Psychological review最新文献

{"title":"As different as fear and anxiety: Introducing the fear and anxiety model of placebo hypoalgesia and nocebo hyperalgesia.","authors":"Daryna Rubanets, Julia Badzińska, Sofiia Honcharova, Przemysław Bąbel, Elżbieta A Bajcar","doi":"10.1037/rev0000521","DOIUrl":"10.1037/rev0000521","url":null,"abstract":"<p><p>Research suggests that negative affective states, such as fear and anxiety that accompany placebo treatment may be considered predictors of placebo hypoalgesia and nocebo hyperalgesia. There is also data showing that the likelihood of developing nocebo hyperalgesia is related to the relatively stable tendency to experience these negative emotions. We aimed to summarize the current state-of-the-art in studies and theoretical models on the role of fear and anxiety in placebo hypoalgesia/nocebo hyperalgesia, with a clear differentiation between these emotions. The role of fear and anxiety accompanying placebo treatment in shaping placebo effects is often studied, but less attention has been given to pretreatment emotional states. We propose a model that combines knowledge from the emotional and pain paradigms with the current research on placebo hypoalgesia and nocebo hyperalgesia to present the involvement of fear and anxiety as traits, as well as pretreatment and posttreatment states of fear and anxiety to placebo effects. The main assumption of the model is that trait fear, trait anxiety, and related pretreatment affective states impact pain perception differently. Heightened fear is associated with decreased pain perception, while heightened anxiety is linked to increased pain perception. Consequently, heightened pretreatment fear may lead to reduced nocebo hyperalgesia and enhanced placebo hypoalgesia, while heightened pretreatment anxiety may result in decreased placebo hypoalgesia and increased nocebo hyperalgesia. In conclusion, we propose future research directions and clinical applications of the model. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"488-504"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142932153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What causes social class disparities in education? The role of the mismatches between academic contexts and working-class socialization contexts and how the effects of these mismatches are explained.","authors":"Sébastien Goudeau, Nicole M Stephens, Hazel R Markus, Céline Darnon, Jean-Claude Croizet, Andrei Cimpian","doi":"10.1037/rev0000473","DOIUrl":"10.1037/rev0000473","url":null,"abstract":"<p><p>Within psychology, the underachievement of students from working-class backgrounds has often been explained as a product of individual characteristics such as a lack of intelligence or motivation. Here, we propose an integrated model illustrating how <i>educational contexts</i> contribute to social class disparities in education over and beyond individual characteristics. According to this new <i>Social Class-Academic Contexts Mismatch model,</i> social class disparities in education are due to several mismatches between the experiences that students from working-class backgrounds bring with them to the classroom and those valued in academic contexts-specifically, mismatches between (a) academic contexts' culture of independence and the working-class orientation to interdependence, (b) academic contexts' culture of competition and the working-class orientation toward cooperation, (c) the knowledge valued in academic contexts and the knowledge developed through working-class socialization, and (d) the social identities valued in academic contexts and the negatively stereotyped social identities of students from working-class backgrounds. Because of these mismatches, students from working-class backgrounds are likely to experience discomfort and difficulty in the classroom. We further propose that, when attempting to make sense of these <i>first-order effects,</i> students and teachers rely on inherent characteristics (e.g., ability, motivation) more often than warranted; conversely, they overlook extrinsic, contextual factors. In turn, this explanatory bias toward inherent features leads (a) students from working-class backgrounds to experience self-threat and (b) their teachers to treat them unfairly. These <i>second-order effects</i> magnify social class disparities in education. This integrated model has the potential to reshape research and discourse on social class and education. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"380-403"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How does depressive cognition develop? A state-dependent network model of predictive processing.","authors":"Nathaniel Hutchinson-Wong, Paul Glue, Divya Adhia, Dirk de Ridder","doi":"10.1037/rev0000512","DOIUrl":"10.1037/rev0000512","url":null,"abstract":"<p><p>Depression is vastly heterogeneous in its symptoms, neuroimaging data, and treatment responses. As such, describing how it develops at the network level has been notoriously difficult. In an attempt to overcome this issue, a theoretical \"negative prediction mechanism\" is proposed. Here, eight key brain regions are connected in a transient, state-dependent, core network of pathological communication that could facilitate the development of depressive cognition. In the context of predictive processing, it is suggested that this mechanism is activated as a response to negative/adverse stimuli in the external and/or internal environment that exceed a vulnerable individual's capacity for cognitive appraisal. Specifically, repeated activation across this network is proposed to update an individual's brain so that it increasingly predicts and reinforces negative experiences over time-pushing an individual at-risk for or suffering from depression deeper into mental illness. Within this, the negative prediction mechanism is poised to explain various aspects of prognostic outcome, describing how depression might ebb and flow over multiple timescales in a dynamically changing, complex environment. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"442-469"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142627180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to \"Levels of analysis and explanatory progress in psychology: Integrating frameworks from biology and cognitive science for a more comprehensive science of the mind\" by Al-Shawaf (2024).","authors":"","doi":"10.1037/rev0000482","DOIUrl":"10.1037/rev0000482","url":null,"abstract":"<p><p>Reports an error in \"Levels of analysis and explanatory progress in psychology: Integrating frameworks from biology and cognitive science for a more comprehensive science of the mind\" by Laith Al-Shawaf (<i>Psychological Review</i>, Advanced Online Publication, Jan 22, 2024, np). Incorrect italic formatting was removed throughout the article, and an unnecessary paragraph of text was removed from the \"Levels of Analysis and the Branches of Psychology: What Is Needed for a Complete Explanation of a Behavior or Cognitive System?\" section. These were editorial production errors. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2024-45670-001.) Levels of analysis are crucial to the progress of science. They frame the epistemological boundaries of a discipline, chart its explanatory goals, help scientists to avoid needless conflict, and highlight knowledge gaps. Two frameworks in particular, <i>Tinbergen's four questions</i> from biology and <i>Marr's three levels</i> from cognitive science, hold immense potential for psychology. This article proposes ways to integrate the two frameworks and suggests that doing so helps resolve key confusions and unnecessary conflicts in psychology. Integrating these two frameworks clarifies what \"mechanism\" really means, sheds light on how to test evolutionary hypotheses in psychology, and specifies what is required for a comprehensive explanation of a behavior or cognitive system. Adopting and integrating these two theoretical frameworks has the capacity to spur progress in psychology and to clarify what is needed for a comprehensive science of the mind. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"415"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140132397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward a generative model for emotion dynamics.","authors":"Oisín Ryan, Fabian Dablander, Jonas M B Haslbeck","doi":"10.1037/rev0000513","DOIUrl":"https://doi.org/10.1037/rev0000513","url":null,"abstract":"<p><p>Most theories of emotion suggest that emotions are reactions to situations we encounter in daily life. Process theories of emotion further specify a feedback loop between our environment, attention, emotions, and action that clarifies the adaptive nature of emotions. In principle, such process theories describe how emotions develop in daily life, and consequently, emotion measures collected from individuals many times a day in studies using the experience sampling methodology should be highly useful in advancing these theories. However, current emotion theories are predominantly verbal theories and therefore do not make clear predictions about such data. In this article, we take a first step toward a generative model of emotion dynamics by formalizing the link between situations and emotions, which provides us with a basic generative model of emotions in daily life. We show that this incomplete model already reproduces nine empirical phenomena in emotion time series related to (temporal) statistical associations between emotions and their distributional form. We then discuss how we can draw on existing (process) theories of emotion to extend our basic model into a complete generative model of emotion dynamics. Finally, we discuss how generative models of emotion dynamics can facilitate theory development and advance measurement, study design, and statistical analysis. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":"132 2","pages":"416-441"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143731475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Networks of beliefs: An integrative theory of individual- and social-level belief dynamics.","authors":"Jonas Dalege, Mirta Galesic, Henrik Olsson","doi":"10.1037/rev0000494","DOIUrl":"10.1037/rev0000494","url":null,"abstract":"<p><p>We present a theory of belief dynamics that explains the interplay between internal beliefs in people's minds and beliefs of others in their external social environments. The networks of belief theory goes beyond existing theories of belief dynamics in three ways. First, it provides an explicit connection between belief networks in individual minds and belief dynamics on social networks. The connection, absent from most previous theories, is established through people's social beliefs or perceived beliefs of others. Second, the theory recognizes that the correspondence between social beliefs and others' actual beliefs can be imperfect, because social beliefs are affected by personal beliefs as well as by the actual beliefs of others. Past theories of belief dynamics on social networks do not distinguish between perceived and actual beliefs of others. Third, the theory explains diverse belief dynamics phenomena parsimoniously through the differences in attention and the resulting felt dissonances in personal, social, and external parts of belief networks. We implement our theoretical assumptions in a computational model within a statistical physics framework and derive model predictions. We find support for our theoretical assumptions and model predictions in two large survey studies (<i>N</i>₁ = 973, <i>N</i>₂ = 669). We then derive insights about diverse phenomena related to belief dynamics, including group consensus and polarization, group radicalization, minority influence, and different empirically observed belief distributions. We discuss how the theory goes beyond different existing models of belief dynamics and outline promising directions for future research. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"253-290"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-decision time: The Higgs Boson of decision.","authors":"Aline Bompas, Petroc Sumner, Craig Hedge","doi":"10.1037/rev0000487","DOIUrl":"10.1037/rev0000487","url":null,"abstract":"<p><p>Generative models of decision now permeate all subfields of psychology, cognitive, and clinical neuroscience. To successfully investigate decision mechanisms from behavior, it is necessary to assume the presence of delays prior and after the decision process itself. However, directly observing this \"non-decision time (NDT)\" from behavior long appeared beyond reach, the field mainly relying on models to estimate it. Here, we propose a biological definition of decision that includes perceptual discrimination and action selection, and in turn, explicitly equates NDT with the minimum sensorimotor delay, or \"deadtime.\" We show how this delay is directly observable in behavioral data, without modeling assumptions, using the visual interference approach. We apply this approach to 11 novel and archival data sets from humans and monkeys gathered from multiple labs. We validate the method by showing that visual properties (brightness, color, size) consistently affect empirically measured visuomotor deadtime (VMDT), as predicted by neurophysiology. We then show that endogenous factors (strategic slowing, attention) do not affect VMDT. Therefore, VMDT consistently satisfies widespread selective influence assumptions, in contrast to NDT parameters from model fits. Last, contrasting empirically observed VMDT with NDT estimates from the EZ, drift diffusion, and linear ballistic accumulator models, we conclude that NDT parameters from these models are unlikely to consistently reflect visuomotor delays, neither at a group level nor for individual differences, in contrast to a widely held assumption. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"330-363"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141591170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"True and false recognition in MINERVA2: Integrating fuzzy-trace theory and computational memory modeling.","authors":"Minyu Chang, Brendan T Johns, Charles J Brainerd","doi":"10.1037/rev0000541","DOIUrl":"https://doi.org/10.1037/rev0000541","url":null,"abstract":"<p><p>Previous research suggests that the MINERVA2 model can capture basic Deese/Roediger/McDermott (DRM) false recognition findings with either randomized representations or distributional semantic representations. In the current article, we extended this line of research by showing that MINERVA2 can accommodate not only basic DRM recognition findings but also the effects of various theory-driven manipulations. Importantly, we incorporated two assumptions of fuzzy-trace theory into MINERVA2: the verbatim-gist distinction and hierarchies of gist. To implement the verbatim-gist distinction, we represented local gist traces with distributional semantic vectors and verbatim traces with holographic word-form vectors. With separate representations incorporated, MINERVA2 successfully simulated a wide range of empirical effects in the DRM illusion, as well as remember/know and source judgments. To incorporate hierarchies of gist into the framework, we added an assumption that an item's storage quality depends on its semantic similarity to the preceding item. This accommodated the effect of global gist beyond that of local gist and solved the problem of storage independence in multitrace models of episodic memory. Our findings provided extensive evidence that MINERVA2 is a viable candidate for scalable modeling of the DRM illusion and strengthened the connection between computational modeling and substantive theories of false memory. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143524201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences in learning across the lifespan emerge via resource-rational computations.","authors":"Rasmus Bruckner, Matthew R Nassar, Shu-Chen Li, Ben Eppinger","doi":"10.1037/rev0000526","DOIUrl":"https://doi.org/10.1037/rev0000526","url":null,"abstract":"<p><p>Learning accurate beliefs about the world is computationally demanding but critical for adaptive behavior across the lifespan. Here, we build on an established framework formalizing learning as predictive inference and examine the possibility that age differences in learning emerge from efficient computations that consider available cognitive resources differing across the lifespan. In our resource-rational model, beliefs are updated through a sampling process that stops after reaching a criterion level of accuracy. The sampling process navigates a trade-off between belief accuracy and computational cost, with more samples favoring belief accuracy and fewer samples minimizing costs. When cognitive resources are limited or costly, a maximization of the accuracy-cost ratio requires a more frugal sampling policy, which leads to systematically biased beliefs. Data from two lifespan studies (<i>N</i> = 129 and <i>N</i> = 90) and one study in younger adults (<i>N</i> = 94) show that children and older adults display biases characteristic of a more frugal sampling policy. This is reflected in (a) more frequent perseveration when participants are required to update from previous beliefs and (b) a stronger anchoring bias when updating beliefs from an externally generated value. These results are qualitatively consistent with simulated predictions of our resource-rational model, corroborating the assumption that the identified biases originate from sampling. Our model and results provide a unifying perspective on perseverative and anchoring biases, show that they can jointly emerge from efficient belief-updating computations, and suggest that resource-rational adjustments of sampling computations can explain age-related changes in adaptive learning. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143524198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical learning subserves a higher purpose: Novelty detection in an information foraging system.","authors":"Ram Frost, Louisa Bogaerts, Arthur G Samuel, James S Magnuson, Lori L Holt, Morten H Christiansen","doi":"10.1037/rev0000547","DOIUrl":"10.1037/rev0000547","url":null,"abstract":"<p><p>Statistical learning (SL) is typically assumed to be a core mechanism by which organisms learn covarying structures and recurrent patterns in the environment, with the main purpose of facilitating processing of expected events. Within this theoretical framework, the environment is viewed as relatively stable, and SL \"captures\" the regularities therein through implicit unsupervised learning by mere exposure. Focusing primarily on language-the domain in which SL theory has been most influential-we review evidence that the environment is far from fixed: It is dynamic, in continual flux, and learners are far from passive absorbers of regularities; they interact with their environments, thereby selecting and even altering the patterns they learn from. We therefore argue for an alternative cognitive architecture, where SL serves as a subcomponent of an <i>information foraging</i> (IF) system. IF aims to detect and assimilate novel recurrent patterns in the input that deviate from randomness, for which SL supplies a baseline. The broad implications of this viewpoint and their relevance to recent debates in cognitive neuroscience are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}