Decades of research document individual differences in prosocial behavior using controlled experiments that model social interactions in situations of interdependence. However, theoretical and empirical integration of the vast literature on the predictive validity of personality traits to account for these individual differences is missing. Here, we present a theoretical framework that identifies 4 broad situational affordances across interdependent situations (i.e., exploitation, reciprocity, temporal conflict, and dependence under uncertainty) and more specific subaffordances within certain types of interdependent situations (e.g., possibility to increase equality in outcomes) that can determine when, which, and how personality traits should be expressed in prosocial behavior. To test this framework, we metaanalyzed 770 studies reporting on 3,523 effects of 8 broad and 43 narrow personality traits on prosocial behavior in interdependent situations modeled in 6 commonly studied economic games (Dictator Game, Ultimatum Game, Trust Game, Prisoner's Dilemma, Public Goods Game, and Commons Dilemma). Overall, meta-analytic correlations ranged between Ϫ.18 Յ Յ .26, and most traits yielding a significant relation to prosocial behavior had conceptual links to the affordances provided in interdependent situations, most prominently the possibility for exploitation. Moreover, for several traits, correlations within games followed the predicted pattern derived from a theoretical analysis of affordances. On the level of traits, we found that narrow and broad traits alike can account for prosocial behavior, informing the bandwidth-fidelity problem. In sum, the meta-analysis provides a theoretical foundation that can guide future research on prosocial behavior and advance our understanding of individual differences in human prosociality. Public Significance StatementThis meta-analysis provides a theoretical framework and empirical test identifying when, how, and which of 51 personality traits account for individual variation in prosocial behavior. The metaanalysis shows that the relations between personality traits and prosocial behavior can be understood in terms of a few situational affordances (e.g., a possibility for exploitation, a possibility for reciprocity, dependence on others under uncertainty) that allow specific traits to become expressed in behavior across a variety of interdependent situations. As such, the meta-analysis provides a theoretical basis for understanding individual differences in prosocial behavior in various situations that individuals face in their everyday social interactions.

Based on lexical studies, the HEXACO (honesty-humility, emotionality, extraversion, agreeableness, conscientiousness, and openness to experience) model of personality has been proposed as a model of basic personality structure that summarizes individual differences in six broad trait dimensions. Although research across various fields relies on the HEXACO model increasingly, a comprehensive investigation of the nomological net of the HEXACO dimensions is missing entirely. Thus, it remains unclear whether each HEXACO dimension accounts for individual variation across theoretically relevant outcome criteria. We close this gap through a large-scale meta-analytic investigation, testing whether each HEXACO dimension is uniquely linked to one broad and theoretically relevant outcome domain. Results from 426 individual meta-analyses, 436 independent samples, and 3,893 effect-size estimates corroborate this unique mapping. Specifically, honesty-humility maps onto the outcome domain of exploitation, emotionality onto insecurity, extraversion onto sociality, agreeableness versus anger onto obstruction, conscientiousness onto duty, and openness to experience onto exploration. Overall, the current investigation provides a comprehensive empirical test of the (breadth of) content captured by the HEXACO dimensions and allows for a broad specification of the nomological net of the HEXACO model overall.

Trust is a key aspect of various social interactions. Correspondingly, trust has been heavily studied across different scientific disciplines. However, an integration of the diverse research and literature is still missing. Addressing this issue, we review several hundred articles on interpersonal trust among strangers and integrate them into a coherent framework, explaining trust behavior among unfamiliar agents based on an interaction between situational features and distinct personality characteristics. Understanding trust as a decision under risk, we distill 3 core components of trust behavior from the extant literature: attitudes toward risky prospects (i.e., risk aversion and loss aversion), trustworthiness expectations, and betrayal sensitivity. Each of these refers to a distinct set of causal determinants, including personality characteristics (anxiety/fear, trustworthiness, and forgiveness) which can be localized in the space defined by models of basic personality structure (e.g., the Five-Factor Model and the HEXACO model of personality). In sum, the review contributes to the understanding of trust behavior by linking and integrating the findings from various fields of trust research. Additionally, it provides fruitful directions and implications for future research.

This target article is part of a theme bundle including open peer commentaries (https://doi.org/10.5964/ps.9227) and a rejoinder by the authors (https://doi.org/10.5964/ps.7961). We point out ten steps that we think will go a long way in improving personality science. The first five steps focus on fostering consensus regarding (1) research goals, (2) terminology, (3) measurement practices, (4) data handling, and (5) the current state of theory and evidence. The other five steps focus on improving the credibility of empirical research, through (6) formal modelling, (7) mandatory pre-registration for confirmatory claims, (8) replication as a routine practice, (9) planning for informative studies (e.g., in terms of statistical power), and (10) making data, analysis scripts, and materials openly available. The current, quantity-based incentive structure in academia clearly stands in the way of implementing many of these practices, resulting in a research literature with sometimes questionable utility and/or integrity. As a solution, we propose a more quality-based reward scheme that explicitly weights published research by its Good Science merits. Scientists need to be increasingly rewarded for doing good work, not just lots of work.