief but as a form of political signaling or identity expression (Altay et al., 2023 ). This poses a challenge for interpretation, as the same item endorsement may reflect different underlying motivations across individuals. Finally, it must be acknowledged that this is only a cross-sectional case study, which does not allow for the observation of the dynamics between variables. Further longitudinal and experimental research would therefore be beneficial, as would research in other countries, given that our case concerns only the Czech Republic. Declarations The study was approved by the Ethics Committee of the Institute of Sociology of the Czech Academy of Sciences. Data availability statement Data are available in anonymized version at https://osf.io/rj825/?view_only=53a4d90f18504758acc34e858be0c9c3 Acknowledgements ANONYMIZED Contributions ANONYMIZED conceived the study. ANONYMIZED designed the survey questionnaire. ANONYMIZED analyzed data. ANONYMIZED revised data analysis. ANONYMIZED wrote the manuscript. All authors revised the manuscript. Ethics declarations The research was conducted in accordance with relevant guidelines, namely the ICC/ESOMAR International Code on Market, Opinion and Social Research and Data Analytics , which sets out the standards for a comprehensive framework of self-regulation for those engaged in market, opinion and social research and data analytics. It sets out essential standards of ethical and professional conduct. The research was also conducted in accordance with the standards of SIMAR (Association of Market and Opinion Research Agencies). The data collection was carried out by the SIMAR member agency and compliance with the standards is monitored through regular inspections by the Association. All legal requirements (e.g. GDPR) were also met. Competing interests statement The authors declare no competing interests. Ethical approval The study was approved by the Ethics Committee of ANONYMIZED . Informed consent Informed consent was obtained through online confirmation by the participant. References Alper, S. (2023). There are higher levels of conspiracy beliefs in more corrupt countries. European Journal of Social Psychology , 53 (3), 503–517. https://doi.org/10.1002/ejsp.2919 Altay, S., Berriche, M., & Acerbi, A. (2023). Misinformation on Misinformation: Conceptual and Methodological Challenges. Social Media + Society , 9 (1), 20563051221150412. https://doi.org/10.1177/20563051221150412 Axt, J. R., Landau, M. J., & Kay, A. C. (2021). Fake news attributions as a source of nonspecific structure. In The psychology of fake news: Accepting, sharing, and correcting misinformation (pp. 220–234). Routledge/Taylor & Francis Group. https://doi.org/10.4324/9780429295379-15 Azen, R., & Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. Psychological Methods , 8 (2), 129–148. https://doi.org/10.1037/1082-989X.8.2.129 Bartsch, A., Neuberger, C., Stark, B., Karnowski, V., Maurer, M., Pentzold, C., Quandt, T., Quiring, O., & Schemer, C. (2025). Epistemic authority in the digital public sphere. An integrative conceptual framework and research agenda. Communication Theory , 35 (1), 37–50. https://doi.org/10.1093/ct/qtae020 Beiser-McGrath, J., & Beiser-McGrath, L. F. (2020). Problems with products? Control strategies for models with interaction and quadratic effects. Political Science Research and Methods , 8 (4), 707–730. https://doi.org/10.1017/psrm.2020.17 Beiser-McGrath, J., & Beiser-McGrath, L. F. (2023). The Consequences of Model Misspecification for the Estimation of Nonlinear Interaction Effects. Political Analysis , 31 (2), 278–287. https://doi.org/10.1017/pan.2022.25 Bergmann, E. (2018). Conspiracy & Populism: The Politics of Misinformation . Springer International Publishing. https://doi.org/10.1007/978-3-319-90359-0 Biddlestone, M., Green, R., Douglas, K. M., Azevedo, F., Sutton, R. M., & Cichocka, A. (2025). Reasons to believe: A systematic review and meta-analytic synthesis of the motives associated with conspiracy beliefs. Psychological Bulletin , 151 (1), 48–87. https://doi.org/10.1037/bul0000463 Birchall, C. (2006). Knowledge Goes Pop: From Conspiracy Theory to Gossip . Berg Publishers. https://doi.org/10.26530/OAPEN_390769 Boh Podgornik, B., Dolničar, D., Šorgo, A., & Bartol, T. (2016). Development, testing, and validation of an information literacy test (ILT) for higher education. Journal of the Association for Information Science and Technology , 67 (10), 2420–2436. https://doi.org/10.1002/asi.23586 Bornand, T., & Klein, O. (2022). Political trust by individuals of low socioeconomic status: The key role of anomie. Social Psychological Bulletin , 17 , e6897. https://doi.org/10.32872/spb.6897 Bowes, S. M., Costello, T. H., & Tasimi, A. (2023). The Conspiratorial Mind: A Meta-Analytic Review of Motivational and Personological Correlates. Psychological Bulletin , 149 (5–6), 259–293. https://doi.org/10.1037/bul0000392 Brandenstein, N. (2022). Going beyond simplicity: Using machine learning to predict belief in conspiracy theories. European Journal of Social Psychology , 52 (5–6), 910–930. https://doi.org/10.1002/ejsp.2859 Bruder, M., Haffke, P., Neave, N., Nouripanah, N., & Imhoff, R. (2013). Measuring Individual Differences in Generic Beliefs in Conspiracy Theories Across Cultures: Conspiracy Mentality Questionnaire. Frontiers in Psychology , 4 , 225. https://doi.org/10.3389/fpsyg.2013.00225 Butter, M., & Knight, P. (2018). The History of Conspiracy Theory Research: A Review and Commentary. In J. E. Uscinski (Ed.), Conspiracy Theories and the People Who Believe Them (p. 0). Oxford University Press. https://doi.org/10.1093/oso/9780190844073.003.0002 Cinelli, M., Etta, G., Avalle, M., Quattrociocchi, A., Di Marco, N., Valensise, C., Galeazzi, A., & Quattrociocchi, W. (2022). Conspiracy theories and social media platforms. Current Opinion in Psychology , 47 , 101407. https://doi.org/10.1016/j.copsyc.2022.101407 Delaney, C. (2005). The Spirituality Scale: Development and Psychometric Testing of a Holistic Instrument to Assess the Human Spiritual Dimension. Journal of Holistic Nursing , 23 (2), 145–167. https://doi.org/10.1177/0898010105276180 Devine, D., & Valgarðsson, V. O. (2023). Stability and change in political trust: Evidence and implications from six panel studies. European Journal of Political Research , 63 (2), 478–497. https://doi.org/10.1111/1475-6765.12606 Douglas, K. M., & Sutton, R. M. (2023). What are conspiracy theories? A definitional approach to their correlates, consequences, and communication. Annual Review of Psychology , 74 , 271–298. https://doi.org/10.1146/annurev-psych-032420-031329 Douglas, K. M., Uscinski, J. E., Sutton, R. M., Cichocka, A., Nefes, T., Ang, C. S., & Deravi, F. (2019). Understanding Conspiracy Theories. Political Psychology , 40 (S1), 3–35. https://doi.org/10.1111/pops.12568 Durkheim, É. (2002). Suicide: A Study in Sociology . Routledge. Enders, A. M., Diekman, A., Klofstad, C., Murthi, M., Verdear, D., Wuchty, S., & Uscinski, J. (2023). On modeling the correlates of conspiracy thinking. Scientific Reports , 13 (1), 8325. https://doi.org/10.1038/s41598-023-34391-6 Fasce, A., Avendaño, D., & Adrián-Ventura, J. (2021). Revised and short versions of the pseudoscientific belief scale. Applied Cognitive Psychology , 35 (3), 828–832. https://doi.org/10.1002/acp.3811 Forberg, P. L. (2022). From the Fringe to the Fore: An Algorithmic Ethnography of the Far-Right Conspiracy Theory Group QAnon. Journal of Contemporary Ethnography , 51 (3), 291–317. https://doi.org/10.1177/08912416211040560 Frederick, S. (2005). Cognitive Reflection and Decision Making. Journal of Economic Perspectives , 19 (4), 25–42. https://doi.org/10.1257/089533005775196732 Furstova, J., Malinakova ,Klara, Sigmundova ,Dagmar, & and Tavel, P. (2021). Czech Out the Atheists: A Representative Study of Religiosity in the Czech Republic. The International Journal for the Psychology of Religion , 31 (4), 288–306. https://doi.org/10.1080/10508619.2020.1844967 Gligorić, V., da Silva, M. M., Eker, S., van Hoek, N., Nieuwenhuijzen, E., Popova, U., & Zeighami, G. (2021). The usual suspects: How psychological motives and thinking styles predict the endorsement of well-known and COVID-19 conspiracy beliefs. Applied Cognitive Psychology , 35 (5), 1171–1181. https://doi.org/10.1002/acp.3844 Harambam, J. (2020). Contemporary Conspiracy Culture . Routledge. Harambam, J., & Aupers, S. (2015). Contesting epistemic authority: Conspiracy theories on the boundaries of science. Public Understanding of Science , 24 (4), 466–480. https://doi.org/10.1177/0963662514559891 Healy, K. (2017). Fuck Nuance. Sociological Theory , 35 (2), 118–127. https://doi.org/10.1177/0735275117709046 Invernizzi, G. M., & Mohamed, A. E. (2023). Trust Nobody: How Voters React to Conspiracy Theories. Journal of Experimental Political Science , 10 (2), 201–208. https://doi.org/10.1017/XPS.2022.11 Jasinskaja-Lahti, I., & Jetten, J. (2019). Unpacking the relationship between religiosity and conspiracy beliefs in Australia. British Journal of Social Psychology , 58 (4), 938–954. https://doi.org/10.1111/bjso.12314 Jones-Jang, S. M., Mortensen, T., & Liu, J. (2021). Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don’t. American Behavioral Scientist , 65 (2), 371–388. https://doi.org/10.1177/0002764219869406 Kapusta, J., & Kostićová, Z. M. (2021). From the Trees to the Wood: Alternative Spirituality as an Emergent ‘Official Religion’? Journal of Religion in Europe , 13 (3–4), 187–213. https://doi.org/10.1163/18748929-20211525 Kim, M., & Cao, X. (2016). The Impact of Exposure to Media Messages Promoting Government Conspiracy Theories on Distrust in the Government: Evidence from a Two-Stage Randomized Experiment. International Journal of Communication , 10 (0), Article 0. Knight, E., & Tsoukas, H. (2019). When Fiction Trumps Truth: What ‘post-truth’ and ‘alternative facts’ mean for management studies. Organization Studies , 40 (2), 183–197. https://doi.org/10.1177/0170840618814557 Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science , 3 (1), 33–67. https://doi.org/10.1007/s13194-012-0056-8 Lazić, A., & Žeželj, I. (2021). A systematic review of narrative interventions: Lessons for countering anti-vaccination conspiracy theories and misinformation. Public Understanding of Science , 30 (6), 644–670. https://doi.org/10.1177/09636625211011881 Leibovitz, T., Shamblaw, A. L., Rumas, R., & Best, M. W. (2021). COVID-19 conspiracy beliefs: Relations with anxiety, quality of life, and schemas. Personality and Individual Differences , 175 , 110704. https://doi.org/10.1016/j.paid.2021.110704 Mahl, D., Schäfer, M. S., & Zeng, J. (2023). Conspiracy theories in online environments: An interdisciplinary literature review and agenda for future research. New Media & Society , 25 (7), 1781–1801. https://doi.org/10.1177/14614448221075759 Mari, S., Gil de Zúñiga, H., Suerdem, A., Hanke, K., Brown, G., Vilar, R., Boer, D., & Bilewicz, M. (2022). Conspiracy Theories and Institutional Trust: Examining the Role of Uncertainty Avoidance and Active Social Media Use. Political Psychology , 43 (2), 277–296. https://doi.org/10.1111/pops.12754 Marwick, A. E., & Partin, W. C. (2022). Constructing alternative facts: Populist expertise and the QAnon conspiracy. New Media & Society , 14614448221090201. https://doi.org/10.1177/14614448221090201 Merton, R. K. (1938). Social Structure and Anomie. American Sociological Review , 3 (5), 672–682. https://doi.org/10.2307/2084686 Moffitt, T. E., Caspi, A., Ambler, A., Bourassa, K., Harrington, H., Hogan, S., Houts, R., Ramrakha, S., Wood, S. L., & Poulton, R. (2022). Deep-seated psychological histories of COVID-19 vaccine hesitance and resistance. PNAS Nexus , 1 (2), pgac034. https://doi.org/10.1093/pnasnexus/pgac034 Mont’Alverne, C., Ross Arguedas, A., Banerjee, S., Toff, B., Fletcher, R., & Nielsen, R. (2023). The Electoral Misinformation Nexus: How news consumption, platform use, and trust in news influence belief in electoral misinformation. Public Opinion Quarterly , 88 , 681–707. Moulding, R., Nix-Carnell, S., Schnabel, A., Nedeljkovic, M., Burnside, E. E., Lentini, A. F., & Mehzabin, N. (2016). Better the devil you know than a world you don’t? Intolerance of uncertainty and worldview explanations for belief in conspiracy theories. Personality and Individual Differences , 98 , 345–354. https://doi.org/10.1016/j.paid.2016.04.060 Mulukom, V., Pummerer, L., Alper, Bai, H., Čavojová, V., J, F., Cs, K., Lb, L., Ejc, L., G, M., I, P. B., J, Š., & I, Ž. (2022). Antecedents and consequences of COVID-19 conspiracy beliefs: A systematic review. Social Science & Medicine , 301 , 114912. https://doi.org/10.1016/j.socscimed.2022.114912 Neuberg, S. L., & Newsom, J. T. (1993). Personal need for structure: Individual differences in the desire for simpler structure. Journal of Personality and Social Psychology , 65 (1), 113–131. https://doi.org/10.1037/0022-3514.65.1.113 Nord, M., Lundstedt, M., Altman, D., Angiolillo, F., Borella, C., Fernandes, T., Gastaldi, L., Good God, A., Natsika, N., & Lindberg, S. I. (2024). Democracy Report 2024: Democracy Winning and Losing at the Ballot . V-Dem Institute. https://www.v-dem.net/documents/43/v-dem_dr2024_lowres.pdf Pennycook, G., & Rand, D. G. (2019). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition , 188 , 39–50. https://doi.org/10.1016/j.cognition.2018.06.011 Pierre, J. M. (2020). Mistrust and misinformation: A two-component, socio-epistemic model of belief in conspiracy theories. Journal of Social and Political Psychology , 8 (2), 617–641. https://doi.org/10.5964/jspp.v8i2.1362 Pierre, J. M. (2023). Conspiracy Theory Belief: A Sane Response to an Insane World? Review of Philosophy and Psychology . https://doi.org/10.1007/s13164-023-00716-7 Pilch, I., Turska-Kawa, A., Wardawy, P., Olszanecka-Marmola, A., & Smołkowska-Jędo, W. (2023). Contemporary trends in psychological research on conspiracy beliefs. A systematic review. Frontiers in Psychology , 14 , 1075779. Popper, K. (1972). Conjectures and Refutations (4th ed.). Routledge Kegan Paul. Primi, C., Morsanyi, K., Chiesi, F., Donati, M. A., & Hamilton, J. (2015). The Development and Testing of a New Version of the Cognitive Reflection Test Applying Item Response Theory (IRT). Journal of Behavioral Decision Making , 29 (5), 453–469. https://doi.org/10.1002/bdm.1883 Robertson, D. G. (2024). Religion and Conspiracy Theories: An Introduction . Routledge. https://doi.org/10.4324/9781003329992 Robinson, J. P., Shaver, P. R., Wrightsman, L. S., & Andrews, F. M. (1991). Measures of personality and social psychological attitudes . Academic Press. RSF. (2024). 2024 World Press Freedom Index – journalism under political pressure . https://rsf.org/en/2024-world-press-freedom-index-journalism-under-political-pressure Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine , 166 (10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092 Srole, L. (1956). Social Integration and Certain Corollaries: An Exploratory Study. American Sociological Review , 21 (6), 709–716. https://doi.org/10.2307/2088422 Stasielowicz, L. (2022). Who believes in conspiracy theories? A meta-analysis on personality correlates. Journal of Research in Personality , 98 , 104229. https://doi.org/10.1016/j.jrp.2022.104229 Stehlík, L. (2017). VALIDATION OF BAYESIAN MODEL OF CAUSAL INFERENCES MADE ON THE BASIS OF PERCEIVED COINCIDENCES [Univerzita Karlova, Filozofická fakulta]. https://dspace.cuni.cz/handle/20.500.11956/95409 Steppat, D., Castro, L., & Esser, F. (2023). What News Users Perceive as ‘Alternative Media’ Varies between Countries: How Media Fragmentation and Polarization Matter. Digital Journalism , 11 (5), 741–761. https://doi.org/10.1080/21670811.2021.1939747 Štětka, V., Mazák, J., & Vochocová, L. (2021). “Nobody Tells us what to Write about”: The Disinformation Media Ecosystem and its Consumers in the Czech Republic. Javnost - The Public , 28 (1), 90–109. https://doi.org/10.1080/13183222.2020.1841381 Štětka, V., & Mihelj, S. (2024). The Illiberal Public Sphere: Media in Polarized Societies . Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54489-7 Strömbäck, J., Broda, E., Bouchafra, S., Johansson, S., Rettenegger, G., & Lindgren, E. (2023). Conspiracy thinking and the role of media use: Exploring the antecedents of conspiratorial predispositions. European Journal of Communication , 38 (3), 255–271. https://doi.org/10.1177/02673231221122951 Sturgis, P., Kuha, J., Baker, N., Callegaro, M., Fisher, S., Green, J., Jennings, W., Lauderdale, B. E., & Smith, P. (2017). An assessment of the causes of the errors in the 2015 UK general election opinion polls. Journal of the Royal Statistical Society: Series A (Statistics in Society) , 181 (3), 757–781. https://doi.org/10.1111/rssa.12329 Sutton, R. M., & Douglas, K. M. (2022). Rabbit Hole Syndrome: Inadvertent, accelerating, and entrenched commitment to conspiracy beliefs. Current Opinion in Psychology , 48 , 101462. https://doi.org/10.1016/j.copsyc.2022.101462 Syrovátka, J. (2023). Czech Conspiracy Websites as Agents of Illiberalism: Case study of Parliamentary Elections 2021. CENTRAL EUROPEAN JOURNAL FOR CONTEMPORARY RELIGION , 5 (1), 25–46. Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods , 16 (2), 209–220. https://doi.org/10.1037/a0023353 Toplak, M. E., West, R. F., & Stanovich, K. E. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking & Reasoning , 20 (2), 147–168. https://doi.org/10.1080/13546783.2013.844729 Urbániková, M., & Smejkal, K. (2023). Trust and Distrust in Public Service Media: A Case Study From the Czech Republic. Media and Communication , 11 (4), 297–307. https://doi.org/10.17645/mac.v11i4.7053 Uscinski, J., Enders, A., Diekman, A., Funchion, J., Klofstad, C., Kuebler, S., Murthi, M., Premaratne, K., Seelig, M., Verdear, D., & Wuchty, S. (2022). The psychological and political correlates of conspiracy theory beliefs. Scientific Reports , 12 (1), Article 1. https://doi.org/10.1038/s41598-022-25617-0 Van Bavel, J. J., Rathje, S., Vlasceanu, M., & Pretus, C. (2024). Updating the identity-based model of belief: From false belief to the spread of misinformation. Current Opinion in Psychology , 56 , 101787. https://doi.org/10.1016/j.copsyc.2023.101787 van Prooijen, J.-W. (2020). An Existential Threat Model of Conspiracy Theories. European Psychologist , 25 (1), 16–25. https://doi.org/10.1027/1016-9040/a000381 van Prooijen, J.-W., & Douglas, K. M. (2018). Belief in conspiracy theories: Basic principles of an emerging research domain. European Journal of Social Psychology , 48 (7), 897–908. https://doi.org/10.1002/ejsp.2530 van Prooijen, J.-W., & van Vugt, M. (2018). Conspiracy Theories: Evolved Functions and Psychological Mechanisms. Perspectives on Psychological Science , 13 (6), 770–788. https://doi.org/10.1177/1745691618774270 Waisbord, S. (2018). Truth is What Happens to News: On journalism, fake news, and post-truth. Journalism Studies , 19 (13), 1866–1878. https://doi.org/10.1080/1461670X.2018.1492881 Ward, C., & Voas, D. (2011). The Emergence of Conspirituality. Journal of Contemporary Religion , 26 (1), 103–121. https://doi.org/10.1080/13537903.2011.539846 Additional Declarations No competing interests reported. Supplementary Files WhatExplainsBCTSuppMaterialHSSC.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Nov, 2025 Reviews received at journal 08 Oct, 2025 Reviews received at journal 08 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviewers agreed at journal 24 Jul, 2025 Reviewers agreed at journal 19 Jul, 2025 Reviewers invited by journal 19 Jul, 2025 Submission checks completed at journal 18 Jul, 2025 First submitted to journal 20 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5682677","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":474293317,"identity":"68ce3989-f05a-4682-a77c-1f7aa9b7b8d2","order_by":0,"name":"Matouš Pilnáček","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYDADNnYwlSBHhFpmqBYInWBMvBYonZDYQEiDbvv5g495/jDk8THzHvzwoyItfX578wOGHzV1DPz9B7BqMTuTzGzM28ZQzMbMlyzZcyYnd8OZYwaMPccOM0gcwKHlQDKbNG8DQ2IbM4+BNGNbRe4GiRygI9kOMBgwYnej2fnHbNJAh4G0GP9m/FeRLj8DpOVfHYMBM1YdDGY3gLbwsIG1mEkzNuQkMNwAamFsY2YwYMOl5bGx4dw2CaBfeMwse46lGYL8crC37zCPxBkcWs4nPnzw5o9Nnnx7j/GNHzXJ8vLtzQ8f/PhWJ4crxKBAIgGFC1LLg089CCQQUjAKRsEoGAUjGAAAzPpS1fg0zpkAAAAASUVORK5CYII=","orcid":"","institution":"Institute of Sociology of the Czech Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Matouš","middleName":"","lastName":"Pilnáček","suffix":""},{"id":474293319,"identity":"e7fdd07f-d248-4928-b35b-2c5974f36725","order_by":1,"name":"Paulína Tabery","email":"","orcid":"","institution":"Institute of Sociology of the Czech Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Paulína","middleName":"","lastName":"Tabery","suffix":""},{"id":474293320,"identity":"b4040fd8-58f4-432e-9d50-fd47be73cb67","order_by":2,"name":"Marie Heřmanová","email":"","orcid":"","institution":"Institute of Sociology of the Czech Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Heřmanová","suffix":""},{"id":474293323,"identity":"a7146918-a444-4d26-8336-e221394d238f","order_by":3,"name":"Josef Šlerka","email":"","orcid":"","institution":"Faculty of Arts, Charles University","correspondingAuthor":false,"prefix":"","firstName":"Josef","middleName":"","lastName":"Šlerka","suffix":""},{"id":474293326,"identity":"d4c20e03-1549-418b-8639-755c591f90be","order_by":4,"name":"Lucie Čejková","email":"","orcid":"","institution":"Faculty of Social Studies, Masaryk University","correspondingAuthor":false,"prefix":"","firstName":"Lucie","middleName":"","lastName":"Čejková","suffix":""}],"badges":[],"createdAt":"2024-12-20 09:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5682677/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5682677/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85716039,"identity":"c0720d39-f3ff-4595-ab78-1bba9ad5ff23","added_by":"auto","created_at":"2025-07-01 04:01:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":99922,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagram of the proposed extended socio-epistemic model (ESoEM). \u003c/strong\u003eESoEM has three key characteristics: (1) the distinction between two groups of variables - individual variables and the variables within the socio-epistemic system; (2) the construction of composite concepts within the socio-epistemic system; and (3) the assumption of a latent dynamic process involving the re-establishment of the interpretation of social reality, which underlies and structures the relationships among the manifest composite concepts.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/f26c7e858467c4da29468ec5.png"},{"id":85716040,"identity":"25d59b15-4034-4af9-a689-4b5cd3b31b69","added_by":"auto","created_at":"2025-07-01 04:01:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77143,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStrength of the relationship with BCT. \u003c/strong\u003eThe figure shows in columns (1) zero-order correlations with BCT; (2) linear regression coefficients, where all variables and education enter as independent variables at once and are standardized to range from 0 to 1; and (3) general dominance, reflecting additional contributions to the explained R\u003csup\u003e2\u003c/sup\u003e of each variable within all subset models. Confidence intervals at the 99% level are constructed using bootstrapping with 2,000 resamples to account for quota selection. Positive coefficient values are shown in green and negative coefficient values are shown in red. *** p \u0026lt; 0.001, **p \u0026lt; 0.01, * p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/e257fb1977e61f8213cf8046.png"},{"id":85716042,"identity":"b6a5fa36-25bb-49d1-976e-6c02485df86d","added_by":"auto","created_at":"2025-07-01 04:01:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29538,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredicted values of the interaction between macro-social adhesion and media consumption orientation (Model 4). \u003c/strong\u003eMean and effect of one standard deviation are shown. Confidence intervals are at the 99% level.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/d9516a4cb9c7252a6195d0cc.png"},{"id":85716619,"identity":"bf266e82-2c10-4537-8788-63ff39253b9c","added_by":"auto","created_at":"2025-07-01 04:09:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":26739,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredicted values of the quadratic term pseudoscientific spirituality (Model 4)\u003c/strong\u003e. Confidence intervals are at the 99% level.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/3e002cc3995565e14a366dfc.png"},{"id":85716620,"identity":"78a5b1cf-a076-4010-a822-c2eabc19bf03","added_by":"auto","created_at":"2025-07-01 04:09:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":97600,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagram of the empirical exploration of the extended socio-epistemic model (ESoEM). \u003c/strong\u003eThe black part of the figure shows schematically the empirical results of the study. The gray part shows the theoretically assumed influence of macro-social characteristics.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/1ad4f44093c49a60cad969ce.png"},{"id":85716829,"identity":"5ad44244-2d64-45f5-86ee-29a644395d12","added_by":"auto","created_at":"2025-07-01 04:17:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1329759,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/384ceb69-50e8-471d-9085-cb5e17277e88.pdf"},{"id":85716623,"identity":"7db91891-7009-4000-8e0c-1fbdd4cfc8ba","added_by":"auto","created_at":"2025-07-01 04:09:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":4997447,"visible":true,"origin":"","legend":"","description":"","filename":"WhatExplainsBCTSuppMaterialHSSC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5682677/v1/633e381563c8366bb2b0a506.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"What Explains the Belief in Conspiracy Theories? Composite Concepts as a New Approach to Studying Conspiracy Theories","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe prevalence of conspiracy theories in contemporary society has led to a significant increase in research activity within this field over the past decade. The potential negative impact of conspiracy theories on various aspects of society (Bowes et al., 2023; Stasielowicz, 2022; Uscinski et al., 2022), including social, political, and personal domains, has prompted a rigorous examination of these beliefs. The COVID-19 pandemic has further elevated the prominence of this issue within both academic discourse and public debate (Mahl et al., 2023; Mulukom et al., 2022). The content, dissemination, prevalence, and impact of conspiracy theories have been the subject of study in a variety of academic fields, including the social sciences, arts and humanities, law, medicine, and information science (Mahl et al., 2023). Furthermore, it is a field that is highly multidisciplinary and interdisciplinary, as well as one dominated by empirical studies (Mahl et al., 2023). The development of coherent theoretical frameworks that describe the relationship between belief in conspiracy theories (BCT) and a broader set of psychological and social concepts is an ongoing challenge. These frameworks would potentially connect findings from psychology, sociology and other domains of social science into a coherent framework that would enable a comprehensive understanding of the phenomenon. However, they remain underdeveloped and are seldom used (Brandenstein, 2022; Douglas \u0026amp; Sutton, 2023; Mahl et al., 2023; Pilch et al., 2023; van Prooijen \u0026amp; Douglas, 2018). While a large number of expected correlates have been investigated (Biddlestone et al., 2025; Bowes et al., 2023; Mulukom et al., 2022; Stasielowicz, 2022; Uscinski et al., 2022), their categorization in meta-studies tends to vary widely (Bowes et al., 2023; Mulukom et al., 2022). Furthermore, the selection of these correlates across studies is not systematic.\u003c/p\u003e\n\u003cp\u003eThe present article responds to long-standing theoretical fragmentation in the study of conspiracy theories by proposing an integrative framework that enables the systematic organization of key correlates. Rather than starting from a single dominant theory, we draw on a diverse body of scholarship, particularly cultural and epistemic approaches, to conceptualize conspiracy theories as alternative interpretations of social reality. This discussion provides the foundation for our adoption of the socio-epistemic model (SoEM), which we expand into the extended socio-epistemic model (ESoEM). The model distinguishes between individual-level and socio-epistemic factors and introduces three composite concepts. The proposed model is empirically explored using cross-sectional survey data from the Czech Republic.\u003c/p\u003e\n\u003ch2\u003eA definition of the term \u0026apos;conspiracy theory\u0026apos;\u003c/h2\u003e\n\u003cp\u003eIn our study, conspiracy theories are defined as complex explanations comprising a series of statements that interpret social events as the result of secret, malicious activities carried out by a group of people (Birchall, 2006), which is the definition agreed upon by most authors and approaches. However, as Douglas and Sutton (2023) have noted, a more detailed definition of conspiracy theories could facilitate the creation of theoretical models and the systematization of empirical knowledge, a necessity that is increasingly apparent. They offer a more detailed definition of conspiracy theories, adding further characteristics to the aforementioned definition. Firstly, conspiracy theories contradict the official explanation of events. Secondly, they contain elements of malice. Thirdly, they attribute actions to specific individuals or groups rather than to systems or structures. Fourthly, they have an epistemic dimension while being \u0026apos;epistemically risky\u0026apos;; that is to say, their explanations are improbable. Furthermore, these explanations are social constructs that not only interpret but also create social reality. Conspiracy theories are also characterized by publicness, i.e. a matter of public interest of which the public should be aware (ibid. 2023, p. 282).\u003c/p\u003e\n\u003cp\u003eAnother distinguishing characteristic of conspiracy theories is that they generate knowledge (Birchall, 2006; Douglas \u0026amp; Sutton, 2023; Harambam \u0026amp; Aupers, 2015). The extent to which conspiracy theories are successful in this regard is determined by various individual and social factors, which have been extensively studied in recent years. Consequently, in the search for a theoretical model to explain BCT, we sought one that would encompass the production of knowledge and relate it to various characteristics, particularly social ones, given that one of the characteristics of conspiracy theories is their public nature.\u003c/p\u003e\n\u003ch2\u003eTheoretical framework\u003c/h2\u003e\n\u003cp\u003eThe manner in which conspiracy theories have been examined has evolved over time; however, since its inception, two fundamental approaches have been identified. Firstly, a pathologizing approach is employed, with a focus on irrationality and individual and psychological characteristics. Secondly, a cultural and social practices approach (Butter \u0026amp; Knight, 2018). Popper (1972) was the first to characterize \u0026apos;conspiracy theory of society\u0026apos; as a simplistic and untrue interpretation of the complexity of social events. In the subsequent period, a pathologizing approach prevailed, with individual characteristics such as paranoia, suspiciousness, fear, and feelings of alienation being examined, as well as negative social impacts such as attitudes toward political extremism and undemocratic attitudes. This pathologizing approach has been challenged in recent decades, with the development of cultural approaches (Butter \u0026amp; Knight, 2018) in the fields of analytical philosophy, cultural studies, sociology and social anthropology.\u003c/p\u003e\n\u003cp\u003eThis growing body of research focuses on the everyday practices and personal engagement of individuals with conspiracy theories, as well as the theories\u0026apos; social and cultural contexts. It considers conspiracy theories to be an alternative form of knowledge production, in relation to what the actors consider to be mainstream science and institutionalized explanations of the world. Inspired by the term \u0026apos;conspiracy milieu\u0026apos;, coined by (Harambam \u0026amp; Aupers, 2015) to represent the complex social, cultural, and economic relations that conspiracy believers find themselves in, this research strand emphasizes the practical obstacles to establishing definitions and the epistemological impossibility of relating conspiracy theories to established notions of \u0026apos;truth\u0026apos; or \u0026apos;reality\u0026apos;.\u003c/p\u003e\n\u003cp\u003eWaisbord (2018) argues with respect to the term \u0026apos;post-truth\u0026apos;, favored by many researchers and a large portion of the media following the 2016 US presidential election, the notions of truth, and consequently post-truth (and related terms such as \u0026apos;fake news\u0026apos; and \u0026apos;misinformation\u0026apos;), are always normative. Similarly, Knight and Tsoukas (2019) observe that \u0026apos;there is no intrinsically accurate language in terms of which to refer to reality\u0026apos; (p. 183).\u003c/p\u003e\n\u003cp\u003eTo overcome the issues of inherent normativity and hierarchy in conspiracy theory research, and to avoid pathologization, many authors turn to ethnography and qualitative research methods. These methods allow them to explore the everyday role of conspiracy theories for those who interact with them, and the meaning-making practices constructed around them (Forberg, 2022; Harambam, 2020). For example, Marwick and Partin (2022) propose the notion of \u0026apos;populist expertise\u0026apos; based on their research inside QAnon-related online communities. They define this as \u0026apos;the rejection of legacy media accounts, scientific consensus, or elite knowledge in favor of a body of \u0026quot;home-grown\u0026quot; forms of expertise and meaning-making generated by those who may feel disenfranchised from mainstream political participation\u0026apos; (p. 2535).\u003c/p\u003e\n\u003cp\u003eThe aforementioned works focus primarily on online communities and rely on qualitative and theoretical research. The present article builds upon these earlier works by employing quantitative research methods and taking into account cultural approaches to conspiracy theories, which treat them as interpretative frameworks.\u003cem\u003e\u0026nbsp;\u003c/em\u003eIn line with this perspective, conspiracy theories do not exist in isolation but become embedded in a broader, complex socio-epistemic system for interpreting social reality.\u003c/p\u003e\n\u003cp\u003eBased on this understanding, we distinguish between variables that structure the interpretative framework and variables that shape individual predispositions toward adopting conspiracy beliefs. This distinction deviates from the commonly used tripartite classification of existential, epistemic, and social needs (Biddlestone et al., 2025; Douglas et al., 2019). Instead, the focus is on the interconnection of socio-epistemic variables, which, in contrast to individual characteristics, exhibit strong reciprocal reinforcement with BCT. Collectively, these variables form a system of meaning-making.\u003c/p\u003e\n\u003cp\u003eWe also argue that, within such a system, many concepts are strongly interconnected through feedback loops. Therefore, we propose merging theoretically related concepts that also exhibit strong empirical relationships into composite concepts. This approach yields a model that is conceptually clearer and analytically more coherent.\u003c/p\u003e\n\u003cp\u003eThe creation of composite concepts is also motivated by additional factors. Since studies on BCT usually include a substantial number of correlates, there is a compelling imperative to streamline theoretical models (Healy, 2017) and an analytical necessity to explore interactions and nonlinear relationships within BCT research (Brandenstein, 2022; Sutton \u0026amp; Douglas, 2022). These interactions and nonlinearities have already been the subject of some empirical studies, the results of which have confirmed their existence and importance (Brandenstein, 2022; Jasinskaja-Lahti \u0026amp; Jetten, 2019; Mari et al., 2022). Without limiting the number of variables using composite variables, it is necessary to use machine learning techniques (Brandenstein, 2022; Enders et al., 2023). However, this does not address the requisite streamlining of the theoretical models.\u003c/p\u003e\n\u003ch2\u003eExtended socio-epistemic model\u003c/h2\u003e\n\u003cp\u003eTo address this conceptual framework explicitly, we employ a socio-epistemic model (Pierre 2020, SoEM), which comprises two components: epistemic mistrust and misinformation processing. Mistrust represents a pivotal element in this context, as a deficiency in trust gives rise to an epistemic vacuum that is subsequently occupied by non-authoritative information. Those who distrust the system cease to accept the official interpretation of social events and instead seek alternative explanations. In accordance with the theoretical approaches previously delineated, the SoEM conceptualizes belief in conspiracy theories (BCT) as a re-establishment of the interpretation of social reality.\u003c/p\u003e\n\u003cp\u003eWhile our approach builds on Pierre\u0026rsquo;s core insight\u0026mdash;that epistemic mistrust leads to the re-establishing of the interpretation of social reality\u0026mdash;it introduces two key modifications informed by the preceding theoretical discussion. These adjustments underpin the development of the extended socio-epistemic model (ESoEM), which is illustrated in Figure 1.\u003c/p\u003e\n\u003cp\u003e[FIGURE 1 ABOUT HERE]\u003c/p\u003e\n\u003cp\u003eFirstly, Pierre (2020) proposes several concepts that could influence epistemic mistrust, information processing, and consequently, BCT. However, a significant number of other concepts have been subjected to rigorous examination in numerous studies over recent years. Some of these have been found to exhibit a robust and consistent relationship with BCT, whereas others have demonstrated either a weaker or no association. In general, both personality predispositions to believe in conspiracy theories and the social conditions in which individuals live are examined. The majority of studies concur that strong correlates include, but are not limited to, trust in institutions, science, socio-political control (Brandenstein, 2022), anomie (Biddlestone et al., 2025; Enders et al., 2023), spirituality (Mulukom et al., 2022) dangerous worldviews (Biddlestone et al., 2025), media consumption from specific sources (Str\u0026ouml;mb\u0026auml;ck et al., 2023), and analytical thinking (Gligorić et al., 2021; Pennycook \u0026amp; Rand, 2019).\u003c/p\u003e\n\u003cp\u003eConsequently, we decided to augment Pierre\u0026apos;s model by incorporating concepts that, as substantiated by extant literature, exhibit a robust and systematic relation with BCT. These concepts facilitate a more thorough elaboration of the social context of the model. This context is shaped not only by mistrust but also by the related concept of anomie. The social context is also formed by the overall epistemological and interpretative framework, which includes spirituality, pseudoscientific beliefs, and media consumption. With respect to individual characteristics, the study incorporated those that exhibited a strong and systematic relationship with BCT, in addition to characteristics associated with information processing, such as information literacy and cognitive reflection.\u003c/p\u003e\n\u003cp\u003eThe ESoEM thus includes the following socio-epsitemic characteristics: institutional trust, operationalized as trust in political institutions (Brandenstein, 2022); mainstream media and scientists (Brandenstein, 2022); anomie (Moulding et al., 2016; Robinson et al., 1991; Srole, 1956); eco-awareness spirituality (Delaney, 2005; Gligorić et al., 2021); pseudoscientific beliefs (Fasce et al., 2021; Stasielowicz, 2022) and consumption of different types of media and information sources (Str\u0026ouml;mb\u0026auml;ck et al., 2023). Additionally, we consider as individual characteristcs, the personal need for structure (Axt et al., 2021; Stehl\u0026iacute;k, 2017), anxiety (Leibovitz et al., 2021; Spitzer et al., 2006), information literacy (Boh Podgornik et al., 2016; Jones-Jang et al., 2021), and cognitive reflection (Frederick, 2005; Pennycook \u0026amp; Rand, 2019; Stehl\u0026iacute;k, 2017). As control variables, we also include standard sociodemographic variables.\u003c/p\u003e\n\u003cp\u003eSecondly, Pierre\u0026apos;s model is not only extended by new variables, but also by composite concepts, namely macro concepts comprising pre-existing concepts. In our study, we have devised three such concepts: macro-social adhesion (MSA), pseudoscientific spirituality (PS), and media consumption orientation (MCO).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMacro-social adhesion\u0026nbsp;\u003c/em\u003e(MSA) is comprised of two widely used concepts: institutional trust and anomie. Trust is a pivotal concept within the SoEM framework and the strong relationship between institutional trust and BCT is substantiated by a multitude of empirical studies (Brandenstein, 2022; Mulukom et al., 2022). However, the model employs the term \u0026apos;epistemic mistrust\u0026apos;, thereby raising the question of whether institutional trust, as measured by trust in political institutions, public service media, and scientists, effectively captures the epistemic dimension. These institutions can be regarded as mainstream epistemic authorities within the BCT study, whereby trust in a given institution also encompasses trust in its interpretation of the world. The concept of epistemic authority is characterized by its dualistic nature, encompassing both expertise and trustworthiness (Bartsch et al., 2025). Pierre (2020, p. 620) defines epistemic mistrust as \u0026ldquo;mistrust of knowledge or, framed within its proper socio-cultural context, mistrust of authoritative informational accounts.\u0026rdquo; He also acknowledges the dual nature of trust, as trust in information hinges on the perceived expertise and trustworthiness of the source. According to Pierre (2020, p. 626), \u0026quot;trust serves as a \u0026apos;heuristic for competence,\u0026apos;\u0026quot; so assessing expertise and credibility are often one and the same. However, distrust of institutions plays a role in BCT not only because of the rejection of official interpretations of events but also because of the suspicion of malevolent intentions on the part of institutional representatives (and this attitude is an integral part of BCT). The second strongly corroborated correlate of conspiracy theories is anomie (Biddlestone et al., 2025), a classical sociological concept. Durkheim\u0026apos;s (2002 [1897]) seminal definition of anomie posits that significant changes in the social order, whether positive or negative, can lead to the breakdown of social norms, thereby weakening the bonds within society. In defining anomie, Merton focused on the discrepancy between the desirable goals set by society and the impossibility of achieving them by legitimate means (1938). This phenomenon gives rise to various strategies of response to the prevailing system and society, which may include rebellion or retreatism. Alternatively, as specified by Srole (1956), it is a loss of attachment to society. Institutional trust and anomie are two distinct concepts, but they are related. For example, Bornand and Klein (2022) demonstrate that anomie can be conceptualized as a predictor of trust and as a mediating variable between socioeconomic status and trust. Trust and anomie can be seen as complementary concepts because anomie captures a broader perspective of society and a view of norms and alienation, while institutional trust refers to key legitimate and epistemic authorities in society. The composite concept of MSA thus represents both individual and general levels of attachment to society. For the wording and frequency of the questions measuring MSA, see Supplementary Material in Section 1 Tables 5 and 6.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePseudoscientific spirituality\u003c/em\u003e (PS) represents a synthesis of two distinct concepts: spirituality and pseudoscientific beliefs. Both of these concepts are strongly and robustly associated with BCT (Gligorić et al., 2021; Mulukom et al., 2022; Stasielowicz, 2022). Pseudoscientific beliefs can be defined as epistemic errors that mimic science. They either take the form of promoting pseudoscience or rejecting science (Fasce et al. 2021).The relationship between spirituality and pseudoscientific beliefs has been extensively investigated, particularly in qualitative research, to the extent that the term \u0026ldquo;conspirituality\u0026rdquo; has been directly referenced in the literature (Ward \u0026amp; Voas, 2011). The term conspirituality emphasizes the common aspects of conspiracy thinking and New Age-type spirituality, including a focus on enlightenment (and the subsequent ability to \u0026ldquo;see the truth\u0026rdquo;), holistic thinking, and a belief in a paradigm shift in human consciousness, as well as the narrative that a hidden group of elites is attempting to prevent this shift. This type of spirituality is therefore closely aligned with pseudoscientific beliefs. Concurrently, it is also measured in quantitative research under the designation of eco-awareness spirituality, which pertains to a conviction in a higher power and the capacity to draw upon inner strength (Mulukom et al., 2022). For the wording and frequency of questions measuring PS, see Supplementary Material in Section 1 Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMedia consumption orientation\u003c/em\u003e (MCO) is a measure of media consumption on a continuum that contrasts mainstream media consumption with alternative media consumption. The consumption of media is a multifaceted phenomenon, and the index is designed to quantify this complexity by subtracting the two types of orientation. Consequently, respondents who consume both types of media in equal measure are situated at the midpoint of the continuum. The majority of research on conspiracy theories has focused on social media (Cinelli et al., 2022), with relatively little attention paid to the role of other types of media. Nevertheless, studies that incorporate sources of information beyond social media have demonstrated that the consumption of mainstream or alternative media is a significant factor in the acceptance of conspiracy theories (Str\u0026ouml;mb\u0026auml;ck et al., 2023) or misinformation (Mont\u0026rsquo;Alverne et al., 2023). The combination of these two orientations into a composite concept allows for a closer alignment with the concept of a mainstream\u0026ndash;alternative spectrum, which is a key analytical tool in the study of alternative media more broadly (Steppat et al., 2023). The index is constructed on the basis of survey questions pertaining to the consumption of different types of information sources. The types of sources are classified as alternative or mainstream in accordance with the particular characteristics of the media landscape in the Czech Republic (\u0026Scaron;tětka et al., 2021). In this instance, it is not assumed that the theoretical division into alternative and mainstream media results in a clear two-factor structure. Consequently, a theoretically based index is employed in lieu of a scale. For the wording and frequency of questions measuring MCO, see Section 1 in Supplementary Material Table 4.\u003c/p\u003e\n\u003cp\u003eIn this study, we employ Pierre\u0026apos;s model as a foundational framework for the examination of BCT. However, we have not tested the process of creating and filling the epistemic vacuum directly. Instead, we propose an extended socio-epistemic model (ESoEM) with the following characteristics:\u003c/p\u003e\n\u003cp\u003e(1) the distinction between two groups of variables\u0026mdash;individual characteristics and the socio-epistemic system;\u003c/p\u003e\n\u003cp\u003e(2) the construction of composite concepts within the socio-epistemic system; and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(3) the assumption of a latent dynamic process involving the re-establishment of the interpretation of social reality, which underlies and structures the relationships among the manifest composite concepts.\u003c/p\u003e\n\u003cp\u003eThe objective of our research is to investigate the proposed composite concepts, their relationship with BCT, their interactions, and the implications of these findings for the further development of ESoEM.\u003c/p\u003e\n\u003cp\u003eRQ1: Is it empirically justifiable to combine the individual correlates into composite concepts, as we have proposed?\u003c/p\u003e\n\u003cp\u003eRQ2: To what extent do composite concepts explain BCT when controlling for other concepts and sociodemographic variables?\u003c/p\u003e\n\u003cp\u003eRQ3: How do composite concepts interact with each other when explaining BCT?\u003c/p\u003e\n\u003cp\u003eFor this purpose, we use representative cross-sectional data from a survey conducted in the Czech Republic (N = 3,880).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe materials, anonymized data, and analysis code are available at\u003c/p\u003e\n\u003cp\u003ehttps://osf.io/rj825/?view_only=53a4d90f18504758acc34e858be0c9c3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample was obtained through the administration of a questionnaire survey to an online opt-in panel. The cross-sectional survey is a quota sample representative of the Czech population aged 18\u0026ndash;65 with internet access (N = 3,880). The quota variables are defined by gender, age, level of education, region, and size of municipality. Table 1 in the Supplementary Material in Section 2 provides a summary of the quota variables and the extent to which they deviate from the population. The data were collected between March 14, 2023, and April 15, 2023. Informed consent was obtained through online confirmation by the participant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Czech context\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Czech Republic is a standard European liberal democracy (Nord et al., 2024) and ranks relatively high in the Reporters Without Borders Press Freedom Index (RSF, 2024). Additionally, Czech public service media restrain from amplifying conspiracy theories, unlike public service media in other Central and Eastern European countries (\u0026Scaron;tětka \u0026amp; Mihelj, 2024; Urb\u0026aacute;nikov\u0026aacute; \u0026amp; Smejkal, 2023).\u003c/p\u003e\n\u003cp\u003eNevertheless, the specific media and political configuration in the Czech Republic provides important context for the division between conspiracy theories as alternative explanations of social reality and mainstream explanations provided by institutional authorities. A significant portion of commercial media outlets and tabloids maintained ties to political actors and oligarchs at the time of data collection, most notably former Prime Minister and leader of the populist ANO party, Andrej Babi\u0026scaron; (\u0026Scaron;tětka \u0026amp; Mihelj, 2024). Although the 2021 parliamentary elections appeared to slow the momentum of anti-system sentiment, an ecosystem providing fertile ground for the spread of conspiracy theories remains active. This includes a network of disinformation websites that disseminate conspiratorial, pro-Russian, and anti-establishment content (\u0026Scaron;tětka et al., 2021; \u0026Scaron;tětka \u0026amp; Mihelj, 2024). Some of these conspiracy outlets sided with Babi\u0026scaron; on specific issues, further complicating the boundary between institutional and alternative framings (Syrov\u0026aacute;tka, 2023). This dual configuration - of formal institutional stability and informal erosion of epistemic authorities makes the Czech Republic an appropriate setting for a case study to investigate ESoEM.\u003c/p\u003e\n\u003cp\u003eThe Czech Republic is also a noteworthy case study in terms of the overlaps between religious beliefs, pseudo-science beliefs and BCT. While the link between participating in various forms of institutionalized religion and BCT has been extensively researched (see for example Robertson, 2024), the Czech Republic consistently ranks among the least religious countries worldwide (Furstova et al., 2021). Although the Czech Republic is a specific country in this respect, there are numerous and diverse forms of non-institutionalized alternative spirituality beliefs present in Czech society (Kapusta \u0026amp; Kostićov\u0026aacute;, 2021). This makes it a fertile ground for researching the links between non-institutionalized spirituality, pseudo-scientific beliefs and BCT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe development, validation, and computation of the BCT scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBCT represents the dependent variable in our study. There are two principal methods of measuring it: 1) by the conspiracy thinking scale or 2) by the set of statements representing the narratives that make up conspiracy theories. We have selected to examine BCT using individual statements representing conspiracy theories. A significant challenge in our selected method of measuring BCT is the process of selecting appropriate statements. The statements representing the conspiracy theories utilized in this study were developed through a quantitative content analysis of Czech conspiracy and disinformation websites, resulting in the identification of four key thematic clusters. Consequently, the selection of statements is grounded in empirical evidence, aiming to assess theories that are currently accessible to Czech audiences, namely content that respondents may encounter in their daily interactions, social media, and online platforms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo ensure that the thematic selection of conspiracy theories clusters was not unduly influenced by the prevalence of COVID-19 pandemic topics, the analysis was based on a content analysis of 21 Czech conspiracy and disinformation websites from 2019. The disinformation and conspiracy websites were selected from a list maintained by the Foundation for Independent Journalism, a resource that has also been utilized in other academic research (\u0026Scaron;tětka et al., 2021). The last 30 articles from each website were downloaded and coded into categories that reflected the categorization from the book \u003cem\u003eConspiracy \u0026amp; Populism\u003c/em\u003e (Bergmann, 2018). Two additional categories were added to this existing categorization: specifically, Czech conspiracies and pro-Kremlin conspiracies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExploratory analysis using hierarchical cluster analysis revealed that the theories could be grouped into four thematic clusters:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1. Health and history. This cluster of stories focusing on health issues, alternative healing theories, and reinterpretations of historical events may reflect a common interest in \u0026ldquo;alternative truths\u0026rdquo; about the body and the past, leading to a rejection of official explanations and a trust in \u0026ldquo;hidden\u0026rdquo; factors affecting health and history. This includes popular historical conspiracies, such as the murder of Princess Diana.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. Cultural threats to European civilization and migration. This cluster includes theories that focus on culture and demography, often with a belief in a deliberate plan to replace European populations with migrations from non-European countries. Fears of \u0026ldquo;the great replacement\u0026rdquo; or \u0026ldquo;white genocide\u0026rdquo; are common in these theories, reflecting fears of loss of cultural identity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3. New World Order. This cluster combines various aspects of New World Order theories, which include ideas of supranational, often secret, forces conspiring to take control of the world. These ideas may include theories of global elites and shadow governments, and may overlap with other conspiratorial motives.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4. Pro-Russian and specific Czech statements. This cluster is specific in that it contains theories and interpretations directly related to the Czech socio-political context and current events, such as the Russian invasion of Ukraine. These theories may include views influenced by Russian propaganda or specific domestic political theories related to national interests and perceptions of international politics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther details regarding the content analysis can be found in the Supplementary Material, specifically in Section 9.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the aforementioned clusters, 20 statements were selected, encompassing all four clusters (for the wording of the conspiracy statements, see Supplementary Material Section 1 Table 2). The selected statements exhibited a range of levels of difficulty and degrees of specificity. The selection of statements was based on the thematic analysis of 27 conspiracy websites, once more from the Foundation for Independent Journalism list, with the inclusion of statements pertaining to current events such as the invasion of Ukraine. In order to avoid the potential for respondents to guess the correct answer (Altay et al., 2023), an explicit \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; option was provided. Additionally, four mainstream statements were included among the conspiracy theories for control purposes. In each case, the respondents were first asked to indicate their level of agreement or disagreement with the statement in question. They were then asked whether they had noticed such statements. The present study focuses exclusively on the level of agreement with the statements included in the BCT scale.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn order to test the validity of the BCT scale, the dataset was randomly divided into two parts, which were then subjected to exploratory and confirmatory factor analysis, respectively. In exploratory factor analysis (EFA), the number of factors is determined using optimal parallel analysis (Timmerman \u0026amp; Lorenzo-Seva, 2011) with polychoric correlations. Subsequently, a standard EFA is conducted with oblique oblimin rotation, and McDonald\u0026rsquo;s omega is calculated to assess the reliability of the scale. The structure of the scale was confirmed by means of a confirmatory factor analysis (CFA) on the second half of the split dataset, employing the WLSMW method. All calculations were conducted (a) for complete observations and (b) with imputed missing values instead of \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; responses. In addition to the original scale, a reduced scale comprising only those statements directly related to the secret plot was employed. The aforementioned methodology was employed to assess the scale. The Pearson correlation between the reduced and unreduced scales of conspiracy theories scales was 0.98, indicating a high degree of correlation between the two sets of data and suggesting that the phenomenon being measured is essentially the same. A second survey was conducted (CAPI, N = 913), in which the conspiracy theories scale was again administered. In the supplementary survey, the conspiracy mentality scale (Bruder et al., 2013) was also administered, which exhibited a Pearson correlation coefficient of 0.57 with the BCT scale. These results imply that the scales assess closely related yet distinct concepts. For detailed results, see Section 7 of the Supplementary Material.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation and calculation of composite concept scales\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe concepts of MSA and PS are both constituted by two of the more common concepts. To test the validity of the composite concepts, an identical procedure was employed as that used for the BCT scale. The dataset was randomly divided into two portions for the purposes of EFA and CFA. The optimal number of factors in the exploratory factor analysis (EFA) was determined using parallel analysis with polychoric correlations (Timmerman \u0026amp; Lorenzo-Seva, 2011). The factor structure was examined using EFA with oblique oblimin rotation, and reliability was calculated using McDonald\u0026rsquo;s omega. The other half of the data was subjected to CFA using the WLSMW method. Given that both composite concepts comprised a mere two factors, an equal loading condition was established for both factors. With regard to MSA, the trust factor was further structured into three sub-factors in accordance with the thematic focus (media, politics, scientists). A graph of the factor structure of MSA is provided in Figure 1 in the Supplementary Material Section 1. All calculations were conducted (a) for complete observations and (b) with imputed missing values instead of \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; responses. For detailed results, see Sections 4 and 6 of the Supplementary Material.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn order to evaluate the number of dimensions for MCO, optimal parallel analysis was also employed (Timmerman \u0026amp; Lorenzo-Seva, 2011). In this case, the results indicate the presence of a one-to-three factor solution with respect to the confidence interval. However, none of the solutions derived from EFA align with the conceptualization of the division between mainstream and alternative media observed in the Czech media environment. Consequently, the items were categorized as either alternative or mainstream media in accordance with the extant literature (\u0026Scaron;tětka et al., 2021). It is therefore evident that MCO is not a standard psychometric scale but, rather, a theoretically constructed index. For a detailed account of the results, see Section 5 of the Supplementary Material.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStandard measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA shortened version of the Personal Need for Structure Scale (PNSS) (Neuberg \u0026amp; Newsom, 1993) was employed, based on the results of the validation study conducted in the Czech Republic (Stehl\u0026iacute;k, 2017). The cognitive reflection test is based on the original version(Frederick, 2005) and its subsequent extensions (Primi et al., 2015; Toplak et al., 2014). The selection of items was based on the validity test in the Czech setting (Stehl\u0026iacute;k, 2017). Anxiety was measured using the standard GAD-7 scale (Spitzer et al., 2006), and information literacy was measured using a previously developed shortened scale (Jones-Jang et al., 2021) derived from the original information literacy test (Boh Podgornik et al., 2016). McDonald\u0026rsquo;s omega was calculated for all these scales, and unidimensionality was confirmed by CFA using the WLSMW method. For detailed results, see Section 3 of the Supplementary Material.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 | Overview of all used variables.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u003cstrong\u003eMcDonald\u0026rsquo;s omega\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRobust CFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRobust RMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of items\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dimensions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eDependent variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eBelief in conspiracy theories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.046\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 81px;\"\u003e\n \u003cp\u003eStandard concepts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003ePersonal need for structure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eInformation literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eCognitive reflection test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 81px;\"\u003e\n \u003cp\u003eComposite concepts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eMacro-social adhesion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003ePseudoscientific spirituality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eMedia consumption orientation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 81px;\"\u003e\n \u003cp\u003eSocio-demographic variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 177px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eSize of municipality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eNet personal income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 91px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eComputation and normalization of measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eScale scores were calculated as the mean of responses to all items. In the case of one-dimensional scales, respondents who did not respond to more than half of the items were excluded from the analysis. For multidimensional scales, respondents who did not respond to more than half of the items in all subscales were excluded from the analysis. All variables were normalized to a range between 0 and 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of the strength of the correlates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree measures were used to assess the strength of the relationship with the BCT scale. First, we used Pearson\u0026rsquo;s correlation coefficient, which measures the strength of the relationship of each correlate separately. In the case of the correlation between gender and the BCT scale, the biserial correlation was used. Second, we adopted a multiple linear regression where all correlates are entered at once (Model 2 in Supplementary Material Section 1 Table 1). B-coefficients are presented, which are comparable due to the normalization of all variables to the range 0\u0026ndash;1. The standardized beta coefficients are also presented in Supplementary Material Section 1 Table 1. To provide information on the contribution of composite concepts to the explained variance, a model with only control variables was also estimated (Model 1 in Supplementary Material Section 1 Table 1). Third, the general dominance (Azen \u0026amp; Budescu, 2003) is presented, which expresses the average explained R\u003csup\u003e2\u003c/sup\u003e within all subsets of the regression models. All three measures have bootstrapped confidence intervals that take into account quota sampling (Sturgis et al., 2017) with 2,000 resamples. See Section 8 of the Supplementary Material for detailed results and tests of linear regressions assumptions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExploring interactions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo test for interactions between the composite concepts, we ran two regressions (Model 3 and Model 4 in Supplementary Material Section 1 Table 1). All three possible interactions between composite concepts are included in Model 3. To test whether the interactions were driven by the interaction of other variables, we added terms in Model 4 that were identified using the adaptive LASSO (Beiser-McGrath \u0026amp; Beiser-McGrath, 2020) method at the 99% significance level. Statistical significance was again assessed using bootstrapping to account for quota sampling. We also performed a test for linearity of the interactions (Beiser-McGrath \u0026amp; Beiser-McGrath, 2023).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAs we measured BCT using a set of statements (see Methods for details), it was first necessary to test whether the dependent variable could be considered a scale, using exploratory (EFA) and confirmatory factor analysis (CFA). As a result, conspiracy statements formed a clear one-dimensional scale with very good reliability. We can conclude that there is a latent variable behind the measurement statements and, therefore, they refer to the one phenomenon they measure.\u003c/p\u003e\n\u003cp\u003eThe justification for combining the individual correlates into composite concepts was evaluated for all three composite concepts (RQ1). The initial step was to conduct EFA. The two-factor structure observed for macro-social adhesion (MSA) and pseudoscientific spirituality (PS) was consistent with the underlying conceptualization of these constructs. This structure was subsequently confirmed in the CFA, which showed good model fit values (see Table 1). However, in order to obtain good fit values for MSA, it was necessary to split trust into three thematic sub-factors (see Supplementary Material Section 1 Figure 1). Overall, MSA and PS showed clear factor structures and good reliability values, justifying their use as single scales from a psychometric standpoint.\u003c/p\u003e\n\u003cp\u003eThe situation was distinct with regard to media consumption orientation (MCO). As anticipated, EFA revealed that MCO did not exhibit a straightforward factor structure. This was predominantly attributable to the impact of media consumption intensity rather than the structure of media consumption itself. Nevertheless, MCO is regarded as a theoretically derived index and can be employed even though it is not a standard scale. The comprehensive results of the factor structure exploration of the composite concepts and the dependent variable are presented in the Supplementary Material Sections 4\u0026ndash;6.\u003c/p\u003e\n\u003cp\u003eTo find out how the composite concepts relate to BCT (RQ2), we created several models. We first estimated a model in which only control variables (i.e., sociodemographic variables and other expected correlates) were entered (Model 1 in Supplementary Material Section 1 Table 1). This model explains 14% of the variance in the data, and the independent variable with the largest B coefficient is information literacy (B = -0.2). This means that information literacy has the strongest association with BCT in this model, with those who are more information literate less likely to believe in conspiracy theories. In comparison, the model with added composite concepts (Model 2) explains 52% of the variance in the data. Such a high level of explained variance is highly unusual for this type of model (Brandenstein, 2022) and indicates a strong association of the added concepts with BCT. The strength of correlates of Model 2 is summarized in Figure 2. The figure shows in each column (1) Pearson correlations, (2) B coefficients, and (3) general dominance (GD), which reflects additional contributions to explained R\u003csup\u003e2\u003c/sup\u003e of each predictor within all subsets of regression models (Azen \u0026amp; Budescu, 2003). By far the most strongly associated of the three composite concepts with BCT is MSA (r = -0.67, B = -0.7, GD = 0.31). The other two most strongly related variables are MCO (r = 0.41, B = 0.23, GD = 0.07) and PS (r = 0.32, B = 0.23, GD = 0.07)\u0026mdash;that is, other composite concepts. These results mean that the higher MSA, the less BCT; the higher the pseudoscientific spirituality, the more BCT. For MCO, if there is a tendency to consume alternative media, there is more BCT. The other correlates explain BCT much less; they are moderately or weakly correlated with BCT and lose most of their substantial association in the regression model. The difference is even more evident in the case of general dominance, where no other variable except the composite concepts exceeds a contribution of 2% of the explained variance. Thus, the studied composite concepts are clearly dominant independent variables compared to the others, indicating their very high interdependence with BCT. Figure 3 in the Supplementary Material Section 1 shows the same analysis of the strength of association of each correlate when the composite concepts are decomposed into pairs of standard correlates. The order of importance of the decomposed correlates in terms of B-coefficients and GD remains the same as for the composite concepts. This result also justifies the validity of merging the correlates into composite concepts and shows that the association with BCT is not realized by only one of its parts.\u003c/p\u003e\n\u003cp\u003e[FIGURE 2 ABOUT HERE]\u003c/p\u003e\n\u003cp\u003eThe next step in the analysis was to explore how the composite concepts interact with each other in predicting BCT (RQ3). When using composite concepts, there are only three possible interactions to explore: MSA with PS, MSA with MCO, and PS with MCO. Regression models were used again to test the interactions. All three interactions between composite concepts are included in Model 3 (see Table 1 in the see Supplementary Material Section 1), and two additional terms identified using the adaptive LASSO method are included in Model 4. The only statistically significant interaction in both models is between MSA and MCO. The effect of the interaction between MSA and MCO is shown in Figure 3. At low MSA values, the inclination toward alternative sources of information further increases the already high BCT value. Although the interaction between MSA and PS is statistically significant in Model 3 (p = 0.004), it loses its significance when the terms identified by adaptive LASSO are added.\u003c/p\u003e\n\u003cp\u003eThe terms identified by adaptive LASSO are primarily used to check that the interactions under investigation are not an artifact of the influence of other variables (Beiser-McGrath \u0026amp; Beiser-McGrath, 2020). However, they are also of substantive interest as they are additional statistically significant regression terms. The terms identified are the quadratic relationship between PS and BCT (see Figure 4) and the interaction between MSA and age (see Figure 3 in the see Supplementary Material Section 1). In the case of the quadratic relationship between PS and BCT, most of the increase in BCT is realized at higher levels of PS, while the increase is much smaller at lower levels. Regarding the interaction between MSA and age, age is not related to BCT when MSA is high; however, when MSA is low, older people are more likely to believe in conspiracy theories. Detailed results of the regression analysis and assumption tests can be found in Supplementary Material Section 8.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;[FIGURE 3 ABOUT HERE]\u003c/p\u003e\n\u003cp\u003e[FIGURE 4 ABOUT HERE]\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eConspiracy theories are extensively studied, particularly during periods of significant social upheaval, such as migration crises, the COVID-19 pandemic, and shifts in political preferences toward populist or authoritarian parties. Multiple disciplines have examined the tendency to believe in conspiracy theories, resulting in a broad yet theoretically fragmented body of knowledge. It is therefore essential to not only develop theoretical frameworks but also to rigorously test and refine them. In this article, we build upon the socio-epistemic model (SoEM) framework with the aim of providing a thorough explanation of belief in conspiracy theories (BCT) while reducing the number of correlates studied in the models. To accomplish this, we developed and tested composite concepts based on existing correlates. The formation and integration of these concepts into the SoEM is based on the idea that an interpretive framework is a complex system. In such systems, individual entities are characterized by feedback relationships, and emergence can be observed. This implies that larger entities may emerge from the aggregation of smaller original parts (Ladyman et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In this way, individual correlates, which previously existed in isolation, can be combined into composite concepts based on theoretical assumptions and empirical testing.\u003c/p\u003e \u003cp\u003eThe utilization of representative survey data from the Czech Republic has demonstrated that the three proposed composite concepts represent a valuable approach for the investigation of BCT. Furthermore, these concepts exhibit a markedly stronger association with BCT in comparison to the other variables included. The model that includes all three composite concepts (Model 2) exhibits an unusually high level of explained variance. First, the most dominant concept, which is most strongly associated with BCT, is macro-social adhesion (MSA). It is not the intention of this study to assume a unidirectional causal relationship between the composite concepts and BCT. Rather, it is proposed that the composite concepts, in conjunction with BCT, constitute a complex system for interpreting social reality. This complex system can be interpreted through the lens of socio-epistemic model (SoEM), which consists of two basic components: epistemic mistrust and information processing. In contrast to SoEM, we extend the concept of epistemic mistrust in traditional authorities to MSA, which includes anomie. Second, in addition to SoEM, we include additional sources for interpreting social reality and information processing, namely pseudoscientific spirituality and media consumption orientation. This substantial extension of the socio-epistemic model (SoEM) is therefore termed the extended socio-epistemic model (ESoEM).\u003c/p\u003e \u003cp\u003eThe findings of our investigation into the composite concepts that constitute ESoEM are schematically summarized in the black section of Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The association between MSA and BCT is notably robust. The association is strong enough to justify the assertion that MSA is an essential component in explaining BCT. A number of studies have confirmed the strength of the relationship between institutional trust or anomie and BCT (Biddlestone et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Brandenstein, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mulukom et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, to the best of our knowledge, institutional trust and anomie have never been examined in the same study. Our results demonstrate that both components of MSA play an important role in understanding BCT, that they are not mutually substitutable, and that it is justified to combine them into a single composite concept.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo some extent, the strength of the association is undoubtedly attributable to the impact of conspiracy theories on MSA, as evidenced by experimental studies examining the influence of conspiracy theories on trust (Invernizzi \u0026amp; Mohamed, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kim \u0026amp; Cao, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, other studies demonstrate that trust in institutions is a remarkably stable phenomenon (Devine \u0026amp; Valgar\u0026eth;sson, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, the roots of distrust in the system are found to originate, at least in part, from early life experiences (Moffitt et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, BCT is influenced by characteristics of the social system, including the level of corruption (Alper, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, a potential strategy for countering the influence of conspiracy theories may lie in a long-term effort to enhance trust in public institutions and foster a sense of attachment to the broader macro-social system (Pierre, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe observed interaction between MSA and age is challenging to interpret, as the role of age in this case may be either a consequence of generation or a reflection of the stage of life. With regard to the stage of life rather than generation, it is conceivable that respondents in later life may feel disadvantaged and weakened. An alternative explanation is that the cognitive abilities of older respondents may decline. Nevertheless, cognitive ability is assessed by two additional variables in the model, and the interaction between age and MSA remains statistically significant. No interaction between MSA and either information literacy or the cognitive reflection test was identified. The ESoEM framework permits a second interpretation of this interaction. The interaction between age and MSA could be an effect of time, during which the association between MSA and BCT deepens in a feedback loop. However, this hypothesis would require testing in longitudinal data. It is also possible that this is a situation specific to the country context, and further testing of the model is needed in other countries.\u003c/p\u003e \u003cp\u003eThe composite concepts of MCO (media consumption orientation) and PS (pseudoscientific spirituality), which serve as sources for interpretation of social reality, exhibit qualitatively distinct relationships with BCT, despite the strength of their linear association being comparable. MCO interact with MSA and reinforce each other in association with BCT. A comparable process has been documented in the context of electoral misinformation (Mont\u0026rsquo;Alverne et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It appears that MSA and MCO can engage in a dynamic interplay, which may serve as a basis for changes in the interpretation of social reality. While the association between MSA and BCT is likely to be relatively stable, the relationship with MCO may exhibit greater dynamism.\u003c/p\u003e \u003cp\u003eThe quadratic relationship between PS and BCT is an intriguing consequence of the investigation into interactions. Lower-level PS is not related to a change in worldview, but higher-level PS is. This outcome suggests the existence of a tipping point at which alternative spirituality could play a larger role in changing the perception of social reality.\u003c/p\u003e \u003cp\u003eThe observation highlights the importance of addressing the possibility of offering counter-statements to conspiracy theories (Lazić \u0026amp; Žeželj, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It would be beneficial to investigate the optimal timing for the dissemination of these counter-statements in future research, as it is plausible that they are more effective when introduced at a time when interpretations of social situations are not yet fully established.\u003c/p\u003e \u003cp\u003eThe results indicate that cognitive reflection tests, information literacy, anxiety, and sociodemographic variables are moderately correlated with BCT. However, when composite concepts are controlled for, the effect disappears. This does not imply that these variables are irrelevant to BCT; rather, it suggests that they are external to the complex, interrelated system that interprets social reality. Future research could investigate how these external variables influence and condition the gradual formation of the system over time.\u003c/p\u003e \u003cp\u003eIn addition to ESoEM, there are other theoretical explanations for BCT. The existential threat model (van Prooijen, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) posits that conspiracy theories emerge and proliferate during periods of crisis, when social events engender a sense of existential threat and prompt a process of sense-making. This aspect is consistent with the ESoEM framework because an unforeseen crisis challenges the MSA and the entire interpretive framework, creating a new situation that requires interpretation. Other theoretical frameworks for explaining BCT include explanations based on evolutionary tendencies to interpret situations conspiratorially (van Prooijen \u0026amp; van Vugt, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These explanations are not incompatible with ESoEM. The added value of ESoEM is that it places conspiracy theories in the context of a broader system for interpreting social reality. This allows for the consideration of biological and psychological dispositions as influencing and conditioning factors in the gradual construction of this system. Furthermore, the added value of our theoretical framework compared to these theories is that it can be used to categorize and simplify a larger number of the correlates under investigation.\u003c/p\u003e \u003cp\u003eIn conclusion, the findings of our study demonstrate that conceptualizing BCT as a constituent part of a comprehensive and intricate system for interpreting reality, simplified by composite concepts, represents a significant and valuable approach. Furthermore, it provides a number of research questions that warrant further investigation in future studies.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e[FIGURE \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eIt is important to acknowledge that this study is subject to several limitations, which may also provide directions for future research. First, it was not feasible to include all the correlates that have been used in previous research on conspiracy theories. To illustrate, narcissism (Stasielowicz, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), a dangerous worldview (Biddlestone et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and socio-political control (Brandenstein, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) are significantly correlated with BCT. Second, the ESoEM approach does not consider the influence of social identity (Van Bavel et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and intergroup conflict (van Prooijen \u0026amp; Douglas, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), which may also be integral to a complex system for interpreting social reality. Third, a further avenue for investigation would be to elaborate more theoretically and empirically on MSA. It would be beneficial to examine how the aforementioned variables, which were not included in this study, interact with MSA, as well as to investigate other policy contexts. The concept of MSA encompasses the concept of trust in institutions. Nevertheless, it is not implausible that these very institutions may, in fact, be complicit in the proliferation of conspiracy theories, particularly those of a political nature. Therefore, if institutions disseminate conspiracy theories, it is possible that there may be a positive correlation between high levels of institutional trust and BCT. This indicates that the empirical results may be reversed in different political contexts. It can be concluded that MSA, as proposed in this study, is currently applicable to stable liberal democracies and that further research is required to ascertain its suitability for different political contexts. It is also important to note that the MSA concept includes trust in public service media, which is not a universal phenomenon and may also manifest in various forms across different contexts. While these facts limit the generalizability of our findings, they highlight an important aspect of the social conditioning of BCT. Fourth, some respondents may endorse conspiracy items not because of genuine belief but as a form of political signaling or identity expression (Altay et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This poses a challenge for interpretation, as the same item endorsement may reflect different underlying motivations across individuals. Finally, it must be acknowledged that this is only a cross-sectional case study, which does not allow for the observation of the dynamics between variables. Further longitudinal and experimental research would therefore be beneficial, as would research in other countries, given that our case concerns only the Czech Republic.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003eThe study was approved by the Ethics Committee of the Institute of Sociology of the Czech Academy of Sciences.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available in anonymized version at https://osf.io/rj825/?view_only=53a4d90f18504758acc34e858be0c9c3\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANONYMIZED\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANONYMIZED\u003c/strong\u003e conceived the study. \u003cstrong\u003eANONYMIZED\u003c/strong\u003e designed the survey questionnaire. \u003cstrong\u003eANONYMIZED\u003c/strong\u003e analyzed data. \u003cstrong\u003eANONYMIZED\u003c/strong\u003e revised data analysis. \u003cstrong\u003eANONYMIZED\u003c/strong\u003e wrote the manuscript. All authors revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was conducted in accordance with relevant guidelines, namely the ICC/ESOMAR International Code on Market, Opinion and Social Research and Data Analytics , which sets out the standards for a comprehensive framework of self-regulation for those engaged in market, opinion and social research and data analytics. It sets out essential standards of ethical and professional conduct. The research was also conducted in accordance with the standards of SIMAR (Association of Market and Opinion Research Agencies). The data collection was carried out by the SIMAR member agency and compliance with the standards is monitored through regular inspections by the Association. All legal requirements (e.g. GDPR) were also met.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of \u003cstrong\u003eANONYMIZED\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained through online confirmation by the participant.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlper, S. (2023). There are higher levels of conspiracy beliefs in more corrupt countries. \u003cem\u003eEuropean Journal of Social Psychology\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(3), 503\u0026ndash;517. https://doi.org/10.1002/ejsp.2919\u003c/li\u003e\n\u003cli\u003eAltay, S., Berriche, M., \u0026amp; Acerbi, A. (2023). Misinformation on Misinformation: Conceptual and Methodological Challenges. \u003cem\u003eSocial Media + Society\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(1), 20563051221150412. https://doi.org/10.1177/20563051221150412\u003c/li\u003e\n\u003cli\u003eAxt, J. R., Landau, M. J., \u0026amp; Kay, A. C. (2021). Fake news attributions as a source of nonspecific structure. In \u003cem\u003eThe psychology of fake news: Accepting, sharing, and correcting misinformation\u003c/em\u003e (pp. 220\u0026ndash;234). Routledge/Taylor \u0026amp; Francis Group. https://doi.org/10.4324/9780429295379-15\u003c/li\u003e\n\u003cli\u003eAzen, R., \u0026amp; Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. \u003cem\u003ePsychological Methods\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(2), 129\u0026ndash;148. https://doi.org/10.1037/1082-989X.8.2.129\u003c/li\u003e\n\u003cli\u003eBartsch, A., Neuberger, C., Stark, B., Karnowski, V., Maurer, M., Pentzold, C., Quandt, T., Quiring, O., \u0026amp; Schemer, C. (2025). Epistemic authority in the digital public sphere. An integrative conceptual framework and research agenda. \u003cem\u003eCommunication Theory\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(1), 37\u0026ndash;50. https://doi.org/10.1093/ct/qtae020\u003c/li\u003e\n\u003cli\u003eBeiser-McGrath, J., \u0026amp; Beiser-McGrath, L. F. (2020). Problems with products? Control strategies for models with interaction and quadratic effects. \u003cem\u003ePolitical Science Research and Methods\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(4), 707\u0026ndash;730. https://doi.org/10.1017/psrm.2020.17\u003c/li\u003e\n\u003cli\u003eBeiser-McGrath, J., \u0026amp; Beiser-McGrath, L. F. (2023). The Consequences of Model Misspecification for the Estimation of Nonlinear Interaction Effects. \u003cem\u003ePolitical Analysis\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(2), 278\u0026ndash;287. https://doi.org/10.1017/pan.2022.25\u003c/li\u003e\n\u003cli\u003eBergmann, E. (2018). \u003cem\u003eConspiracy \u0026amp; Populism: The Politics of Misinformation\u003c/em\u003e. Springer International Publishing. https://doi.org/10.1007/978-3-319-90359-0\u003c/li\u003e\n\u003cli\u003eBiddlestone, M., Green, R., Douglas, K. M., Azevedo, F., Sutton, R. M., \u0026amp; Cichocka, A. (2025). Reasons to believe: A systematic review and meta-analytic synthesis of the motives associated with conspiracy beliefs. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e151\u003c/em\u003e(1), 48\u0026ndash;87. https://doi.org/10.1037/bul0000463\u003c/li\u003e\n\u003cli\u003eBirchall, C. (2006). \u003cem\u003eKnowledge Goes Pop: From Conspiracy Theory to Gossip\u003c/em\u003e. Berg Publishers. https://doi.org/10.26530/OAPEN_390769\u003c/li\u003e\n\u003cli\u003eBoh Podgornik, B., Dolničar, D., \u0026Scaron;orgo, A., \u0026amp; Bartol, T. (2016). Development, testing, and validation of an information literacy test (ILT) for higher education. \u003cem\u003eJournal of the Association for Information Science and Technology\u003c/em\u003e, \u003cem\u003e67\u003c/em\u003e(10), 2420\u0026ndash;2436. https://doi.org/10.1002/asi.23586\u003c/li\u003e\n\u003cli\u003eBornand, T., \u0026amp; Klein, O. (2022). Political trust by individuals of low socioeconomic status: The key role of anomie. \u003cem\u003eSocial Psychological Bulletin\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e, e6897. https://doi.org/10.32872/spb.6897\u003c/li\u003e\n\u003cli\u003eBowes, S. M., Costello, T. H., \u0026amp; Tasimi, A. (2023). The Conspiratorial Mind: A Meta-Analytic Review of Motivational and Personological Correlates. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e149\u003c/em\u003e(5\u0026ndash;6), 259\u0026ndash;293. https://doi.org/10.1037/bul0000392\u003c/li\u003e\n\u003cli\u003eBrandenstein, N. (2022). Going beyond simplicity: Using machine learning to predict belief in conspiracy theories. \u003cem\u003eEuropean Journal of Social Psychology\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(5\u0026ndash;6), 910\u0026ndash;930. https://doi.org/10.1002/ejsp.2859\u003c/li\u003e\n\u003cli\u003eBruder, M., Haffke, P., Neave, N., Nouripanah, N., \u0026amp; Imhoff, R. (2013). Measuring Individual Differences in Generic Beliefs in Conspiracy Theories Across Cultures: Conspiracy Mentality Questionnaire. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 225. https://doi.org/10.3389/fpsyg.2013.00225\u003c/li\u003e\n\u003cli\u003eButter, M., \u0026amp; Knight, P. (2018). The History of Conspiracy Theory Research: A Review and Commentary. In J. E. Uscinski (Ed.), \u003cem\u003eConspiracy Theories and the People Who Believe Them\u003c/em\u003e (p. 0). Oxford University Press. https://doi.org/10.1093/oso/9780190844073.003.0002\u003c/li\u003e\n\u003cli\u003eCinelli, M., Etta, G., Avalle, M., Quattrociocchi, A., Di Marco, N., Valensise, C., Galeazzi, A., \u0026amp; Quattrociocchi, W. (2022). Conspiracy theories and social media platforms. \u003cem\u003eCurrent Opinion in Psychology\u003c/em\u003e, \u003cem\u003e47\u003c/em\u003e, 101407. https://doi.org/10.1016/j.copsyc.2022.101407\u003c/li\u003e\n\u003cli\u003eDelaney, C. (2005). The Spirituality Scale: Development and Psychometric Testing of a Holistic Instrument to Assess the Human Spiritual Dimension. \u003cem\u003eJournal of Holistic Nursing\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(2), 145\u0026ndash;167. https://doi.org/10.1177/0898010105276180\u003c/li\u003e\n\u003cli\u003eDevine, D., \u0026amp; Valgar\u0026eth;sson, V. O. (2023). Stability and change in political trust: Evidence and implications from six panel studies. \u003cem\u003eEuropean Journal of Political Research\u003c/em\u003e, \u003cem\u003e63\u003c/em\u003e(2), 478\u0026ndash;497. https://doi.org/10.1111/1475-6765.12606\u003c/li\u003e\n\u003cli\u003eDouglas, K. M., \u0026amp; Sutton, R. M. (2023). What are conspiracy theories? A definitional approach to their correlates, consequences, and communication. \u003cem\u003eAnnual Review of Psychology\u003c/em\u003e, \u003cem\u003e74\u003c/em\u003e, 271\u0026ndash;298. https://doi.org/10.1146/annurev-psych-032420-031329\u003c/li\u003e\n\u003cli\u003eDouglas, K. M., Uscinski, J. E., Sutton, R. M., Cichocka, A., Nefes, T., Ang, C. S., \u0026amp; Deravi, F. (2019). Understanding Conspiracy Theories. \u003cem\u003ePolitical Psychology\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(S1), 3\u0026ndash;35. https://doi.org/10.1111/pops.12568\u003c/li\u003e\n\u003cli\u003eDurkheim, \u0026Eacute;. (2002). \u003cem\u003eSuicide: A Study in Sociology\u003c/em\u003e. Routledge.\u003c/li\u003e\n\u003cli\u003eEnders, A. M., Diekman, A., Klofstad, C., Murthi, M., Verdear, D., Wuchty, S., \u0026amp; Uscinski, J. (2023). On modeling the correlates of conspiracy thinking. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1), 8325. https://doi.org/10.1038/s41598-023-34391-6\u003c/li\u003e\n\u003cli\u003eFasce, A., Avenda\u0026ntilde;o, D., \u0026amp; Adri\u0026aacute;n-Ventura, J. (2021). Revised and short versions of the pseudoscientific belief scale. \u003cem\u003eApplied Cognitive Psychology\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(3), 828\u0026ndash;832. https://doi.org/10.1002/acp.3811\u003c/li\u003e\n\u003cli\u003eForberg, P. L. (2022). From the Fringe to the Fore: An Algorithmic Ethnography of the Far-Right Conspiracy Theory Group QAnon. \u003cem\u003eJournal of Contemporary Ethnography\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(3), 291\u0026ndash;317. https://doi.org/10.1177/08912416211040560\u003c/li\u003e\n\u003cli\u003eFrederick, S. (2005). Cognitive Reflection and Decision Making. \u003cem\u003eJournal of Economic Perspectives\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(4), 25\u0026ndash;42. https://doi.org/10.1257/089533005775196732\u003c/li\u003e\n\u003cli\u003eFurstova, J., Malinakova ,Klara, Sigmundova ,Dagmar, \u0026amp; and Tavel, P. (2021). Czech Out the Atheists: A Representative Study of Religiosity in the Czech Republic. \u003cem\u003eThe International Journal for the Psychology of Religion\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(4), 288\u0026ndash;306. https://doi.org/10.1080/10508619.2020.1844967\u003c/li\u003e\n\u003cli\u003eGligorić, V., da Silva, M. M., Eker, S., van Hoek, N., Nieuwenhuijzen, E., Popova, U., \u0026amp; Zeighami, G. (2021). The usual suspects: How psychological motives and thinking styles predict the endorsement of well-known and COVID-19 conspiracy beliefs. \u003cem\u003eApplied Cognitive Psychology\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(5), 1171\u0026ndash;1181. https://doi.org/10.1002/acp.3844\u003c/li\u003e\n\u003cli\u003eHarambam, J. (2020). \u003cem\u003eContemporary Conspiracy Culture\u003c/em\u003e. Routledge.\u003c/li\u003e\n\u003cli\u003eHarambam, J., \u0026amp; Aupers, S. (2015). Contesting epistemic authority: Conspiracy theories on the boundaries of science. \u003cem\u003ePublic Understanding of Science\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(4), 466\u0026ndash;480. https://doi.org/10.1177/0963662514559891\u003c/li\u003e\n\u003cli\u003eHealy, K. (2017). Fuck Nuance. \u003cem\u003eSociological Theory\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(2), 118\u0026ndash;127. https://doi.org/10.1177/0735275117709046\u003c/li\u003e\n\u003cli\u003eInvernizzi, G. M., \u0026amp; Mohamed, A. E. (2023). Trust Nobody: How Voters React to Conspiracy Theories. \u003cem\u003eJournal of Experimental Political Science\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(2), 201\u0026ndash;208. https://doi.org/10.1017/XPS.2022.11\u003c/li\u003e\n\u003cli\u003eJasinskaja-Lahti, I., \u0026amp; Jetten, J. (2019). Unpacking the relationship between religiosity and conspiracy beliefs in Australia. \u003cem\u003eBritish Journal of Social Psychology\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e(4), 938\u0026ndash;954. https://doi.org/10.1111/bjso.12314\u003c/li\u003e\n\u003cli\u003eJones-Jang, S. M., Mortensen, T., \u0026amp; Liu, J. (2021). Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don\u0026rsquo;t. \u003cem\u003eAmerican Behavioral Scientist\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(2), 371\u0026ndash;388. https://doi.org/10.1177/0002764219869406\u003c/li\u003e\n\u003cli\u003eKapusta, J., \u0026amp; Kostićov\u0026aacute;, Z. M. (2021). From the Trees to the Wood: Alternative Spirituality as an Emergent \u0026lsquo;Official Religion\u0026rsquo;? \u003cem\u003eJournal of Religion in Europe\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(3\u0026ndash;4), 187\u0026ndash;213. https://doi.org/10.1163/18748929-20211525\u003c/li\u003e\n\u003cli\u003eKim, M., \u0026amp; Cao, X. (2016). The Impact of Exposure to Media Messages Promoting Government Conspiracy Theories on Distrust in the Government: Evidence from a Two-Stage Randomized Experiment. \u003cem\u003eInternational Journal of Communication\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(0), Article 0.\u003c/li\u003e\n\u003cli\u003eKnight, E., \u0026amp; Tsoukas, H. (2019). When Fiction Trumps Truth: What \u0026lsquo;post-truth\u0026rsquo; and \u0026lsquo;alternative facts\u0026rsquo; mean for management studies. \u003cem\u003eOrganization Studies\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(2), 183\u0026ndash;197. https://doi.org/10.1177/0170840618814557\u003c/li\u003e\n\u003cli\u003eLadyman, J., Lambert, J., \u0026amp; Wiesner, K. (2013). What is a complex system? \u003cem\u003eEuropean Journal for Philosophy of Science\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(1), 33\u0026ndash;67. https://doi.org/10.1007/s13194-012-0056-8\u003c/li\u003e\n\u003cli\u003eLazić, A., \u0026amp; Žeželj, I. (2021). A systematic review of narrative interventions: Lessons for countering anti-vaccination conspiracy theories and misinformation. \u003cem\u003ePublic Understanding of Science\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(6), 644\u0026ndash;670. https://doi.org/10.1177/09636625211011881\u003c/li\u003e\n\u003cli\u003eLeibovitz, T., Shamblaw, A. L., Rumas, R., \u0026amp; Best, M. W. (2021). COVID-19 conspiracy beliefs: Relations with anxiety, quality of life, and schemas. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e, \u003cem\u003e175\u003c/em\u003e, 110704. https://doi.org/10.1016/j.paid.2021.110704\u003c/li\u003e\n\u003cli\u003eMahl, D., Sch\u0026auml;fer, M. S., \u0026amp; Zeng, J. (2023). Conspiracy theories in online environments: An interdisciplinary literature review and agenda for future research. \u003cem\u003eNew Media \u0026amp; Society\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(7), 1781\u0026ndash;1801. https://doi.org/10.1177/14614448221075759\u003c/li\u003e\n\u003cli\u003eMari, S., Gil de Z\u0026uacute;\u0026ntilde;iga, H., Suerdem, A., Hanke, K., Brown, G., Vilar, R., Boer, D., \u0026amp; Bilewicz, M. (2022). Conspiracy Theories and Institutional Trust: Examining the Role of Uncertainty Avoidance and Active Social Media Use. \u003cem\u003ePolitical Psychology\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(2), 277\u0026ndash;296. https://doi.org/10.1111/pops.12754\u003c/li\u003e\n\u003cli\u003eMarwick, A. E., \u0026amp; Partin, W. C. (2022). Constructing alternative facts: Populist expertise and the QAnon conspiracy. \u003cem\u003eNew Media \u0026amp; Society\u003c/em\u003e, 14614448221090201. https://doi.org/10.1177/14614448221090201\u003c/li\u003e\n\u003cli\u003eMerton, R. K. (1938). Social Structure and Anomie. \u003cem\u003eAmerican Sociological Review\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(5), 672\u0026ndash;682. https://doi.org/10.2307/2084686\u003c/li\u003e\n\u003cli\u003eMoffitt, T. E., Caspi, A., Ambler, A., Bourassa, K., Harrington, H., Hogan, S., Houts, R., Ramrakha, S., Wood, S. L., \u0026amp; Poulton, R. (2022). Deep-seated psychological histories of COVID-19 vaccine hesitance and resistance. \u003cem\u003ePNAS Nexus\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(2), pgac034. https://doi.org/10.1093/pnasnexus/pgac034\u003c/li\u003e\n\u003cli\u003eMont\u0026rsquo;Alverne, C., Ross Arguedas, A., Banerjee, S., Toff, B., Fletcher, R., \u0026amp; Nielsen, R. (2023). The Electoral Misinformation Nexus: How news consumption, platform use, and trust in news influence belief in electoral misinformation. \u003cem\u003ePublic Opinion Quarterly\u003c/em\u003e, \u003cem\u003e88\u003c/em\u003e, 681\u0026ndash;707.\u003c/li\u003e\n\u003cli\u003eMoulding, R., Nix-Carnell, S., Schnabel, A., Nedeljkovic, M., Burnside, E. E., Lentini, A. F., \u0026amp; Mehzabin, N. (2016). Better the devil you know than a world you don\u0026rsquo;t? Intolerance of uncertainty and worldview explanations for belief in conspiracy theories. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e, 345\u0026ndash;354. https://doi.org/10.1016/j.paid.2016.04.060\u003c/li\u003e\n\u003cli\u003eMulukom, V., Pummerer, L., Alper, Bai, H., Čavojov\u0026aacute;, V., J, F., Cs, K., Lb, L., Ejc, L., G, M., I, P. B., J, \u0026Scaron;., \u0026amp; I, Ž. (2022). Antecedents and consequences of COVID-19 conspiracy beliefs: A systematic review. \u003cem\u003eSocial Science \u0026amp; Medicine\u003c/em\u003e, \u003cem\u003e301\u003c/em\u003e, 114912. https://doi.org/10.1016/j.socscimed.2022.114912\u003c/li\u003e\n\u003cli\u003eNeuberg, S. L., \u0026amp; Newsom, J. T. (1993). Personal need for structure: Individual differences in the desire for simpler structure. \u003cem\u003eJournal of Personality and Social Psychology\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(1), 113\u0026ndash;131. https://doi.org/10.1037/0022-3514.65.1.113\u003c/li\u003e\n\u003cli\u003eNord, M., Lundstedt, M., Altman, D., Angiolillo, F., Borella, C., Fernandes, T., Gastaldi, L., Good God, A., Natsika, N., \u0026amp; Lindberg, S. I. (2024). \u003cem\u003eDemocracy Report 2024: Democracy Winning and Losing at the Ballot\u003c/em\u003e. V-Dem Institute. https://www.v-dem.net/documents/43/v-dem_dr2024_lowres.pdf\u003c/li\u003e\n\u003cli\u003ePennycook, G., \u0026amp; Rand, D. G. (2019). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. \u003cem\u003eCognition\u003c/em\u003e, \u003cem\u003e188\u003c/em\u003e, 39\u0026ndash;50. https://doi.org/10.1016/j.cognition.2018.06.011\u003c/li\u003e\n\u003cli\u003ePierre, J. M. (2020). Mistrust and misinformation: A two-component, socio-epistemic model of belief in conspiracy theories. \u003cem\u003eJournal of Social and Political Psychology\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(2), 617\u0026ndash;641. https://doi.org/10.5964/jspp.v8i2.1362\u003c/li\u003e\n\u003cli\u003ePierre, J. M. (2023). Conspiracy Theory Belief: A Sane Response to an Insane World? \u003cem\u003eReview of Philosophy and Psychology\u003c/em\u003e. https://doi.org/10.1007/s13164-023-00716-7\u003c/li\u003e\n\u003cli\u003ePilch, I., Turska-Kawa, A., Wardawy, P., Olszanecka-Marmola, A., \u0026amp; Smołkowska-Jędo, W. (2023). Contemporary trends in psychological research on conspiracy beliefs. A systematic review. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e, 1075779.\u003c/li\u003e\n\u003cli\u003ePopper, K. (1972). \u003cem\u003eConjectures and Refutations\u003c/em\u003e (4th ed.). Routledge Kegan Paul.\u003c/li\u003e\n\u003cli\u003ePrimi, C., Morsanyi, K., Chiesi, F., Donati, M. A., \u0026amp; Hamilton, J. (2015). The Development and Testing of a New Version of the Cognitive Reflection Test Applying Item Response Theory (IRT). \u003cem\u003eJournal of Behavioral Decision Making\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(5), 453\u0026ndash;469. https://doi.org/10.1002/bdm.1883\u003c/li\u003e\n\u003cli\u003eRobertson, D. G. (2024). \u003cem\u003eReligion and Conspiracy Theories: An Introduction\u003c/em\u003e. Routledge. https://doi.org/10.4324/9781003329992\u003c/li\u003e\n\u003cli\u003eRobinson, J. P., Shaver, P. R., Wrightsman, L. S., \u0026amp; Andrews, F. M. (1991). \u003cem\u003eMeasures of personality and social psychological attitudes\u003c/em\u003e. Academic Press.\u003c/li\u003e\n\u003cli\u003eRSF. (2024). \u003cem\u003e2024 World Press Freedom Index \u0026ndash; journalism under political pressure\u003c/em\u003e. https://rsf.org/en/2024-world-press-freedom-index-journalism-under-political-pressure\u003c/li\u003e\n\u003cli\u003eSpitzer, R. L., Kroenke, K., Williams, J. B. W., \u0026amp; L\u0026ouml;we, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. \u003cem\u003eArchives of Internal Medicine\u003c/em\u003e, \u003cem\u003e166\u003c/em\u003e(10), 1092\u0026ndash;1097. https://doi.org/10.1001/archinte.166.10.1092\u003c/li\u003e\n\u003cli\u003eSrole, L. (1956). Social Integration and Certain Corollaries: An Exploratory Study. \u003cem\u003eAmerican Sociological Review\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(6), 709\u0026ndash;716. https://doi.org/10.2307/2088422\u003c/li\u003e\n\u003cli\u003eStasielowicz, L. (2022). Who believes in conspiracy theories? A meta-analysis on personality correlates. \u003cem\u003eJournal of Research in Personality\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e, 104229. https://doi.org/10.1016/j.jrp.2022.104229\u003c/li\u003e\n\u003cli\u003eStehl\u0026iacute;k, L. (2017). \u003cem\u003eVALIDATION OF BAYESIAN MODEL OF CAUSAL INFERENCES MADE ON THE BASIS OF PERCEIVED COINCIDENCES\u003c/em\u003e [Univerzita Karlova, Filozofick\u0026aacute; fakulta]. https://dspace.cuni.cz/handle/20.500.11956/95409\u003c/li\u003e\n\u003cli\u003eSteppat, D., Castro, L., \u0026amp; Esser, F. (2023). What News Users Perceive as \u0026lsquo;Alternative Media\u0026rsquo; Varies between Countries: How Media Fragmentation and Polarization Matter. \u003cem\u003eDigital Journalism\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(5), 741\u0026ndash;761. https://doi.org/10.1080/21670811.2021.1939747\u003c/li\u003e\n\u003cli\u003e\u0026Scaron;tětka, V., Maz\u0026aacute;k, J., \u0026amp; Vochocov\u0026aacute;, L. (2021). \u0026ldquo;Nobody Tells us what to Write about\u0026rdquo;: The Disinformation Media Ecosystem and its Consumers in the Czech Republic. \u003cem\u003eJavnost - The Public\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(1), 90\u0026ndash;109. https://doi.org/10.1080/13183222.2020.1841381\u003c/li\u003e\n\u003cli\u003e\u0026Scaron;tětka, V., \u0026amp; Mihelj, S. (2024). \u003cem\u003eThe Illiberal Public Sphere: Media in Polarized Societies\u003c/em\u003e. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54489-7\u003c/li\u003e\n\u003cli\u003eStr\u0026ouml;mb\u0026auml;ck, J., Broda, E., Bouchafra, S., Johansson, S., Rettenegger, G., \u0026amp; Lindgren, E. (2023). Conspiracy thinking and the role of media use: Exploring the antecedents of conspiratorial predispositions. \u003cem\u003eEuropean Journal of Communication\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(3), 255\u0026ndash;271. https://doi.org/10.1177/02673231221122951\u003c/li\u003e\n\u003cli\u003eSturgis, P., Kuha, J., Baker, N., Callegaro, M., Fisher, S., Green, J., Jennings, W., Lauderdale, B. E., \u0026amp; Smith, P. (2017). An assessment of the causes of the errors in the 2015 UK general election opinion polls. \u003cem\u003eJournal of the Royal Statistical Society: Series A (Statistics in Society)\u003c/em\u003e, \u003cem\u003e181\u003c/em\u003e(3), 757\u0026ndash;781. https://doi.org/10.1111/rssa.12329\u003c/li\u003e\n\u003cli\u003eSutton, R. M., \u0026amp; Douglas, K. M. (2022). Rabbit Hole Syndrome: Inadvertent, accelerating, and entrenched commitment to conspiracy beliefs. \u003cem\u003eCurrent Opinion in Psychology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e, 101462. https://doi.org/10.1016/j.copsyc.2022.101462\u003c/li\u003e\n\u003cli\u003eSyrov\u0026aacute;tka, J. (2023). Czech Conspiracy Websites as Agents of Illiberalism: Case study of Parliamentary Elections 2021. \u003cem\u003eCENTRAL EUROPEAN JOURNAL FOR CONTEMPORARY RELIGION\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), 25\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eTimmerman, M. E., \u0026amp; Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. \u003cem\u003ePsychological Methods\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(2), 209\u0026ndash;220. https://doi.org/10.1037/a0023353\u003c/li\u003e\n\u003cli\u003eToplak, M. E., West, R. F., \u0026amp; Stanovich, K. E. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. \u003cem\u003eThinking \u0026amp; Reasoning\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e(2), 147\u0026ndash;168. https://doi.org/10.1080/13546783.2013.844729\u003c/li\u003e\n\u003cli\u003eUrb\u0026aacute;nikov\u0026aacute;, M., \u0026amp; Smejkal, K. (2023). Trust and Distrust in Public Service Media: A Case Study From the Czech Republic. \u003cem\u003eMedia and Communication\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(4), 297\u0026ndash;307. https://doi.org/10.17645/mac.v11i4.7053\u003c/li\u003e\n\u003cli\u003eUscinski, J., Enders, A., Diekman, A., Funchion, J., Klofstad, C., Kuebler, S., Murthi, M., Premaratne, K., Seelig, M., Verdear, D., \u0026amp; Wuchty, S. (2022). The psychological and political correlates of conspiracy theory beliefs. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), Article 1. https://doi.org/10.1038/s41598-022-25617-0\u003c/li\u003e\n\u003cli\u003eVan Bavel, J. J., Rathje, S., Vlasceanu, M., \u0026amp; Pretus, C. (2024). Updating the identity-based model of belief: From false belief to the spread of misinformation. \u003cem\u003eCurrent Opinion in Psychology\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e, 101787. https://doi.org/10.1016/j.copsyc.2023.101787\u003c/li\u003e\n\u003cli\u003evan Prooijen, J.-W. (2020). An Existential Threat Model of Conspiracy Theories. \u003cem\u003eEuropean Psychologist\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(1), 16\u0026ndash;25. https://doi.org/10.1027/1016-9040/a000381\u003c/li\u003e\n\u003cli\u003evan Prooijen, J.-W., \u0026amp; Douglas, K. M. (2018). Belief in conspiracy theories: Basic principles of an emerging research domain. \u003cem\u003eEuropean Journal of Social Psychology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(7), 897\u0026ndash;908. https://doi.org/10.1002/ejsp.2530\u003c/li\u003e\n\u003cli\u003evan Prooijen, J.-W., \u0026amp; van Vugt, M. (2018). Conspiracy Theories: Evolved Functions and Psychological Mechanisms. \u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(6), 770\u0026ndash;788. https://doi.org/10.1177/1745691618774270\u003c/li\u003e\n\u003cli\u003eWaisbord, S. (2018). Truth is What Happens to News: On journalism, fake news, and post-truth. \u003cem\u003eJournalism Studies\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(13), 1866\u0026ndash;1878. https://doi.org/10.1080/1461670X.2018.1492881\u003c/li\u003e\n\u003cli\u003eWard, C., \u0026amp; Voas, D. (2011). The Emergence of Conspirituality. \u003cem\u003eJournal of Contemporary Religion\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(1), 103\u0026ndash;121. https://doi.org/10.1080/13537903.2011.539846\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"conspiracy theories, trust, anomie, media consumption","lastPublishedDoi":"10.21203/rs.3.rs-5682677/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5682677/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBelief in conspiracy theories (BCT) negatively impacts various aspects of personal and public life, making it a significant subject of research. Previous studies, spanning multiple disciplines, have been predominantly empirical, resulting in considerable fragmentation in both analyses and theoretical foundations. Our paper seeks to systematize research on BCT by introducing a socio-epistemic model (SoEM) and empirically developing this theoretical framework using composite concepts. We introduce three composite concepts: macro-social adhesion, pseudoscientific spirituality, and media consumption orientation, each formed by combining two standard concepts. This approach enhances the analysis of interactions between concepts and nonlinear relationships. Using cross-sectional data from the Czech Republic (N\u0026thinsp;=\u0026thinsp;3,880), we develop an extended socio-epistemic model (ESoEM) and demonstrate that BCT is significantly explained by a composite concept of institutional trust and anomie, which we term macro-social adhesion.\u003c/p\u003e","manuscriptTitle":"What Explains the Belief in Conspiracy Theories? 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