The WEIRD framework-Western, educated, industrialized, rich, democratic-introduced in 2010 by Henrich et al. drew widespread attention to psychology's overreliance on Western samples and its assumption of universal human psychology. However, in this article I argue that the framework's popularization-particularly in work explaining the origins and consequences of WEIRD psychology-has paradoxically generated a new form of exceptionalism. By designating Western populations as psychologically "peculiar," the framework inadvertently maintains the West as the central reference point against which human variation is measured. I identify three mechanisms through which this occurs. First, the WEIRD acronym itself embeds developmental assumptions: Its components connote achievements rather than neutral differences, while implicitly defining non-WEIRD populations through deficit (uneducated, undeveloped, poor, authoritarian). Second, the comparative structure positions WEIRD populations as the persistent baseline, with non-WEIRD psychologies understood through their deviation from Western patterns rather than as autonomous systems. Third, cultural-historical accounts tracing WEIRD psychology to internal European developments risk obscuring how extraction and violence constituted the material conditions for Western institutional dominance. I propose that genuinely decentering Western psychology requires moving beyond binary comparative frameworks, developing research programs that engage diverse cultural psychologies on their own terms and transforming institutional structures that implicitly favor Western theoretical frameworks as unmarked universals.
The shift to a society organized around digital data has come with significant-although sometimes still underappreciated-implications for psychological research. In part, this is owed to the narrowness of discussions about data ethics in the discipline, although also to the ontological assumptions about data that implicitly shape researchers' discussions and practices. The prevailing representationalist ontology of data-understanding data to be a passive abstraction that represents some preexisting phenomenon-draws researchers' attention to methodological issues, such as data quality, while simultaneously turning attention away from different kinds of issues. Informed by feminist technoscience and feminist-new-materialist thinkers, we argue for an alternative ontology of data that helps understand it as being material-relational-as something that is active and entangles researchers in (often invisible) relations that have real, material consequences. These ontological commitments can draw attention to those relations and their implications and help researchers consider what ethical issues are at stake, thus creating the conditions to advocate for new kinds of responsible research practices. We put this ontology to work by looking at two issues: the labor problems from data collection on MTurk and the environmental impacts of data storage. We conclude by offering practical recommendations for more responsible data practices in psychology.
Prevailing theories of cognitive aging depict late life as a period of compensatory decline-an effort to preserve performance despite progressive neural deterioration. We propose instead that aging represents a continuation of development: a genetically conserved, adaptive reorganization of memory systems that parallels the brain's earlier-life transitions. Drawing on convergent molecular, network, behavioral, and comparative evidence, we argue that the well-documented decline in episodic-memory precision reflects a deliberate recalibration of plasticity from hippocampal to cortical circuits, favoring semantic integration and schematic stability over rapid encoding of novel details. This shift, we suggest, is not a workaround for loss but an evolved optimization suited to the cognitive ecology of late life, when accumulated knowledge, social insight, and intergenerational teaching become primary adaptive functions. The resulting semantic mode of cognition supports narrative coherence, emotional regulation, and wisdom, distinguishing normal aging from pathological derailments such as Alzheimer's disease. We outline testable predictions across longitudinal, neuroimaging, and computational domains and reinterpret constructs like cognitive reserve as expressions of this developmental reallocation. By reframing aging as purposeful maturation rather than compensation, the adaptive-aging hypothesis positions late-life cognition as a distinct, evolutionarily honed phase of human development.
Early career researchers, because of their role in data collection and analysis, are often first to experience the emotional impact of null or nonreplicable results. In this article, we lift the veil on null results by presenting their causes (i.e., low prior probability of the hypothesis, theoretical ambiguity) and consequences and offer early career researchers-especially researchers at less wealthy institutions-tools to deal with null results.
Replication-duplicating methods to reexamine findings-is the bedrock of science. To survey this foundation for psychological science, Makel et al. (2012) searched 100 psychology journals, finding that all-fields database searches for replicat* returned 2% to 3% of articles. Coding the contents of 500 such articles, they estimated that only 1% to 2% of psychology articles report new replication research. Four studies, reported here, reexamined these results-including two preregistered replications with extension that sampled psychology articles (published pre-2012) without first searching databases. Nearly 20% of these 1,224 articles used "replication" or a variant term to identify replication as a study aim, report duplicating methods, or describe reexamining findings from prior studies. Moreover, authors frequently described reproducing procedures or retesting results without referring to "replication." My investigation identified possible reasons why previous prevalence estimates for author-identified replication in behavioral research ranged from 1% to 76%, including what discipline, subdiscipline, report sections, study features, or terminology the researchers considered when identifying replications. Chief among these reasons is the fact that around 90% of articles that discuss replication and over 80% of articles with author-identified replications are missed by searching databases for replicat* because databases hold few details per article. Equivalent limitations of database searches may present similar challenges for metascience investigations and research syntheses.
Generative artificial intelligence (GenAI) is rapidly transforming the context in which adolescents develop, presenting both opportunities and risks. Adolescence is a sensitive life period during which the accomplishment of key psychosocial developmental tasks-including social belonging, emotion regulation, autonomy, and identity formation-leads to lifelong consequences. Here, we synthesize interdisciplinary research on how adolescents' use of GenAI chatbots such as ChatGPT may have unique impacts during this life stage. Although GenAI may provide low-stakes opportunities to simulate social interactions, scaffold emotional regulation, and support identity exploration in some contexts, it also threatens to displace or thwart essential developmental experiences. Risks include increasing social isolation, undermining distress tolerance, distorting expectations for human relationships, compromising identity and purpose development, and exposing youth to biased, inaccurate, or sexually inappropriate content. We call for a developmental science framework to guide future research, technology design, and policy. Longitudinal studies are needed-especially those that examine specific use cases, address all domains of development holistically, account for varying levels of vulnerability across stages and populations of adolescence, leverage interdisciplinary and academic-industry partnerships, and incorporate the perspectives of youth. As adolescents increasingly integrate GenAI into their daily lives, we must urgently address how these tools are shaping their transition to adulthood.
For many years, research on attention has been dominated by theories based on the assumption that attention is limited in capacity. These include the limited-capacity-channel theories of Welford and Broadbent and capacity or resource theories by Moray, Posner, and Kahneman. This article challenges these theories and their many descendants by asking why capacity is limited and what role capacity plays in the computations required to perform attention tasks. There are few satisfactory answers in limited-capacity and resource theories of attention. I show that the effects of load on performance, which are commonly interpreted as evidence for limited capacity, can be produced by models that assume unlimited, limited, and fixed capacity. I argue that attention is better construed as a selection of information that we need to achieve our goals. Following current research on computational models of attention in associative learning, categorization, perceptual learning, cognitive development, neuroscience, and artificial intelligence, I propose that attention is a process of choice in which selection is implemented as multiplicative gain control and processing is constrained by normalization. This perspective focuses on interactions between representations and decision processes applied to them, explaining many attentional phenomena without assuming attention is a limited resource.
Many people want to change their personality in some way, and personality traits have been found to predict various important aspects of life, including well-being, health, relationship quality, and work success. As a result, volitional personality interventions designed to elicit personality-trait change in desired directions have recently gained momentum in research and public discourse. Although the initial evidence on the effectiveness of these interventions is promising, concerns regarding their benefits, risks, and societal implications remain underexplored. In this review, we discuss 10 concerns regarding methodological, ethical, and practical limitations of volitional personality-change interventions. Drawing on research across different areas of psychology, we provide a balanced discussion of each concern and outline directions for future research and practical applications of these interventions. Volitional personality-change interventions have the potential to improve people's lives and increase satisfaction with the self. However, realizing this potential requires sustained research effort, thoughtful study design, and careful implementation of these interventions to maximize benefits and mitigate concerns.
Why do people punish wrongdoers when they are not personally affected? Researchers on costly third-party punishment have long debated whether such behavior reflects strategic self-interest or a moral commitment to fairness and justice. Recent developmental evidence offers important insights into this question. We argue that the origins of costly third-party punishment in early childhood are best explained by nonstrategic moral concerns. Young children selectively punish norm violators, incur personal costs to do so, and intervene even when they stand to gain nothing-often without reputational incentives or expectations of future benefit. Empirical studies indicate that children's punishment is driven by egalitarian norms, retributive motives, and efforts to alleviate victims' distress. In contrast, strategic motivations, such as reputation management and self-protection, appear only later in development. These findings challenge the view that third-party punishment is grounded in self-interest and instead support the idea that a concern for justice underlies the earliest forms of human norm enforcement. We conclude that whereas strategic considerations may shape punishment in adolescence and adulthood, they build upon an early-emerging moral foundation centered on fairness and justice.
Thanks to our remarkable ability to transmit technical content, our technologies have become more sophisticated. Intuitively, one might assume that this evolution has imposed greater demands on the technical brain. However, recent neuroscientific research suggests that this evolution has also increasingly engaged the social brain to address the opacity it has generated in making, transactive, and use processes. Here, we build on these findings to design a neurocognitive framework that outlines the role of the social brain in (a) facilitating the transmission of making processes, (b) relying on human experts as extensions of our technical cognition, and (c) engaging with certain technologies-including machines-as if they were intentional biological agents. The framework emphasizes the dynamic interplay between the technical and social brain and explores the mechanisms that drive switching between these networks in response to technological opacity, including bottom-up perceptual cues and causal uncertainty. It also considers how expertise modulates network engagement and guides the allocation of cognitive resources. Overall, this framework provides a unified perspective on how humans navigate complex technological environments, illustrating the coevolution of technical and social cognition and the adaptive strategies that allow us to interact with technologies that we cannot fully understand.
Teaching phonics-that is, systematic mappings between letters and sounds-plays a foundational role in how children learn to read in alphabetical writing systems. Although the reading sciences yield important insights into the factors underlying effective phonics instruction, these findings have not been sufficiently linked to key decisions that teachers must make in the classroom-for instance, which spelling-sound regularities to teach, in what order to introduce them, how to illustrate them with example words, and when to teach exception words. We first show that existing phonics programs provide varying guidance on these aspects, which may affect learning outcomes in ways that are poorly understood. We then discuss how research on reading and learning can inform key considerations regarding the use of effective phonics content. We also highlight gaps in current knowledge that remain to be addressed by further work. Finally, we outline a road map for how future research could support the design and selection of optimized phonics content, thus benefiting the professional practice of diverse stakeholders in education.
Research has established that children are “naive psychologists”, adept at understanding and navigating the social world from an early age. However, most of this work has focused on how children process information that they acquire incidentally, for example by passively observing others’ actions. Here, we draw on literature framing children as intuitive scientists, who actively seek information and test hypotheses, to propose a view of children as naive experimental psychologists. From this perspective, children play an active role in selecting and pursuing relevant social information (e.g., about agents’ goals, traits, or relationships), whereby their search strategies are influenced both by context and task demands, as well as their prior beliefs, concepts, and domain-specific naive theories. We argue that the particular challenges associated with learning and reasoning about other minds may necessitate that children leverage their active learning competences, and we outline how the social domain uniquely constrains and shapes the learning process. We review existing research on social-information seeking in children and adults, and identify directions for future research, emphasizing that children’s developing social cognition should be understood in terms of the active, exploratory role they take in learning about and participating in the social world.
Traditional developmental science has often described child growth as a sequence of stages or linear progressions, yet many phenomena-abrupt spurts and regressions, idiosyncratic pathways, and widening individual differences-resist linear accounts. This article proposes chaos theory as a framework for quantifying developmental trajectories. Chaos theory, which addresses how complex patterns emerge from simple rules in deterministic yet unpredictable ways, aligns with observations of sensitive developmental periods, emergent behaviors, and divergent outcomes. I situate chaos theory alongside dynamic systems theory, neuroconstructivism, and developmental-cascade models and clarify how chaos might add mathematical precision to established insights: Bifurcation analysis identifies tipping points at which behaviors reorganize; Lyapunov exponents quantify stability and sensitivity to small perturbations; state-space methods reconstruct attractor landscapes from dense time series; and complexity metrics discriminate structured variability from noise. These tools convert powerful metaphors-soft assembly, attractors, cascades-into testable hypotheses about when and why qualitative change occurs. Such a framework also motivates microgenetic and high-density longitudinal designs, computational modeling of phase transitions, and interventions conceived as targeted perturbations delivered near sensitive windows. Finally, I discuss why adopting a chaos framework can be advantageous compared with (or in concert with) traditional linear models.
Comparisons in psychological research are often directional, with one entity (a group, situation, condition, or measurement) that is the "target" of the comparison being compared to a baseline or reference point (the "referent"). A particular unidirectional framing often gets entrenched in a research tradition. This can be problematic because people (including researchers) focus disproportionately on the target rather than on the referent of directional comparisons. They thus mainly seek explanations for differences or similarities in processes associated with the target. As a consequence, a unidirectional perspective obscures ideas and impedes theoretical progress, particularly if the designation of the referent was arbitrary (i.e., not representing a default) to begin with. We first examine mechanisms that entail unidirectionality in research traditions. Drawing primarily on social psychology (but with an eye toward the broader field of psychology), we review examples in which a dominant unidirectional perspective has been fruitfully challenged. We then present four case studies from domains characterized by unidirectionality in which reversing the direction of comparison could stimulate new insights. We provide guidelines for avoiding or reversing one-way theoretical paths and consider metaquestions that our analysis provokes. We end with limitations of our work and recommendations for future research.
People increasingly live their lives online, which means that their identities are increasingly constituted by and displayed through their activities on digital platforms. Existing theorizing about the psychology of digital identity has emphasized the social roles that people perceive and aim to verify online. These accounts can explain how digital identities are shaped by the social environment but not how they come together to create social life online. Moreover, there are unique features of digital identities, imposed by the digital platforms on which they are enacted, that cannot be accounted for by existing theories of offline social identity. To address these limitations, in the current article we propose a social digital identity theory that outlines how a person's digital identity is shaped by their online and offline group memberships, as well as the implications of this psychological process for the well-being and performance of both individuals and groups. In outlining this theory, we aim to extend theorizing around social identity and digital identity by integrating these fields within a framework that recognizes and helps us better understand the merging of online and offline life.
Nuclear weapon threats are increasing and may be comparable to levels not seen since the worst periods of the Cold War. There could be value in psychologists documenting and explaining people's responses to nuclear weapons. More than 3 decades have passed since the last major reviews of people's responses to nuclear weapons. We thus aimed to understand how psychologists and researchers from related fields have empirically studied responses to nuclear weapons since the end of the Cold War. We systematically mapped articles reporting on people's responses. A search in Web of Science and Scopus identified 18,505 hits. Screening resulted in 256 suitable articles. We assessed (a) publication patterns, including how many articles focused on responses to nuclear weapons, when those articles were published, and in which field; (b) the research community, namely author collaborations and focal journals; (c) research themes, as indicated by cocitation networks and theoretical backgrounds; and (d) the validity, generalizability, and replicability of empirical findings, as indicated by adequate samples and validated measures. We found renewed interest in the field but not yet a coherent research community and only some evidence for its evolution from occasional, scattered, one-off studies toward a coherent and coordinated scholarly field.
The "socioeconomic achievement gap" refers to socioeconomic disparities in children's academic outcomes. Do these gaps invariably reflect cognitive processes that are similar in kind across the socioeconomic status (SES) spectrum but differ quantitatively in their efficacy? Or, in some cases, do they reflect cognitive processes that differ, in kind, between higher and lower SES, that is, qualitatively? In this systematic review, we used the ways in which brain structure and function relate to cognitive performance to answer these questions, focusing on academically relevant cognitive abilities. Specifically, the brain correlates of performance served as a signal regarding the underlying cognitive processes used to perform cognitive tasks. The literature was searched for studies that reported whether SES moderated the brain-cognition relation. In 15 cases, significant moderation was found, suggesting that children from diverse SES backgrounds may use underlying brain systems differently to achieve cognitive task performance. Three general mechanisms are reviewed, as are the broader implications of qualitative differences for teaching and for the causal relations leading to socioeconomic disparities in cognition.
The sense of presence is typically defined as the feeling of "being there" in a virtual environment, whereas the sense of reality is defined as the ability to discriminate between real and unreal phenomena. We challenge this rigid dichotomy, arguing that presence and reality can be considered conceptually, mechanistically, and phenomenologically continuous. We first demonstrate that both cognitive sciences and virtual reality (VR) studies use the terms inconsistently and interchangeably. We then go on to identify and combine perceptual and cognitivist accounts of presence, arguing that presence, like reality, is likely to be formed from integrative mechanisms. We then go further to identify converging psychophysical findings from the two fields in multisensory integration, self-embodiment, and agency. This is further supported by results from preliminary neuroimaging studies, indicating a shared frontolimbic substrate for generating the feeling of "realness." This reconceptualization has significant implications, including validating the use of VR as a tool for studying the sense of reality and its clinical disorders. We conclude by advocating for directly comparing these phenomena in future research to systematically test for their functional and neural equivalence.
In 1961, Donald Hebb established a classic paradigm for studying repetition learning: He asked participants to remember several memory sets for an immediate serial recall task and repeated one set multiple times throughout the experiment. Participants' ability to recall the repeated set improved gradually with repetitions, thereby demonstrating repetition learning. Explaining this effect has concerned researchers for decades because it provides key insights into how we form durable memory representations through repeated exposure. In this article, we revisit the dominant views on the mechanisms underlying repetition learning, thereby challenging the central assumption that repetition learning is gradual and implicit. We show how these views have emerged from flawed analytical approaches, summarize recent evidence strongly contradicting these claims, and reanalyze previously published data to illustrate how correcting implausible analytical assumptions leads to different theoretical conclusions. We propose an updated theoretical framework of the cognitive mechanisms underlying repetition learning that integrates elements from previous models of the Hebb repetition effect with established models of episodic memory, thereby joining two branches of the memory literature.
