Annual review of psychology最新文献

Moral psychology was shaped around three categories of agents and patients: humans, other animals, and supernatural beings. Rapid progress in artificial intelligence has introduced a fourth category for our moral psychology to deal with: intelligent machines. Machines can perform as moral agents, making decisions that affect the outcomes of human patients or solving moral dilemmas without human supervision. Machines can be perceived as moral patients, whose outcomes can be affected by human decisions, with important consequences for human-machine cooperation. Machines can be moral proxies that human agents and patients send as their delegates to moral interactions or use as a disguise in these interactions. Here we review the experimental literature on machines as moral agents, moral patients, and moral proxies, with a focus on recent findings and the open questions that they suggest.

Music training is generally assumed to improve perceptual and cognitive abilities. Although correlational data highlight positive associations, experimental results are inconclusive, raising questions about causality. Does music training have far-transfer effects, or do preexisting factors determine who takes music lessons? All behavior reflects genetic and environmental influences, but differences in emphasis-nature versus nurture-have been a source of tension throughout the history of psychology. After reviewing the recent literature, we conclude that the evidence that music training causes nonmusical benefits is weak or nonexistent, and that researchers routinely overemphasize contributions from experience while neglecting those from nature. The literature is also largely exploratory rather than theory driven. It fails to explain mechanistically how music-training effects could occur and ignores evidence that far transfer is rare. Instead of focusing on elusive perceptual or cognitive benefits, we argue that it is more fruitful to examine the social-emotional effects of engaging with music, particularly in groups, and that music-based interventions may be effective mainly for clinical or atypical populations.

Achievement goals have been defined as the purpose of competence-relevant behavior. In this respect they connect one of the basic human needs, i.e., competence, to one of society's core values, i.e., achievement. We propose to look at achievement goals through the lens of social influence. We review both the influence that cultural, structural, and contextual factors have on achievement goal endorsement and the influence that endorsing achievement goals allows people to have within their social space. The review allows us to propose a circular model of the influence on and of achievement goals: The culture, social structures, and contexts that are typical of a certain society shape the specific environments in which individuals develop their achievement goals, which in turn has an influence on the expression and circulation of these achievement goals into society, in a social influence cycle.

Disasters cause sweeping damage, hardship, and loss of life. In this article, we first consider the dominant psychological approach to disasters and its narrow focus on psychopathology (e.g., posttraumatic stress disorder). We then review research on a broader approach that has identified heterogeneous, highly replicable trajectories of outcome, the most common being stable mental health or resilience. We review trajectory research for different types of disasters, including the COVID-19 pandemic. Next, we consider correlates of the resilience trajectory and note their paradoxically limited ability to predict future resilient outcomes. Research using machine learning algorithms improved prediction but has not yet illuminated the mechanism behind resilient adaptation. To that end, we propose a more direct psychological explanation for resilience based on research on the motivational and mechanistic components of regulatory flexibility. Finally, we consider how future research might leverage new computational approaches to better capture regulatory flexibility in real time.

Similarity and categorization are fundamental processes in human cognition that help complex organisms make sense of the cacophony of information in their environment. These processes are critical for tasks such as recognizing objects, making decisions, and forming memories. In this review, we provide an overview of the current state of knowledge on similarity and psychological spaces, discussing the theories, methods, and empirical findings that have been generated over the years. Although the concept of similarity has important limitations, it plays a key role in cognitive modeling. The review surfaces three key themes. First, similarity and mental representations are merely two sides of the same coin, existing as a similarity-representation duality that defines a psychological space. Second, both the brain's mental representations and the study of mental representations are made possible by exploiting second-order isomorphism. Third, similarity analysis has near-universal applicability across all levels of cognition, providing a common research language.

There is always room for moral improvement. However, very few prior reviews have focused on the phenomenon of moral improvement of self, social relations, or society. We first consider prevailing notions of the self-concept by highlighting the niche of theory and research that identifies an improving self as a possible identity and basis of motivation to act better and to be better. Second, we discuss moral improvement in the context of social relations, especially the close interpersonal relations that should most facilitate moral improvement. Third, we examine the moral improvement of society, focusing on the factors that facilitate or inhibit caring about potential immorality despite the fact that issues such as inequality, discrimination, and the climate crisis seem to be morally distant and impersonal. Finally, we discuss future directions for theory, research, and application.

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.

Men who have sex with men (MSM) are disproportionately affected by HIV, accounting for two-thirds of HIV cases in the United States despite representing ∼5% of the adult population. Delivery and use of existing and highly effective HIV prevention and treatment strategies remain suboptimal among MSM. To summarize the state of the science, we systematically review implementation determinants and strategies of HIV-related health interventions using implementation science frameworks. Research on implementation barriers has focused predominantly on characteristics of individual recipients (e.g., ethnicity, age, drug use) and less so on deliverers (e.g., nurses, physicians), with little focus on system-level factors. Similarly, most strategies target recipients to influence their uptake and adherence, rather than improving and supporting implementation systems. HIV implementation research is burgeoning; future research is needed to broaden the examination of barriers at the provider and system levels, as well as expand knowledge on how to match strategies to barriers-particularly to address stigma. Collaboration and coordination among federal, state, and local public health agencies; community-based organizations; health care providers; and scientists are important for successful implementation of HIV-related health innovations.

Can happiness be reliably increased? Thousands of studies speak to this question. However, many of them were conducted during a period in which researchers commonly "p-hacked," creating uncertainty about how many discoveries might be false positives. To prevent p-hacking, happiness researchers increasingly preregister their studies, committing to analysis plans before analyzing data. We conducted a systematic literature search to identify preregistered experiments testing strategies for increasing happiness. We found surprisingly little support for many widely recommended strategies (e.g., performing random acts of kindness). However, our review suggests that other strategies-such as being more sociable-may reliably promote happiness. We also found strong evidence that governments and organizations can improve happiness by providing underprivileged individuals with financial support. We conclude that happiness research stands on the brink of an exciting new era, in which modern best practices will be applied to develop theoretically grounded strategies that can produce lasting gains in life satisfaction.

The restorative function of sleep is shaped by its duration, timing, continuity, subjective quality, and efficiency. Current sleep recommendations specify only nocturnal duration and have been largely derived from sleep self-reports that can be imprecise and miss relevant details. Sleep duration, preferred timing, and ability to withstand sleep deprivation are heritable traits whose expression may change with age and affect the optimal sleep prescription for an individual. Prevailing societal norms and circumstances related to work and relationships interact to influence sleep opportunity and quality. The value of allocating time for sleep is revealed by the impact of its restriction on behavior, functional brain imaging, sleep macrostructure, and late-life cognition. Augmentation of sleep slow oscillations and spindles have been proposed for enhancing sleep quality, but they inconsistently achieve their goal. Crafting bespoke sleep recommendations could benefit from large-scale, longitudinal collection of objective sleep data integrated with behavioral and self-reported data.