Abstract: Research has shown that offenders differ from nonoffenders in personality traits such as aggression and anger. However, less is known about differences within offender subgroups and personality styles conceptually related to personality disorders but assessed at a subclinical level. In this study, we examined personality styles, aggression, and anger in 342 male offenders in Bavaria, Germany, using standardized self-report measures. We hypothesized that elevated personality styles conceptually related to Cluster-B personality disorders increased aggression and anger compared to normative samples and subgroup differences. Compared to normative data, offenders exhibited higher levels of paranoid, histrionic, and rhapsodic personality styles, and lower levels of aggression-related patterns. Subgroup analysis revealed that bodily harm offenders reported higher Cluster-B personality styles than sexual offenders and higher levels of aggression and anger. These findings underscore the importance of examining offender subgroups, as differences in personality styles appear to be associated with the type and expression of criminal behavior.
: This study examined the structural organization of relations between personality nuances and different types of criminal offenses using an item-offense approach. The sample consisted of 592 male prisoners in Croatia (Mage = 39.55 years, SDage = 11.16). Network analysis showed a central role of the nervousness nuance in offending and recidivism, as well as its importance in distinguishing between violent and nonviolent offenses. Nervousness was positively associated with violent offenses but negatively with nonviolent ones. Moreover, trustworthiness also emerged as a central nuance for violent offenses, while thoroughness and laziness were key for nonviolent offenses. Overall, this study offers valuable insight into the relations between personality and criminal behavior using an item-level approach.
: This longitudinal study examines whether personal moral rules and criminogenic exposure interact to predict youth offending in China and the UK. Testing the morality-exposure component of the situational action theory (SAT), three annual waves of self-reported data from adolescents aged 14-16 in China (n = 588) and the UK (n = 716) were analyzed. In the UK sample, lower moral rules and higher criminogenic exposure independently predicted greater delinquency, and their interaction further amplified risk. In the Chinese sample, moral rules and criminogenic exposure showed weaker and less consistent main effects, and the interaction term was nonsignificant at all three ages. Developmental patterns also differed across contexts. In the UK, morality appeared relatively more prominent by age 16, whereas in China, the overall model weakened markedly at age 15, which may reflect the constraining effects of intense examination preparation on unsupervised peer activity. These findings provide partial support for SAT. The main effects of moral rules and criminogenic exposure were observed in both contexts, though more consistently in the UK, while the morality-exposure interaction emerged only in the UK sample. SAT's general emphasis on the joint relevance of personal and environmental factors thus appears partially transportable across contexts, but the situational interaction at the core of the theory may be contingent on social structure, developmental timing, and the distribution of criminogenic opportunities.
: Police officers encounter the darker sides of human behavior on a daily basis, including crime and challenging interactions with civilians. Moreover, officers are bound by strict social hierarchies within the police force. Survey evidence, mostly from North America, suggests that such exposure can lead to substantial attitude change in police recruits, especially when combined with a strong police culture. These changes often tilt toward more authoritarian and less prosocial orientations. However, most existing evidence relies on cross-sectional data and cannot capture within-person change. We extend this work to a German context using a truly longitudinal design. New police students were surveyed three times during their first year of training, from entry through their initial field experiences. We measured a range of attitudes and personality traits, including social dominance orientation, HEXACO's honesty-humility, and general trust, and compared them with two reference groups: a large sample from the German general population and first-year university students surveyed at the same times with identical instruments. Our results reveal notable changes over time. Police recruits start their training with higher-than-average levels of honesty-humility and trust, suggesting a more positive social outlook. However, they also show higher social dominance orientation (SDO), which increases further across waves, while other measures decline, gradually converging toward population averages. These findings suggest that hierarchical environments and repeated exposure to high-stress social encounters may shape attitudes during early police socialization. Beyond their academic implications, our results offer practical insights for designing police training programs that help sustain recruits' prosocial motivations and trust in society.
Abstract: This study examined the predictive contributions of the Dark Factor of Personality (D) and maladaptive personality domains (PID-5) to criminologically relevant outcomes in 228 offenders (193 males; M age = 39.5 years, SD = 10.6). Logistic regression models tested predictors of violent versus nonviolent offending, criminal persistence, and prior imprisonment, with three model specifications estimated per outcome: PID-5 only, D only, and both entered simultaneously. PID-5 domains, particularly higher Detachment and lower Antagonism, differentiated violent from nonviolent offenders, whereas D did not contribute independently to this. For recidivism, both frameworks showed modest and largely overlapping predictive utility, with neither demonstrating clear incremental superiority in the combined model. D most parsimoniously predicted prior imprisonment, remaining significant after controlling for PID-5 domains. Overall, the findings support partial complementarity rather than redundancy between the two frameworks, with predictive utility varying as a function of the criminological criterion examined.
: Psychopathy encompasses a range of personality traits, including deceitfulness, lack of empathy, impulsivity, and antisociality. While it has often been assumed that extremists are inherently psychopathic, this assumption lacks solid empirical support. Two studies examined this relationship. Using public and legal reports on right-wing extremists and Islamists in Study 1 and PIRUS (Profiles of Individual Radicalization in the United States) data on Islamists in Study 2, psychopathy was assessed with the PCL-R. Results showed that extremists diverge from full-spectrum psychopathy. Specifically, they exhibited elevated psychopathic traits in Facets 1 (Interpersonal) and 2 (Affective), at levels comparable to or exceeding those of other offenders, whereas Facets 3 (Parasitic Lifestyle) and 4 (Antisocial) were considerably less pronounced. Notably, the Interpersonal Facet was especially characteristic of lone actors, whereas the Affective Facet predicted radicalization intensity. These findings suggest that psychopathic traits in extremists may reflect processes associated within radicalization rather than inherent personality dispositions.
: Research from the past few decades has pointed to a clear link between both basic and so-called aversive personality traits - such as narcissism, Machiavellianism, and psychopathy - and crime. Across two studies, we herewith contribute to the literature on personality and crime by providing evidence on how the Dark Factor of Personality (D) - the common core underlying all aversive traits - relates to criminal behavior. We examined this relation not only through self-reported criminal prosecutions (Study 1, n = 7,026) but also by linking D to a broad range of officially registered criminal convictions recorded over a 41-year period (Study 2, n = 11,979). Results from both studies provide clear and consistent evidence of a positive association between D and crime. In brief, this research highlights the relevance of D in accounting for not only self-reported criminal behavior but also actual convictions.
Abstract: This meta-analysis examines the effectiveness of intervention programs targeting callous-unemotional (CU) traits and social competence (SC) as risk and protective factors in youths at risk for crime. CU traits, marked by lack of remorse, guilt, and empathy are robust predictors of delinquency, whereas SC represents a key protective factor. A total of 3,227 participants across the included studies were analyzed. Random-effects meta-analysis of pre- to postintervention changes revealed a significant reduction in CU ( d = −0.19, p < .001) and significant improvement in SC ( d = 0.29, p < .001) across studies. Sensitivity analyses indicated that these effects were generally robust. However, SC effects attenuated under stricter quality criteria and became nonsignificant for some, but not all, quality thresholds. In addition, SC interventions produced short-term improvements that were not maintained at follow-up. Overall, CU-focused interventions yielded small to moderate effects that were sustained over time, suggesting that these programs can produce measurable changes in youth and hold promise for crime-related prevention intervention efforts during adolescence.
: In this conceptual replication, we examined differences in adolescents' math competence-related beliefs across broader racial/ethnic groups (African-American, Asian-American, European-American, and Latin & eacute;-American) and assessed whether these patterns were replicated among male and female students across four US datasets. The datasets included 32,170 adolescents in 9th to 12th grade (51% male, 12% African-Americans, 10% Asian-Americans, 45% European-Americans, 33% Latin & eacute;-Americans). We applied meta-analytic techniques by calculating both dataset-specific and overall effect sizes to examine the robustness and heterogeneity of racial/ethnic differences within gender groups. On average, African-American students reported higher math competence-related beliefs after controlling for parent education, income, and students' achievement. In total, 60% of the observed racial/ethnic differences for the full sample of each dataset did not replicate among either gender. Moreover, greater variation across racial/ethnic groups emerged among female than male students. These two patterns highlight the importance of applying an intersectional lens when understanding adolescents' math competence-related beliefs.
: Individual participant data (IPD) meta-analysis (MA) is an advanced method for synthesizing research by using raw data from individual studies rather than using aggregated statistics. IPD-MA offers higher statistical power and flexibility, thereby enabling researchers to standardize measures, explore subgroup effects, and examine sources of variability often inaccessible in traditional MA. While common in clinical fields, IPD-MA remains less prevalent in psychology, partly due to challenges in data access and perceived complexity. This primer provides a nonmathematical introduction to IPD-MA, outlining its core concepts (the what), the main phases of implementation (the how), and its potential to address the credibility crisis in psychological science and offer novel insights through diverse applications (the why). We conclude with guidance on data sharing practice and infrastructure. We aim to promote IPD-MA as a transformative tool for improving cumulative knowledge consolidation, replicability, open science practices, as well as theoretical and methodological development in psychology.
: Affective polarization - defined as the disparity between in-party positive sentiment and out-party negative sentiment - has become a central concern due to its relation to democratic backsliding, declining trust, and social fragmentation. While once seen as a mere US phenomenon, recent studies reveal its global relevance across diverse political systems. Based on a systematic review, we present two evidence gap maps that offer an overview of existing research on determinants, consequences, and interventions. Although affective polarization has been linked to severe societal impacts, systematic analyses remain scarce. Our maps indicate the relative dominance of political science in affective polarization research and reveal gaps, especially in non-Western contexts and regarding behavioral outcomes. By identifying these blind spots, this review provides a roadmap for future research and informs strategies to mitigate affective polarization's effects. Meta-analyses based on evidence gap maps are proposed as a tool for structuring and advancing future, ideally interdisciplinary, research.
: This study examines the predictive validity of the HEXACOD personality model, which extends HEXACO by adding the Disintegration (D) factor to capture psychosis proneness. Based on a systematic review and meta-analysis of trait-outcome associations, we created three meta-analytic evidence gap maps (MetaEGMs) to visualize research coverage and identify gaps. Outcomes were grouped using three taxonomies: affects-behaviors-cognitions-desires (ABCD), theory of planned behavior (TPB), and life domains. Results support increased predictive validity for various Health, Citizenship, Social Life, Affects, and Cognitions outcomes. However, key areas such as motivational constructs and Finance, Leisure, and Achievement outcomes remain underexplored. Moderate average effect sizes and considerable heterogeneity highlight the need to examine moderators such as culture, age, and sample type. Future studies should focus on specific outcomes and diverse populations to improve precision and generalizability. Overall, the findings support the HEXACOD model's predictive value and offer a clear avenue for future personality research.
: The imposter phenomenon refers to an intense, persistent feeling of inferiority and undeserved success by often high-achieving individuals and is associated with negative psychological consequences. Previous research has shown that the imposter phenomenon is closely related to perfectionism. However, some recent findings suggest that this relationship is not consistent across different dimensions of perfectionism, specifically perfectionistic strivings (PS) and perfectionistic concerns (PC). We conducted a meta-analysis of studies reporting these correlations to provide mean estimates of the disparate relationships. Twenty-six records providing 91 unique effect sizes were included. The mean reliability-adjusted correlation with the imposter phenomenon was significantly smaller for PS (z = .159, 95% CI [.051, .268]) than for PC (z = .747, 95% CI [.632, .863]). Partial correlations revealed that PS showed no unique relationship with the imposter phenomenon (z = -.069, 95% CI [-.179, .041]), whereas the unique relationship for PC was strong (z = .783, 95% CI [.547, 1.020]).
: Large language models (LLMs) like ChatGPT have emerged as transformative tools across various research fields. To illustrate the development of perceived benefits and concerns of LLMs across research fields, this umbrella review synthesized findings from 116 systematic reviews. Additionally, we employed LLM-supported data extraction and reported its promising evaluation. Applications in medicine and education dominate the literature, with accuracy and reliability as prominent challenges across disciplines and generally more benefits mentioned than concerns. Thematic analysis of most benefits within the field of psychology revealed LLMs' potentials in empathy and emotional awareness simulation, help with clinical decision-making, and supporting interventions. There were no clear temporal shifts in the perception of LLMs, except for decreasing benefits in ethics and decreasing concerns in education. To inform further research on interdisciplinary applications of LLMs, we have made our full data set consisting of nearly 3,800 extracted benefits and 3,400 concerns publicly available.
: This study used data from 7,436 patients across seven psychosomatic rehabilitation clinics to explore predictors of treatment success and to assess the feasibility of predicting rehabilitation outcomes using machine learning. Five outcomes based on the biopsychosocial model - activity, depressive symptoms, participation, phobic fears, and somatoform complaints - were derived from the HEALTH-49 and ICF AT-50 Psych. The outcomes were dichotomized to indicate relevant change from admission (T1) to discharge (T2). Random forests using baseline scores, PAREMO-20, and SIMBO-C items, treatment year, clinic, sex, and age, outperformed all dummy classifiers, yielding accuracies between 63.0% (participation) and 75.9% (phobic fears). Feature importances revealed baseline scores as key predictors. Skepticism toward rehabilitation predicted all outcomes except phobic fears, while willingness to change predicted all outcomes except depressive symptoms. Difficulties in social interaction impacted depressive symptoms and phobic fears. Work-related challenges were key predictors for activity and participation. Age, sex, year, and clinic had no impact.
