Social robotics is a rapidly advancing field dedicated to the development of embodied artificial agents capable of social interaction with humans. These systems are deployed across domains such as health care, education, service, and entertainment-contexts that demand nuanced social competence. Yet, the social dimension of social robotics remains insufficiently conceptualized and empirically grounded. Many companies have failed as their robots struggle to sustain meaningful, long-term engagement with users. Understanding human responses to these agents requires robust psychological frameworks. While prior work has emphasized emotion expression and affective cues, human social interaction is shaped by broader constructs, including individual goals and roles, self-presentation, and culture. Generative artificial intelligence is reshaping human-robot interaction but has yet to resolve foundational challenges in social engagement. Addressing these gaps necessitates deeper integration of psychological theory, methodology, and data. A sustained dialogue between psychology and robotics holds promise not only for advancing socially adept machines but also for enriching psychological science itself.

Intensive longitudinal methods (ILMs) represent a class of longitudinal designs used to understand the flow of people's thoughts, feelings, physiology, and behaviors in their natural settings. This term encompasses daily diary, experience sampling, ecological momentary assessment, ambulatory assessment, and related methods. Research on ILMs has grown exponentially, evolving into a core approach that complements more traditional designs. This article builds on this journal's first review on this topic, published in 2003. In the quarter-century since, there have been marked advances in design, technology, and statistical modeling. Three core ideas permeate this review: To build adequate theories of psychological functioning in natural settings, researchers must focus on () kinematics, () dynamics, and () heterogeneity. Kinematics answers the question, What happened? Dynamics answers the question, Why did it happen? Heterogeneity answers the question, How much do people vary in the whats and whys? ILMs can address these three goals of psychological science.

Originally postulated in 2001, the impaired response inhibition and salience attribution (iRISA) model of addiction highlights the prefrontal cortex (especially the orbitofrontal, dorsolateral, anterior cingulate, and inferior frontal regions) as central to drug addiction symptomatology. Accordingly, drug cues assume a heightened salience and value that overpower alternative reinforcers, with a concomitant decrease in inhibitory control, especially in a drug-related context. These processes may manifest in metacognitive impairments (e.g., self-awareness of choice), obstructing insight into illness, as a function of recency of drug use. In this review, we update the neurobehavioral evidence for iRISA two decades later, emphasizing the robust measurement of the iRISA interaction (between a drug-related cue/context and a cognitive-behavioral function), and highlight relevant individual differences (e.g., drug use severity, craving). Crucially, we describe data suggesting functional recovery (with abstinence, treatment, and other emerging modalities) and the need for identifying valid outcome biomarkers. We end by highlighting recent developments in artificial intelligence (e.g., natural language processing applied to spontaneous speech) and computational modeling, and call for enhanced ecological validity to facilitate dynamic and clinically meaningful neural explorations in drug addiction.

How a developing nervous system discovers meaning in complex sensory inputs has typically been examined separately for each sensory modality. Even as studies have uncovered modality-specific strategies, it remains unclear whether common principles underlie such discovery. Here, we pursue the thesis that the detection and exploitation of temporal regularities may provide a unifying mechanism for sensory organization across modalities. We synthesize research spanning neurophysiology and cognitive neuroscience and incorporate results from theoretical computer science. This integration supports the conclusion that time may be the fundamental dimension along which the brain organizes its sensorium and that the computational complexity of this problem is rendered tractable by ecologically appropriate heuristics. This proposal suggests the centrality of temporal processing in perceptual development, with implications for studies of typical and atypical development, clinical populations, and computational modeling.

Our memories shape our perception of the world and guide adaptive behavior. Rather than a veridical record of experiences, memory is selective. An accumulating body of work suggests that motivational states, emerging from the interplay between internal and external demands, play a critical role in determining what information is encoded in memory and how. Central to the regulation of motivational states are dopaminergic and noradrenergic neuromodulatory systems that can coordinate brain activity to determine how information is propagated, shaping memory outcomes. In this review, we propose that motivational states supported by the dopaminergic ventral tegmental area would facilitate the formation of flexible associative memory, while the noradrenergic locus coeruleus would facilitate unitized goal-relevant memory. By considering how neuromodulatory systems can support different neural contexts, we aim to explain how motivation enables an adaptive memory system, and in bridging motivation and memory, we aim to offer a framework for insights applicable to education and clinical practice.

The advent of noninvasive imaging methods like functional magnetic resonance imaging (fMRI) transformed cognitive neuroscience, providing insights into large-scale brain networks and their link to cognition. In the decades since, the majority of fMRI studies have employed a group-level approach, which has characterized the average brain-a construct that emphasizes features aligned across individuals but obscures the idiosyncrasies of any single person's brain. This is a critical limitation, as each brain is unique, including in the topography (i.e., arrangement) of large-scale brain networks. Recently, a new precision fMRI movement, emphasizing extensive scanning of single subjects, has spurred another leap in progress, allowing fMRI researchers to reliably map whole-brain network organization within individuals. Precision fMRI reveals a more detailed picture of functional neuroanatomy, unveiling common features that are obscured at the group level as well as forms of individual variation. However, this presents conceptual hurdles. For instance, if all brains are unique, how do we identify commonalities? And what forms of variation in functional organization are meaningful for understanding cognition? Which sources of variability are stochastic, and which are due to measurement noise? Here, we review recent findings and describe how precision fMRI can be used () to account for variation across individuals to identify core principles of brain organization and () to characterize how and why human brains vary. We argue that, as we dive deeper into the individual, overarching principles of brain organization emerge from fine-scale features, even when these vary across individuals.

My career began with the exciting beginnings of cognitive psychology. It took me to memory, mental representations, categorization, spatial cognition, language, event cognition, stories, discourse, visualizations, comics, gesture, joint action, creativity, design, and more. On the way I enjoyed collaborations with friends and students in many areas and many countries. I am slowing down just as brain, AI, computational models, and big data are taking over the field, bringing new methods and new ways of thinking and, with that, new talent and inspired minds.

This article provides a critical overview of research on human rationality. Rationality research poses a number of unusual challenges to psychologists. For one, it is unusually interdisciplinary and involves research conducted in adjacent disciplines (e.g., economics, education, communication, computer science and philosophy), not all of which are accessible with psychological training. What underlies this diversity, however, is an arguably even more unusual feature: the fact that even purely descriptive research, focused on what we actually do, cannot proceed without reference to normative considerations, that is, considerations of what we ought to do. Empirical results can thus only be understood with some understanding of the relevant norms of rationality. This article introduces the range of relevant frameworks, followed by examples of the different ways these frameworks are put to use. The bulk of the article then surveys research findings on human rationality across the core areas of (probability) judgment, reasoning, decision-making, and argumentation. Two final sections provide cross-cutting themes, one on the contrast (and interrelationship) between individual and collective rationality and one on the unique challenges of linking rationality research to real-world concerns.

As masculinities are changing, taking a social identity perspective on men and their relations with others helps to understand how men navigate their social world. Combining this with other common approaches in the psychology of gender, men, and masculinities, we review how such a perspective helps to understand men's differing health and well-being outcomes, work/family choices, and their responses to changing gender relations and other social developments (privilege, threat, allyship). In so doing, we emphasize that men's audiences (i.e., who precisely is watching them) play a key role in shaping these outcomes as well. For practitioners working in the fields of health and well-being, work and family, or gender equality, we identify key implications that follow from the reviewed research. We end our review with suggestions for future research.

This review specifies how individuals' relationship power (actor power) and their partners' power (partner power) influence distinct behaviors in close relationships. High-power actors can promote their own needs, whereas low-power actors must inhibit their needs or enact aggression or manipulation to fight for their needs. Actors must also accommodate the needs of high-power partners but can neglect or may feel obliged to protect low-power partners. Structural power asymmetries outside relationships prompt ideologies that shape perceptions, expectations, and subsequent behavioral responses to power within relationships. Using gender ideologies to illustrate, competitive ideologies (hostile sexism) motivate aggression by those who fight for power or prompt inhibition by those who cede power. Cooperative ideologies (benevolent sexism) divide power, generating accommodation of partners' needs in some domains and neglect in others. We emphasize the need to consider actor and partner power, relationship and structural power, power symmetries and asymmetries, and competitive and cooperative ideologies.

A robust approach to understanding dyadic emotion regulation needs to incorporate insights from affective science and relationship science. To date, research emerging from these two traditions has largely unfolded separately with limited cross-disciplinary collaboration. Here we review research from these two disciplinary perspectives, focusing on social support and dyadic coping in the close relationship literature and on extrinsic interpersonal emotion regulation in the affective science literature. We also present a framework of dyadic emotion regulation. This framework includes both affect-improving and affect-worsening processes that can be motivated by hedonic or instrumental goals and that can have effects not only on the emotions targeted for regulation but also on the relationship dynamics of the dyadic partners. We identify key gaps in the literature and directions for future research, and we conclude that recognition of the complex interplay between emotion regulation and relationship processes allows for deeper and more nuanced models of dyadic emotion regulation.

The past decade has seen a surge in developing just-in-time adaptive interventions (JITAIs)-an intervention approach that leverages advancements in digital technologies to address the rapidly changing needs of individuals in daily life. This article provides an overview of the state of science on JITAI development and highlights important directions for future research. We explain what a JITAI is (and what it is not) and review the scientific and practical rationales underlying this approach. We also call attention to three key challenges relating to the development of JITAIs. The first challenge is that individuals may not be able to engage with (i.e., invest energy in) an intervention when they need it most in daily life. The second concerns the generally suboptimal engagement of individuals in interventions that leverage digital technologies as currently implemented. The third concerns the paucity of research on ways to harness the power of social relationships in JITAIs. We conclude that much research effort is needed to build more sophisticated and effective JITAIs.

Recent progress in artificial intelligence (AI) is exciting, but can AI models tell us about the human mind? AI models have a long history of being used as theoretical artifacts in cognitive science, but one key difference in the current generation of models is that they are stimulus computable, meaning that they can operate over stimuli that are similar to those experienced by people. This advance creates important opportunities for deepening our understanding of the human mind. We argue here that the most exciting of these is the use of AI models as cognitive models, wherein they are trained using human-scale input data and evaluated using careful experimental probes. Such cognitive models constitute a substantial advance that can inform theories of human intelligence by helping to explain and predict behavior.

This review synthesizes and critiques research on early life adversity and stress effects on multidomain health outcomes in child samples to fill a gap in the literature that has largely focused on adults. Prioritizing evidence from meta-analytic and systematic reviews as well as findings from (quasi-)experimental or large prospective longitudinal studies, we integrate interdisciplinary findings to characterize patterns of evidence for stress associations with child outcomes, including mental, physical, and positive health; academic, social, and justice system-related domains; and intermediary phenotypes that may predict disease, including biomarkers. We note cohesive evidence for sensitive periods of susceptibility to stress exposure and describe key mediators and moderators of stress effects, especially family-level factors. Then we highlight interventions targeting malleable factors that hold promise for ameliorating the effects of stress on children. Leveraging a developmental lens, we conclude with field-wide limitations and propose future directions for stress and health research that centers child development.

Around the turn of the millennium, the social representation of minorities in Western societies shifted from marginalized deviants to victims of injustice, prompting calls for recognition and reparation. Drawing on the social identity tradition, we argue that this shift in representation gave rise to new identity needs, with victim groups seeking to restore their agentic identity and perpetrator groups their moral identity. We review two research trends that emerged from this shift in representation and its relationship to identity needs. The first trend focuses on group apologies, forgiveness, and corresponding gestures. We suggest that these gestures can promote reconciliation by satisfying group members' identity needs; we also acknowledge the limitations and critiques of using the apology-forgiveness cycle to promote intergroup reconciliation. The second trend concerns groups' engagement in competitive victimhood. We propose that this engagement stems from the same identity needs and discuss its consequences and strategies for reducing it. Finally, we outline future directions and practical takeaways and reflect on the changing zeitgeist.

Domain-general object recognition () is the ability to discriminate between objects at the subordinate level. It describes the general ability that applies across object categories, in contrast to abilities that apply only to a specific category. Interest in this ability emerged from vision research and cognitive neuroscience. However, research into high-level visual abilities has been relatively independent of the wider literature on individual differences in abilities. This review seeks to bridge this gap. To assess whether represents a novel construct, we compare it with the closest preexisting constructs. We argue that abilities such as visual memory and perceptual speed share conceptual overlap with , but none of these abilities have the kind of subordinate-level discrimination at their core that does. Despite theoretical differences, some tests of these constructs may serve as adequate indicators of . We also connect to theory about the structure of cognitive abilities.

Are attitudes or intentions related to behavior change? Does changing attitudes or intentions change behavior? These are important questions for increasing our understanding of the determinants of behavior and how to change behavior. This review employs four stages of the experimental medicine approach to answer these questions. First, attitudes and intentions have been identified as key determinants of behavior in many theories (identification stage). Second, correlational studies show that attitudes and intentions have small- to medium-sized relationships with behavior change, while experimental studies show that medium-sized changes in attitudes and intentions produce small-sized changes in behavior (validation stage). Third, evidence shows that interventions can change attitudes or intentions (engagement stage). Fourth, changes in attitudes and intentions at least partially mediate the intervention effects on behavior change (intervention stage). A systematic program of experimental work is needed to extend our understanding of what works for whom, when, how, and for what behaviors.

Many psychologists rely on surveys, questionnaires, and measurement scales because psychological constructs like depression, motivation, or extraversion cannot be directly measured with physical instruments. Scale validation crucially provides evidence that scores from such scales capture their intended target. The prevailing scale validation approach involves comparing factor-analytic model fit indices to suggested benchmarks, and it is so engrained in psychological research that the article proposing the benchmarks is among the most cited works across any scientific discipline. However, methodological research finds that psychologists overgeneralize the benchmarks so that they no longer function as originally intended. This has widespread implications for psychologists and casts some doubt on conclusions regarding the validity of our measurement scales. This review covers the history and origin of scale validation benchmarks, how benchmarks rose to prominence and became overgeneralized, recently proposed alternatives to traditional benchmarks, and future directions in this methodological area that affects many subfields of psychology.

Looking back on our life and work, we reflect on the changes in our thinking due to three scientific and technological revolutions. These are information processing, computers, and brain imaging, and together they ousted behaviorism from its dominant position in experimental psychology. We champion a model of the mind that is hierarchically organized with both a robust unconscious and a harder-to-pin-down conscious mode of operation. Our studies were inspired by disorders that made us realize that cognitive processes at all levels of the information processing hierarchy impact social interactions. We locate the influence of culture at the highest level of this processing hierarchy. Here we see the interface between different minds and the importance of norms when regulating the opposing trends in our complex and even contradictory social nature.

Cognitive biases significantly influence decision-making by distorting how individuals perceive and evaluate outcomes over time. This systematic review synthesizes research from various domains, including behavioral economics, psychology, and health, to explore six time-related biases affecting intertemporal judgments and trade-offs. We analyze the underlying mechanisms of each bias, map their interrelationships, and uncover their impacts on both individual choices and societal decisions. Drawing upon empirical evidence, we propose tailored strategies to mitigate the adverse effects of these biases. Our findings contribute to the literature not only by enhancing the understanding of time-related cognitive biases but also by providing practical insights for improving decision-making and policy design aimed at promoting long-term well-being. The review concludes by highlighting critical gaps in the literature and outlining a future research agenda to further investigate and address biases in intertemporal decision-making.

The mechanistic underpinnings of sustained attention, vigilance, and the ability to continue responding to critical stimuli over time, despite decades of research, are not well understood. Although sustained attention is vital for survival and is studied in many taxa, a lack of comparative work and a greater research focus on the high-level psychological aspects of human sustained attention performance have hindered progress in our understanding of it. We posit that an interdisciplinary approach between the biological and psychological fields, involving research on humans and nonhuman animals, will illuminate the biological mechanisms involved. A key obstacle to a comparative approach is the vast terminology used to illustrate similar phenomena across disciplines. We compare the research on sustained attention in humans and animals, showing that the comparative gap is not insurmountable. To resolve the communication issue, we outline the different terms used and suggest future directions to encourage productive engagement between the two fields. Additionally, we propose that an interdisciplinary perspective will be advantageous for developing countermeasures to declining sustained attention.