Communications Psychology最新文献

This longitudinal study examined the relationship between social connections and personal agency, as well as their association with loneliness over time. Utilizing four waves of data from the Irish Longitudinal Study on Ageing, analyses found four distinct prototypes within each data wave that reflect combinations of social connection and personal agency. Subsequent analyses showed that one prototype (low agency, low communion) experienced the highest levels of loneliness, while another (high agency, high communion) reported the lowest. The remaining two prototypes exhibited intermediate loneliness despite differences in the social connection levels between them. Tracking transitions between prototypes across waves revealed that shifts toward less favorable prototypes were associated with increased loneliness, whereas transitions toward more favorable prototypes were associated with reduced loneliness. These findings enhance our understanding of loneliness, an experience generally thought to be driven by relational deficits, highlighting the role of personal agency.

How do we understand actions performed by others? Recent studies suggest that actions can be represented as points in a multidimensional space, where the perceived similarity of two actions is thought to be related to their proximity within this space. Here we present a data-driven approach to reveal key dimensions underlying this space using a carefully selected stimulus database of 768 one-second video clips spanning 256 action categories. We gathered similarity ratings for these videos from 6,036 participants and used a computational modeling procedure to identify key dimensions underlying these ratings. This approach revealed 28 meaningful dimensions (e.g. interaction, sport and craft) which capture information concerning human actions as well as a broad range of related domains (e.g. living and non-living things). Explicit ratings of actions along these dimensions gathered in a separate group of participants revealed a high correlation between ratings and weights along these dimensions, demonstrating that these dimensions are interpretable and can be used by participants. The multidimensional action space established in the current study enables the quantification of the similarity between different actions, which will be useful for the generation of hypotheses and future experimental manipulations. Together, our results provide a window into the nature of the representations underlying the ability to interpret other people's actions and pave the way for future lines of research.

Adaptation to climate change continues to fall short of needs. Emerging research in psychology and other social sciences suggests that hope may be an important emotion and cognitive process for enabling climate action, and for keeping despair at bay. Drawing on and extending this research, we present a theoretical model to show how hope has the capacity to be a powerful driving force for adaptation. We suggest that hope can, in theory, spur adaptation to climate change in situations where individuals and collectives identify adaptation goals and pathways to achieve those goals; and that effective collective adaptation can in turn reinforce hope. We propose a program of systematic research in communities experiencing climate change impacts to assess the relationship between hope and adaptation, and explore conditions where hope could be leveraged to promote much-needed momentum in climate change adaptation.

Past work has long recognized the important role of context in guiding how humans search their memory. While context-based memory models can explain many memory phenomena, it remains unclear why humans develop such architectures over possible alternatives in the first place. In this work, we demonstrate that foundational architectures in neural machine translation - specifically, recurrent neural network (RNN)-based sequence-to-sequence models with attention - exhibit mechanisms that directly correspond to those specified in the Context Maintenance and Retrieval (CMR) model of human memory. Since neural machine translation models have evolved to optimize task performance, their convergence with human memory models provides a deeper understanding of the functional role of context in human memory, as well as presenting alternative ways to model human memory. Leveraging this convergence, we implement a neural machine translation model as a cognitive model of human memory search that is both interpretable and capable of capturing complex dynamics of learning. We show that our model accounts for both averaged and optimal human behavioral patterns as effectively as context-based memory models using a publicly available free recall experiment dataset involving 171 participants. Further, we demonstrate additional strengths of the proposed model by evaluating how memory search performance emerges from the interaction of different model components.

Every social situation that people encounter in their daily lives comes with a set of unwritten rules about what behavior is considered appropriate or inappropriate. These everyday norms can vary across societies: some societies may have more permissive norms in general or for certain behaviors, or for certain behaviors in specific situations. In a preregistered survey of 25,422 participants across 90 societies, we map societal differences in 150 everyday norms and show that they can be explained by how societies prioritize individualizing moral foundations such as care and liberty versus binding moral foundations such as purity. Specifically, societies with more individualistic morality tend to have more permissive norms in general (greater liberty) and especially for behaviors deemed vulgar (less purity), but they exhibit less permissive norms for behaviors perceived to have negative consequences in specific situations (greater care). By comparing our data with available data collected twenty years ago, we find a global pattern of change toward more permissive norms overall but less permissive norms for the most vulgar and inconsiderate behaviors. This study explains how social norms vary across behaviors, situations, societies, and time.

How do people learn about their own abilities? Often, people receive rewards that offer information about their performance level. Yet, even when two people perform equivalently on a task, they may receive disparate rewards. In these cases, could rewards still influence self-evaluations of ability? In two behavioral experiments, we asked whether people feel more capable and confident when they receive more rewards, even when their performance is held constant, and they know how they objectively performed. Participants played a perceptual game in which they received trial-by-trial accuracy feedback; a staircase procedure held their objective performance constant. However, participants were assigned to either a high or low-reward condition, which varied the probability of receiving a reward for a correct answer. In Experiment 1 (N = 340), we found evidence that rewards bias overall self-evaluations of ability after the task-particularly estimations of objective accuracy. Next, in Experiment 2 (N = 342), we examined whether reward feedback would inflate participants' trial-by-trial expectations of their own accuracy before each round of the game. Results indicated that participants updated their expectations to a greater extent when a correct response was accompanied with a reward. These findings suggest that rewards enhance how much people integrate accuracy feedback into their dynamic self-beliefs.

Influential models conceive human thinking as an interplay between intuition and deliberation. Yet, it's unclear how people actually perceive these types of reasoning. Across 13 studies (n = 239, 241, 240, 240, 241, 240, 184, 482, 479, 240 and 240 for Studies 1, 2, 3, 4, 5, 6, 7, 10, 11, 12 and 13, respectively), we examined whether humans favor intuition or deliberation and if this replicates in LLMs. Participants rated individuals' reasoning quality in short vignettes that varied by reasoning type (fast-intuitive vs. slow-deliberative) and past accuracy (high, low, unspecified). Consistently, participants rated deliberative reasoning as superior to intuition, even when accounting for accuracy. Deliberative thinkers were seen as smarter and more trustworthy-a preference that held under time pressure and cognitive load, suggesting it arises intuitively. Studies with LLMs (ChatGPT 3.5 and 4) replicated the human preference pattern, indicating that AI language models capture human folk beliefs about reasoning. These findings suggest humans intuitively link deliberation with reliability and have implications for public trust in human and AI recommendations.

Anecdotally, excessive risk-taking can be traced back to minor acts that escalated gradually. What leads to risk-taking escalation and why is escalation fast in some individuals, but not in others? Here, over three experiments (N_{Main Experiment} = 160, N_{Validation Experiment} = 35, N_{Control Experiment} = 30), we used Virtual Reality to simulate physical risk by having participants walk on a virtual plank suspended in midair. We demonstrate that with repeated opportunities to engage in such risk, emotional responses habituate and risk-taking escalates. The rate of escalation differed dramatically across individuals. We found no credible evidence that individuals' baseline emotions or trait anxiety predicted risk escalation. Instead, the key was how fast anxiety and excitement declined. Individuals who reported faster reduction of anxiety or excitement tended to take more risk over time. The findings may help to identify individuals prone to risk-taking escalation and to develop tools that restore emotions to reduce fatal risk-taking.

The nature of self-awareness has been a topic of inquiry for thousands of years, with profound implications for law and ethics, as well as for understanding a host of neurological and psychiatric pathologies. An influential view in philosophy of mind is that the "self" is a construct of consciousness, its basic functions - such as the sense of agency, the capacity by which we attribute sensory events to our own control - cease when they fall out of awareness. An alternative view is that some core processes that constitute the self can operate outside of awareness, and self-awareness arises when these extant processes become contents of consciousness. We aimed to test between these views empirically by investigating whether intentional binding - an implicit marker of sense of agency in which the perceived time of an action is shifted toward its sensory outcome - occurs even when the outcome is masked from conscious awareness. To our surprise, the intentional binding effect was not just abolished when participants were unaware of their actions' sensory outcomes but appeared to be reversed; the perceived time of the action was repelled from the time of its unconsciously perceived consequence. Results demonstrate that the intentional binding effect, and by extension ordinary processing of sensorimotor contingencies, is functionally dependent upon conscious awareness.