Despite often being perceived as morally objectionable, stereotypes are a common feature of social groups, a phenomenon that has often been attributed to biased motivations or limits on the ability to process information. We argue that one reason for this continued prevalence is that preexisting expectations about how others will behave, in the context of social coordination, can change the behaviors of one's social partners, creating the very stereotype one expected to see, even in the absence of other potential sources of stereotyping. We use a computational model of dynamic social coordination to illustrate how this "feedback loop" can emerge, engendering and entrenching role-consistent stereotypic behavior and then show that human behavior on the task generates a comparable feedback loop. Notably, people's choices on the task are not related to social dominance or system justification, suggesting biased motivations are not necessary to maintain these stereotypes.

People are regularly conceptualized at varying levels of resolution, sometimes characterized by their idiosyncratic features while at other times seen as mere tokens of their social groups. Decades of research have sought to understand when perceivers will draw upon each of these types of representations, detailing the perceiver- and target-related features that may decrease reliance on stereotypes in favor of individuated knowledge. However, little work has examined how these representations might be formed in the first place: In order for individuated representations of others to be used, they must first be built through experience. Here, we offer a novel approach to characterizing the formation of social representations through the use of computational models of category learning. Across three experiments, participants learned about members of novel social groups who behaved positively or negatively toward them. Computational modeling of participants' task behavior revealed a critical interaction of perceiver motivations and learning context on representations. Participants who received selective feedback about targets only upon approaching them formed more categorical representations than those who received full feedback. Further, we found tentative evidence that this difference was most pronounced in those who held more racist attitudes, measured in an entirely separate context. Thus, more informative learning contexts could potentially act as a "protective factor" that shields perceivers' representations from their negative attitudes. The results shed light on the psychological underpinnings of prejudice, using a novel approach to reveal how social categorization is selectively employed in a manner that maintains negative stereotypes. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Theories on group-bias often posit an internal preparedness to bias one's cognition to favor the in-group (often envisioned as a product of evolution). In contrast, other theories suggest that group-biases can emerge from nonspecialized cognitive processes. These perspectives have historically been difficult to disambiguate given that observed behavior can often be attributed to innate processes, even when groups are experimentally assigned. Here, we use modern techniques from the field of AI that allow us to ask what group biases can be expected from a learning agent that is a pure blank slate without any intrinsic social biases, and whose lifetime of experiences can be tightly controlled. This is possible because deep reinforcement-learning agents learn to convert raw sensory input (i.e. pixels) to reward-driven action, a unique feature among cognitive models. We find that blank slate agents do develop group biases based on arbitrary group differences (i.e. color). We show that the bias develops as a result of familiarity of experience and depends on the visual patterns becoming associated with reward through interaction. The bias artificial agents display is not a static reflection of the bias in their stream of experiences. In this minimal environment, the bias can be overcome given enough positive experiences, although unlearning the bias takes longer than acquiring it. Further, we show how this style of tabula rasa group behavior model can be used to test fine-grained predictions of psychological theories.

We propose a hybrid approach to machine Theory of Mind (ToM) that uses large language models (LLMs) as a mechanism for generating hypotheses and likelihood functions with a Bayesian inverse planning model that computes posterior probabilities for an agent's likely mental states given its actions. Bayesian inverse planning models can accurately predict human reasoning on a variety of ToM tasks, but these models are constrained in their ability to scale these predictions to scenarios with a large number of possible hypotheses and actions. Conversely, LLM-based approaches have recently demonstrated promise in solving ToM benchmarks, but can exhibit brittleness and failures on reasoning tasks even when they pass otherwise structurally identical versions. By combining these two methods, this approach leverages the strengths of each component, closely matching optimal results on a task inspired by prior inverse planning models and improving performance relative to models that utilize LLMs alone or with chain-of-thought prompting, even with smaller LLMs that typically perform poorly on ToM tasks. We also exhibit the model's potential to predict mental states on open-ended tasks, offering a promising direction for future development of ToM models and the creation of socially intelligent generative agents.

A significant amount of punishment that happens in society is state punishment, that is, third-party punishment carried out by an organized political community in response to a rule violation. We argue that a complete psychology of punishment must consider state punishment as a distinct form. State punishment is a unique type of punishment because it is a special case of third-party punishment, pre-specified to occur after the violation of official rules and policies, carried out by people acting on behalf of a nation or government. State punishment, especially as compared to interpersonal punishment, is regarded as a legitimate form of violence, which communicates not just disapproval but information about procedures and power. Moreover, state punishment is made possible by state rules, which, unlike norms, are formalized, can be fully articulated and are perfectly transmissible across generations. We end the paper with implications for the psychology of punishment more broadly and future directions for better understanding the unique psychology of state punishment.

People's beliefs sometimes diverge after observing the same information, which has been interpreted as evidence of irrationality. This behaviour has been proposed to result from people's limited cognitive resources and motivated reasoning, but how belief revision differs across these explanations has not been formalized or compared to a rational norm. Further, while people may be biased relative to a normative ideal, they may still make optimal choices given their limited cognitive resources, or rationally balance the utility of holding accurate beliefs with the belief's intrinsic utility. Across two studies, we develop and test a unified computational account of belief polarization under these proposed mechanisms, showing that people's performance on a belief updating task best fits a limited-resource Bayesian model; external motivations may contribute to divergence (or convergence) by determining what pre-existing information people consider relevant to a situation, rather than by changing how people evaluate new information in isolation.

Objectives: Some autistic people “camouflage” their differences by modeling neurotypical behaviors to survive in a neurotypical-dominant social world. It remains elusive whether camouflaging is unique to autism or if it entails similar experiences across human groups as part of ubiquitous impression management (IM). Here we examined camouflaging engagement and theoretical drivers in the general population, drawing on the transactional IM framework and contextualizing findings within both contemporary autism research and the past IM literature. Methods: A large representative U.S. general population sample (N = 972) completed this survey study. We combined exploratory item factor analysis and graph analysis to triangulate the dimensional structure of the Camouflaging Autistic Traits Questionnaire (CAT-Q) and examined its correspondence with prior autism-enriched psychometric findings. We then employed hierarchical regression and elastic-net regression to identify the predictors of camouflaging, including demographic (e.g., age, gender), neurodivergence (i.e., autistic and ADHD traits), socio-motivational, and cognitive factors. Results: We found a three-factor/dimensional structure of the CAT-Q in the general population, nearly identical to that found in previous autism-enriched samples. Significant socio-motivational predictors of camouflaging included greater social comparison, greater public self-consciousness, greater internalized social stigma, and greater social anxiety. These camouflaging drivers overlap with findings in recent autistic camouflaging studies and prior IM research. Conclusions: The novel psychometric and socio-motivational evidence demonstrates camouflaging as a shared social coping experience across the general population, including autistic people. This continuity guides a clearer understanding of camouflaging and has key implications for autism scholars, clinicians, and the broader clinical intersecting with social psychology research. Future research areas are mapped to elucidate how camouflaging/IM manifests and functions within person-environment transactions across social-identity and clinical groups.

Background: Camouflaging, the strategies that some autistic people use to hide their differences, has been hypothesized to trigger mental health ramifications. Camouflaging might reflect ubiquitous impression management experiences that are not unique to autistic people and similarly impact the mental health of non-autistic people. Aims: We first examined whether individuals in the general population camouflage and manage impressions while experiencing mental health repercussions, and how gender and neurodivergent traits modified these associations. We then assessed how camouflaging and impression management arose from internalized stigma, and their inter-relationships in shaping mental health outcomes. Methods: Data were collected from 972 adults from a representative U.S. general population sample, with measures pertaining to camouflaging, impression management, mental health, internalized stigma, and neurodivergent traits. Multivariate hierarchical regression and moderated mediation analyses were used to address the two research aims. Results: Both camouflaging and self-presentation (a key component of impression management) were associated with mental health presentations in the general population, which overlapped with those previously reported in autistic people. These associations were more pronounced in women compared with men and were of different directions for individuals with higher autistic traits versus higher ADHD traits. Internalized stigma might be a key stressor that could elicit camouflaging and impression management through social anxiety, which in turn might lead to adverse mental health outcomes. Conclusions: These findings advance the conceptual clarity and clinical relevance of camouflaging and impression management across social and neurodiverse groups in the general population. The ramifications of camouflaging and impression management underscore the need to alleviate internalized stigma for better mental health across human groups.

Navigating the social world requires individuals to balance multiple goals, including the drives to improve one's own outcomes, aid ingroup members, and help or hurt outgroup members. While self-interest and intergroup bias are both well-established motivational phenomena, less is known about how these goals may interact. Here we examine the nature of goal tradeoffs in intergroup decision-making using a novel task in which participants simultaneously make monetary decisions for themselves, an arbitrary ingroup, and the corresponding outgroup. Across four behavioural studies and one eye-tracking study (total N = 704), we find that goals in intergroup contexts are pursued sequentially rather than concurrently, with non-linear upweighting of group-related goals when self-related goals cannot be pursued. Further, we find evidence for stronger self-ingroup than self-outgroup tradeoffs, which manifest in both altered attention to information and altered use of the attended information in decision-making. The results shed light on the cognitive structuring of interrelated goals in intergroup decision-making, furthering our understanding of when and how both intergroup biases and prosocial behaviour may emerge.

People generate evaluations of different attitude objects based on their goals and aspects of the social context. Prior research suggests that people can shift between at least three types of evaluations to judge whether something is good or bad: pragmatic (how costly or beneficial it is), moral (whether it’s aligned with moral norms), and hedonic (whether it feels good; Van Bavel et al., 2012). The current research examined the neurocognitive computations underlying these types of evaluations to understand how people construct affective judgments. Specifically, we examined whether different types of evaluations stem from a common neural evaluation system that incorporates different information in response to changing evaluation goals (moral, pragmatic, or hedonic), or distinct evaluation systems with different neurofunctional architectures. We found support for a hybrid evaluation system in which people rely on a set of brain regions to construct all three forms of evaluation, but recruit additional distinct regions for each type of evaluation. The three types of evaluations all relied on common neural activity in affective structures such as the amygdala, the insula, and the hippocampus. However, moral evaluations involved greater neural activation in the orbitofrontal and cingulate cortex compared to pragmatic evaluations, and temporoparietal regions compared to hedonic evaluations. These results suggest that people use a hybrid system that includes common evaluation components as well as distinct ones to generate moral judgments.

AIM:We examined associations among injury severity, white matter structural connectivity within functionally defined brain networks and psychosocial/adaptive outcomes in children with traumatic brain injury (TBI). METHOD:Participants included 58 youths (39 male) with complicated-mild TBI (cmTBI; n = 12, age =  12.6 ± 2.0), moderate/severe TBI (msTBI; n =  16, age =  11.4 ± 2.9) and a comparison group with orthopedic injury (OI; n =  24, age =  11.7 ± 2.1), at least 1 year post-injury. Participants underwent diffusion tensor imaging and parents rated children's behavioral and adaptive function on the CBCL and ABAS-3, respectively. Probabilistic tractography quantified streamline density. Group differences were analyzed for structural connectivity and behavioral outcomes. RESULTS:Groups differed in structural connectivity within regions of the default mode and central executive networks (ps < .05, FDR corrected). The msTBI group displayed decreased connectivity relative to cmTBI and OI, whereas the cmTBI group displayed increased connectivity relative to msTBI and OI. Similar patterns emerged in several behavioral domains. Ordinary least squares path analyses showed that structural connectivity mediated the relationship between injury severity and multiple parent-reported outcomes for msTBI. INTERPRETATION:White matter structural connectivity may explain unique variance in long-term psychosocial and adaptive outcome in children with TBI, particularly in cases of moderate-to-severe injury.

Attitudes are intertwined with culture and language. But to what extent? Emerging perspectives in attitude research suggest that cultural representations in language are more related to implicitly measured (vs. explicitly measured) attitudes, and that such relationships persist across history and diverse languages. We offer a comprehensive test of these ideas by correlating (a) attitudes toward 55 topics (e.g., Rich/Poor, Dogs/Cats, Love/Money) from ~100,000 U.S. English-speaking participants with (b) representations of those same topics in word embeddings from contemporary English text, 200 years of English books, and 53 non-English languages. Strong and robust relationships emerged between representations in contemporary English and implicitly but not explicitly measured attitudes. Moreover, strong correlations with implicitly measured attitudes persisted across 200 years of books, and most non-English languages. Results provide new insights into the nature of implicitly measured attitudes and how they are intertwined with cultural representations that are relatively hidden in patterns of language across time and place.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

Self-reports remain affective science’s only direct measure of subjective affective experiences. Yet, little research has sought to understand the psychological process that transforms subjective experience into self-reports. Here, we propose that by framing these self-reports as dynamic affective decisions, affective scientists may leverage the computational tools of decision-making research, sequential sampling models specifically, to better disentangle affective experience from the noisy decision processes that constitute self-report. We further outline how such an approach could help affective scientists better probe the specific mechanisms that underlie important moderators of affective experience (e.g., contextual differences, individual differences, and emotion regulation) and discuss how adopting this decision-making framework could generate insight into affective processes more broadly and facilitate reciprocal collaborations between affective and decision scientists towards a more comprehensive and integrative psychological science.

Activating relevant responses is a key function of automatic processes in De Neys's model; however, what determines the order or magnitude of such activation is ambiguous. Focusing on recently developed sequential sampling models of choice, we argue that proactive control shapes response generation but does not cleanly fit into De Neys's automatic-deliberative distinction, highlighting the need for further model development.

Objective:Pediatric traumatic brain injury (TBI) is the leading cause of disability in children under the age of 15, often resulting in executive function deficits and poor behavioral outcomes. Damage to white matter tracts may be a driving force behind these difficulties. We examined if whether 1) greater TBI severity was associated with worse neurobehavioral outcome, 2) greater TBI severity was associated with tract-based white matter microstructure, and 3) worse neurobehavioral outcome was associated with white matter microstructure.Participants and Methods:Twelve children with complicated-mild TBI (cmTBI; Mage=12.59, nmale=9), 17 with moderate-to-severe TBI (msTBI; Mage =11.50, nmale=11), and 21 with orthopedic injury (OI; Mage =11.60, nmale=16), 3.94 years post injury on average, were recruited from a large midwestern children’s hospital with a Level 1 Trauma Center. Parents completed the Behavior Rating Inventory of Executive Function (BRIEF) and Child Behavior Checklist (CBCL) while children completed 64-direction diffusion tensor imaging in a Siemens 3T scanner. White matter microstructure was quantified with FMRIB’s Diffusion Toolbox (FSLv6.0.4). Tract-Based Spatial Statistics computed fractional anisotropy (FA) and mean diffusivity (MD) for the cingulum bundle (CB), inferior fronto-occipital fasciculus (IFOF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF), bilaterally.Results:Group differences were assessed using one-way ANOVA. Children with msTBI were rated as having worse Sluggish Cognitive Tempo on the CBCL than children with cmTBI and OI (p=.02, eta2=.143); no other parent-rated differences reached significance. Group differences were found in left SLF FA (p=.031; msTBIOI) and left SLF MD (p=.013; msTBI>cmTBI=OI). Bivariate correlations assessed cross-domain associations. Higher left IFOF FA was associated with better BRIEF Metacognitive Skills (r=-.301, p=.030) and CBCL School Competence (r=.280; p=.049). Higher left SLF FA was associated with better BRIEF Behavioral Regulation and Metacognitive Skills (r=-.331, p=.017 and r=-.291, p=.036, respectively), and CBCL School Competence and Attention Problems (r=.398, p=.004 and r=-.435, p=.001, respectively). Similarly, higher right UF FA was broadly associated with better neurobehavioral outcomes, including Behavioral Regulation and Metacognitive Skills (r=-.324, p=.019 and r=-.359, p=.009, respectively), and School Competence, Attention Problems, and Sluggish Cognitive Tempo (r=.328, p=.020, r=-.398, p=.003, and r=-.356, p=.010, respectively). Higher right CB MD was associated with worse Behavioral Regulation (r=.327, p=.018) and more Attention Problems (r=.278, p=.046); higher left and right SLF MD was associated with Sluggish Cognitive Tempo (r=.363, p=.008, r=.408, p=.003, respectively).Conclusions:Children with TBI, particularly msTBI, were rated as having cognitive slowing; while other anticipated group differences in neurobehavioral outcomes were not found, this appears driven by milder difficulties in cmTBI and OI groups. In fact, across CBCL and BRIEF subscales, children with msTBI were rated as approaching or exceeding a full standard deviation deficit based on normative data. TBI severity was also associated with white matter microstructure and cross-domain associations linked microstructure with observable neurobehavioral morbidities, suggesting a possible mechanism post-injury. Future longitudinal studies would be useful to examine the temporal evolution of deficits.

Social categorization is often framed as the antecedent to stereotyping, with perceivers rationally sorting the social world on the basis of perceptually salient categories before applying biased or motivated beliefs about those categories. Here, we instead suggest that the construction of social categories by individuals is itself subject to motivational influences, such that perceivers will attend to a given dimension of social categorization (e.g., race or gender) insofar as doing so fits within their motivations. Drawing from classic conceptualizations of social structure as the interplay of schemas and resources, we focus on how the motivations for shared schemas and for material benefits or resources may shape attention to social category dimensions. We outline the potential cognitive mechanisms through which these motivations may act on attention, before discussing the implications of this model for individual differences, conceptualizations of social categorization as rational information reduction, and prejudice reduction. Public Abstract Social categories like race and gender often give rise to stereotypes and prejudice, and a great deal of research has focused on how motivations influence these biased beliefs. Here, we focus on potential biases in how these categories are even formed in the first place, suggesting that motivations can influence the very categories people use to group others. We propose that motivations to share schemas with other people and to gain resources shape people's attention to dimensions like race, gender, and age in different contexts. Specifically, people will pay attention to dimensions to the degree that the conclusions produced from using those dimensions align with their motivations. Overall, we suggest that simply examining the downstream effects of social categorization like stereotyping and prejudice is not enough, and that research should look earlier in the process at how and when we form the categories on which those stereotypes are based.

Careful bias management and data fidelity are key.

We investigated whether any differences in the psychological conceptualization of hate and dislike were simply a matter of degree of negativity (i.e., hate falls on the end of the continuum of dislike) or also morality (i.e., hate is imbued with distinct moral components that distinguish it from dislike). In three lab studies in Canada and the United States, participants reported disliked and hated attitude objects and rated each on dimensions including valence, attitude strength, morality, and emotional content. Quantitative and qualitative measures revealed that hated attitude objects were more negative than disliked attitude objects and associated with moral beliefs and emotions, even after adjusting for differences in negativity. In Study 4, we analysed the rhetoric on real hate sites and complaint forums and found that the language used on prominent hate websites contained more words related to morality, but not negativity, relative to complaint forums.