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A plentitude of research has analyzed citizens' belief in conspiracy theories and its individual‐level correlates. Yet, the effects of (political) context factors on the causes and effects of individual belief in conspiracy theories are still neglected. However, such context should be especially relevant when it comes to the impact of one's belief in conspiracy theories on one's political preference. In this article, we argue that the communication of governmental actors exerts a moderating influence on the link leading from a belief in conspiracy theories to political attitudes. In a nutshell, the belief in conspiracy theories should make citizens less likely to distrust their government—and the political system in general—in contexts where these theories are shared or at least publicly represented by governmental actors. Using two original data sets with data from Germany, Poland, and Jordan (Study 1) and data from Germany, Poland, Sweden, and France (Study 2), we test our argument based on an overall sample of about 10,000 cases. Our results indicate that higher degrees of generic conspiracy theories beliefs are associated with higher levels of political distrust across countries. Yet, confirming our argument, such an effect takes place less strongly in those countries in which governmental actors use conspiracy theories as a political communication strategy.

Conspiracy mentality (CM), the general propensity to believe in conspiracy theories, has been linked to political behaviors, prejudice, and non‐compliance with public health guidelines. While there is increasing evidence that conspiracy beliefs are pervasive, research on individual‐level predictors of CM is scarce. Specifically, we identify three gaps in research: First, evidence on the question which individual‐level characteristics predict CM is inconsistent and often based on small samples. Second, personality, political, and religious predictors are usually examined in isolation. Third, differences on the societal level have been mostly neglected. In the present research, we gathered CAWI (Study 1) and CATI (Study 2) data on generalized interpersonal trust (GIT), right‐wing authoritarianism (RWA), and religiosity in two politically and culturally different European countries, namely Germany (N = 2,760) and Poland (N = 2,651). This allowed for a well‐powered test of three theoretically relevant predictors of CM, including their unique predictive value. Moreover, we were able to explore whether these associations replicate across or are moderated by country context. Our findings underline the role of GIT and RWA in predicting CM in both countries. Analyses based on RWA subdimensions yielded a differentiated picture of the role of RWA. Furthermore, we found cross‐country differences with stronger associations of GIT and RWA with CM in Germany. Findings are discussed concerning political and religious differences between the examined countries.

AbstractRecruiters routinely use LinkedIn profiles to infer applicants' individual traits like narcissism and intelligence, two key traits in online network and organizational contexts. However, little is known about LinkedIn profiles' predictive potential to accurately infer individual traits. According to Brunswik's lens model, accurate trait inferences depend on (a) the presence of valid cues in LinkedIn profiles containing information about users' individual traits and (b) the sensitive and consistent utilization of valid cues. We assessed narcissism (self‐report) and intelligence (aptitude tests) in a sample of 406 LinkedIn users along with 64 LinkedIn cues (coded by three trained coders) that we derived from trait theory and previous empirical findings. We used a transparent, easy‐to‐interpret machine learning algorithm leveraging practical application potentials (elastic net) and applied state‐of‐the‐art resampling techniques (nested cross‐validation) to ensure robust results. Thereby, we uncover LinkedIn profiles' predictive potential: (a) LinkedIn profiles contain valid information about narcissism (e.g. uploading a background picture) and intelligence (e.g. listing many accomplishments), and (b) the elastic nets sensitively and consistently using these valid cues attain prediction accuracy (r = .35/.41 for narcissism/intelligence). The results have practical implications for improving recruiters' accuracy and foreshadow potentials and limitations of automated LinkedIn‐based assessments for selection purposes.

Previous research has followed a binary perspective in analyzing the effects of modernization and globalization, often assumed to produce the societal camps of both "winners" and "losers" in economic, cultural, and political terms. However, our understanding of these individual differences and the social groups that perceive themselves as disadvantaged by society is still limited. Hence, in contrast to previous findings we argue that the phenomenon may be better grasped by following a "pattern approach." Hence, in three different samples (total N = 2,566), we applied Latent Class Analysis to investigate subgroups representing individual differences in Perceived Societal Marginalization (PSM). Furthermore, we explored sociodemographic, personal-resource-related, attitudinal, and personality determinants of people's class membership probabilities to better understand the subgroups—or: patterns—we identified in substantive terms. In the discussion, we focus on the implications of our findings regarding societal cleavages, prejudice toward minority groups, and the support of far-right political parties.

Very wealthy people influence political and societal processes by wielding their economic power through foundations, lobbying groups, media campaigns, as investors and employers. Because personality shapes goals, attitudes, and behaviour, it is important to understand the personality traits that characterize the rich. We used representative survey data to construct two large samples, one from the general population and one consisting of individuals with at least 1 million euros in individual net wealth, to analyse what personality traits characterize the wealthy and why their traits differ from those of the general population. High wealth was associated with higher Risk tolerance, Emotional Stability, Openness, Extraversion, and Conscientiousness. This "rich" personality profile was more prominent among individuals who had accumulated wealth through their own efforts ("self-mades") than among individuals who had been born into wealth ("inheritors"). Thus, our evidence is suggestive of a unique configuration of personality traits contributing to self-made millionaires' economic success.

The present study examined the nomological network of the Short Dark Tetrad scale (SD4). The SD4 measures narcissism, psychopathy, Machiavellianism, and sadism. We translated the original English SD4 into German and used an online sample (N = 594, 77% women) to investigate its nomological network with regard to the Big Five, honesty-humility, maladaptive personality traits, impulsivity, aggression, motives, values, sociosexual orientation, the octants of the interpersonal circumplex model, and self-esteem. The overall profile similarities between the observed and hypothesized nomological networks were very high. Few correlations differed concerning direction or magnitude. Hence, our study extends the nomological network of the Dark Tetrad in a meaningful way and suggests that the SD4 can be validly interpreted and used for the assessment of narcissism, psychopathy, Machiavellianism, and sadism.

Individuals differ in the extent to which they perceive threat imposed by out-groups like migrants. An established distinction in intergroup threat research is between symbolic and realistic threat. While symbolic threats concern a perceived menace against societal values, realistic threats jeopardize in-group members' well-being more directly. Typically applied realistic threat conceptions explicitly include the aspect of physical integrity, but most empirical research captures only realistic economic threats, arguably also due to a lack of appropriate measures. Therefore, we have developed the Perceived Realistic Physical Threat scale (PRPT) with samples from Germany and the UK (total N = 1,391). Moreover, we conducted follow-up analyses with data from a subsample (N = 473) of the initial UK sample. Factor analyses indicated an 8-item one-factorial solution for the PRPT scale. We further identified measurement invariance across samples and over time and stability across 21 months. We found convincing evidence for its convergent and divergent validity and for its predictive and, importantly, incremental validity, above and beyond the prediction of relevant criteria by other threat types. The PRPT scale appears to be a distinct, comprehensive, and psychometrically sound measure of perceived realistic physical threat, complementing the existing body of available measures.

Abstract. Prior research has reported less favorable attitudes toward and more violent crimes against ethnic out-group members in East (vs. West) Germany. We conducted two pre-registered lost letter studies in West versus East German cities (Study 1, N = 400) and in West versus East German rural areas (Study 2, N = 400). To investigate supportive behavior regarding refugee integration, we manipulated the addressee (refugee-integration vs. immigration-stop projects). Contrary to predictions, letter return rates did not differ between West and East Germany. Across western and eastern German regions, return rates were higher for the refugee-integration project in urban areas while no differences emerged in rural areas. A pooled analysis found greater support for the refugee-integration (vs. immigration-stop) project.