Perspectives on Psychological Science最新文献

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.

In psychological research, noise is often considered a nuisance that obscures rather than contributes information. This simplification overlooks that noise can be informative and that by exploring the nature of the noise one can often draw additional conclusions concerning the underlying psychological processes. It is arguably only in recent years that the mainstream of researchers has taken this idea to heart and demonstrated that it can lead to breakthroughs in the understanding of human behavior. The aim of this special section is to showcase some of the ways in which systematic exploration of noise can be achieved and how it can enrich psychological research. In this introductory article, we introduce the idea of treating noise as endogenous as opposed to exogenous to the theoretical and statistical models of psychological phenomena. We then contribute a historical review of the role of noise in psychological research, including discussions of previous endogenous treatments of noise in the literature. As an illustration, we describe our own research on the precise/not precise model and show how noise distributions can be used to delineate analytic and intuitive modes of reasoning. Finally, we briefly introduce the other contributions to this special section.

In the present age of unprecedented access to information, it is important to understand how and why people avoid information. Multiple definitions of "information avoidance" exist, and key aspects of these definitions deserve attention, such as distinguishing information avoidance from (lack of) information seeking, considering the intentionality and temporal nature of information avoidance, and considering the personal relevance of the information. In this review, we provide a cross-disciplinary historical account of theories and empirical research on information avoidance and seeking, drawing from research in multiple fields. We provide a framework of antecedents of information avoidance, categorized into beliefs about the information (e.g., risk perceptions), beliefs about oneself (e.g., coping resources), and social and situational factors (e.g., social norms), noting that constructs across categories overlap and are intertwined. We suggest that research is needed on both positive and negative consequences of information avoidance and on interventions to reduce information avoidance (when appropriate). Research is also needed to better understand temporal dynamics of information avoidance and how it manifests in everyday life. Finally, comprehensive theoretical models are needed that differentiate avoidance from seeking. Research on information avoidance is quickly expanding, and the topic will only grow in importance.

Many new technologies, such as smartphones, computers, or public-access systems (like ticket-vending machines), are a challenge for older adults. One feature that these technologies have in common is that they involve underlying, partially observable, structures (state spaces) that determine the actions that are necessary to reach a certain goal (e.g., to move from one menu to another, to change a function, or to activate a new service). In this work we provide a theoretical, neurocomputational account to explain these behavioral difficulties in older adults. Based on recent findings from age-comparative computational- and cognitive-neuroscience studies, we propose that age-related impairments in complex goal-directed behavior result from an underlying deficit in the representation of state spaces of cognitive tasks. Furthermore, we suggest that these age-related deficits in adaptive decision-making are due to impoverished neural representations in the orbitofrontal cortex and hippocampus.

Research on aggression usually aims at gaining a better understanding of its more negative aspects, such as the role and effects of aversive social interactions, hostile cognitions, or negative affect. However, there are conditions under which an act of aggression can elicit a positive affective response, even among the most nonviolent of individuals. One might experience the "sweetness of revenge" on reacting aggressively to a betrayal or social rejection. A soldier may feel elated after "shooting to kill" in the name of the flag. There are many factors that contribute to the appeal of aggression, but despite growing interest in researching these phenomena, there is still no unitary framework that organizes existing theories and empirical findings and can be applied to a model to generate testable hypotheses. This article presents a narrative review of the literature on positive-affect-related forms of aggression and explores the role of aggression in eliciting positive affect across diverse social situations and relational contexts. An integrative model that unifies existing theories and findings is proposed, with the objective to inspire and inform future research.

Psychologists address social-justice problems in their research and applied work, and their scholarly efforts have been influenced by assumptions, constructs, and hypotheses from the political left. Recently, some psychologists have called for increased intellectual and political diversity in psychology, particularly as such diversity may lead to improved problem-solving. As an attempt to increase intellectual diversity in psychology, we review here the scholarship of Thomas Sowell. His work represents a rich source of hypotheses for psychologists' future research. We focus on his views on the importance of freedom; the extent to which reforms can reduce freedom; the importance of free markets to human flourishing; the role of free markets in producing costs for discrimination; the way spontaneously ordered systems can contain knowledge that can be overlooked in reforms; and the importance of culture and cultural capital. We will also discuss Sowell's more thoroughgoing economic analyses of problems and solutions and his analyses of contingencies operating on politicians and reformers, as well as his views on conflicts in fundamental visions about human nature and the pivotal role of improvements in minority education.