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Abstract

Conspiracy theories assert that others have engaged in dishonest actions. However, existing research indicates that individuals who believe in conspiracy theories may themselves be more inclined to engage in dishonest behavior. We conducted two preregistered studies—one in Turkey (N = 706) and the other in Canada (N = 835) and South Africa, (N = 867)—testing the hypotheses that conspiracy beliefs would be positively correlated with (a) dishonest behavior during a monetary incentivized lying task and (b) overestimating the prevalence of dishonesty among other people. Overall, we found that stronger conspiracy beliefs were associated with higher dishonesty. Participants tended to overestimate dishonesty among their peers, but this tendency was significantly more pronounced among people with stronger conspiracy beliefs. Contrary to our hypothesis, country-level corruption did not moderate this association. These results shed light on the complex relationship between conspiracy beliefs, dishonesty, and expectations of dishonesty.

Keywords

conspiracy deception dishonesty lying

Conspiracy theories imply that others have acted dishonestly, but evidence suggests that people with stronger conspiracy beliefs themselves might also be more likely to act dishonestly. For example, the more people believe in conspiracy theories, the more they tend to be self-centered, antisocial, and willing to violate social norms (Douglas & Sutton, 2011; Hughes & Machan, 2021; Jolley et al., 2019; Kay, 2021; March & Springer, 2019). Furthermore, associations between conspiracy beliefs and paranoia (e.g., Imhoff & Lamberty, 2018; van der Linden et al., 2021) and distrust (Abalakina-Paap et al., 1999; Douglas et al., 2019; Douglas & Sutton, 2018) suggest that people with stronger conspiracy beliefs might be prone to overestimate others’ dishonesty. The current research examines the link between belief in conspiracy theories, dishonesty, and expectations of dishonesty. We examine whether people with stronger conspiracy beliefs are more likely to (a) act dishonestly in a lying task and (b) overestimate others’ dishonesty.

Are Conspiracy Beliefs and Dishonesty Correlated?

Conspiracy theories propose that events of public interest are the result of secret plots by typically powerful groups (Douglas & Sutton, 2023). They allege that others have acted dishonestly to achieve a sinister goal. Belief in conspiracy theories therefore entails a deep suspicion of others’ motives and allegations that they have been deceitful. However, while believers in conspiracy theories are quick to point out the dishonesty in others, research suggests that they themselves may also be more likely to be dishonest. Research has shown that people with stronger conspiracy beliefs express more willingness to engage in conspiracies themselves (Douglas & Sutton, 2011). This proclivity to project their own intentions to conspire onto others might partially explain their receptivity to conspiracy theories about others. In other words, conspiracy believers could find conspiracy theories more plausible because they are more dishonest themselves.

People with stronger conspiracy beliefs are also more likely to violate social norms and have higher intentions to commit everyday crimes (Jolley et al., 2019). They are more likely to break rules and behave aggressively (Poon et al., 2024). Conspiracy beliefs also correlate with the Dark Triad personality traits (Kay, 2021; March & Springer, 2019), which are universally recognized as malevolent (Muris et al., 2017; Paulhus & Williams, 2002). Belief in conspiracy theories has also been observed to be negatively related to honesty–humility (Jolley et al., 2019) and to prosocial intentions across 52 countries (Alper, Douglas, Capraro, 2021). Taken together, research suggests that conspiracy beliefs are likely to correlate with self-interest, antisociality, and dishonesty. We therefore hypothesize that stronger conspiracy beliefs will correlate with higher likelihood of engaging in dishonest behavior (H1).

Are Conspiracy Beliefs and Overestimating Others’ Dishonesty Correlated?

All conspiracy beliefs are based on the assumption that dishonest, malevolent actors are involved in secret plots. Thus, unsurprisingly, believing in conspiracy theories is related to a lack of trust in others (Abalakina-Paap et al., 1999; Douglas et al., 2019; Douglas & Sutton, 2018; Goertzel, 1994; Golec de Zavala & Federico, 2018; van Prooijen & Acker, 2015) and with lower levels of trust in governments, authorities, media, and experts (Eberl et al., 2021; Mari et al., 2021). The higher-order social factors that undermine trust, such as corruption (Alper, 2023), inequality (Casara et al., 2022), and lack of political control (Kofta et al., 2020) are also associated with stronger conspiracy beliefs. Also, although they are conceptually distinct, conspiracy beliefs and paranoia share common characteristics, such as hypervigilance against alleged malevolent intentions of others (Greenburgh & Raihani, 2022; Imhoff & Lamberty, 2018). Thus, conspiracy beliefs appear to be closely linked with distrust and paranoia, suggesting that increased suspicion of, and distrust in, others may be potentially inflated.

Another line of research suggesting that people with stronger conspiracy beliefs might overestimate dishonesty stems from studies on their perceptions of trust in experimental games. Recent research demonstrated that conspiracy believers were less trustful of their counterparts in an economic game, and that conspiracy believers also perceived their counterparts’ faces to be more threatening, regardless of their actual facial trustworthiness (Frenken & Imhoff, 2023; Meuer & Imhoff, 2021). This suggests that conspiracy believers’ perceptions of threat are likely to be inaccurate. However, facial cues are only indirect measures of potential untrustworthiness and do not provide information on whether the target person behaves dishonestly. Considering these findings, we expect that higher expectations of dishonesty associated with stronger conspiracy beliefs will likely be an overestimation (H2).

Overview of the Current Research

In this research, we test two main hypotheses. H1 posits that conspiracy beliefs will be positively related to dishonesty. We measured dishonesty through both a self-report and a behavioral measure. The behavioral measure involved a monetary incentivized lying task (Capraro et al., 2019), which offers participants the opportunity to lie for personal gain. This serves as an effective measure of whether dishonest tendencies translate into actual behavior. Observing actual dishonest behavior allows us to compare individuals’ expectations of dishonesty with the observed frequency of dishonest actions within the sample. This comparison leads to our second hypothesis that conspiracy beliefs will be positively associated with overestimations of others’ dishonesty.

H2 predicts that conspiracy beliefs will be positively related to overestimating the prevalence of dishonesty among other participants.¹ Overestimation is calculated by comparing the predictions of participants with the actual frequency of dishonest behavior among the remaining participants. In Study 2, we also test whether the link between conspiracy beliefs and overestimation is weaker in country with a high-level corruption, compared with a low-corruption country because people indeed would be more likely act dishonestly in such contexts (Gächter & Schulz, 2016; Muthukrishna et al., 2017).

Study 1

Hypotheses, sampling plan, exclusion criteria, and analysis procedure were preregistered prior to data collection (https://osf.io/gqmtx). Data and materials are available at https://osf.io/t7pjr/.

A Priori Power Analysis

We based our sample size estimation on the detection of moderate-size correlations (i.e., r = .20, as recommended in the work by Funder & Ozer, 2019). Assuming power of .80 and alpha of .05, we estimated that the minimum required number of participants to detect such correlations was 193, using G*Power software (Faul et al., 2007). We preregistered that we would continue data collection for 14 days. If the total number of participants was 193 or more, we would stop data collection, otherwise we would continue until reaching that size.

Participants and Exclusion Criteria

We recruited a convenience sample of Turkish participants via social media. We announced the study on the social media platform Twitter (now X) with a brief description and the information that three randomly selected participants would win a gift card of 100 Turkish Liras (an equivalent of US$11.89 and 3% of the monthly minimum wage in Turkey at the time of data collection). As per the preregistration, we stopped recruiting participants after 2 weeks of data collection, which resulted in a sample of 711 participants who completed all materials and correctly responded to both comprehension questions. We also excluded those who (a) failed an attention check (embedded in the Generic Conspiracist Beliefs Scale) in which they were instructed to choose “2,” or (b) completed the study either too quickly (z for completion time in seconds < −3) or too slowly (z > 3). The resulting N was 706 (549 female, 156 male, 1 other; M_age = 28.00, SD = 8.54). The resulting N of 706 was sensitive to detect a correlation as small as .09 with 80% power.

Materials and Procedure

Lying Task

First, participants completed a lying task to measure their dishonest behavior. We used a variant of Gneezy’s deception game to measure whether participants choose to communicate a message they know to be untrue to maximize their monetary payoff at the expense of others’ payoff (Gneezy, 2005). Two players are paired, and one of them can lie for their personal benefit. However, unlike Gneezy’s game, the second player is passive and makes no decision. We implemented this change to avoid the behavior of the first player being confounded by their beliefs about the behavior of the second player. We used the paradigm introduced in the work by Capraro et al. (2019; see also Biziou-van-Pol et al., 2015; Capraro, 2017; Gneezy et al., 2013). We informed participants that they were randomly assigned to one of the two groups and they were matched with another participant who was assigned to the opposite group. This was a cover story and there was no real counterpart. We then provided participants with a choice: If they honestly report the group they were assigned to, both the participant and the other person receive five tickets for a gift lottery (honest response). However, if they report being assigned to the other group, they receive eight tickets while the other person receives only two tickets (dishonest response). A dummy variable (0 = honest, 1 = dishonest) was computed based on participants’ responses.

Expectations Regarding Others’ Dishonesty

Second, we asked participants to estimate what percentage of other participants would act dishonestly (on the same dishonesty paradigm) on a scale ranging from 0% to 100%.

Conspiracy Beliefs

After participants reported their expectations regarding others’ dishonesty, we measured conspiracy beliefs using two different scales. First was the Generic Conspiracist Beliefs Scale (henceforth referred to as generic conspiracy beliefs; Brotherton et al., 2013; translated into Turkish by Alper, Bayrak, Yilmaz, 2021), which is a 15-item scale (e.g., “Secret organizations communicate with extraterrestrials, but keep this fact from the public”) using a five-point response format (1 = definitely not true, 5 = definitely true; α = .90). We also used the Turkish version of the Conspiracy Mentality Questionnaire (henceforth referred to as conspiracy mentality; Bruder et al., 2013), which is a five-item scale (e.g., “I think that government agencies closely monitor all citizens”) using an 11-point response format (0 = 0% definitely no, 11 = 100% definitely yes; α = .79).

Honesty–Humility

Next, as a supplement to the main measure of behavioral dishonesty, we also measured self-reported dishonesty using the Turkish version of the honesty–humility subscale of HEXACO Personality Inventory (Ashton & Lee, 2009). The scale consists of 10 items (e.g., “I would never accept a bribe, even if it were very large”) and uses a five-point response format (1 = strongly disagree, 5 = strongly agree; α = .72). We preregistered the analyses involving honesty–humility as exploratory.

Demographics

Finally, participants stated their age, gender (male, female, other), education status (seven-point scale, ranging from elementary school to PhD), and perceived income status on a ladder from 1 (people with the least money) to 10 (people with the most money). We preregistered to adjust for differences in these covariates when analyzing the relationship between conspiracy beliefs and dishonesty-related measures. At the end of the survey, we also asked “How likely do you think the other participant you were matched with was a real person?” (1 = very unlikely, 7 = very likely). This was an exploratory question and we report the distribution of responses in the Supplementary Materials (SM) 1.

Results

Dishonesty

A one unit increase in conspiracy mentality was associated with an 11.5% increase in the likelihood of dishonesty, b = .109, SE = .055, Z = 1.980, p = .048, OR = 1.115, 95% CI for OR = [1.001, 1.242], while generic conspiracy beliefs were not associated with dishonesty, b = .177, SE = .130, Z = 1.360, p = .174, OR = 1.193, 95% CI for OR = [.925, 1.529] (see Table 1 and Figure 1). Controlling for differences in age, gender, education status, and income did not change the results (see SM 1 for more details). Thus, Hypothesis 1 received partial support: Conspiracy beliefs, as measured by the conspiracy mentality scale, were related to dishonesty, while generic conspiracy beliefs were not.²

Table 1

Correlation Table and Descriptive Statistics of the Main Variables for the Turkish Sample in Study 1

Variables	Generic conspiracy beliefs	Conspiracy mentality	Expectations of dishonesty	Dishonesty	Honesty–humility
Generic conspiracy beliefs	—
Conspiracy mentality	.708***	—
Expectations of dishonesty	.087*	.128***	—
Dishonesty	.051	.075*	.331***	—
Honesty–humility	−.143***	−.103**	−.090*	−.248***	—
Mean	2.679	6.766	59.234	0.171	3.536
Standard deviation	0.765	1.883	22.446	0.377	0.653

p < .05, **p < .01, ***p < .001. N = 706.

Figure 1

Plots Depicting How Conspiracy Mentality and Generic Conspiracy Beliefs Predict the Probability of a Dishonest Response in Study 1

We also found that both generic conspiracy beliefs, b = −.122, SE = .032, β = −.143, 95% CI for β = [−.216, −.070], t = −3.835, p < .001, and conspiracy mentality, b = −.036, SE = .013, β = −.103, 95% CI for β= [−.176, −.029], t = −2.741, p = .006, were associated with lower levels of self-reported honesty–humility, supporting H1. We also checked the association between self-reported honesty–humility and dishonest behavior in the lying task to ensure conceptual consistency. A one unit increase in honesty–humility was associated with a 63.6% decrease in the odds of dishonesty behavior, b = −1.011, SE = .160, Z = −6.323, p < .001, OR = .364, 95% CI for OR = [.266, .498].

Expectations Regarding Others’ Dishonesty

The actual rate of participants who chose the dishonesty option in the lying task was 17.1%. Most people overestimated others’ dishonesty (see Figure 2) but overestimation was positively related to both conspiracy mentality, b = 1.527, SE = .445, β = .128, 95% CI for β = [.055, .202], t = 3.428, p < .001, and generic conspiracy beliefs, b = 2.550, SE = 1.102, β = .087, 95% CI for β = [.013, .161], t = 2.314, p = .021. Adjusting for control variables did not change the findings (see SM 1). In an unregistered exploratory analysis, we controlled for participants’ own dishonesty. After adjusting for own dishonesty in the first step, both generic conspiracy beliefs, b = 2.058, SE = 1.043, β = .070, 95% CI for β = [.010, 4.106], t = 1.973, p = .049, and conspiracy mentality, b = 1.249, SE = .423, β = .104, 95% CI for β = [.410, 2.070], t = 2.932, p = .003, were associated with higher expectations of dishonesty. Thus, H2 was supported: Conspiracy beliefs were positively correlated with overestimation of others’ dishonesty (see Figure 2).

Figure 2

Scatter Plots Depicting the Association Between Expectations of Dishonesty and Both Conspiracy Mentality and Generic Conspiracy Beliefs in Study 1

The preregistered hypotheses therefore received overall support. Conspiracy beliefs were related to higher levels of dishonesty in the lying task, but only when measured by the conspiracy mentality scale. Both measures of conspiracy beliefs were significantly and negatively related to self-reported honesty while positively correlated with overestimation of others’ dishonesty.

Study 2

We aimed to replicate the findings of Study 1 in two culturally distinct countries, Canada and South Africa. The reason why we chose Canada and South Africa was that these two countries have very different levels of country-level corruption (Transparency International, 2023). Research has demonstrated that people are more likely to act dishonestly in more corrupt countries (Gächter & Schulz, 2016; Muthukrishna et al., 2017). Based on this, we expected that people with higher conspiracy beliefs would be more likely to expect others to act dishonestly, but that this association would be weaker in more corrupt countries where dishonesty is, in fact, more widespread. This is because in high-corruption contexts, as in low-corruption contexts, people with high conspiracy beliefs would continue to have high expectations of dishonesty. However, in high-corruption contexts, other people would indeed be more likely to act dishonestly, making it less likely that a high expectation of dishonesty is an overestimation. Thus, in addition to the hypotheses in Study 1, we also tested the hypothesis that the association between conspiracy beliefs and overestimating others’ dishonesty would be weaker in countries with high-corruption levels. We used the same materials, leveraging the widespread use of English in both countries. We slightly modified the incentive structure: Participants were rewarded with real money based on their decisions, moving away from the extra lottery ticket rewards used in Study 1. We also randomized the order of the lying task and the conspiracy measures to check for a potential order effect.

Hypotheses, sampling plan, exclusion criteria, and analysis procedure were preregistered prior to data collection (https://osf.io/j5z69). Data and materials are available at https://osf.io/t7pjr/.

Participants

We aimed to recruit 855 participants each from Canada and South Africa. The sample size was limited by our available budget. We recruited participants from Prolific data collection service (www.prolific.co). Participation was in exchange for £1 UK currency, and participants were informed that they might earn a bonus payment up to an additional £0.10. The preregistered exclusion criteria were the same as in Study 1. After the exclusions, the resulting sample consisted of 835 participants from Canada (411 female, 401 male, 19 non-binary/other, 4 rather not say; M_age = 34.27, SD = 11.30) and 867 participants³ from South Africa (430 female, 431 male, 4 non-binary/other, 2 rather not say; M_age = 28.79, SD = 7.63). The total sample of 1,702 participants was sensitive to detect a correlation of r = .07, assuming the alpha level of .05 and statistical power of .80.

Materials and Procedure

The materials were the same as in Study 1 with three exceptions. In the lying task, participants were allowed to earn bonus payments, instead of winning extra tickets for a lottery. We also randomized the order of the lying task and conspiracy beliefs measures, and included a one-item measure of individual-level perceived corruption measured on a scale ranging from 1 (“there is no corruption in Canada [South Africa]”) to 10 (“there is abundant corruption in Canada [South Africa]”).

Results

Dishonesty

In the Canadian sample, a one unit increase in conspiracy mentality was associated with an 12.8% increase in the likelihood of dishonesty, b = .120, SE = .046, Z = 2.588, p = .010, OR = 1.128, 95% CI for OR = [1.030, 1.235], and a one unit increase in generic conspiracy beliefs was associated with an 41.7% increase in the likelihood of dishonesty, b = .349, SE = .103, Z = 3.374, p < .001, OR = 1.417, 95% CI for OR = [1.157, 1.736] (see Tables 2 and 3; see Figure 3). In the South African sample, neither conspiracy mentality, b = .087, SE = .051, Z = 1.714, p = .087, OR = 1.091, 95% CI for OR = [.988, 1.205] nor generic conspiracy beliefs, b = .108, SE = .093, Z = 1.153, p = .249, OR = 1.114, 95% CI for OR = [.927, 1.337] were associated with dishonest behavior. Controlling for differences in age, gender, education status, and income did not change the results (see SM 1). Thus, Hypothesis 1 was supported in the Canadian, but not in the South African, sample.

Table 2

Correlation Table and Descriptive Statistics of the Main Variables for the Canadian Sample in Study 2

	Generic conspiracy beliefs	Conspiracy mentality	Expectations of dishonesty	Dishonesty	Honesty–humility
Generic conspiracy beliefs	—
Conspiracy mentality	.762	—
Expectations of dishonesty	.160	.171	—
Dishonesty	.118	.090	.414	—
Honesty–humility	−.201	−.198	−.136	−.189	—
Mean	2.468	6.705	49.747	0.192	3.343
Standard deviation	0.830	1.956	23.295	0.394	0.667

Note. All correlations are significant at p < .001. N = 835.

Table 3

Correlation Table and Descriptive Statistics of the Main Variables for the South African Sample in Study 2

	Generic conspiracy beliefs	Conspiracy mentality	Expectations of dishonesty	Dishonesty	Honesty–humility
Generic conspiracy beliefs	—
Conspiracy mentality	.695***	—
Expectations of dishonesty	.120***	.141***	—
Dishonesty	.039	.058	.317***	—
Honesty–humility	−.164***	−.083*	−.055	−.147***	—
Mean	3.428	8.647	66.946	0.302	3.284
Standard deviation	0.823	1.508	22.498	0.459	0.663

p < .05, **p < .01, ***p < .001. N = 867.

Figure 3

Plots Depicting How Conspiracy Mentality and Generic Conspiracy Beliefs Predict the Probability of a Dishonest Response in Study 2

We also found that, in the Canadian sample, both generic conspiracy beliefs, b = −.126, SE = .017, β = −.179, 95% CI for β = [−.226, −.133], t = −7.519, p < .001, and conspiracy mentality, b = −.050, SE = .008, β = −.149, 95% CI for β [−.196, −.101], t = −6.192, p < .001, were associated with lower levels of self-reported honesty–humility. In the South African sample, similarly, both generic conspiracy beliefs, b = −.136, SE = .028, β = −.164, 95% CI for β = =[−.230, −.098], t = −3.894, p < .001, and conspiracy mentality, b = −.036, SE = .015, β = −.083, 95% CI for β = [−.149, −.016], t = −2.449, p = .015, were associated with lower levels of self-reported honesty–humility. Thus, Hypothesis 1 was supported in both samples, when dishonesty was measured using the self-reported questionnaire. We also checked the association between self-reported honesty–humility and dishonest behavior in the lying task to ensure conceptual consistency. A one unit increase in honesty–humility was associated with a 52.5% decrease in the odds of dishonesty behavior, b = −.745, SE = .139, Z = −5.358, p < .001, OR = .475, 95% CI for OR = [.361, 623] in Canada, and 39% in South Africa, b = −.494, SE = .116, Z = −4.279, p < .001, OR = .610, 95% CI for OR = [.486, 765].

Expectations Regarding Others’ Dishonesty

The actual rate of participants who chose the dishonesty option in the lying task was 19.2% in Canada and 30.2% in South Africa. Most people overestimated others’ dishonesty (see Figure 4) but overestimation was positively related to both generic conspiracy beliefs, b = 4.478, SE = .960, β = .160, 95% CI for β [.092, .227], t = 4.663, p < .001, and conspiracy mentality, b = 2.040, SE = .407, β = .171, 95% CI for β [.104, .238], t = 5.017, p < .001, in the Canadian sample. In the South African sample, similarly, both generic conspiracy beliefs, b = 3.372, SE = .946, β = .120, 95% CI for β = [.054, .187], t = 3.565, p < .001, and conspiracy mentality, b = 2.108, SE = .502, β = .141, 95% CI for β [.075, .207], t = 4.198, p < .001, were positively related to expectations of dishonesty. Adjusting for control variables did not change the results (see SM 1). Thus, Hypothesis 2 was supported in both samples: People with stronger conspiracy beliefs were more likely to expect others to be dishonest and this was an overestimation. Although most people overestimated dishonesty among other people (see Figure 4), people with stronger conspiracy beliefs overestimated to a greater extent.

Figure 4

Scatter Plots Depicting the Association Between Expectations of Dishonesty (What Percentage of Other Participants Was Expected to Behave Dishonestly) and Both Conspiracy Mentality and Generic Conspiracy Beliefs in Study 2

Corruption as a Moderator

We hypothesized that the association between conspiracy beliefs and expectations of dishonesty would be stronger in a low-corruption country (Canada) compared with a high-corruption country (South Africa). However, neither generic conspiracy beliefs, b = −1.106, SE = 1.348, 95% CI for b = [−3.747, 1.535], z = −.821, p = .412, nor conspiracy mentality, b = .068, SE = .648, 95% CI for b = [−1.202, 1.338], z = .105, p = .916, interacted with country (Canada vs. South Africa). Generic conspiracy beliefs, b = .098, SE = .302, 95% CI for b = [−.493, .689], z = .325, p = .745, and conspiracy mentality, b = .119, SE = .121, 95% CI for b = [−.119, .356], z = .978, p = .328, also did not interact with individual-level perceived corruption. Thus, contrary to our hypothesis, corruption level did not moderate the association between conspiracy beliefs and expectations of other people’s dishonesty.

Order Effects

We also checked for any potential order effect. When participants first completed the conspiracy measures and then the lying task, odds ratios tended to be higher, compared with the opposite order (see Table 4; see SM 3 for more details), especially in Canada. This suggests that if the order of measures has an effect, it is more likely that when participants first reported their conspiracy beliefs, they tended to act more dishonestly, compared with an effect in the opposite direction. However, these results should be read with caution since the differences between significant and non-significant odds ratios did not reach statistical significance at p < .05.

Table 4

Odds Ratios for Different Orders in Study 2

		Generic conspiracy beliefs	Conspiracy mentality
Canada	Conspiracy beliefs first	1.686*	1.197*
	Lying task first	1.226	1.076
South Africa	Conspiracy beliefs first	1.096	1.110
	Lying task first	1.132	1.075

p < .05.

Discussion

We examined how conspiracy beliefs were associated with dishonesty and expectations of dishonesty in samples from three diverse cultures (Turkey, Canada, and South Africa). As predicted (H1), conspiracy beliefs were positively correlated with dishonesty. When measuring dishonesty through a self-report questionnaire, this finding held across the three countries; when measuring dishonesty through a lying task, this finding held in Canada and Turkey, but not in South Africa, although the results trended in the same direction. As predicted (H2), conspiracy beliefs positively correlated with overestimations of others’ dishonesty, despite the general trend to overestimate dishonesty (see also Martuza et al., 2024). Taken together, our results align with findings that link conspiracy beliefs with antisocial, self-centered tendencies (Douglas & Sutton, 2011; Hughes & Machan, 2021; Jolley et al., 2019; Kay, 2021; March & Springer, 2019), and negative traits (Douglas, 2021; van Mulukom et al., 2022), and they extend existing research by showing how conspiracy believers are more prone to expect others to behave dishonestly.

Research has established that individuals are more inclined to engage in unethical conduct when they believe such actions are common among others (Gächter & Schulz, 2016; Köbis et al., 2015). Therefore, one potential explanation for our results is that individuals with stronger conspiracy beliefs may internalize a descriptive norm characterized by a widespread perception of malevolent actions, potentially accounting for their propensity toward dishonest behavior. Consistent with this theoretical framework, our data reveal a correlation between personal dishonesty and the anticipation of dishonesty in others, with correlation coefficients ranging from .317 to .414. This finding is particularly troubling given that individuals may be influenced by the perceived descriptive norm of dishonesty, yet do not search for information regarding whether this norm is accurate (Leib, 2023).

Another potential explanation is an order effect. In Study 1, participants first completed the lying task and then the conspiracy belief measures. It is possible that when people lied, they might have attempted to justify themselves by reporting higher perceived dishonesty in the world, in the form of conspiracy beliefs. However, we randomized the order of the lying task and conspiracy measures in Study 2, and found that the association between the two was not stronger when people first completed the lying task. In Canada, it was even weaker. This analysis should be repeated on larger samples as our sample size was underpowered to detect whether these differences were statistically significant. There might also be an order effect of dishonest behavior on expectations of dishonesty, as participants always completed the task first and then reported their expectation. People who lied might be more likely to expect higher dishonesty among other people to justify their own behavior.

The finding that conspiracy beliefs were positively associated with overestimations of others’ dishonesty underscores the importance of trust dynamics. The pronounced distrust that is argued to be a characteristic of conspiracy beliefs (e.g., van Prooijen et al., 2022) may fuel a self-reinforcing cycle, preventing conspiracy believers from engaging in trust-based relationships and recognizing their misjudgments in distrusting others. Research indicates that people tend to underestimate others’ trustworthiness (Fetchenhauer & Dunning, 2009, 2010). This is attributed to feedback asymmetry: Individuals learn from instances when their trust is betrayed but lack opportunities to discover if unextended trust would have been reciprocated. Consequently, conspiracy believers’ overestimation of dishonesty might be self-perpetuating because they seldom learn that their mistrust is unwarranted.

Limitations and Future Directions

We found similar results in different cultural contexts, but future research should explore potential cross-cultural differences. Recent studies have increasingly focused on the role of national and cultural factors in shaping conspiracy beliefs, yielding findings that are not always consistent (e.g., Alper, 2023; Alper et al., 2024; Alper & Imhoff, 2023; Douglas et al., 2023; Enea et al., 2023; Hornsey et al., 2023; Hornsey & Pearson, 2022). We have tested country-level corruption as a potential moderator in Study 2 but failed to find any effect. The fact that we were able to compare only two countries is an important limitation; however, we found similar results with individual-level perceived corruption as a moderator. Future research could consider other country-level factors that might moderate the association between conspiracy beliefs and dishonesty-related variables. In addition, our data can only speak to correlational associations and cannot directly attest to a causal relationship. Experimental manipulation of conspiracy beliefs could help establish causal effects on dishonesty. Another potential issue with establishing causality is the possibility of confounding factors. Some contextual factors, such as country-level corruption (e.g., Alper, 2023; Alper & Imhoff, 2023; Muthukrishna et al., 2017), might increase conspiracy beliefs, dishonesty, and expectations of dishonesty simultaneously, which might be the reason for their positive association. This possibility is further corroborated by our finding that a higher percentage of participants from a high-corruption country (South Africa; 30.2%) acted dishonestly compared with those from a low-corruption country (Canada; 19.2%), consistent with previous findings (Gächter & Schulz, 2016; Muthukrishna et al., 2017). Future research should also account for any order effects and ensure that any observed associations are not solely dependent on the order of measures in the study. Finally, we have found some differences in terms of whether dishonesty is measured behaviorally or using a self-report measure. This gap between attitude and behavior is expected (Sheeran & Webb, 2016) but its reason in the context of conspiracy beliefs should be further investigated.

Conclusion

The present findings reveal that individuals with stronger conspiracy beliefs are not only more prone to dishonest behavior but also tend to overestimate others’ dishonesty. This contribution enriches research suggesting that there are adverse consequences of conspiracy beliefs. These results also open up investigations into the interplay between personal integrity and conspiracy beliefs, alongside exploring effective interventions to correct conspiracy believers’ distorted perceptions of others’ trustworthiness.

Supplemental Material

sj-docx-1-spp-10.1177_19485506241302878 – Supplemental material for Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty

Supplemental material, sj-docx-1-spp-10.1177_19485506241302878 for Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty by Sinan Alper, Daniel Toribio-Flórez, Valerio Capraro and Karen M. Douglas in Social Psychological and Personality Science

Supplemental Material

sj-docx-2-spp-10.1177_19485506241302878 – Supplemental material for Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty

Supplemental material, sj-docx-2-spp-10.1177_19485506241302878 for Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty by Sinan Alper, Daniel Toribio-Flórez, Valerio Capraro and Karen M. Douglas in Social Psychological and Personality Science

Supplemental Material

sj-docx-3-spp-10.1177_19485506241302878 – Supplemental material for Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty

Supplemental material, sj-docx-3-spp-10.1177_19485506241302878 for Stronger Conspiracy Beliefs Are Associated With a Stronger Tendency to Act Dishonestly and an Overestimation of Others’ Dishonesty by Sinan Alper, Daniel Toribio-Flórez, Valerio Capraro and Karen M. Douglas in Social Psychological and Personality Science

Footnotes

Handling Editor: Christian Unkelbach

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The current research was funded by Yasar University, as a part of the project entitled as “Conspiracy Beliefs and Cooperation” (Project no: BAP 138).

The authors thank the support of the European Research Council Advanced Grant “Consequences of conspiracy theories—CONSPIRACY_FX” (grant no. 101018262) in the preparation of this article.

Data Availability

Data and materials are available at

ORCID iDs

Sinan Alper

Daniel Toribio-Flórez

Valerio Capraro

Karen M. Douglas

Supplemental Material

The supplemental material is available in the online version of the article.

Notes

Author Biographies

Sinan Alper is an Associate Professor of Psychology at Yasar University in Turkey. His research focuses on moral and political attitudes, as well as social cognitive processes related to receptivity to misinformation. His work seeks to integrate individual and social predictors of the spread and sharing of misinformation.

Daniel Toribio-Flórez is a postdoctoral research fellow and a member of the CONSPIRACY_FX research project, at the University of Kent. His research focuses on the impact of conspiracy beliefs on political attitudes, behaviors, and interpersonal relationships. His work intersects with broader interests in social norms, attitudinal ambivalence, and open science, extending to the areas of political psychology, moral judgment, and meta-research.

Valerio Capraro is an Associate Professor in the Department of Psychology at the University of Milan-Bicocca, Italy. His research integrates human experiments, mathematical modelling, and numerical simulations to shed light on human behaviour, with a special focus on moral decision-making. His research has been published in leading academic journals.

Karen M. Douglas is a Professor of Social Psychology at the University of Kent in the United Kingdom. In her research, she examines why conspiracy theories appeal to so many people, and the consequences of conspiracy theories for individuals, groups, and societies. She has authored over 150 academic publications, and she is the director of the CONSPIRACY_FX project which is funded by the European Research Council.

References

Abalakina-Paap

Stephan

W. G.

Craig

Gregory

W. L.

(1999). Beliefs in conspiracies. Political Psychology, 20(3), 637–647. https://doi.org/10.1111/0162-895X.00160

Alper

(2023). There are higher levels of conspiracy beliefs in more corrupt countries. European Journal of Social Psychology, 53, 503–517. https://doi.org/10.1002/ejsp.2919

Alper

Bayrak

Yilmaz

(2021). Psychological correlates of COVID-19 conspiracy beliefs and preventive measures: Evidence from Turkey. Current Psychology, 40(11), 5708–5717. https://doi.org/10.1007/s12144-020-00903-0

Alper

Douglas

K. M.

Capraro

(2021, September 23). Conspiracy beliefs and generosity across 52 Countries during the COVID-19 pandemic. https://doi.org/10.31234/osf.io/fdyxr

Alper

Imhoff

(2023). Suspecting foul play when it is objectively there: The association of political orientation with general and partisan conspiracy beliefs as a function of corruption levels. Social Psychological and Personality Science, 14(5), 610–620. https://doi.org/10.1177/19485506221113965

Alper

Yelbuz

B. E.

Akkurt

S. B.

Yilmaz

(2024). The positive association of education with the trust in science and scientists is weaker in highly corrupt countries. Public Understanding of Science, 33(1), 2–19. https://doi.org/10.1177/09636625231176935

Ashton

M. C.

Lee

(2009). The HEXACO–60: A short measure of the major dimensions of personality. Journal of Personality Assessment, 91(4), 340–345. https://doi.org/10.1080/00223890902935878

Biziou-van-Pol

Haenen

Novaro

Occhipinti-Lieberman

Capraro

(2015). Does telling white lies signal pro-social preferences? Judgment and Decision Making, 10, 538–548.

Brotherton

French

C. C.

Pickering

A. D.

(2013). Measuring belief in conspiracy theories: The generic conspiracist beliefs scale. Frontiers in Psychology, 4, Article 279. https://doi.org/10.3389/fpsyg.2013.00279

10.

Bruder

Haffke

Neave

Nouripanah

Imhoff

(2013). Measuring individual differences in generic beliefs in conspiracy theories across cultures: Conspiracy Mentality Questionnaire. Frontiers in Psychology, 4, Article 225. https://doi.org/10.3389/fpsyg.2013.00225

11.

Capraro

(2017). Does the truth come naturally? Time pressure increases honesty in deception games. Economics Letters, 158, 54–57.

12.

Capraro

Schulz

Rand

D. G.

(2019). Time pressure and honesty in a deception game. Journal of Behavioral and Experimental Economics, 79, 93–99. https://doi.org/10.1016/j.socec.2019.01.007

13.

Casara

B. G. S.

Suitner

Jetten

(2022). The impact of economic inequality on conspiracy beliefs. Journal of Experimental Social Psychology, 98, 104245. https://doi.org/10.1016/j.jesp.2021.104245

14.

Douglas

K. M.

(2021). Are conspiracy theories harmless? The Spanish Journal of Psychology, 24, Article e13. https://doi.org/10.1017/SJP.2021.10

15.

Douglas

K. M.

Sutton

R. M.

(2011). Does it take one to know one? Endorsement of conspiracy theories is influenced by personal willingness to conspire. British Journal of Social Psychology, 50(3), 544–552. https://doi.org/10.1111/j.2044-8309.2010.02018.x

16.

Douglas

K. M.

Sutton

R. M.

(2018). Why conspiracy theories matter: A social psychological analysis. European Review of Social Psychology, 29(1), 256–298. https://doi.org/10.1080/10463283.2018.1537428

17.

Douglas

K. M.

Sutton

R. M.

(2023). What are conspiracy theories? A definitional approach to their correlates, consequences, and communication. Annual Review of Psychology, 74, 271–298. https://doi.org/10.1146/annurev-psych-032420-031329

18.

Douglas

K. M.

Sutton

R. M.

Van Lissa

C. J.

Stroebe

Kreienkamp

Agostini

. . .Leander

N. P.

(2023). Identifying important individual-and country-level predictors of conspiracy theorizing: A machine learning analysis. European Journal of Social Psychology, 53(6), 1191–1203. https://doi.org/10.1002/ejsp.2968

19.

Douglas

K. M.

Uscinski

J. E.

Sutton

R. M.

Cichocka

Nefes

Ang

C. S.

Deravi

(2019). Understanding conspiracy theories. Political Psychology, 40, 3–35.

20.

Eberl

J. M.

Huber

R. A.

Greussing

(2021). From populism to the “plandemic”: Why populists believe in COVID-19 conspiracies. Journal of Elections, Public Opinion and Parties, 31, 272–284. https://doi.org/10.1080/17457289.2021.1924730

21.

Enea

Eisenbeck

Carreno

D. F.

Douglas

K. M.

Sutton

R. M.

Agostini

. . .Leander

N. P.

(2023). Intentions to be vaccinated against COVID-19: The role of prosociality and conspiracy beliefs across 20 countries. Health Communication, 38(8), 1530–1539. https://doi.org/10.1080/10410236.2021.2018179

22.

Faul

Erdfelder

Lang

A.-G.

Buchner

(2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. https://doi.org/10.3758/BF03193146

23.

Fetchenhauer

Dunning

(2009). Do people trust too much or too little? Journal of Economic Psychology, 30(3), 263–276. https://doi.org/10.1016/j.joep.2008.04.006

24.

Fetchenhauer

Dunning

(2010). Why so cynical? Asymmetric feedback underlies misguided skepticism regarding the trustworthiness of others. Psychological Science, 21(2), 189–193. https://doi.org/10.1177/0956797609358586

25.

Frenken

Imhoff

(2023). Don’t trust anybody: Conspiracy mentality and the detection of facial trustworthiness cues. Applied Cognitive Psychology, 37(2), 256–265. https://doi.org/10.1002/acp.3955

26.

Funder

D. C.

Ozer

D. J.

(2019). Evaluating effect size in psychological research: Sense and nonsense. Advances in Methods and Practices in Psychological Science, 2(2), 156–168. https://doi.org/10.1177%2F2515245919847202

27.

Gächter

Schulz

J. F.

(2016). Intrinsic honesty and the prevalence of rule violations across societies. Nature, 531(7595), 496–499. https://doi.org/10.1038/nature17160

28.

Gneezy

(2005). Deception: The role of consequences. American Economic Review, 95, 384–394.

29.

Gneezy

Rockenbach

Serra-Garcia

(2013). Measuring lying aversion. Journal of Economic Behavior & Organization, 93, 293–300.

30.

Goertzel

(1994). Belief in conspiracy theories. Political Psychology, 15(4), 731–742. https://doi.org/10.2307/3791630

31.

Golec de Zavala

Federico

C. M.

(2018). Collective narcissism and the growth of conspiracy thinking over the course of the 2016 United States presidential election: A longitudinal analysis. European Journal of Social Psychology, 48(7), 1011–1018. https://doi.org/10.1002/ejsp.2496

32.

Greenburgh

Raihani

N. J.

(2022). Paranoia and conspiracy thinking. Current Opinion in Psychology, 47, 101362. https://doi.org/10.1016/j.copsyc.2022.101362

33.

Hornsey

M. J.

Bierwiaczonek

Sassenberg

Douglas

K. M.

(2023). Individual, intergroup and nation-level influences on belief in conspiracy theories. Nature Reviews Psychology, 2(2), 85–97. https://doi.org/10.1038/s44159-022-00133-0

34.

Hornsey

M. J.

Pearson

(2022). Cross-national differences in willingness to believe conspiracy theories. Current Opinion in Psychology, 47, 101391. https://doi.org/10.1016/j.copsyc.2022.101391

35.

Hughes

Machan

(2021). It’s a conspiracy: Covid-19 conspiracies link to psychopathy, Machiavellianism and collective narcissism. Personality and Individual Differences, 171, 110559. https://doi.org/10.1016/j.paid.2020.110559

36.

Imhoff

Lamberty

(2018). How paranoid are conspiracy believers? Toward a more fine-grained understanding of the connect and disconnect between paranoia and belief in conspiracy theories. European Journal of Social Psychology, 48(7), 909–926. https://doi.org/10.1002/ejsp.2494

37.

Jolley

Douglas

K. M.

Leite

A. C.

Schrader

(2019). Belief in conspiracy theories and intentions to engage in everyday crime. British Journal of Social Psychology, 58(3), 534–549.

38.

Kay

C. S.

(2021). Actors of the most fiendish character: Explaining the associations between the Dark Tetrad and conspiracist ideation. Personality and Individual Differences, 171, 110543. https://doi.org/10.1016/j.paid.2020.110543

39.

Köbis

N. C.

Van Prooijen

J. W.

Righetti

Van Lange

P. A.

(2015). “Who doesn’t?”—The impact of descriptive norms on corruption. PLOS ONE, 10(6), Article e0131830. https://doi.org/10.1371/journal.pone.0131830

40.

Kofta

Soral

Bilewicz

(2020). What breeds conspiracy antisemitism? The role of political uncontrollability and uncertainty in the belief in Jewish conspiracy. Journal of Personality and Social Psychology, 118(5), 900. https://psycnet.apa.org/doi/10.1037/pspa0000183

41.

Leib

(2023). People imitate others’ dishonesty but do not intentionally search information about it. Journal of Behavioral Decision Making, 36(2), Article e2296. https://doi.org/10.1002/bdm.2296

42.

March

Springer

(2019). Belief in conspiracy theories: The predictive role of schizotypy, Machiavellianism, and primary psychopathy. PLOS ONE, 14(12), Article e0225964. https://doi.org/10.1371/journal.pone.0225964

43.

Mari

Gil de Zúñiga

Suerdem

Hanke

Brown

Vilar

. . .Bilewicz

(2021). Conspiracy theories and institutional trust: Examining the role of uncertainty avoidance and active social media use. Political Psychology. https://doi.org/10.1111/pops.12754

44.

Martuza

Thorbjørnsen

Sjåstad

(2024, June 27). Beliefs versus reality: People overestimate the actual dishonesty of others. https://doi.org/10.31234/osf.io/nm2cz

45.

Meuer

Imhoff

(2021). Believing in hidden plots is associated with decreased behavioral trust: Conspiracy belief as greater sensitivity to social threat or insensitivity towards its absence? Journal of Experimental Social Psychology, 93, 104081. https://doi.org/10.1016/j.jesp.2020.104081

46.

Muris

Merckelbach

Otgaar

Meijer

(2017). The malevolent side of human nature: A meta-analysis and critical review of the literature on the dark triad (narcissism, Machiavellianism, and psychopathy). Perspectives on Psychological Science, 12(2), 183–204. https://doi.org/10.1177%2F1745691616666070

47.

Muthukrishna

Francois

Pourahmadi

Henrich

(2017). Corrupting cooperation and how anti-corruption strategies may backfire. Nature Human Behaviour, 1(7), Article 0138. https://doi.org/10.1038/s41562-017-0138

48.

Paulhus

D. L.

Williams

K. M.

(2002). The dark triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of Research in Personality, 36(6), 556–563. https://doi.org/10.1016/S0092-6566(02)00505-6

49.

Poon

K. T.

Chan

R. S.

Lai

H. S.

(2024). Are rules made to be broken? Conspiracy exposure promotes aggressive behavior. Political Psychology, 45, 923–940. https://doi.org/10.1111/pops.12947

50.

Sheeran

Webb

T. L.

(2016). The intention–behavior gap. Social and Personality Psychology Compass, 10(9), 503–518. https://doi.org/10.1111/spc3.12265

51.

Transparency International. (2023). Corruption Perceptions Index 2023. https://www.transparency.org/en/cpi/2023

52.

van der Linden

Panagopoulos

Azevedo

Jost

J. T

. (2021). The paranoid style in American politics revisited: An ideological asymmetry in conspiratorial thinking. Political Psychology, 42(1), 23–51. https://doi.org/10.1111/pops.12681

53.

van Mulukom

Pummerer

L. J.

Alper

Bai

Čavojová

Farias

Žeželj

. (2022). Antecedents and consequences of COVID-19 conspiracy beliefs: A systematic review. Social Science & Medicine, 301, 114912. https://doi.org/10.1016/j.socscimed.2022.114912

54.

van Prooijen

J. W.

Acker

. (2015). The influence of control on belief in conspiracy theories: Conceptual and applied extensions. Applied Cognitive Psychology, 29(5), 753–761. https://doi.org/10.1002/acp.3161

55.

Van Prooijen

J. W.

Spadaro

Wang

(2022). Suspicion of institutions: How distrust and conspiracy theories deteriorate social relationships. Current Opinion in Psychology, 43, 65–69. https://doi.org/10.1016/j.copsyc.2021.06.013