Perspectives on Psychological Science最新文献

The ongoing debate between basic emotion theories (BETs) and the theory of constructed emotion (TCE) hampers progress in the field of emotion research. Providing a new perspective, here we aim to bring the theories closer together by dissecting them according to Tinbergen's four questions to clarify a focus on their evolutionary basis. On the basis of our review of the literature, we conclude that whereas BETs focus on the evolution question of Tinbergen, the TCE is more concerned with the causation of emotion. On the survival value of emotions both theories largely agree: to provide the best reaction in specific situations. Evidence is converging on the evolutionary history of emotions but is still limited for both theories-research within both frameworks focuses heavily on the causation. We conclude that BETs and the TCE explain two different phenomena: emotion and feeling. Therefore, they seem irreconcilable but possibly supplementary for explaining and investigating the evolution of emotion-especially considering their similar answer to the question of survival value. Last, this article further highlights the importance of carefully describing what aspect of emotion is being discussed or studied. Only then can evidence be interpreted to converge toward explaining emotion.

Some studies show that living conditions, such as economy, gender equality, and education, are associated with the magnitude of psychological sex differences. We systematically and quantitatively reviewed 54 articles and conducted new analyses on 27 meta-analyses and large-scale studies to investigate the association between living conditions and psychological sex differences. We found that sex differences in personality, verbal abilities, episodic memory, and negative emotions are more pronounced in countries with higher living conditions. In contrast, sex differences in sexual behavior, partner preferences, and math are smaller in countries with higher living conditions. We also observed that economic indicators of living conditions, such as gross domestic product, are most sensitive in predicting the magnitude of sex differences. Taken together, results indicate that more sex differences are larger, rather than smaller, in countries with higher living conditions. It should therefore be expected that the magnitude of most psychological sex differences will remain unchanged or become more pronounced with improvements in living conditions, such as economy, gender equality, and education.

Noise in behavior is often considered a nuisance: Although the mind aims for the best possible action, it is let down by unreliability in the sensory and response systems. Researchers often represent noise as additive, Gaussian, and independent. Yet a careful look at behavioral noise reveals a rich structure that defies easy explanation. First, in both perceptual and preferential judgments sensory and response noise may potentially play only minor roles, with most noise arising in the cognitive computations. Second, the functional form of the noise is both non-Gaussian and nonindependent, with the distribution of noise being better characterized as heavy-tailed and as having substantial long-range autocorrelations. It is possible that this structure results from brains that are, for some reason, bedeviled by a fundamental design flaw, albeit one with intriguingly distinctive characteristics. Alternatively, noise might not be a bug but a feature. Specifically, we propose that the brain approximates probabilistic inference with a local sampling algorithm, one using randomness to drive its exploration of alternative hypotheses. Reframing cognition in this way explains the rich structure of noise and leads to the surprising conclusion that noise is not a symptom of cognitive malfunction but plays a central role in underpinning human intelligence.

People often categorize the same object variably over time. Such intraindividual behavioral variability is difficult to identify because it can be confused with a bias and can originate in different categorization steps. The current work discusses possible sources of behavioral variability in categorization, focusing on perceptual and cognitive processes, and reports a simulation with a similarity-based categorization model to disentangle these sources. The simulation showed that noise during perceptual or cognitive processes led to considerable misestimations of a response determinism parameter. Category responses could not identify the source of the behavioral variability because different forms of noise led to similar response patterns. However, continuous model predictions could identify the noise: Noisy feature perception led to variable predictions for central stimuli on the category boundary, noisy feature attention increased the prediction variability for stimuli differing from each category on another feature, and noisy similarity computation increased the variability for stimuli with moderate predictions. Measuring category beliefs in a continuous way (e.g., through category probability judgments) may therefore help to disentangle perceptual and process-related sources of behavioral variability. Ultimately, this can inform interventions aimed at improving human categorizations (e.g., diagnosis training) by indicating which steps of the categorization mechanism to target.

In education, the term "gamification" refers to of the use of game-design elements and gaming experiences in the learning processes to enhance learners' motivation and engagement. Despite researchers' efforts to evaluate the impact of gamification in educational settings, several methodological drawbacks are still present. Indeed, the number of studies with high methodological rigor is reduced and, consequently, so are the reliability of results. In this work, we identified the key concepts explaining the methodological issues in the use of gamification in learning and education, and we exploited the controverses identified in the extant literature. Our final goal was to set up a checklist protocol that will facilitate the design of more rigorous studies in the gamified-learning framework. The checklist suggests potential moderators explaining the link between gamification, learning, and education identified by recent reviews, systematic reviews, and meta-analyses: study design, theory foundations, personalization, motivation and engagement, game elements, game design, and learning outcomes.

A considerable amount of experimental research has been devoted to uncovering biased forms of reasoning. Notwithstanding the richness and overall empirical soundness of the bias research, the field can be described as disjointed, incomplete, and undertheorized. In this article, we seek to address this disconnect by offering "coherence-based reasoning" as a parsimonious theoretical framework that explains a sizable number of important deviations from normative forms of reasoning. Represented in connectionist networks and processed through constraint-satisfaction processing, coherence-based reasoning serves as a ubiquitous, essential, and overwhelmingly adaptive apparatus in people's mental toolbox. This adaptive process, however, can readily be overrun by bias when the network is dominated by nodes or links that are incorrect, overweighted, or otherwise nonnormative. We apply this framework to explain a variety of well-established biased forms of reasoning, including confirmation bias, the halo effect, stereotype spillovers, hindsight bias, motivated reasoning, emotion-driven reasoning, ideological reasoning, and more.

Chaotic responses to COVID-19, political polarization, and pervasive misinformation raise the question of whether some or many individuals exercise irrational moral judgment. We provide the first mathematically correct test for transitivity of moral preferences. Transitivity is the most prominent rationality criterion of the behavioral, biological, and economic sciences. However, transitivity is conceptually, mathematically, and statistically difficult to evaluate empirically. We tested three parsimonious, order-constrained, probabilistic characterizations: First, the weak utility model treats an individual's choices as noisy reflections of a single, deterministic, underlying transitive preference; second, a variant severely limits the allowable response noise; and third, by the general random utility hypothesis, individuals' choices reveal uncertain, but transitive, moral preferences. Among 28 individuals, everyone's data were consistent with the weak utility model and general random utility model, thus supporting both operationalizations. Tightening the bounds on error rates in noisy responses yielded a poorly performing model, thus rejecting the model according to which choices are highly consistent with a single transitive preference. Bayesian model selection favored probabilistic transitive preferences and hence the equivalent random utility hypothesis. This suggests that there is some order underlying the apparent chaos: Rather than presume widespread disregard for moral principles, policymakers may build on navigating and reconciling extreme heterogeneity compounded with individual uncertainty.

There has been slow progress in the development of interventions that prevent and/or reduce mental-health morbidity and mortality. The National Institute of Mental Health (NIMH) launched an experimental-therapeutics initiative with the goal of accelerating the development of effective interventions. The emphasis is on interventions designed to engage a target mechanism. A target mechanism is a process (e.g., behavioral, neurobiological) proposed to underlie change in a defined clinical endpoint and through change in which an intervention exerts its effect. This article is based on discussions from an NIMH workshop conducted in February 2020 and subsequent conversations among researchers using this approach. We discuss the components of an experimental-therapeutics approach such as clinical-outcome selection, target definition and measurement, intervention design and selection, and implementation of a team-science strategy. We emphasize the important contributions of different constituencies (e.g., patients, caregivers, providers) in deriving hypotheses about novel target mechanisms. We highlight strategies for target-mechanism identification using published and hypothetical examples. We consider the decision-making dilemmas that arise with different patterns of results in purported mechanisms and clinical outcomes. We end with considerations of the practical challenges of this approach and the implications for future directions of this initiative.