Abstract

Conspiracy theories have become a popular phenomenon in pop culture as well in research. The increasing number of articles often focuses on the role of control and trust for the development of conspiracy thinking. Until now, the results as well as the measured concepts are still heterogeneous, lots of single study papers exist and causal evidence is often missing, resulting in a disparate set of findings that have rarely been drawn together. The goal of this research is to systematically investigate the role of trust in contrast to control on conspiracy thinking. A three-level meta-analysis of correlational studies supported the hypothesis that trust have a stronger influence on conspiracy thinking than control – moderated by the operationalization of the respective measurements on level 2. In Study 2 (N

= 226), the findings of the meta-analysis were insofar replicated that trust predicted conspiracy mentality contrary to control – with reverse results for the belief in specific conspiracy theories. Study 3 (N = 279) experimentally tested whether trust or control predicted the belief in conspiracy theories and illusory pattern perception. Even though the manipulation influenced the level personal efficacy, there were no differences in conspiracy beliefs across conditions. In sum, these findings point to the potential role of trust and to a smaller degree of control for the development of conspiracy beliefs.

Key words: conspiracy theories; conspiracy mentality; generalized political attitudes; trust; control

Conspiracy Theories, Trust and Control 1

Introduction ...... 4 Uncovering hidden agencies: Different approaches to study belief in conspiracy theories .. 5 Control versus Trust: A conceptual differentiation ...... 9 Control in psychological research: A brief overview ...... 11 The role of control for the endorsement of conspiracy thinking ...... 12 Definition of control for further research ...... 15 Trust in psychological research: A brief overview ...... 16 The role of trust for the endorsement of conspiracy thinking ...... 17 Definition of trust for further research ...... 19 Integrating trust and control in research on conspiracy thinking ...... 20 The present research ...... 24 Study 1 ...... 25 Study 2 ...... 43 Study 3 ...... 54 General Discussion ...... 58 References ...... 64

Conspiracy Theories, Trust and Control 2

Tables

Table 1 Different approaches studying conspiracy beliefs ...... 7 Table 2 Classification of the three main generalized political attitudes ...... 9 Table 3 Examples of used measurements of control in the research on conspiracy beliefs .... 14 Table 4 Used measurements of trust in the research on conspiracy beliefs ...... 18 Table 3 Conceptualization of control and trust in this work ...... 21 Table 5 Overview of the studies included in the meta-analysis ...... 36

Table 6 Results of the multivariate meta-analysis model M1: Two‐level estimates of fixed effects and variance components ...... 39

Table 7 Model Results of the multivariate meta-analysis model M2: Three‐level estimates of fixed effects and variance components ...... 41 Table 8 Correlations between the main variables in Study 2 ...... 47 Table 9 Descriptive Statistics and Correlations of Conspiracy Thinking, Trust and Control with specific events ...... 51 Table 10 Correlations between Conspiracy beliefs, trust, control and specific situations ..... 52 Table 11 Descriptive statistics of the dependent variables across the experimental conditions ...... 57 Table 12 Results of meta-analysis on the role of lack of control on the development of conspiracy beliefs...... 60

Conspiracy Theories, Trust and Control 3

Figures

Figure 1. Published articles on trust and control between 1956 and 2016 (Source: Web of Science) ...... 10 Figure 2. Search results for the meta-analysis from July 2016 ...... 26 Figure 3. Funnel Plot (computed with Meta-Essentials; Van Rhee, Suurmond, & Hak, 2015) ...... 32 Figure 4. Forest plot for the effect sizes of trust and control on conspiracy thinking (computed with OpenMeta[Analyst]; Wallace et al., 2012)...... 34

Figure 5. Profile Likelihood Plots for model M1 ...... 38

Figure 6. Profile Likelihood Plots for model M2 ...... 40 Figure 7. Effect sized of trust (yellow) and control (green) on conspiracy beliefs in dependency of the trust/control- classification...... 42 Figure 8. Correlations of conspiracy mentality (left) and belief in specific conspiracy theories (right) with trust (orange) and control (green) ...... 48 Figure 9. Interaction of Trust and Control for Belief in specific conspiracy theories ...... 49 Figure 10. Reanalysis of past findings on lack of control on conspiracy thinking divided in two subgroups (computed with OpenMeta[Analyst]; Wallace et al., 2012)...... 61

Conspiracy Theories, Trust and Control 4

Introduction

Osama bin Laden is still alive, Israel employs dolphins for espionage, US-President

Obama can control the weather, and the moon does not exist but the Nazis have a base on the moon. Those perspectives have in common that they are labeled as conspiracy theories.

Conspiracy Theories are part of our everyday lives, they are circulating through direct discussions with others, newspapers and magazines, TV, the Internet, and other media

(Butter, & Reinkowski, 2014; Fenster, 2008).

A conspiracy theory provides an alternative explanation to the established understanding of a historical or current event. The event (such as the death of Lady Diana) is often perceived as the result of conscious manipulations by individuals or secretive power

(Imhoff & Bruder, 2013). Belief in conspiracy theories can been defined as “the attribution of deliberate agency to something that is more likely to be accidental or unintended, therefore it is the unnecessary assumption of conspiracy when other explanations are more probable”

(Aaronovitch, 2011, p.29). Due to our incomplete knowledge about the world, it can usually not ultimately be decided which explanatory model is more true - the established understanding of an event or the respective conspiracy theory.

The term conspiracy theory is often used to label an argumentation as foolish and groundless. Nevertheless, conspiracy thinking is not per se pathologic: it is a normally distributed social phenomenon in every society – not only in the western world (e.g., Pipes,

1998). Contrary to the popular conception, conspiracy theories are not solely the domain of a handful of paranoid or psychologically disturbed people (Miller, Saunders, & Farhat, 2015).

Almost 40 percentage of the American population believe in the conspiracy theory that global warming is a hoax or fear that a power elite wants to rule the world through a New World

Order (Public Policy Polling, 2013). Conspiracy Theories, Trust and Control 5

From a psychological perspective, the belief in conspiracy theories has several important functions such as the explanation of negative events, the prediction of future events, the detection of threats and moral justification of discrimination (e.g., Kofta & Sedek,

2005). An integral part of most definitions is the notion that actors or groups which are more powerful than the average citizen engage in wide-ranging activities and try to control the lives of the population (Imhoff & Bruder, 2014; Miller, et al., 2015). According to Sunstein and Vermeule (2009), conspiracy theories are “an effort to explain some event or practice by reference to the machinations of powerful people, who attempt to conceal their role” (p. 205).

Some scholars follow a functional approach and have argued that conspiracy thinking can be conceptualized as a motivated collective social cognition (Krekó, 2015). Conspiracy theories are collective in terms of their origin and their targets (Krekó, 2015). They emerge in groups and are rooted in the identity of a social group. In that sense, conspiracy theories can mirror the social characteristics of the ingroup as well as the outgroup and the political system as a whole (Kofta & Sedek, 2005). In addition, conspiracy stereotypes are rooted in the motivations and emotions of a group. They can justify stereotypes and prejudice up to violence (Kofta & Sedek, 2005) and tell us who are the goodies and who are the baddies.

They are cognitive in the sense that they provide a cognitive mindset that enables people to structure their world and belief and can be used to deal with inconsistencies and dissonances that appear in society and are sometimes functional and adaptive in an instable environment

(Krekó, 2015).

Uncovering hidden agencies: Different approaches to study belief in conspiracy theories

Historically, early research on conspiracy theories in psychology was mainly interested on the relationship between belief in conspiracy theories and particular personality traits (Lantian, 2013). Belief in specific conspiracy theories was for example associated with feelings of powerlessness and low self-esteem (Abalakina-Paap, Stephan, Craig, & Gregory, Conspiracy Theories, Trust and Control 6

1999), low levels of agreeableness (Swami et al., 2011) or schizotypy (Darwin, Neave, &

Holmes, 2011). Some researchers found small correlations between conspiracy thinking and the Big-5 personality traits, whereas others failed to replicate these findings (e.g., Swami &

Furnham, 2012). It has been shown that conspiracy believers are not less intelligent (Swami et al., 2011), not less educated (Imhoff & Bruder, 2014), and do not have a greater desire to reach quick definite answers (Need for closure, Imhoff & Bruder, 2014).

However, this correlational approach is limited because of the restricted informative value of the results concerning the causal direction of these effects (Spencer, Zanna, & Fong,

2015). To deal with that kind of validity problems, other researchers were more interested in the determinants of conspirational thinking using experimental designs (Lantian, 2013).

Douglas and Sutton (2008), for instance, have shown that reading statements about conspiracy theories increased the agreement with conspiracy theories compared to a control condition. In the same way, Swami and his colleagues (2013) have demonstrated that presenting participants information supportive of the conspiracy theory resulted in stronger conspiracist beliefs. Experimentally induced lack of control led to participants’ to stronger belief in conspiracies, following the findings of Whitson and Galinsky (2008).

Not only the methodological approaches (correlational versus experimental approach) differ, also the used scales follow different conceptualizations. Some researchers developed scales measuring attitudes towards one concrete conspiracy theory (see Table 1). Conspiracy beliefs about HIV, for example, were linked to delayed diagnosis, and medication nonadherence within HIV-infected, minority, adolescent men (e.g., Gillman, et al., 2013).

Others found out that anti-vaccine conspiracy beliefs and vaccination intentions were negatively related (e.g., Jolley & Douglas, 2014). However, the informational value of this approach is limited. That people who belief that Ebola is a form of genocide against Africans are less likely to seek care for Ebola is probably not a surprising result (e.g., Earnshaw, Conspiracy Theories, Trust and Control 7

Bogart, Klompas, & Katz, 2016). Accordingly, psychologists investigated to identify more general processes that are related to the belief in conspiracy theories.

Table 1 Different approaches studying conspiracy beliefs

Approach Definition Operationalization Sample Sample Item Series of conspiracy theory Belief in a statements for one e.g., single conspiracy theory on one HIV is a manmade Stable, concrete Zekeri et conspiracy certain topic (e.g., AIDS, virus. belief system al., 2015 theory vaccination, Jewish conspiracy) The attack on the Twin e.g., Towers was not a Series of conspiracy theory Conspiracist Stable, abstract Douglas terrorist action but a statements on different ideation belief system & Sutton, governmental conspiracy theories 2011 conspiracy.

There are many very e.g., Generalized General tendency to belief important things Conspiracy Imhoff & political attitude, in secret plots realized by happening in the world Mentality Bruder, personality trait powerful groups about which the public 2014 is not informed.

One robust finding to emerge from the existing literature is that the endorsement of specific conspiracy theories is associated with greater belief in other conspiracy theories - even if those were mutually contradictory (Imhoff & Bruder, 2014; Swami et al., 2011;

Wood, Douglas, & Sutton, 2012). Participants who thought that Princess Diana was murdered were also more likely to believe that she faked her own death (Wood, et al., 2012). Based on these findings, researchers have created several self-report measures as an attempt to measure individual differences in conspiracist ideation. The perspective in research was changing from researching belief in single conspiracy theories to a conceptualization of a stable conspiracy ideation predicting a wide range of attitudes (Brotherton, French, & Pickering,

2013) and behaviors (Wood, et al., 2012). One approach has been to use a self-report questionnaire assessing belief in a previously selected number of different specific conspiracy Conspiracy Theories, Trust and Control 8 theories concerning real-world events (Goertzel, 1994; Abalakina-Paap et al., 1999; Darwin et al., 2011; Douglas and Sutton, 2011).

One problem of those scales is that they try to measure an individuals’ generalized tendency toward conspiracy thinking via a limited number of specific conspiracy theories.

This leads to the problem that those measurements may use only a top down selected subsect out of potentially infinite pool of different conspiracy theories – based on the assumption that those theories reflect the general tendency to belief in a conspiracy in a representative way

(Brotherton, et al., 2013). To minimize and deal with this kind of validity concerns, new concepts were developed to be able to measure belief in conspiracy theories in a more general, abstract way, and therefore, the concept of a coherent conspiracy mentality has been established in research (Bruder, et al., 2013; Imhoff, & Bruder, 2014). First introduced by

Moscovici (1987), conspiracy mentality can be described as a stable generalized political attitude (Imhoff, & Bruder, 2013) – comparable to and distinct from other political ideologies established in the literature (see Table 2).

Conspiracy Theories, Trust and Control 9

Table 2 Classification of the three main generalized political attitudes

Status Ideology Core belief Sample Outgroup Target Right-Wing Deviants (e.g., feminists, Dangerous world  Authoritarianism homosexuals) Social Inevitable group Low status groups (e.g., women, Dominance  hierarchies Muslims) Orientation Conspiracy Ingroup defensive High power groups (e.g., Jews)  Mentality Note. Adaption and extension from Fiske (2013)

The conspiracy mentality leads to a mindset where people tend to doubt the official version of a social event and can be characterized by a monological belief system (Goertzel,

1994). As Goertzel (1994) notes, conspiracy theories are connected to feelings of insecurity and associated with more negative attitudes towards groups perceived as powerful (see Table

2). This mindset comes along with greater prejudice against groups perceived as powerful such as Jews or Americans (Imhoff & Bruder, 2014).

Summing this up, there exists a wide range of approaches studying belief in conspiracy theories. Until now, there are still many unanswered questions and it is necessary to figure out if the different approaches capture the same construct or if there are differences concerning for example the stability of the belief system or the psychological correlates.

Control versus Trust: A conceptual differentiation

In the research on conspiracy thinking, two concepts are often the focus of attention: trust and control (e.g., Goertzel, 1994; Imhoff, 2015). The idea that lack of control would increase conspiratorial thinking (and illusory pattern perception in general) goes back to an article by Whitson and Galinsky (2008) published in science. Lack of control was induced in six experiments to show an increase of conspiracy thinking and illusory pattern perception Conspiracy Theories, Trust and Control 10 compared to the control conditions. It is assumed that conspiracy thinking is one possible way to deal with a world which is perceived as chaotic and gain a sense of control.

There is a great body of research that focus on both concepts separately. A research on web of science (August 2, 2016) shows, that between 1945 and 2016 N = 4,673 articles on control and N = 6,376 articles on trust have been published in the fields of psychology, behavioral science, neuroscience, economics and management.1 As figure 1 shows, within the last few years there is an increasing number of articles published on trust and control every year – especially on trust.

Figure 1. Published articles on trust and control between 1956 and 2016 (Source: Web of Science)

To date, however, only a small handful of studies have begun to investigate the distinction between control and trust in general (Maguire, Phillips, & Hardy, 2001;

Möllering, 2005). If people trust each other they assume that there is something predictable in other’s behavior. Similar mechanisms can be found for control: To be able to control

1 Note that this research includes also non-empirical paper. The increasing number of articles in general published within the last years is not taken into account. Conspiracy Theories, Trust and Control 11 something, an event or the own behavior must be predictable. In addition, there must be the opportunity to influence events.

Thus, the two constructs trust and control are conceptually very close (Maguire et al.,

2001). There are, however, still differences between the two constructs which have not yet been investigated systematically in research. One reason for this lack of research might be the enormous number of definitions and measurement methods of control and trust. The goal of this work is to determine clear definitions of both concepts to systematically investigate conceptual overlaps and differences and apply these findings to the research on conspiracy beliefs. The heterogeneity of the definitions come along with a various number of measurements. In addition, it is not clear how far the scales on trust and control measure the respective construct they want to measure and in what sense the heterogeneity of the results is due to an unprecise operationalization.

Control in psychological research: A brief overview

Control is probably one of the most important or well researched constructs especially in personality and social psychology. The desire to reduce uncertainty can be described as a

“fundamental motivating force in human life” (Whitson & Galinsky, 2008, p. 115) with a large influence on psychological well-being and mental health (e.g., Skinner, 1996;

Thompson & Spacapan, 1991). A multitude of studies have examined a link between depression and locus of control (e.g., Akande & Lester, 1994; Tobin & Raymundo, 2010) or found that differences in self-control in childhood are related to unemployment throughout the life span (Daly, Delaney, Egan, & Baumeister, 2015; Mischel et al., 2010).

However, there is still a wide-ranging heterogeneity concerning the operationalization of the construct itself - some scholars focus on achieving behavioral outcomes whereas others mainly look at the cognitive processes behind the construct (Skinner, 1996; Thompson &

Spacapan, 1991). Researchers use a huge amount of different terms which sometimes seem to Conspiracy Theories, Trust and Control 12 be overlapping (e.g., self-control, sense of control, locus of control, cognitive control, primary control, secondary control). On the other hand, some researchers do not use the term control, but the constructs they research seem to be conceptually very similar (e.g., learned helplessness, efficacy, agency), whereas others use the same labels for different constructs

(Skinner, 1996).

Also the suggested taxonomies differ: Some scholars have proposed that there are three main dimensions of control: contingency versus competence versus control beliefs, primary versus secondary control and global versus specific measures of control (e.g.,

Thompson & Spacapan, 1991). In contrast to those approaches, Paulhus & Christie (1981), for example, suggest a taxonomy of control with the three dimensions source, sphere of activity and target. Another taxonomy is taken by Skinner (1996) who tried to systematize control in agents, means and ends and their different relations to each other. As well within one construct, there are huge differences concerning the conceptualization of the construct itself and the theoretical background. Following de Ridder, Lensvelt-Mulders, Finkenauer,

Stok, and Baumeister (2012), self-control, for instance, can be studied via the discounting model of impulsiveness (e.g., Ainslie, 1975), the hot/cool system approaches to self- regulation (e.g., Mischel, Shoda, & Rodriguez, 1989), or the self-regulatory strength model of self-control (Baumeister, Heatherton, & Tice, 1994). Other scholars try to extend the self- control research on a dual-system perspective (e.g., Hofmann, Friese, & Strack, 2009).

The role of control for the endorsement of conspiracy thinking

There are several studies demonstrating the role of control for conspiracy thinking

(e.g., Newheiser, Farias, & Tausch, 2011; Sullivan, Landau, & Rothschild, 2010; van

Prooijen & Jostmann, 2013). In their famous studies, Whitson and Galinsky (2008) showed in several experiments that lack of control increases illusory pattern perceptions, including a belief in conspiracies and superstitions. Following the meaning maintenance model (Heine, Conspiracy Theories, Trust and Control 13

Proulx, & Vohs, 2006), which proposes that people have a need for meaning, it could be argued that belief in conspiracy theories serves a psychological function by providing a sense of meaning and control (Newheiser, Farias, & Tausch, 2011). Dispositional as well as situational lack of perceived control were linked to attributing more influence to a personal enemy and a greater belief in the conspiratorial power of a political enemy (Sullivan, Landau,

& Rotschild, 2010). Prooijen und Acker (2015) were able to show that also a societal threat of control was linked to conspiracy thinking.

But there is no coherent pattern; other studies were not able to replicate the association between lack of control and conspiracy thinking (Imhoff, 2015). However, when using hierarchical regression analysis with control experiences and trust as predictors, there were higher correlations between trust and conspiracy thinking than between control and conspiracy thinking (Prooijen & Acker, 2015, Studie 2). Bruder and Imhoff (2013; study 4), for example, found no link between conspiracy beliefs and personal efficacy as well as interpersonal control. Significant correlations were only between perceived socio-political control and conspiracy mentality.

It is important to note that the empirical evidence for the relationship between people’s desire for control and conspiracy thinking is limited in several ways. As a first limitation, there is a lack of external validity especially on experimental research on conspiracy thinking and control (van Prooijen & Acker, 2015). Lots of research used paradigms were situations where people lacked control were compared with situations where people had control (e.g., Whitson & Galinsky, 2008). From this paradigms it is difficult to conclude whether a lack of control increases or a sense of control decreases conspiracy beliefs. Control threats were often measured with essay priming where people should remind a situation where they lacked control (Rothschild, Landau, Sullivan, & Keefer, 2012;

Sullivan, Landau, & Rothschild, 2010; Whitson & Galinsky, 2008) or were confronted with Conspiracy Theories, Trust and Control 14 fictitious scenarios. These methods are often used in social cognition research but come along with several methodological problems (Bodenhausen & Wyer, 1987).

Table 3 Examples of used measurements of control in the research on conspiracy beliefs

Locus of Generali- Focus Scale Original Source control zability Spheres of control: internal intrapersonal Paulhus, 1983 general Personal efficacy Spheres of control: internal interpersonal Paulhus, 1983 general interpersonal Spheres of control: internal general societal Paulhus, 1983 socio-political control Feelings of Clatterbuck, internal general intrapersonal uncertainty 1979 Lamberty & internal general societal Political Control Flade, 2016 Lamberty & internal general intrapersonal Personal Control Flade, 2016 Burger & internal general intrapersonal Desirability of control Cooper, 1979 World Assumptions external general - Janoff-Bulman, Scale (controllability 1989 of the world) Van Prooijen & mixed context mixed Y2K control threat Acker, 2015 specific Witkowska et internal general intragroup Sense of collective al., under control review

The issue of the heterogeneity of the empirical findings may be influenced by the fact that the psychological construct of control varies in a wide range across different studies (see

Table 3). Some scholars focus on personal feelings of control (Paulhus, 1983), whereas others aim at a societal relevant form of control feelings (Lamberty & Flade, 2016). Abalakina-Paap and colleagues (1994), for example, used the internal versus external locus of control scale introduced by Rotter (1966), which can be described as the belief than either an individual controls his or her own life or that events in life are caused by somebody or something else.

Rotter (1966, 1967, 1971) conceptualized control as unidimensional: The score of the locus Conspiracy Theories, Trust and Control 15 of control scale in its original form represented a relative position along a dimension of internal-external locus of control – although the empirical evidence for only one factor of control is missing (Paulhus & Christie, 1981). Others studied the role of control on conspiracy thinking within the spheres of control concept introduced by Paulhus (1983), which describes an individuals’ beliefs about what amount of control they have over their life in different domains (e.g., Bruder et al., 2013). Others used scales which were developed especially for this specific study and context (e.g., Van Prooijen & Acker, 2015). This makes comparability even more difficult. All of these measures are often lumped together under the label control. However, it is still unclear what the opposite concept of feelings of control is.

Is a control threat the other side of the coin of feelings of control? Or something different altogether? The same applies for desirability of control.

Furthermore, correlations between conspiracy thinking and concepts which are defined as indicators of lack of control such as unemployment are reported (Imhoff, 2015).

However, it is not clear if these constructs are a good operationalization of control deprivation. Unemployment is empirically also associated with a low level of confidence

(Lindström, 2009) or an increase in distrust (International Labour Organization, 2013) and therefore no clear indication of lack of control.

Definition of control for further research

In sum, it is almost impossible to systemize the research that has been conducted on the control-construct as a whole. Because research exploring the role of control on conspiracy theories use heterogeneous control measures, it is impossible to focus on one specific approach. After reviewing the literature on control, I suggest the following definition of control: Control can be described as an individual’s ability to gain predictability and influenceability of a certain kind of outcome (e.g., behavior, thoughts, feelings, attitudes, desires, or judgements) in the desired direction. Conspiracy Theories, Trust and Control 16

The goal of this definition is to capture a wide range of the concepts related to control and be as general as possible to be useful for the research on control as a predictor of conspiracy thinking. The majority of the research on control in psychology focuses on subjective control as a perception, (e.g., Whitson & Galinsky, 2008), need (Skinner, 1995) or ability (e.g., Fiske & Taylor, 2013). Two components are important to be able to control something (objectively or psychologically): predictability (e.g., Katz, & Wykes, 1985) and influenceability (e.g., Nemeth & Staw, 1989). As for example, Whitson and Galinsky (2008) showed in their experiments that if something happens at random people experience a lack of control. In experiment 1, they used a concept-identification paradigm with random performance feedback that was not contingent on the responses to increase participants’ feelings of lack of control. Lacking control included two components in this paradigm: A lack of predictability and influenceability. A perceived lack of control emerged because participants’ were not able to predict the feedback they received from the computer and did not have the ability to influence the results of the feedback.

The definition tries to capture many of the constructs related to the control construct such as decision control (Steiner, 1970), spheres of control (Paulhus, 1983), need for control

(Leotti, Iyengar, & Ochsner, 2010), or self-control (Baumeister et al., 1994).

Trust in psychological research: A brief overview

Examining the role of trust for different domains has been the center of interest in economics, sociology and psychology for ages. Posten and Mussweiler (2013) describe trust as the “social glue that brings people together and facilitates their interactions” (p. 567). Or how Sissela Bok put it in a nutshell in her book Lying: Moral Choice in Public and Private

Life: “Whatever matters to human beings, trust is the atmosphere in which it thrives”.

Trustworthiness is one of the main evaluative dimensions in social judgements (Oosterhof &

Todorov, 2008). The detection of trustworthiness seems to be a basal psychological Conspiracy Theories, Trust and Control 17 mechanism – not only but also for humans (Posten & Mussweiler, 2013). People can automatically make trustworthiness judgments from facial appearance after minimal time exposure (Todorov, Pakrashi, & Oosterhof, 2009). Therefore, trust is related to a large range of psychological processing and behaviors. Trust is, for instance, a positive predictor for cooperation (Balliet & Van Lange, 2013). People who trust in others report greater life satisfaction and more physical health – they even live longer (e.g., Balliet & Van Lange,

2013b; Yamagishi, 2011).

Comparable with the research on control, the definitions as well the main paradigms used to study the role of trust differ considerably across different researchers/ research groups and disciplines (Posten, Ockenfels, & Mussweiler, 2014). Following Yamagishi and

Yamagishi (1994), trust can be described as an expectation of goodwill and benign intent.

Some researchers define trust as a state (e.g., Lewicki & Bunker, 1995), whereas others focus more on trust as a personality trait (e.g., Wrightsman, 1964). Trust can be studied from an intrapersonal (as a person's dispositional tendency to trust others) or from an interpersonal/- group perspective (such as trust in the relationship with a specific partner/ group). Scholars have argued that trust might be the variable that has the strongest influence on interpersonal and intergroup behavior (e.g., Ferrin, Bligh, & Kohles, 2008; Golembiewski & McConkie,

1975).

The role of trust for the endorsement of conspiracy thinking

In general, research has linked beliefs in conspiracy theories with low levels of trust

(e.g., Jolley, & Douglas, 2014). One reason why people may believe in conspiracies is that they are distrustful of others (e.g., Abalakina-Paap, et al., 1999; Goertzel, 1994; Kramer,

1994). This might be true especially for people or social groups perceived as powerful

(Imhoff & Bruder, 2014). A number of scholars have highlighted that mistrust (e.g., in the government or the official discourse) is designated as one of the antecedents of belief in Conspiracy Theories, Trust and Control 18 conspiracy theories (Abalakina-Paap, et al., 1999; Goertzel, 1994; Klein, Van der Linden,

Pantazi, & Kissine, 2015). Jolley and Douglas (2014, Study 2) have demonstrated that exposure to anti-vaccine conspiracy theories directly affects vaccination intentions – mediated by mistrust in authorities and perceived powerlessness. Conspiracist ideation in general tends to be associated with a mistrust of science (e.g., rejection of climate change,

AIDS).

Table 4 Used measurements of trust in the research on conspiracy beliefs

Scale Original Source TC Generalizability Focus Interpersonal Trust Goertzel, 1994 general interpersonal Trust in physicians Hall et al., 2002 context specific Interpersonal Mistrust towards Van de Meer (2010) context specific Society Institutions Trust in sources Leiserowitz et al., 2003 Society Political Trust Lamberty & Flade, 2016 general Society Personal Trust Lamberty & Flade, 2016 general Interpersonal Intergroup Distrust Mashuri & Zaduqisti, 2014 context specific Intergroup Trust Miller et al., 2015 general mixed Trust in government Van Prooijen & Acker, 2015 context specific Society Witkowska et al., under Outgroup trust context specific Intergroup review

The trust measures differ in the way they measure interpersonal (Goertzel, 1994) or intergroup (Mashuri & Zaduqisti, 2014) trust (see Table 4). The target of trust is sometimes a person or group, sometimes a more abstract institution like the media or the government.

Some of them measure trust in a more general way (Miller, 2015), whereas others do so with regard to a special context (Hall et al., 2002).

Some groups seem to be more vulnerable to such kind of thinking: Goertzel (1994) for example reported that belief in conspiracies was associated with low levels of trust and high levels of anomia as a feeling of alienation and disaffection from the system, and such Conspiracy Theories, Trust and Control 19 beliefs enabled people to externalize their negative or angry feelings and provide them with enemies on which to vent such feelings. Members of an ethnic minority were much more likely to believe in conspiracies than members of an ethnic majority. This relationship between minority status and conspiracy thinking was mediated via a lower level of interpersonal trust and anomia (Goertzel, 1994).

Whereas there are ambiguous results for the link between conspiracy beliefs and control, the correlation between trust and conspiracy beliefs seems to be more stable.

However, the problem concerning the research on the role of trust on conspiracy theories is mainly causality. Some scholars point out, that mistrust is crucial for the development of conspiracy thinking whereas others see low levels of trust as a consequence of a conspirational worldview. However, at this stage of research it cannot be ascertained if a low level of trust is an antecedent or a consequence of conspiracy thinking. Further research is needed to figure out the causal relationship between trust and conspiracy thinking.

Definition of trust for further research

Summarizing the previous literature on trust, I suggest the following definition as base for my own research: Trust can be defined as the (actual or general) expectation that the behaviors, thoughts, feelings, attitudes, desires or judgements of somebody else (a person, a group or institutions) are predictable (e.g., Cunningham, & MacGregor, 2000; Doney,

Cannon, & Mullen, 1998, Rotter, 1971) and that the intentions of the other person or group are benign (e.g., Rotter, 1971).

The goal of this definition is to capture a wide range of the concepts related to trust and be as general as possible to be useful for the research on trust as a predictor of conspiracy thinking. Scholars have pointed out that trust can be understand either as a state or as a trait.

The definition points out this distinction (actual or general expectation). People differ interindividually in their level of trust towards other people. Besides this stable personality Conspiracy Theories, Trust and Control 20 trait, the trustworthiness of the target (trustee) differ. Some people seem to be more reliable than others, some sources more trustworthy. In the research on conspiracy thinking, for example, it has been shown that people trust lay people more than experts (Imhoff, Lamberty

& Klein, 2016) – independent of the position of the lay respectively the expert.

Another part of the definition refers to the actions of the trustee. Trust may affect different areas. People in romantic relationships may trust their partners that they do neither have negative feelings towards them nor romantic feelings to other people. Trust can also aim at desires, judgements or behaviors.

One psychological function of trust is that it makes life predicable – even if the situation itself is not. When we trust we believe that the person or group who is trusted will do what we expect – in a good manner. Trust means confidence in the integrity of a person or group.

Integrating trust and control in research on conspiracy thinking

There is a widespread consensus in psychological research that human cognition about the social world is not objective but partially motivated (Duckitt, 2001; Kruglanski,

1996). Therefore, conspiracy beliefs can be understood as a motivated cognition, as mentioned above. This leads to the conclusion that people tend to believe what seems to be useful for them or adaptive somehow (even if it seems to be negative at first sight). People might adopt conspiracy beliefs about their social environment as a reaction of distrust or lack of control to deal with these threats and search for meaning on a symbolic or conceptual level.

Past research has discussed both trust and control as antecedents of conspiracy beliefs.

Conceptually both constructs are somehow overlapping. Nonetheless, it is still unclear, how much they refer to and create each other. As the previously introduced definitions try to show, trust and control are less distinct than is typically assumed (see Table 3). Conspiracy Theories, Trust and Control 21

Table 5 Conceptualization of control and trust in this work

Variables Expectancy Intentions Influenceability

Control Predictability - Yes

No Control Unpredictability - No

Trust Predictability benign No

No Trust Predictability malicious No

Both constructs imply the expectancy that a certain behavior (or feelings, thoughts, etc.) is predictable. Trust implies that we can predict how other people or groups will behave.

The child trust the father that he will bring it to school and pick it up in the afternoon. Trust always refers to a future event – it is a prediction about how somebody will behave.

Similarly, when we feel in control we can predict what may happen, change things and cope with problems. The leader of a company predicts that his or her employees follow his or her instructions, the student have the desire to influence the outcome of an exam by studying every day.

Differences that are detectable include the expectancy, the intentions and the possibility of influenceability. Trust can be defined as the belief that the action of others will be rather benign than malicious (Child, 2001). The pupil trusts her teacher that he will not give her a bad grade for no reason, the employee relies on the fair behavior of his boss.

Unlike, control does not necessarily imply good intentions of others. It refers to the expectation or perception that an individual is able to influence incidents, behaviors or feelings – also if they are negative. Therefore, influenceability is one of the key elements of control. Contrary, trust means by definition relinquishing influenceability to a certain degree.

We have (the illusion of) control if we drive the car by our own, we can decide which route Conspiracy Theories, Trust and Control 22 we want to take or how fast we want to drive. However, when somebody else drives the car, we have to give up control. If we expect, that we can rely on the driver at this very moment, we experience trust.

As noted before, conspiracy mentality and conspiracy thinking are stable predictors of stereotypical thinking and prejudice (e.g., Imhoff & Bruder, 2014; Kofta & Sedek, 2005).

A lack of trust and control might be responsible for this mindset. There is a consensus that people try to gain control when it’s under threat – and if they are not in the position to do so objectively (e.g., changing the status of unemployment) they try to recover control psychologically or perceptually (e.g., Whitson & Galinsky, 2008). Conspiracy thinking (as one form of illusory pattern perception) is one opportunity to restructure the world and gain a sense of control.

Only little is known about how trust affects the perception of others. Some scholars have argued that distrust reduces stereotyping because it causes cognitive nonroutine strategies and leads to a more pronounced dissimilarity-focus (Posten & Mussweiler, 2013).

However, the majority of researchers assume that prejudice (and conspiracy beliefs can be understood as a special form of prejudice) is particularly motivated by distrust (Gervais,

Shariff, & Norenzayan, 2011) and that a lack of trust in the outgroup is associated with stronger intergroup biases (Voci, 2006). Conspiracy beliefs might be one opportunity to deal with distrust. They serve as explanation of negative social events and help people to make sense out of their feelings of distrust. In addition, they can be used as a prediction of future events and motivation to collective self-defense against threats from outgroups (Kofta, 2005).

With this in mind, conspiracy beliefs might be an adaptive opportunity to deal with an environment, which is perceived as hostile.

I argue that trust is more important for the development of conspiracy thinking compared to control. Conspiracy theories emerge immediately after almost every societal Conspiracy Theories, Trust and Control 23 event. After the Nice attack, there were some conspiracy theories that the attack was a False

Flag. Recently, after the military coup in Turkey, people claimed that power grab attempt was faked by Erdogan to suppress all opposition. Conspiracy theories develop when people have no possibility to influence a societal event. People know they usually cannot influence the politics of Erdogan or prevent suicide bombings of IS members. An efficient way of dealing with the kind of situations where people cannot influence the outcome of a social event is trust, the expectancy that somebody has benign intentions and will do everything possible to prevent bad things from the own ingroup. If this is not the case, if people have the feeling that their own government, the media or somebody else is up to no good and something bad happens, conspiracy theories emerge. People expect that the government will hide the truth or that the media have a hidden agenda. The distrust against high power groups does probably exist before a negative event happens (Imhoff & Bruder, 2014).

Conspiracy Theories are not only a modern phenomenon. Since human social life exists, conspiracy theories are probably part of the society - in every part of the world (Krekó,

2015). Concerning an opinion poll from 2008, in only nine of 17 countries a majority believe al Qaeda was behind the 9/11 attacks. From 16,063 participants, 15 percent made the U.S. government, 7 percent Israel and 7 percent made some other perpetrator responsible for 9/11

(Program on International Policy Attitudes, 2008). This might lead to the assumption that there is an evolutionary base of conspiracy thinking (Krekó, 2015). Equally, from that point of view it makes much more sense to assume that trust is a stronger predictor of conspiracy beliefs compared to control. A typical example for a situation where people have and had no sense of control is the weather. Even if there are some conspiracy beliefs about weather manipulation, it does not seem adaptive from an evolutionary point of view to believe that somebody influenced the weather to be able to deal with that issue. Probably every event in Conspiracy Theories, Trust and Control 24 the nonsocial environment is out of our control. According to that, conspiracy theories would spring up every time the weather changes.

Conversely, if people assume that an outgroup acts maliciously towards their ingroup believing in a conspiracy theory might protect them from harm. Conspiracy beliefs as a social phenomenon help to detect threats toward the well-being of the own group and can be a motivation to collective self-defense (Kofta & Sedek, 2005). Higher suspicion to the social environment and the sensitivity to clues about danger might be an adaptive strategy to safe the survival of the own social group (Krekó, 2015).

However, too little research actually addresses the concepts trust and control at the same time. Previous research on the relationship between both constructs has mainly been conducted in sociology and management studies, whereas psychological research still considers them as completely separate issues.

The present research

As a contribution to the literature on the psychology of conspiracy theories, the present work sought to examine the influence of trust and control on the endorsement of conspiracy thinking. The present work provides a meta-analysis of past research on the role of trust and control on the endorsement of conspiracy thinking. The aim of this meta-analysis is to show that there is a higher influence of trust compared to control on conspiracy thinking.

In addition, it is assumed that the influence of control of conspiracy in past research is influenced by the operationalization of the measurements. In addition, a correlational study was conducted to test whether conspiracy mentality was associated with lower trust and a lack of control by using less ambiguous measurements of control and trust. To replicate these findings and strengthen the empirical argument for a causal relationship, study 3 tested in an experimental setting the prediction that trust (compared to control) caused belief in conspiracy theories. Conspiracy Theories, Trust and Control 25

Due to actual debates especially in social psychology concerning the quality of psychological research (e.g., Kerr, 1998; Simmons, Nelson, & Simonsohn, 2011), there is a growing interest in transparency, reproducibility, and reducing publication bias which has led scientists and journals to become more interested in the pre-registration of research (van 't

Veer & Ginder-Sorolla, 2016). In order to be able to meet all these requirements, Study 2 and

Study 3 were pre-registered via aspredicted.org before collecting the data and all material of the studies are uploaded on the Open Science Framework (https://osf.io/kwz3p).

Study 1

Past research has often pointed out the role of trust and control for the development of conspiracy thinking – with heterogeneous results. The goal of this meta-analysis is to provide answers regarding the relationship between trust and control on conspiracy beliefs. The central question is, therefore, whether trust or control play a stronger role for conspiracy beliefs. Additionally, the operationalization of the measurements will be investigated systematically within this analysis. A three-level mixed effects model with different scales nested within study as random effect was calculated to get a deeper insight in the importance of both variables for conspiracy thinking.

Method

Literature Search Strategy. In this search, I focused on articles, dissertations, or book chapters published until July 1, 2016. I retrieved published literature through a detailed search in PsycLIT and PsycINFO, the two main, databases for psychological research articles, PSYNDEXplus, a database with mainly German articles, Web of Science, an interdisciplinary database, Google scholar, a freely accessible web search engine, as well as

ProQuest, the main database for doctoral dissertations. Additionally, the literature research of

ResearchGate was used. The following keywords were used: conspiracy, conspiracy theory, conspiracy mentality, conspirational thinking. Additional references were retrieved by cross- Conspiracy Theories, Trust and Control 26 referencing of selected articles. In order to locate gray literature (i.e., technical reports, unpublished manuscripts, articles currently in press) and be able to minimize publication bias and the file drawer problem, e-mail requests were sent to several researchers working in the field of conspiracy thinking. Masters and Bachelors theses, as well as Studies written in languages other than English or German were not included in this analysis.

Excluding clearly unrelated work (e.g., on conspiracy Numbers algorithm), this search strategy yielded a total of N =221 unduplicated citations on conspiracy thinking in general. All of them could be retrieved either in electronic or print format for possible inclusion in the meta-analysis.

Figure 2. Search results for the meta-analysis from July 2016

As can be seen in Figure 2, the majority of citations consisted of published journal articles. There was only a small amount of unpublished reports/drafts/data and doctoral dissertations. Conspiracy Theories, Trust and Control 27

Study Eligibility. Of the 221 citations retrieved, n =186 were excluded for one of the following reasons (see Figure 2): On the basis of the title, the abstract, and a scanning of the text, the citation (a) was determined to be a review paper or otherwise theoretical in nature (n

= 52), (b) clearly did not include at least one measurement of trust or control (n = 112), (c) was written in a language not spoken by the authors (n = 1), or (d) did not measure interindividual differences (n = 21).

The remaining 35 citations yielded a total of 77 studies. The following criteria were applied to determine the eligibility of each study for inclusion in the meta-analysis:

1. The study included at least one correlational measurement of trust and control.

Studies must be correlative or include correlative measurements. If the study was

an experimental or quasi-experimental manipulation of trust or control and no

correlative measurement was reported, it was excluded from the analysis. As far

as the author knows, trust was only measured in correlational studies and there

exists no experimental manipulation of trust in the research on conspiracy

thinking so far. For this reason, it is impossible to compare trust and control in

an experimental setting. Therefore, studies measuring control in only an

experimental setting were excluded (n = 5).

2. In addition, studies not measuring trust or control or not measuring conspiracy

beliefs (n = 38) were excluded from the analysis.

3. Studies that reported the data in a way that at least one relevant effect size

contrast could be coded from the data and transformed into Fisher's z were

included in the analysis. In many cases, the relevant data were only presented in

multiple regression analysis or as Odds Ratio. Great efforts were made to contact

authors by e-mail and request missing data. Even though many requests were Conspiracy Theories, Trust and Control 28

answered and the requested effect size data provided, effect size statistics could

not be computed for a total of n =14 studies.

4. Studies were not included if they had already been reported in another citation

included in the meta-analysis (n = 2) in order to avoid duplication.

After application of these exclusion criteria, 18 independent studies stemming from a total of 14 citations were retained for coding of study characteristics and effect sizes.

Coding of Study Characteristics. Eligible studies that were published in English or

German were coded by the author. The coding was done through the use of a data coding form and a clearly arranged coding manual (available at the OSF). The coding form displayed all variables and possible coding options. The manual contained further brief explanations on the relevant coding variables and the respective category assignments. Each study was coded in a hierarchical manner that was also reflected in the arrangement of the coding sheet.

Codings that could not be determined because the relevant information was either absent from the text or ambiguous were marked as missing.

On the article level, data were coded referring to the whole study: study identification

(study ID), authors, publication year, title, journal, language, number of studies, publication type (e.g., peer reviewed journal), discipline and impact factor (in the year of publication).

Separate coding sheets were used for the description of the sample, the measures and the effect sizes. To describe the sample, sample size, country of the sample, population type, data collection, setting, design type, gender proportion and mean age were coded. The used measurements were described with scale name, number of items, scale type, scale points, reliability and reliability coefficient, and original source for each construct.

Meta-Analytic Procedure. In the meta-analysis, I was interested in the influence of trust and control on conspiracy beliefs. This analysis required four principal decisions: Conspiracy Theories, Trust and Control 29

First, there is broad discussion on whether to use raw correlations in the meta-analysis or Fisher’s z -transformed correlations. Because of its better sample properties such as more stable variance and normality some advocate analyzing Fisher’s z-transformation, whereas others recommend the use of raw correlations, due to biased estimates using Fisher’s z - transformation. In this study, I follow Overton (1998) and perform the meta-analysis (random effects model) using Fisher’s z-transformed correlations Fisher’s z is an often used and recommended effect size for random-effects meta-analysis for correlations (for discussion about Fisher’s z as effect size for meta-analyses see Hafdahl & Williams, 2009).

Second, it must be decided which form of maximum likelihood estimation should be chosen. I decided to use the restricted maximum likelihood (REML) estimator. It is considered to produce slightly more accurate heterogeneity results compared to the maximum likelihood (ML) method (López‐López, et al., 2014).

Third, it must be decided whether a fixed effects model or a random effects model should be chosen (Borenstein, Hedges, Higgins, & Rothstein, 2009). The fixed effect model

(M0) implies that the correlation estimates in the population are fixed but unknown constants, whereas the random effects models assume that the population correlation themselves vary randomly from study to study. The null hypothesis of homogeneous correlation can be tested using the Q statistic, which follows a χ2 distribution. In this meta-analysis random effects models were favored over fixed effect models. The classification of trust/control was expected to be a moderator and therefore, it was assumed that there might be differences between subgroups of studies.

Fourth, the structure of the clustered data must be sufficiently captured by the model.

In this study, the correlation coefficients were clustered within studies and I had to deal with the dependency of the measures. Many studies yielded more than one effect size and measured trust and control at the same time. Since trust and control were often measured Conspiracy Theories, Trust and Control 30 within one study, the estimates are correlated (Gleser & Olkin, 2009). Past research handled dependency by either ignoring it, averaging dependent effect sizes within studies or one effect size per study (Cheung, 2014). In order to ensure independence of the effect sizes entered in the meta-analysis (Lipsey & Wilson, 2001), a multi-level mixed effects model with different scales nested within study as random effect and Trust-Control as moderator was chosen. Three-level meta-analysis has been proposed to model effect sizes with nested structures as a novel approach to deal with dependent effect sizes and meta-analyze the two constructs simultaneously.

This leads to a three-level mixed effects meta-analysis model (Cheung, 2014): with sampling error for each correlation as level 1, with trust/control classification as level 2, and with trust/control classification by studies as level 3. Random effects were not only at level 2, but also at the study level (level 3). All in all, the following three models were estimated in this paper:

M0: fixed effect model.

M1: mixed effects model with two levels and trust/control classification as moderator on level 2

M2: mixed effects model with three levels and trust/control classification as moderator on level 2 and trust/control classification by studies as level 3.

The analyses were performed using the metafor package (Viechtbauer, 2010) and metaSEM (Cheung, 2015) for the main analysis, OpenMeta[Analyst] (Wallace et al., 2012) for the forest plot and Meta-Essentials (Van Rhee, Suurmond, & Hak, 2015) for the funnel plot.

Coding of Effect Sizes and effect size transformation. On the lowest level of the coding sheet, the available effect size data were coded with mean, standard deviation, effect size, coefficient and p-value. Many of the studies, did not report the correlations themselves. Conspiracy Theories, Trust and Control 31

Instead, many used either only hierarchical regressions or odds ratio. However, if the information of the effect size was not provided in the study itself, the authors were contacted.

When the correlation coefficient r was available, the coefficient was transformed into

Fisher’s z (Fisher, 1915). Before transforming the correlational coefficients into Fisher’s z, the reverse coded correlations were recoded. Most of the studies reported scales where higher values indicated a higher values of trust and control, but some coded their scale the other way round. Some measured lack of control, whereas others used control measures. The correlations were coded in such a way that positive correlations indicate that higher levels of trust and control come along with a higher level of conspiracy thinking and vice versa.

Dependency of the outcome variable. Many studies included several, sometimes very similar, measures of conspiracy thinking in their analysis. Since the main focus of the meta- analysis was on the role of trust and control, several measurements within one study had to be excluded from further analysis to keep one scale of conspiracy thinking per study and avoid dependent effect sizes (see coding sheet on OSF). Measures which were never used before in other research and therefore less comparable were excluded (e.g., single item conspiracy belief scale from Latian, 2016).

Results

Descriptive Statistics. The sample sizes ranged between 47 and 2485 participants

(MSample = 589.61, SDSample = 708.61). In total, N =14,876 participants were included in the analysis. The proportion of females in the samples included in the meta-analysis were Mfemales

= 55%, SDfemales = 21%. Out of the K = 18 studies, k = 7 were mixed samples, followed by student samples (k = 4), representative samples (k = 3) and psychology students (k = 2) as well as nonstudents (k = 2). The majority of the studies were recruited online (k = 12).

However, only two studies used Amazon Mechanical Turk for data collection, whereas the other k = 10 were recruited via e.g., snowball sampling or social networks. Five of the studies Conspiracy Theories, Trust and Control 32 were conducted offline (laboratory (k = 1), in class (k =1) or field (k = 2) and one information concerning the data collection was missing.

Assessment of potential publication bias. Publication bias and the file drawer problem as often discussed problems concerning the validity of meta-analysis occurs whenever published literature is systematically unrepresentative of the population of completed studies. Inter alia because of the actual journal politics, studies with non- significant results still have a smaller likelihood to be published than studies with significant or hypotheses conform findings (Duva, & Tweedie, 2000). This may lead to a wrong conclusion about what that body of research shows; the missing studies may influence the overall mean that is estimated in the meta-analysis. The probably most common method to deal with the problems stemming from the publication bias is the funnel plot introduced by

Light, and Pillemer (1984), a plot of sample size versus effect size.

Figure 3. Funnel Plot (computed with Meta-Essentials; Van Rhee, Suurmond, & Hak, 2015) Conspiracy Theories, Trust and Control 33

It is assumed that observed effect sizes with similar precision should be more or less symmetrically distributed around the combined effect size. The funnel plot suggests, as

Figure 3 shows, that results with rather large effect sizes are missing which indicates that there might be a publication bias. Seven results are imputed in order to adjust for this absence. However, the results should be interpreted with much caution because of the high level of heterogeneity in this set of effect sizes.

General correlation between trust/ control and conspiracy beliefs. Because of the dependency of the different studies, it was required to calculate a multi-level meta-analysis.

Before conducting the main sets of analyses, I conducted a subgroup meta-analysis with

OpenMeta[Analyst] (Wallace et al., 2012) to get a descriptive overview of the different effect sizes on trust and control on conspiracy thinking. Conspiracy Theories, Trust and Control 34

Figure 4. Forest plot for the effect sizes of trust and control on conspiracy thinking (computed with OpenMeta[Analyst]; Wallace et al., 2012).

The mean overall effect size was Fisher-z = -.26 (SDFisher-z = -.17), with a maximum effect size of Fisher-z = - .57 and a minimum of Fisher-z =.03. As can be seen in Figure 4, the mean effect size of control on conspiracy thinking is Fisher-z = -.20, whereas the mean effect size between trust and conspiracy thinking is higher on a descriptive level with Fisher-z = -

.30.

Effects of trust and control on conspiracy beliefs. In Tables 6 and 7 the results of model M1 and M2 are shown, the results for M0 are reported only in the text. As mentioned above the results refer to Fisher-Z-transformed correlations, not to raw correlations. The null hypothesis that all bivariate correlations between trust/ control and belief in conspiracy

2 theories are the same except for random fluctuations due to sampling errors (σSE = .00082) must be rejected (fixed-effect model, M0). A statistically significant Q-statistic, Q(25) = Conspiracy Theories, Trust and Control 35

235.08, p < .0001, shows that the correlations are heterogeneous. Therefore, the fixed-effect model does not fit the data.

Due to the heterogeneity of the used measures and concepts (which are often not validated), it is unclear if the respective scales measure the construct they are supposed to measure as mentioned above. To deal with the heterogeneity of the measurements, a trust/control classification was computed to test for these differences. Nintey-two MTurkers

(Mage = 31.78, SDage = 9.185, n = 52 males) were asked to rate to what extent every scale measures either control or trust using a shortened version on the definitions invented above this paper.

These ratings were transformed into a score that reflects to what extend the respective scale measures either control or trust for every single scale (see Table 5; a more detailed summary of the pretest is available on OSF via https://osf.io/kwz3p). The ratings of the scales were mainly in line with the own classification of the authors (see Table 4; exception for trust: Lamberty, 2016 and for control: Jolley, 2014b). Conspiracy Theories, Trust and Control 36

Table 6 Overview of the studies included in the meta-analysis

Trust/ Study Trust/ Control Trust/ Study ID Conspiracy Measure Control N r ID Scale Control classification Brotherton, 2013 1 Generic conspiracist beliefs scale Interpersonal Trust -1 -1.837 208 -.34 Spheres of control: Bruder, 2013 2 Conspiracy mentality questionnaire 1 2.152 280 .029 personal Spheres of control: Bruder, 2013 2 Conspiracy mentality questionnaire 1 1.044 280 -.091 interpersonal Spheres of control: Bruder, 2013 2 Conspiracy mentality questionnaire socio-political 1 1.63 280 -.22 control Gillman, 2013 3 Conspiracy beliefs Trust in physicians -1 -1.308 47 -.432 Goertzel, 1994 4 Belief in Specific Conspiracies Trust -1 -1.837 348 -.19 Beliefs in anti-vaccine Trust towards Jolley, 2014 5 -1 -1.011 89 -.46 conspiracy authorities Beliefs in anti-vaccine Trust towards Jolley, 2014 6 -1 -1.011 246 -.259 conspiracy authorities Mistrust towards Jolley, 2014b 7 Belief in conspiracy theories -1 -1.196 186 -.386 Institutions Feelings of Jolley, 2014b 7 Belief in conspiracy theories 1 -0.467 186 -.515 uncertainty Conspiracy Mentality Scale (Short Lamberty, 2016 8 Political Trust -1 -1.154 636 -.466 version) Conspiracy Mentality Scale (Short Lamberty, 2016 8 Personal Trust -1 0.554 636 -.056 version) Conspiracy Mentality Scale (Short Lamberty, 2016 8 Political Control 1 1.967 636 -.421 version)

Conspiracy Theories, Trust and Control 37

Conspiracy Mentality Scale (Short Lamberty, 2016 8 Personal Control 1 1.846 636 -.088 version) Generic Conspiracist Beliefs Lantian, 2016 9 Trust -1 -1.84 111 -.43 scale (GCB) Subscale Conspiracy Beliefs Desirability of Lobato, 2014 10 1 1.935 455 -.16 (Epistemically unwarranted beliefs) control (DOC) Mashuri, 2014 11 Belief in a conspiracy theory Intergroup Distrust -1 -1.294 205 -.41 Belief in a conspiracy theory: Miller, 2015 12 Trust -1 -1.576 2203 -.135 conservative index Belief in a conspiracy theory: Miller, 2015 13 Trust -1 -1.143 2485 -.193 conservative index World Assumptions Scale Conspiracy Mentality Questionnaire Moulding, 2016 14 (WAS): 1 1.670 120 -.13 (CMQ) controllability of the world Trust in Uscinski, 2016 15 Conspiratorial predispositions -1 -0.935 1230 -.25 government Van Prooijen, 16 UFO conspiracy belief Y2K control threat 1 1.326 1256 -.16 2015 Van Prooijen, Trust in 16 UFO conspiracy belief -1 -0.956 1256 -.18 2015 government Sense of collective Witkowska, 2016 17 Conspiracy Mentality 1 1.462 155 -.07 control Sociopolitical Witkowska, 2016 18 Conspiracy Mentality 1 1.630 353 -.31 control Witkowska, 2016 18 Conspiracy Mentality Outgroup trust -1 -1.272 353 -.36 Note. Trust/Control = If authors indicated that the scale measures trust (-1) or control (1). Trust/Control classification = Score from the pretest ranging from trust (-3) to control (3)

Conspiracy Theories, Trust and Control 38

The first model that was calculated was the multi-level mixed effects model M1 with trust/control as moderator on level 2 (see Konstantopoulos, 2011). The Q-test suggested that there was a significant amount of heterogeneity left in these data, QE(24) = 285.33, p < .0001.

Figure 5. Profile Likelihood Plots for model M1

The profile likelihood plot of the variance components in the model indicated that there was a significant amount of explained variance in the model (see Figure 5). The profile likelihood plot is peaked at the respective parameter estimates (indicated by the vertical dotted lines) and the log likelihoods quickly decrease (i.e., become more negative) as the values of the components are moved away from the actual REML estimates. Hence, the variance component is identifiable.

Conspiracy Theories, Trust and Control 39

Table 7 Results of the multivariate meta-analysis model M1: Two‐level estimates of fixed effects and variance components

Estimate SE Z p 95% CIlower 95% CIupper

Fixed Effect

Intercept -.238 .033 7.20 <.001 -.302 .173 Effect size .072 .023 3.18 .001 .028 .117

Random Effects Trust/ Control .024 .001 .013 .050 classification Note. k = 26. Method = REML. SE = Standard Error

As can be seen in Table 6, the test of moderators indicated that there was a significant moderation of the trust/control classification on conspiracy beliefs, QM(1) = 10.081, p < .0001 – in line with the prior hypotheses. There was a significant effect on level 1 which was moderated by the classification of the measurement. The more the respective scale was rated as measuring trust the higher the effect size was. The explained variance of the whole model was r2= .024,

95% CI [.011, .057].

To be able to control for a potential effect of the studies and to be able to deal with dependency of the outcomes, a three-level mixed-effect meta-analysis using SEM approach with multi-level structure and scales clustered in studies was calculated (Cheung, 2014). Again, the Q- test suggests that there is a significant amount of heterogeneity left in these data, QE(25) =

309.97, p < .0001.

Conspiracy Theories, Trust and Control 40

Figure 6. Profile Likelihood Plots for model M2

As Figure 6 shows, both variance components are identifiable. The profile likelihood plots are peaked at the respective parameter estimates and the log likelihoods quickly decrease as the values of the components are moved away from the actual REML estimates.

Conspiracy Theories, Trust and Control 41

Table 8 Model Results of the multivariate meta-analysis model M2: Three‐level estimates of fixed effects and variance components

2 Estimates SE Z p 95% CIlower 95 CIupper R

Fixed Effect

Intercept -.237 .039 -6.50 <.0001 -.309 -.656

Effect size .072 .022 3.28 <.001 .029 .148

Random Effects Trust/ Control classification .024 .010 2.21 <.05 .003 .042 .024 (Level 2) Studies (Level 3) .000 .007 0.00 -.014 -.014 .000

Note. N2 of observed statistics = 26 (level 2). N3 of studies = 18 (level 3). Method = REML. SE = Standard Error

The three‐level analysis estimates are summarized in Table 7. As can be seen the random variation was between the trust/control classification and not between studies within the trust/control classification. Therefore, it is plausible that all variation is due to trust/control differences.

The three-level model M2 used in the meta-analysis above allows for the underlying true effects within districts to be correlated. In the present case, the Intra-Class-Correlation is estimated to be ICCModel3 = .602. Therefore, the underlying true effects within studies are estimated to correlate quite strongly. This underpins empirically that both constructs are somehow overlapping. However, it is important to note that the number of studies which used both measures was relatively small and it might be possible that the Intra-Class-Correlation overestimates the true effect size.

Conspiracy Theories, Trust and Control 42

Figure 7. Effect sized of trust (yellow) and control (green) on conspiracy beliefs in dependency of the trust/control- classification.

In sum, results of both models M1 and M2 revealed that there was a stronger influence of trust in contrast to control on conspiracy beliefs (see Figure 7 and Table 6 and 7). These findings are in line with the prior hypothesis that trust has a greater relevance for conspiracy beliefs than control has.

Discussion

Trust and control are two important constructs in the research on conspiracy thinking.

Nonetheless, the results of past research have different limitations, the results especially on control are very heterogeneous as mentioned before. The main goal of this meta-analysis was to compare the effect sizes of trust and control depending on the content of the measurement.

Across the main sample of 18 studies, the mean effects of trust and control on conspiracy beliefs had medium effect sizes with Fisher’s z = -.203 for control and Fisher’s z = -.301 for trust

(Cohen, 1977), indicating the role of both constructs for conspiracy thinking. The second party

Conspiracy Theories, Trust and Control 43 of the question (“Is the influence of trust on conspiracy beliefs stronger compared to control?”) can be answered from the assessment of the moderation analysis. Results indicated, that trust plays a more important role for conspiracy thinking – with an influence of the measurement itself. The results of past research were confounded because of the less precise operationalization of the used measurements.

Like all meta-analyses, the present work is limited by the empirical evidence available.

Substantial efforts were made to collect all relevant data, but the sample is still small compared to other meta-analyses with only 18 included studies. Even if many attempts were made to include non-published results, it might be reasonably assumed that there might be a publication bias that might lead to an overestimation of the effect sizes (Duva, & Tweedie, 2000).

It must be noted that there was still heterogeneity left in the data – also after including trust/control as moderator – and only a small amount of variance was explained. This might be due to the heterogeneity of the used measurements for conspiracy thinking (ranging from scales measuring attitudes towards one specific conspiracy theory to scales measuring conspiracy mentality as a personality trait). The meta-analysis took into account the differences for trust and control, the variance in conspiracy measures remain outside the analysis, which also might influence the analysis.

Study 2

Study 2 was conducted to bolster the findings from the meta-analysis. The trust and control scales with the respective highest score from the pretest were used in this study to have the most unambiguous measure of the respective construct. It was hypothesized that trust as well as control were linked with conspiracy thinking with a greater influence of trust compared to control. In addition, situations where participants lacked control or felt mistrust were assessed

Conspiracy Theories, Trust and Control 44 and shall be linked with conspiracy thinking. For exploratory purposes, two different measurements of conspiracy belief were included in the analysis: one more abstract measurement which accesses conspiracy belief as a personality trait, the conspiracy mentality, and a more specific one which measures agreement with concrete conspiracy theories. As mentioned before in the discussion of the meta-analysis, the measures of conspiracy thinking are quite diverse.

Agreement with specific conspiracy theories might be therefore more influenceable by certain life events compared to a personality trait such as conspiracy mentality.

Methods

Participants. Following recent recommendations regarding the sample size to receive stable correlations (n = 250; Schönbrodt & Perugini, 2013), N = 264 participants were recruited to complete the online survey from Amazon Mechanical Turk (MTurk) in exchange for $0.50.

The use of MTurk in psychological research provides access to more demographically diverse samples of the U.S. voting-age population than student-convenience and non-probability Internet samples and are as reliable as those from traditional methods (e.g., Buhrmester, Kwang, &

Gosling, 2011). Thirty-eight participants were excluded from the analysis because they indicated that their data should not be used (n = 25) or because they skipped the question on data quality (n

=13). Two hundred twenty-six participants (115 men, 111 women; Mage = 36.51 years, SDage =

11.73 years) remained in the sample. The majority of the participants were white (n = 170) and had a relatively high level of education (n = 136 had a university degree).

Measures

Control. An individuals’ beliefs about what amount of control they have over the nonsocial environment was measured with the subscale personal efficacy of the spheres of

Conspiracy Theories, Trust and Control 45 control scale by Paulhus (1983) with ten items using 7-point ratings from 1 (Not at all) to 7 (Very much). Sample item was “I can usually achieve what I want if I work hard for it”.

Trust. A further scale was included to measure trust with a modified version of the interpersonal trust scale introduced by Goertzel (1994) with three items (e.g., “I can trust my relatives”). Participants were asked to rate their agreement with the statements on a 7-point

Likert scale ranging from 1 (Not at all) to 7 (Very much).

Experiences of distrust/ lacking control. Past research suggests that real life events such as unemployment can be operationalized as indicators of control deprivation (e.g., Imhoff, 2015).

However, it is still unclear what kind of events cause feelings of control deprivation and which ones lead to feelings of distrust. To measure participants experiences with situations potentially causing feelings of lacking control or distrust, they were asked to specify the frequency of 16 different events and situations (e.g., war, insomnia, unwanted pregnancy, bondage, lies, sexual affairs of a partner) in their life on a 7-point scale ranging from 1 (Never) to 7 (Very frequently).

In addition, they were asked to rate whether the respective situation was related to a lack of trust or control ranging from 1 (trust) to 7 (control).

Conspiracy Mentality. Conspiracy Mentality as a generalized political attitude was assessed using a twelve items scale introduced by Imhoff and Bruder (2013; e.g., “Most people do not see how much our lives are determined by plots hatched in secret”). Responses were given on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Belief in specific conspiracies. Belief in specific conspiracy theories was measured with an existing scale of endorsement of various real-world conspiracy theories with 17 items

(Douglas & Sutton, 2011). The measure presents statements relating to various popular conspiracy theories, including the deaths of Princess Diana and President Kennedy, 9/11, climate

Conspiracy Theories, Trust and Control 46 change, the European Union or HIV/AIDS (e.g., “Princess Diana’s death was an accident”).

Participants rated the extent to which they agreed with each statement on a 7-point Likert Scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Procedure

After giving informed consent, participants completed the scales measuring trust and control, rated their experiences with the different situations and if they perceived them as representative for trust and control before filling in the conspiracy belief scales, and giving demographic information about age, gender, education, ethnicity, and a subjective estimate of their own data quality. The wording of the data quality question was as follows “As the last question, we would like you to estimate the quality of your data. Sometimes, one is distracted or unmotivated while completing a survey and the given responses are more or less random. To give us a chance to sort out data that is probably useless, we ask you to estimate the quality of your data (this will have no effect on your payment!)”. Answers were given on a scale ranging from 1 (definitely not use my data) to 4 (definitely use my data). At the conclusion of the study, participants were debriefed and thanked for their participation.

Results

Firstly, a link between trust and conspiracy beliefs as well as between control and conspiracy beliefs was predicted. As can be seen in Table 8, the zero-order correlations confirmed the hypotheses that conspiracy mentality was stronger related to trust compared to control as hypothesized before.

Conspiracy Theories, Trust and Control 47

Table 9 Correlations between the main variables in Study 2

M SD α 1 2 3 4 1 Conspiracy 4.458 1.255 .913 .444** -.347** -.151* Mentality 2 Belief in Specific Conspiracy 2.841 1.059 .886 -.097 -.215** Theories 3 Trust 5.088 1.253 .732 .320** 4 Control 5.133 0.928 .833 Note. N = 226. ** p < .001 , * < .05. All scales were measured on a 7 point Likert scale.

For exploratory purposes, two different measures of conspiracy thinking were included in the analysis. However, the correlation between the two conspiracy measures and trust differed, z

= -3.68, p <.001. Contrarily, for the correlations of the two measures with control no such difference was found, z = 0.93, p = .177. These findings show that there might be conceptual differences between the two measures – especially for the role of trust on conspiracy beliefs.

To test the central hypothesis that trust has a greater impact on conspiracy thinking compared to control, a multiple hierarchic regression model was conducted. Trust and control were regressed as z-standardized variables on conspiracy mentality. In line with the hypothesis, conspiracy mentality was predicted by trust, β = -.332, p < .001. Contrary to the prior assumption that control also predicted conspiracy mentality (but to a lesser extent), control had no influence on conspiracy mentality when simultaneously entered in the analysis, β = -.045, p = .497 (Step 1,

R2 = .122).

In addition, a further multiple hierarchic regression model was calculated including a more concrete measure of conspiracy beliefs. Interestingly, the analysis showed a reverse pattern. Trust had no significant influence on the belief in specific conspiracy theories, β = -.031, p = .654, whereas control significantly predicted the belief in specific conspiracy theories, β = -

Conspiracy Theories, Trust and Control 48

.205, p = .003 (Step 1, R2 = .047). The scatter plots of both correlations can be found in Figure 8 illustrating the different correlations for conspiracy mentality and belief in specific conspiracy beliefs. It can be seen that the scale measuring belief in specific conspiracy theories has a lower mean and more data points beneath the midpoint of the scale, the agreement in general is lower compared to the general tendency to endorse a conspiracy mentality.

Figure 8. Correlations of conspiracy mentality (left) and belief in specific conspiracy theories (right) with trust (orange) and control (green)

For exploratory purposes, the interaction of trust and control on conspiracy beliefs was calculated, too. It might be the case that conspiracy beliefs emerge in particular if people have no control over their lives and cannot compensate those feelings of lack of control with trust. Model

1 using 1000 bootstrap samples in the Process macro for SPSS (v2.13.2; Hayes, 2015) was used to calculate the moderation. For conspiracy mentality no such interaction was observed, β = -

.136, p = .089 (Step 2, ΔR = .011).

Conspiracy Theories, Trust and Control 49

Figure 9. Interaction of Trust and Control for Belief in specific conspiracy theories

Contrary, belief in specific conspiracy theories was predicted by the interaction of both variables, β = -.219, p = .002 (Step 2, ΔR = .041). The unstandardized simple slope for participants 1 SD below the mean of trust was .19, p = .057, the unstandardized simple slope for participants with a mean level of trust was -.026, p = .713, and the unstandardized simple slope for participants 1 SD above the mean of trust was -.246, p = .013 (see Figure 9). Low trust was always associated with stronger beliefs in conspiracy theories, there was no significant moderation and therefore no influence of control on the degree of acceptance of conspiracy beliefs. However, if people had a high level of trust, the level of perceived control played an important role for the agreement with specific conspiracy theories. High control was associated with a lesser extent of belief in conspiracy theories, whereas the combination of low control and high trust led to the strongest conspiracy beliefs (see Figure 9).

In addition, participants were asked to estimate whether they perceive the single situations as representative for a lack of either control or trust. This allowed to test whether participants perceived different events rather as lack of trust than lack of control. Past research has only focused on unemployment as a real life situation where people lack control (Imhoff,

2015). Even though they did not measure lack of control or lack of trust directly, Swami and

Conspiracy Theories, Trust and Control 50 colleagues (2016) showed that there was a link between threating experiences in life and conspiracy believes which can be also understand as indicators of lack of control.

However, as far as the author knows, this is the first time that the influence of a larger number of situations from various aspects of human life where people might experience a lack of control and trust was investigated in the research on conspiracy beliefs.

Conspiracy Theories, Trust and Control 51

Table 10 Descriptive Statistics and Correlations of Conspiracy Thinking, Trust and Control with specific events

Belief in Conspiracy specific M SD M SD Trust Control Experience Experience Rating Rating Mentality Conspiracy Theories Lack of Control

Natural disaster 2.57 1.65 4.86 1.66 .158* .373** -.030 -.058

War 1.88 1.39 5.44 1.51 .091 .288** -.014 -.091

Drug use 2.35 1.72 5.09 1.63 .058 .148* -.122 -.126 Fixed-term 3.47 1.96 4.90 1.79 .119 .178** .186** .149* contract Masochism 1.92 1.40 4.82 1.80 .124 .412** -.121 -.278** Drastic political 2.40 1.64 4.77 1.72 .208** .363** -.064 -.192** change Insomnia 3.89 2.07 4.74 1.45 .201** .048 -.183** -.217**

Bondage 1.86 1.53 4.58 2.11 .226** .414** -.035 -.243**

Liabilities 3.12 1.77 4.51 1.67 .136* .173** -.022 -.125 Unwanted 1.61 1.27 4.50 1.73 .083 .414** .019 -.202** pregnancy Extreme sport 2.04 1.61 4.48 1.66 .208** .406** .001 -.092 Sexual 2.30 1.77 4.16 2.20 .275** .396** -.036 -.166* Submission Anesthesia 2.76 1.69 4.15 2.02 .167* .234** .034 -.106

Lack of Trust

Lies 4.38 1.75 3.31 2.26 .219** .134* -.291** -.125 Sexual affair(s) 2.29 1.74 3.12 2.10 .199** .350** -.029 -.113 of the partner Somebody else has broken 4.55 1.51 2.96 2.07 .185** .205** -.208** -.193** his/her promise Note. N = 226. ** p < .001 , * < .05. MExperience and SDExperience indicate the ratings of the participants in study 2 how often they have experienced the respective situation ranging from 1 (never) to 7 (Very frequently) MRating and SDRating reflect the rating of the participants whether they perceive the respective events as lack in trust or control. Higher values indicate a higher lack of control. All scales were measured on 7-point Likert scales.

Conspiracy Theories, Trust and Control 52

As can be seen in Table 9, there were significant correlations between the self-reported frequency for most of the different situations and conspiracy beliefs. These findings are in line with the results of Imhoff (2015) who indicates that not a situational but a chronic loss of control leads to conspiracy beliefs. However, it is unclear if people high in conspiracy thinking have objectively experienced more negative events or if they feel that bad things happen to them more often (or conversely people low in conspiracy beliefs are more likely to forget or ignore these kind of events).

In general, the correlations between the specific measure of conspiracy thinking and the different situations are somehow higher than the link between conspiracy mentality and the different situations - with a small number of exceptions (see Table 9). For exploratory purposes, a principal component and a principal axis analysis were computed. A two factor solution explaining 35.39% of the variance reflecting situations where people either lacked trust (e.g., sexual affair of the partner, 3 items, α = .660) or control (e.g., bondage, 13 items, α = .870).

Table 11 Correlations between Conspiracy beliefs, trust, control and specific situations

1 2 3 4 5 6 1 Conspiracy Mentality .444** -.347** -.151* .257** .260** 2 Specific Conspiracy Theories -.097 -.215** .453** .296** 3 Trust .320** -.048 -.221** 4 Control -.205** -.183** 5 Situations lacking control .651** 6 Situations lacking trust Note. N = 226. ** p < .001 , * < .05. All scales were measured on 7-point Likert scales.

Conspiracy Theories, Trust and Control 53

As can be seen in Table 10, the correlation between belief in specific conspiracy theories and situations where people lacked control was significantly higher than with trust, z = 2.759, p =

.003. No significant difference was found between situation where people lacked control and trust and conspiracy mentality, z = -0.05, p = .48. In addition, there was no significant difference between the two measures of conspiracy beliefs and the experience of situations lacking trust, z =

-0.535, p = .296, but for control, z = -3.038, p < .001.

Discussion

The main aim of Study 2 was to replicate the findings of the meta-analysis concerning the role of trust and control on conspiracy thinking. In line with the hypothesis, there was a significant correlation between trust, control and both of the conspiracy measures – with a higher influence of trust on conspiracy mentality. Unexpectedly, the pattern for the specific measure of belief in conspiracy theories was vice versa. This pattern was also more or less replicated for concrete situations which lead to a lack of control or trust: Situations which were rated as lacking control were linked to belief in specific theories more than to conspiracy mentality.

Currently, there exists a wide range of measurements – some measure the belief in a concrete, single conspiracy belief, whereas other conceptualize the belief in conspiracy theories as a stable, interindividual personality trait. It appears to be the case that the different measurements are linked to different psychological processes and therefore they cannot be put in one basket.

The correlations between the conspiracy measures and the experiences of situations where people lacked trust or control show a higher correlation with control for both measures. It

Conspiracy Theories, Trust and Control 54 might be the case that past experiences of lacking control are more important for the development of conspiracy beliefs than a dispositional control belief.

Study 3

Whereas there is some research exploring experimentally the role of control on conspiracy theories (e.g., Sullivan, et al., 2010; Whitson & Galinsky, 2008; Van Prooijen &

Acker, 2014), the role of trust has not been tested experimentally yet as far as the author knows.

To test the causal role of trust and control on the development of conspiracy theories, experiences where people had no control compared to no trust were manipulated directly. I hypothesized that as well trust as control would lead to an increase in conspiracy thinking compared to the control condition – with a greater effect for trust.

Method

Participants. Following the effect size reported in the study from Whitson and Galinsky

(2008, experiment 4), a large effect for control on conspiracy thinking could be assumed (f = -

.438) and a sample size of N = 103 would be appropriate for detecting an effect of this size

(G*Power; Faul, Erdfelder, Lang, & Buchner, 2007). However, the study of Whitson and

Galinsky probably overestimated the effect size due to the small sample size (N = 25). Therefore,

I aimed for N = 300 participants. Three hundred and five participants from MTurk completed an online survey in exchange for $0.60. Thirty-four participants were excluded because they indicated that their data definitively should not be used (n =26) or skipped the question on data quality (n =8). Two hundred seventy-nine participants (148 men, 128 women, 1 other, 2 missings; Mage = 34.55 years, SDage = 11.38 years) remained in the sample.

Independent variable

Conspiracy Theories, Trust and Control 55

Participants were asked to write about an autobiographical experience (following

Whitson & Galinsky, 2008, Study 3). Participants were either exposed to the task to the non-trust condition (“Please recall a particular incident in which you had the expectancy that somebody else’s behavior was not predictable and the intentions were not benign”), the no-control condition (“Please recall a particular incident in which something happened and you did not belief that a certain kind of outcome was predictable and influenceable in the desired direction.”) or the control group without any task. In the no-trust or no-control condition, participants were asked to describe the situation in a few sentences. Participants were randomly assigned to one of the three conditions.

Measures

Trust and Control. Trust and control were measured with the same scale as in study 2.

Conspiracy Thinking. Conspiracy mentality and belief in specific conspiracy theories beliefs were measured identically as in study 2.

Illusory pattern perception. Illusory pattern perception was measured with a modified form of the Snowy Pictures Task (Whitson & Galinsky, 2008, Study 2). The task consists of 24

'snowy' pictures whereby half of the sample contained images and half of them contained only snow. Participants were asked to indicate whether the pictures had objects in them or not. The first study measuring the role of control on conspiracy thinking by Whitson and Galinsky (2008) was underpowered due to a too small sample size, but is still the argumentative base for the research in conspiracy thinking. Some attempts to replicate these findings failed for conspiracy thinking (e.g., Imhoff, 2015), whereas others succeeded (Van Prooijen & Acker, 2015). The measure was included to get a better understanding on the role of control for illusory pattern perception in general and conspiracy beliefs.

Conspiracy Theories, Trust and Control 56

Design

Following the experimental setting of Whitson and Galinsky (2008), participants were told that they would be completing several unrelated tasks. After giving informed consent, participants were exposed to the experimental manipulation and asked either to recall a situation where they had no trust or no control or to the control condition. Participants completed the scales measuring trust, control, and conspiracy beliefs, and completed the modified form of the

Snowy Pictures Task. They completed demographic questions and a subjective estimate of their own data quality as in study 2. At the conclusion of the study, participants were debriefed and thanked for their participation.

Results

First of all, I checked whether the experiment manipulation influenced the level of trust and control as manipulation check. The experimental manipulation had a significant effect on the level of perceived control, F(2, 276) = 3.958, p = .020, η2 = .028. As can be seen in Table 11, surprisingly, participants reported a slightly higher level of control in the control and also in the trust condition compared to the control group. For trust no difference was found between the conditions, F(2, 276) = 0.940, p = .392, η2 = .007.

Conspiracy Theories, Trust and Control 57

Table 12 Descriptive statistics of the dependent variables across the experimental conditions

Belief in Illusory Control Trust Conspiracy specific pattern Mentality conspiracies perception M SD M SD M SD M SD M SD Lack of Control 5.26 1.06 4.96 1.29 4.53 1.26 2.90 1.04 11.93 5.05

Lack of Trust 5.32 0.95 5.07 1.21 4.39 1.21 2.64 0.98 12.45 4.68

Control Group 4.95 0.98 5.19 1.07 4.39 1.21 2.78 1.01 10.93 4.59 Note. All scales were measured on a 7-point Likert scale except for illusory pattern perception. Illusory pattern perception ranged between 0 (no object) and 24 (object in every picture). Higher values indicate higher levels of agreement.

To test the main hypothesis that lack of trust as well lack of control would increase conspiracy mentality - with greater effects of trust – an ANOVA was conducted. However, there was no effect of the experimental manipulation on conspiracy mentality, F(2, 276) = 0.293, p =

.746, η2 = .002. For exploratory purposes, also belief in specific conspiracies and illusory pattern perception was measured. Again, no effect was found for belief in specific conspiracy theories,

F(2, 276) = 1.288, p = .278, η2 = .009. Likewise, the experimental manipulation did not affect illusory pattern perception, F(2, 276) = 2.428, p = .090, η2 = .019. Thereby neither the main hypothesis could be confirmed nor the results from Whitson and Galinsky (2008) be replicated.2

Discussion

Study 3 replicated in so far the findings of the meta-analysis and study 2 that the link between trust and conspiracy mentality was stronger (r = -.227, p <.001 for the whole sample;

2 Even if the trust condition was excluded and the control condition was compared only with the control group to have a more or less direct replication of the Whitson and Galinsky (2008) study, there was no difference found for illusory pattern perception, F(1, 172) = 1.827, p = .178, η2 = .011, nor for belief in specific conspiracy theories, F(1, 197) = 0.692, p = .663, η2 = .003, nor for conspiracy mentality, F(1, 197) = 0.628, p = .429, η2 = .003.

Conspiracy Theories, Trust and Control 58 see table in the OSF for the correlations across the single conditions) compared to control (r =

.004, p = .945 for the whole sample), z = -3.021, p = .001.

However, the manipulation itself did not affect neither the two measures of conspiracy thinking nor illusory pattern perception. Whereas the experimental manipulation did not affect the level of trust, there was an effect of the experimental manipulation on the level of control – but in an unexpected direction: participants in the lack of control as well in the lack of trust condition reported significant higher personal efficacy after the essay priming compared to the control condition. It might be the case that the manipulation prompted participants to remind themselves of situations where they lacked control or felt distrust and successfully dealt with this threat. According to this, the manipulation would not lead to a lack of control and therefore explain the higher means in lack of control condition. However, this does not explain why also the trust condition led to an increase in control.

The design was chosen to be able to replicate the findings of Whitson and Galinsky

(2008) and be able to compare the influence of trust and control on conspiracy beliefs (and illusory pattern perception). Apparently, it was not suitable to induce a lack of control as well as a lack of trust. Further research should address that and use other paradigms for the research of trust and control on conspiracy thinking. In addition, it might be the case that prior level of trust and control feelings influence the strength of the manipulation. To be able to control for trust and control, both variables should be measured before.

General Discussion

In one meta-analysis, a correlational study and one experiment, the role of trust and control for the development of conspiracy thinking was explored. In line with the hypothesis, it can be shown that there was a stronger influence of trust on conspiracy thinking compared to

Conspiracy Theories, Trust and Control 59 control and that the operationalization of the measurements influenced the effect size (study 1).

Study 2 replicated those findings for conspiracy mentality. The influence of control disappeared when trust was analyzed at the same time. Contrary to prior expectancies, those findings pointed in the opposite direction for the belief in specific conspiracy theories. Belief in specific conspiracy theories was not linked to trust in any way. These findings suggest the importance of systematizing the different measurements of conspiracy thinking.

Past research has not distinguished precisely between the different measurements of conspiracy theories. Following the findings in this research, it might be the case that the used scales are linked to different psychological processes. Conspiracy mentality, for instance, is theoretically conceptualized as a personality trait. This implies that conspiracy mentality should be less influencable by external circumstances and more robust compared to scales measuring attitudes towards specific conspiracy theories.

Reanalysis of past findings of lack of control on conspiracy beliefs

Study 3 was conducted to show that distrust and not control invokes conspirational thinking in participants. Even if the experimental manipulation affected the level of control (in an unexpected direction) but not the level trust, there was no difference between the experimental and the control conditions in conspiracy thinking. Although the experimental conditions influences the control feelings of the participants, no change in all of the three measures were observed. Based on these findings it seems difficult to conclude that a lack of control increases conspiracy beliefs or illusory pattern perception.

To get a general idea of the effects of control threat on conspiracy thinking in experimental settings, I reanalyzed the results of past experiments on lack of control on conspiracy beliefs insofar the data were available. Three published and four unpublished

Conspiracy Theories, Trust and Control 60 experiments were included in the analysis. Cohen's d (1988) was used to compute unified effect sizes. Based on these seven individual effect sizes, a random effects meta-analysis was computed with OpenMeta[Analyst] (Wallace et al., 2012) with subgroup analysis to compare published and unpublished results.

Table 13 Results of meta-analysis on the role of lack of control on the development of conspiracy beliefs

Studies Estimate 95% CIlower 95% CIupper SE p Unpublished -0.108 -0.287 0.070 .091 .235 Published -1.057 -1.453 -0.660 .202 <.001 Overall -0.445 -0.849 -0.042 .206 .031 Note. k = 7. SE = Standard Error

In total, the meta-analysis suggests a low to moderate effect size for lack of control on conspiracy beliefs indicating stronger conspiracy beliefs in the control threat condition (see

Table 12). However, the mean overall effect differed significantly from zero, p = .031. The effect sizes ranged between d = .21 and d = -1.33 with only one comparison having a positive effect

(i.e., less conspiracy thinking in the control threat condition compared to the control condition).

Conspiracy Theories, Trust and Control 61

Figure 10. Reanalysis of past findings on lack of control on conspiracy thinking divided in two subgroups (computed with OpenMeta[Analyst]; Wallace et al., 2012).

The main analysis indicated that the whole sample cannot be seen as studies of one

(homogeneous) population, Q(6)= 38.12, p = .002 (see Figure 10) – that’s why the sample was divided into subgroups. The subgroup analysis showed different effects for published (in a peer- reviewed journal) versus unpublished data (e.g., non-published or book chapter). The mean effect size for the published data was d = -1.057, whereas the mean effect size for unpublished data was much smaller, d = -0.108. Probably due to the smaller sample size, the confidence interval was larger for the published data indicating less precise studies. Unfortunately, there was a confound of non-published results and lab.

Similar differences were found for the replication of the influence of control threat on magical thinking (which is often studied together with conspiracy thinking, e.g., Darwin et al.,

2011; Pennycook, Cheyne, Barr, Koehler, & Fugelsang, 2015) between published and unpublished data. Some scholars tried to replicate that control threat leads to an increase in

Conspiracy Theories, Trust and Control 62 magical thinking. However, in the studies of Lodder and van Elk (2013), control threat did not influence magical thinking – using Bayesian analyses they even found support for the null hypothesis.

To sum it up, there are huge differences in the effect sizes between published and unpublished data. The overall effect of the reanalysis suggests that there is a significant effect of lacking control on conspiracy beliefs. It might be noteworthy that the confidence interval of the overall effect is relatively huge and very close to zero. From the current data it can be carefully concluded that there might be an effect of lacking control on conspiracy beliefs.

Limitations and Future Directions

The major strength of the present research lies in its systematic investigation of the association between a generalized political attitude and trust and control. However, the current research had some important limitations that should also be addressed in future research. As noted before, the results of the meta-analysis can only be as reliable as the data the meta-analysis uses and is limited by the empirical evidence available and by methodological constraints. Even though lots of effort was made to collect all data that has been conducted on that topic, several issues could not be examined in detail because of the small number of studies addressing those issues. For instance, there were no studies testing the role of trust on the development of conspiracy thinking experimentally. As the funnel plot of the main meta-analysis and the results of the overview of the experimental data on control and conspiracy thinking show, a publication bias might be likely for the present analysis.

A further complication is that the heterogeneity of the scales used in the research on conspiracy thinking. I could only account for the heterogeneity of the trust and control scales, whereas the different conceptualization of conspiracy thinking was not taken into account.

Conspiracy Theories, Trust and Control 63

Probably the main result of this work is that psychological research should be more precise with the definitions of their constructs. For the trust and control measurements but also for conspiracy thinking it turned out that results were different whichever scale was used. Future research should address that and do more conceptual work on the distinction between the concrete belief in a conspiracy theory and the more abstract conspiracy mentality.

Conclusion

Past research has pointed out the role of trust and control on the development of conspiracy thinking – with ambiguous findings. The present work offer a systematic approach to extend the research on the two constructs to deal with the heterogeneity of past results. In sum, the findings reveal that trust as well as control play role for conspiracy thinking – with different results depending of the used measurement.

Conspiracy Theories, Trust and Control 64

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