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[Correction Notice: An Erratum for this article was reported in Vol 115(6) of Journal of Personality and Social Psychology (see record 2018-63189-002). In the article, the original supplemental material has been revised to include a clarifying note to the Tests of model fit over larger sample (Samples C-G) section and post-peer review analyses added to the Post-peer review Factor Analytic Tests section. All versions of this article have been corrected.] Philosophers and behavioral scientists refer to wisdom as unbiased reasoning that guides one toward a balance of interests and promotes a good life. However, major instruments developed to test wisdom appear biased, and it is unclear whether they capture balance-related tendencies. We examined whether shifting from global, de-contextualized reports to state-level reports about concrete situations provides a less biased method to assess wise reasoning (e.g., intellectual humility, recognition of uncertainty and change, consideration of the broader context at hand and perspectives of others, integration of these perspectives or compromise), which may be aligned with the notion of balancing interests. Results of a large-scale psychometric investigation (N = 4,463) revealed that the novel Situated WIse Reasoning Scale (SWIS) is reliable and appears independent of psychological biases (attribution bias, bias blind spot, self-deception, and impression management), whereas global wisdom reports are subject to such biases. Moreover, SWIS scores were positively related to indices of living well (e.g., adaptive emotion regulation, mindfulness), and balancing of cooperative and self-protective interests, goals (influence-vs.-adjustment), and causal inferences about conflict (attribution to the self-vs.-other party). In contrast, global wisdom reports were unrelated or negatively related to balance-related measures. Notably, people showed modest within-person consistency in wise reasoning across situations or over time, suggesting that a single-shot measurement may be insufficient for whole understanding of trait-level wisdom. We discuss theoretical and practical implications for research on wisdom, judgment and decision making, well-being, and prosociality. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The open science movement has been gaining steam in numerous scientific disciplines (e.g., ecology, cancer biology, economics) as well as sub-disciplines of psychology (e.g., social, personality). These issues, however, have been scantly discussed in the context of identity research. This presentation will include an overview of core issues in the open science movement and how they apply to research on identity. Emphasis will be placed on how incorporating open science principles can improve both theoretical and empirical work on identity.

This dissertation deals with the problem of modeling psychopathology. Its first part focuses on statistical (data) models and introduces a number of models for cross-sectional and time series data that can be visualized as a network. This includes Mixed Graphical Models (MGMs), which allow one to include variables of different types in a statistical network model, Moderated Network Models (MNMs) which allow pairwise interactions to be moderated by other variables in the model, and time-varying Vector Autoregressive (VAR) models and MGMs that relax the standard assumption of stationarity. In addition, I discuss several methodological issues related to statistical network models such as the importance of considering predictability, model selection between AR and VAR models, and how the interpretation of the Ising model depends on its domain. The second part focuses on formal theories of psychopathology and how to develop them using data models. I first illustrate the fundamental difficulties in obtaining a formal theory with a purely statistical approach, by trying to recover an assumed bistable system for emotion dynamics with currently popular time series analyses. Next, I present a formal theory of panic disorder, based on an extensive review of the literature on the phenomenology of panic disorder and existing theories. Finally, I discuss three different ways to use data models to construct formal theories about psychopathological phenomena. Based on this discussion, I put forward an abductive framework for constructing formal theories for psychological and psychopathological phenomena.

Replicability is widely taken to ground the epistemic authority of science. However, in recent years, important published findings in the social, behavioral, and biomedical sciences have failed to replicate, suggesting that these fields are facing a “replicability crisis.” For philosophers, the crisis should not be taken as bad news but as an opportunity to do work on several fronts, including conceptual analysis, history and philosophy of science, research ethics, and social epistemology. This article introduces philosophers to these discussions. First, I discuss precedents and evidence for the crisis. Second, I discuss methodological, statistical, and social‐structural factors that have contributed to the crisis. Third, I focus on the philosophical issues raised by the crisis. Finally, I discuss several proposals for solutions and highlight the gaps that philosophers could focus on.

The positive manifold of intelligence has fascinated generations of scholars in human ability. In the past century, various formal explanations have been proposed, including the dominant g factor, the revived sampling theory, and the recent multiplier effect model and mutualism model. In this article, we propose a novel idiographic explanation. We formally conceptualize intelligence as evolving networks in which new facts and procedures are wired together during development. The static model, an extension of the Fortuin–Kasteleyn model, provides a parsimonious explanation of the positive manifold and intelligence’s hierarchical factor structure. We show how it can explain the Matthew effect across developmental stages. Finally, we introduce a method for studying growth dynamics. Our truly idiographic approach offers a new view on a century-old construct and ultimately allows the fields of human ability and human learning to coalesce.

Philosophers have been interested in happiness and well-being since the Hellenic period. More recently, psychologists have begun to study how happy people are and what makes people’s lives go well. Today, these fields begin to converge, as philosophers are increasingly interested in empirical approaches and some psychologists use philosophical theories to develop accounts of how to measure well-being and happiness. Yet, are philosophers and psychologists really studying the same concept? In this paper, we answer this question. We describe philosophical accounts of well-being and happiness and their corresponding psychological accounts on six characteristics: (a) temporal dimension (short term vs. long term), (b) degree of stability (trait vs. state), (c) psychological process (affective vs. cognitive), (d) constituent element (internal vs. external), (e) perspective (objective vs. subjective), and (f) theoretical approach (descriptive vs. normative). As a result, we identified three broad groups of theoretical accounts: mental state accounts, flourishing accounts, and multidimensional accounts. This classification highlights similarities and differences among the accounts and allows researchers to assess where philosophical and psychological accounts overlap and where they diverge. We conclude our paper with a discussion of the implications of our new way of integrating philosophical and psychological accounts, and present open questions that should be addressed in future research. Keywords: Happiness, Well-Being, Characteristics, Hedonic and Eudaimonic Well-Being, Life satisfaction, Philosophy of Well-Being

Duration perception is not the same as perception duration. Time is an object of perception in its own right and is qualitatively different to exteroceptive or interoceptive perception of concrete objects or sensations originating within the self. In reviewing evidence for and against the experienced moment, White (2017, Psychol. Bull., 143, 735–756) proposed a model of global integration of information dense envelopes of integration. This is a valuable addition to the literature because it supposes that, like Tononi’s (2004, BMC Neurosci., 5, 42) Integrated Information Theory, consciousness is an integral step above perception of objects or the self. Consciousness includes the perception of abstract contents such as time, space, and magnitude, as well as post-perceptual contents drawn from memory. The present review takes this logic a step further and sketches a potential neurobiological pathway through the salience, default mode, and central executive networks that culminates in a candidate model of how duration perception and consciousness arises. Global integration is viewed as a process of Bayesian Prediction Error Minimisation according to a model put forward by Hohwy, Paton and Palmer (2016, Phenomenol. Cogn. Sci., 15, 315–335) called ‘distrusting the present’. The proposed model also expresses global integration as an intermediate stage between perception and memory that spans an approximate one second duration, an analogue of Wittmann’s (2011, Front. Integr. Neurosci., 5, 66) experienced moment.

We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (Journal of Experimental Psychology: General, 143(4), 1457–1475 2014) for the common t test. This reconceptualization is computationally simpler and generalizes easily to most common experimental designs for which Bayes factors are available.

A majority of statistically educated scientists draw incorrect conclusions based on the most commonly used statistical technique: null hypothesis significance testing (NHST). Frequentist techniques are often claimed to be incorrectly interpreted as Bayesian outcomes, which suggests that a Bayesian framework may fit better to inferences researchers frequently want to make (Briggs, 2012). The current study set out to test this proposition. Firstly, we investigated whether there is a discrepancy between what researchers think they can conclude and what they want to be able to conclude from NHST. Secondly, we investigated to what extent researchers want to incorporate prior study results and their personal beliefs in their statistical inference. Results show the expected discrepancy between what researchers think they can conclude from NHST and what they want to be able to conclude. Furthermore, researchers were interested in incorporating prior study results, but not their personal beliefs, into their statistical inference.

Starting from the view that progress in science consists of the improvement of our theories, in the current paper we ask two questions: what makes a theory good, and how much do the current method-oriented solutions to the replication crisis contribute to the development of good theories? Based on contemporary philosophy of science, we argue that good theories are hard-to-vary: they (1) explain what they are supposed to explain, (2) are consistent with other good theories, and (3) cannot easily be adapted to explain anything. Theories can be improved by identifying problems in them either by argument or by experimental test, and then correcting these problems by changing the theory. Importantly, such changes and the resultant theory should only be assessed based on whether they are hard-to-vary. An assessment of the current state of the behavioral sciences reveals that theory development is arrested by the lack of consideration for how easy it is to change theories to account for unexpected observations. Further, most of the current method-oriented solutions are unlikely to contribute much to the development of good theories, because they do not work towards eliminating this problem. Instead, they reward only temporary inflexibility in theories, and promote the assessment of theory change based on whether the theory was changed before (confirmatory) or after (exploratory) an experimental test, but not whether that change yields a hard-to-vary theory. Finally, we argue that these methodological solutions would become irrelevant if we turned our focus to the explicit aim of developing theories that are hard-to-vary.

Drawing on the philosophy of psychological explanation, we suggest that psychological science, by focusing on effects, may lose sight of its primary explananda: psychological capacities. We revisit Marr’s levels-of-analysis framework, which has been remarkably productive and useful for cognitive psychological explanation. We discuss ways in which Marr’s framework may be extended to other areas of psychology, such as social, developmental, and evolutionary psychology, bringing new benefits to these fields. We then show how theoretical analyses can endow a theory with minimal plausibility even before contact with empirical data: We call this the theoretical cycle. Finally, we explain how our proposal may contribute to addressing critical issues in psychological science, including how to leverage effects to understand capacities better. https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

The finding that intuitions about the reference of proper names vary cross-culturally (Machery et al. Cognition 92: 1–12. 2004) was one of the early milestones in experimental philosophy. Many follow-up studies investigated the scope and magnitude of such cross-cultural effects, but our paper provides the first systematic meta-analysis of studies replicating (Machery et al. Cognition 92: 1–12. 2004). In the light of our results, we assess the existence and significance of cross-cultural effects for intuitions about the reference of proper names.

Psychology is a broad field that endeavors to develop explanatory theories of human capacities and behaviors based on a wide variety of methodologies and dependent measures. Here we argue that whether or not researchers choose to employ modeling (viz., choose to create computational models of their theories over and above their data during the scientific inference process) is one of the most important and divisive factors in our field. Modeling is underdiscussed and underemployed, yet, in our view, holds integrative promise for advancing the goals of psychological science. The inherent demands of computational modeling oer invaluable momentum towards a better, and more open, psychological science. These demands force the scientist to conceptually analyze, specify, and ideally, formalise intuitions and ideas which would otherwise remain implicit or unexamined — something we propose should be called “open theory”. Constraining our inference process through specification and modeling is what will enable us as a field to meaningfully interpret data, and to build theories that explain and predict. In this piece, we present scientific inference in psychology as a path function, where each step shapes the next. Computational modeling can constrain the steps in the path, and has the potential to advance scientific inference over and above the stewardship of the experimental practice (e.g., preregistration, choosing frequentist or Bayesian statistics, power and sample size, and other estimation variables). If as a field we continue to eschew, inadvertently avoid, or remain ignorant of formal and computational modeling, we set ourselves up for a persistent lack of replicability and, moreover, for failure at coherent theory-building that includes explanatory force. We explain how the basic steps in the modeling process can be accomplished and we touch on the cultural and practical issues that need to be faced therein, emphasizing that the advantages of modeling can be achieved by anyone with benefit to all. The process of computational modeling promotes transparent theorising; “open science” should include open theory alongside, e.g., open data and open source code.

Data analysis is a risky endeavor, particularly among those unaware of its dangers. In the words of Cook and Campbell (1976; see also Cook, Campbell, and Shadish 2002), “Statistical Conclusions Validity” threatens all experiments that subject themselves to the dark arts of statistical magic. Although traditional statistics classes may advise against certain practices (e.g., multiple comparisons, small sample sizes, violating normality), they may fail to cover others (e.g., outlier detection and violating linearity). More common, perhaps, is that researchers may fail to remember them. In this paper, rather than rehashing old warnings and diatribes against this practice or that, I instead advocate a general statistical analysis strategy. This graphically-based eight step strategy promises to resolve the majority of statistical traps researchers may fall in without having to remember large lists of problematic statistical practices. These steps will assist in preventing both Type I and Type II errors and yield critical insights about the data that would have otherwise been missed. I conclude with an applied example that shows how the eight steps highlight data problems that would not be detected with standard statistical practices.

A large amount of variation exists in beliefs about the purpose and benefits of preregistration, making it difficult to implement and evaluate, and limiting its usefulness. Additionally, no single resource exists to describe what a preregistration should contain or how it should be used. In this paper, I describe what an effective preregistration should contain and when it should be used. Specifically, preregistration should 1) restrict as many researcher degrees of freedom as possible, 2) detail all aspects of a study’s method and analysis, 3) detail information on decisions made during the planning stages, and 4) specify how the results will be used and interpreted. Further, a preregistration must be publicly verifiable and permanent. Finally, I argue that preregistration should be used in any situation where researchers intend to collect data in order to make a claim, description, decision, or inference based on that data. I also note that preregistrations which do not address each of these points do more harm than good by falsely signalling credibility and quality.

A variety of conceptualizations of psychological uncertaintyexist. From an information-theoretic perspective, probabilistic uncertainty can be formalized as mathematical entropy. Cognitive emotion theories posit that uncertainty appraisals and motivation to reduce uncertainty are modulated by emotional state. Yet little is known about how people evaluate probabilistic uncertainty, and about how emotional state modulates people’s evaluations of probabilistic uncertainty and behavior to reduce probabilistic uncertainty. We tested intuitive entropyevaluations and entropy reduction strategies across four emotion conditions in the Entropy Mastermind game. We used the unified Sharma-Mittal space of entropy measures to quantify participants’ entropy evaluations. Results suggest that many people use a heuristic strategy, focusing on the number of possible outcomes, irrespective of the probabilities in the probability distribution. This result is surprising, given that previous work suggested that people are very sensitive to the maximum probability when choosing queries on probabilistic classification tasks. Emotion induction generally increased participants’heuristic assessment. The uncertainty associated with emotional states also affected game play: participants needed fewer queries and spent less time on games in high-uncertainty than in low-uncertainty emotional states. Yet entropy perceptions were not related to subjectively reported uncertainty, numeracy or entropy knowledge, suggesting that entropy perceptions may form an independent psychological construct.

Psychedelics have a checkered past, alternately venerated as sacred medicines and vilified as narcotics with no medicinal or research value. After decades of international prohibition, a growing dissatisfaction with conventional mental health care and the pioneering work of the Multidisciplinary Association for Psychedelic Science (MAPS) and others has sparked a new wave of psychedelic research. Positive media coverage and new entrepreneurial interest in this potentially lucrative market, along with their attendant conflicts of interest, have accelerated the hype. Given psychedelics’ complex history, it is especially important to proceed with care, holding ourselves to a higher scientific rigor and standard of transparency. Universities and researchers face conflicting interests and perverse incentives, but we can avoid missteps by expecting rigorous and transparent methods in the growing science of psychedelics. This paper provides a pragmatic research checklist and discusses the importance of using the modern research and transparency standards of Open Science using preregistration, open materials and data, reporting constraints on generality, and encouraging replication. We discuss specific steps researchers should take to avoid another replication crisis like those devastating psychology, medicine, and other fields. We end with a discussion of researcher intention and the value of actively deciding to abide by higher scientific standards. We can build a rigorous, transparent, replicable psychedelic science by using Open Science to understand psychedelics’ potential as they re-enter science and society.

We have introduced a common wisdom model to establish a shared language, clarify underlying theoretical assumptions, advance assessment tools, and foster evidence-based interventions for stimulating wisdom during challenging societal times. The common wisdom model synthesizes the views of numerous contemporary scientists working on wisdom and includes two components: perspectival meta-cognition and moral aspirations. Having received insightful commentaries on our model, here we consider the overall motivation for the model, address remaining jingle-jangle fallacies, clarify the meaning of morality for wisdom, and expand upon the relationship between moral and meta-cognitive components within the common wisdom model. We reflect on how the common wisdom model provides a nexus for integrating insights across multiple areas of research, affording plentiful opportunities for future research into wisdom’s development, function, and underlying processes. We situate our reflections in the context of present-day pandemic-related uncertainties and unfolding societal shifts.

Open Science advocates recommend deposit of stimuli, data and code sufficient to support all assertions in a scientific Ms. Most ‘respectable’ journals and funding bodies have endorsed Open Science. i.e. they ‘talk the talk’. Nevertheless, most published Mss. do not ‘walk the walk’ by following the Open Science guidelines. Professional statisticians, e.g. the America Statistical Association, The Royal Statistical Society provide guidance on inferential statistics reporting that proscribes null-hypothesis statistical tests. This guidance is also widely ignored. The purpose of this Ms. is to increase the proportion of Mss. following open science practices by providing guides to transparent reporting that are easily useable by authors and reviewers. The Ms. comprises the guides themselves, already public, and a rationale as to why recommendations have been chosen, together with suggestions to promote open science practices. The guides are unique in including, in a single document, the three main phases for the conduction of replicable science: planning and execution, Ms. generation and publication; and deposit of supplementary materials. A main aim of the Ms. is to subject the guidance and justifications to peer review.

Begin maart kreeg Özcan Akyol de pennen in beweging met zijn polemische boekenweekessay Generaal zonder leger. In dat boekje, voor een deel gebaseerd op eerdere columns van de auteur, trekt Akyol van leer tegen de in zijn ogen elitaire boekenwereld. De opvattingen van de rebelse dwarsdenker verdwenen echter al snel naar de achtergrond door de uitbraak van de coronacrisis. Ook ikzelf liet het boekje na een eerste lectuur al snel liggen om te kunnen wennen aan de quarantaine waarin ons gezin beland was. Deze week nam ik het echter weer eens ter hand en keerde dat gevoel terug dat me ook tijdens de eerste lezing overviel: een bepaalde welwillendheid om het met Akyol eens te zijn, die echter overschaduwd wordt door een onstuitbare ergernis. Hoewel ik principiële sympathie heb voor iedereen die een lans breekt voor een verbreding van de leescultuur en het literatuuronderwijs, is Akyol argumentatief een cowboy met een klappistooltje. Of, om bij de oorlogsmetaforiek uit zijn titel te blijven: een schutter zonder munitie.

Single empirical tests are always ambiguous in their implications for the theory under investigation, because non-corroborative evidence leaves us underdetermined in our decision as to whether the main hypothesis or one or more auxiliary hypotheses should bear the burden of falsification. Methodological falsificationism tries to solve this problem by relegating auxiliary hypotheses that increase the testability of theories to unproblematic background knowledge and disallowing others. However, decisions to accept such auxiliaries as unproblematic are seldom conclusively justified in the social and behavioral sciences, where operationalizations play a central role, but are much less theory-driven and independently testable. Close and conceptual replications are crucial in tackling different aspects of underdetermination, but they fail to serve this purpose when conducted in isolation. To facilitate rational decision-making regarding falsifications, we propose Systematic Replications Framework (SRF) that organizes subsequent tests into a pre-planned series of logically interlinked close and conceptual replications. SRF reduces underdetermination by disentangling the implications of non-corroborative findings for the main hypothesis and the operationalization-related auxiliaries. It also serves as a severe-testing procedure through systematically organized self-replications. SRF will be particularly useful if applied to contested theoretical claims with mixed evidence and realized through adversarial collaboration. We also discuss how applying this framework can scaffold judgments regarding the permissibility of ad hoc hypothesizing in reference to the Lakatosian notions of progressive and degenerative research programs.

About two decades ago, scholars from the scientific disciplines that study human behavior and cognition, suggested an era of post-cognitivism was imminent, in which the computer metaphor, computationalism and representationalism would be discarded as viable theoretical frameworks for explaining phenomena of the body and the mind. In the present paper I argue that explanations of complex adaptive behavior require a theory of meaning mechanics that explains how complex adaptive systems can use semantic information to coordinate their behavior. This calls for a unification of sorts between the insights obtained in ecological psychology and embodied embedded cognition with principles of natural computation (cf. Decastro, 2007) in the context of explaining the behavior and properties of complex adaptive systems and networks (see e.g., Freeman et al., 2001; Chialvo, 2010; Flack, 2017a; Scheffer et al., 2018). I will refer to this framework as Radical Embodied Computation (REC++) and discuss some of the philosophical and theoretical issues that have to be resolved. I conclude by suggesting a mechanism for the emergence of meaning that is based the conception of self-affine scaling as the reproduction of similarity by analogy.

Attribution theorists widely assume that people rely on character assessments to assign blame. But there is disagreement over why. One camp holds that character has a fundamental effect on blame. Another camp holds that character merely provides evidence about the mental states and processes that determine responsibility. We provide empirical evidence for a two-channel view, where character simultaneously has both fundamental and evidential effects on blame. In two large factorial studies (n = 505), participants rate whether someone is blameworthy when he makes a mistake (burns a cake or misses a bus stop). Although mental state inferences predict blame judgments, character assessments do not. Studies 3 and 4 (n = 447) perform a mediation analysis and find that character assessments (about forgetfulness) influence responsibility via two channels, one direct and another indirect. Forgetfulness directly increases judgments of responsibility, presumably because one’s mistakes manifest bad character. But forgetfulness also decreases judgments of state control, which indirectly decreases responsibility judgments. These two channels cancel out, which is why we find no aggregate effect of forgetfulness on responsibility. This is the catch-22 of forgetfulness. Our results challenge several fundamental assumptions in the moral psychology of character, including that good character always decreases blame.

We report the results of a study that investigated the views of researchers working in sevenscientific disciplines and in history and philosophy of science in regard to four hypothesizeddimensions of scientific realism. Among other things, we found (i) that natural scientiststended to express more strongly realist views than social scientists, (ii) that historyand philosophy of science scholars tended to express more antirealist views than naturalscientists, (iii) that van Fraassen’s characterization of scientific realism failed to clusterwith more standard characterizations, and (iv) that those who endorsed the pessimistic inductionwere no more or less likely to endorse antirealism.

Theory of Personal Needs systematizes the relationships between Personal Needs, Feelings, Goods, Services, and Actions that meet these Personal Needs. The postulates of the Theory are a new modern view of the origin of emotions and feelings. The Theory has high validity. Based on the Theory, technologies with real practical results have been created and applied.

General principles of a unified theory of cognition and its relationships with the brainare outlined, integrating insights from several existing theories and approaches. Structure, dynamics, and development of the neural/cognitive system are described. Cognitive Feature Detectors (CFDs) are the fundamental units: they have a (minimalist) semantic value, strictly related to their location in a cognitive space. A cognitivo-neural isomorphism is postulated between CFDs in this cognitive space, and single (or small sets of) neurons in the neural network. The cognitive space is made of two parts (executive and perceptive), densely connected, both hierarchically organized and clustered in cognitive maps. Within maps, inhibitory connections implement competition between incompatible CFDs. This theoretical sketch is hoped to help addressing general theoretical issues such as the relationship between brain and mind, on the basis of the neural localization of cognitive elements.

The topic of synchronicity has long intrigued philosophers, scientists and the general public. Carl Jung formally introduced the term “synchronicity” in the 1950s, however to date very little empirical research has explored the underlying mechanisms of synchronicity. In other words, why do synchronicities occur? Are synchronicities random, or do they hold clues about the ultimate nature of reality? Drawing on theoretical and empirical research, the current paper explores the idea that synchronicity might be one way that the fundamental (i.e., ontologically primary) nature of consciousness reveals itself to us in everyday life, and that contemplative practices such as meditation might be capable of invoking synchronicity. In addition, while several useful theoretical overviews of synchronicity exist, there are very few peer-reviewed academic articles on synchronicity, and even fewer empirical research studies. Therefore a further purpose of this paper is to summarize theoretical perspectives on synchronicity in an attempt to spark a renewed interest in conducting empirical research on this topic. The evidence presented in this paper suggests that consciousness might represent the underlying nature of reality, that contemplative practices might give humans access to this fundamental consciousness, and that synchronicity might be one way that this fundamental consciousness reveals itself to us in everyday life.

Causal inference is a central goal of research. However, most psychologists refrain from explicitly addressing causal research questions and avoid drawing causal inference on the basis of nonexperimental evidence. We argue that this taboo against causal inference in nonexperimental psychology impairs study design and data analysis, holds back cumulative research, leads to a disconnect between original findings and how they are interpreted in subsequent work, and limits the relevance of nonexperimental psychology for policymaking. At the same time, the taboo does not prevent researchers from interpreting findings as causal effects—the inference is simply made implicitly, and assumptions remain unarticulated. Thus, we recommend that nonexperimental psychologists begin to talk openly about causal assumptions and causal effects. Only then can researchers take advantage of recent methodological advances in causal reasoning and analysis and develop a solid understanding of the underlying causal mechanisms that can inform future research, theory, and policymakers.

Lieder and Griffiths rightly urge that computational cognitive models be constrained by resource usage, but they should go further. The brain's primary function is to regulate resource usage. As a consequence, resource usage should not simply select among algorithmic models of “aspects of cognition.” Rather, “aspects of cognition” should be understood as existing in the service of resource management.

Practicality was a valued attribute of academic psychological theory during its initial decades, but usefulness has since faded in importance to the field. Theories are now evaluated mainly on their ability to account for decontextualized laboratory data and not their ability to help solve societal problems. With laudable exceptions in the clinical, intergroup, and health domains, most psychological theories have little relevance to people’s everyday lives, poor accessibility to policymakers, or even applicability to the work of other academics who are better positioned to translate the theories to the practical realm. We refer to the lack of relevance, accessibility, and applicability of psychological theory to the rest of society as the practicality crisis. The practicality crisis harms the field in its ability to attract the next generation of scholars and maintain viability at the national level. We describe the practicality crisis and its effects on the field using theories of self-control as an illustrative case example. Psychology is historically and scientifically well positioned to become useful should scholars in the field decide to value practicality. We offer a set of principles to return social psychology to the Lewinian vision of a useful science that speaks to pressing social issues.

In the face of unreplicable results, statistical anomalies, and outright fraud, introspection and changes in the psychological sciences have taken root. Vibrant reform and meta-science movements have emerged. These are exciting developments, and may point towards practical improvements in the future. Yet there is nothing so practical as good theory. This paper outlines aspects of reform and meta-science in psychology that are ripe for an injection of theory, including a lot of excellent and overlooked theoretical work from different disciplines. I review established frameworks that model the process of scientific discovery, the types of scientific networks that we ought to aspire to, and the processes by which problematic norms and institutions might evolve, focusing especially on modeling from the philosophy of science and cultural evolution. We have unwittingly evolved a toxic scientific ecosystem; existing interdisciplinary theory may help us intelligently design a better one. Unpaywalled print at https://psyarxiv.com/jcs6e/

The study of the evolution of brain-behavior relationships concerns understanding the causes and repercussions of cross- and within-species variability. Understanding such variability is a main objective of evolutionary and cognitive neuroscience, and it may help explaining the appearance of psychopathological phenotypes. Although the brain evolution is related to the progressive action of selection and adaptation through multiple paths (e.g., mosaic vs. concerted evolution, metabolic vs. structural and functional constraints), a coherent, integrative framework is needed to combine evolutionary paths and neuroscientific evidence. Here, we review the literature on evolutionary pressures focusing on structural-functional changes and developmental constraints. Taking advantage of progresses in neuroimaging and cognitive neuroscience, we propose a twofold model of brain evolution. Within this model, global and local trajectories imply rearrangements of neural subunits and subsystems as well as of behavioral repertoires of a species, respectively. We incorporate these two processes in a game in which the global trajectory shapes the structural-functional neural substrates (i.e., players), while the local trajectory shapes the behavioral repertoires (i.e., stochastic payoffs).

Temporality is a foundational topic in phenomenological psychopathology, and it plays an especially important role in its analysis of depression and melancholia (e.g., Fuchs, 2001; Fuchs, 2013; Gallagher, 2012; Ratcliffe, 2015). An intuitive strategy is to explain abnormal experiences of time by appealing to a fundamental disruption of the temporal structure of consciousness, yet Lenzo and Gallagher (this volume) highlight that this strategy is problematic.

This paper aims to improve theory formation in psychology by developing a practical methodology for constructing explanatory theories: Theory Construction Methodology (TCM). TCM is a sequence of five steps. First, the theorist identifies empirical phenomena to become the target of explanation. Second, the theorist constructs a proto-theory: a set of theoretical principles that potentially explain these phenomena. Third, the proto-theory is used to construct a formal model: a set of model equations or simulation models that encode the explanatory principles. Fourth, the theorist investigates this model’s explanatory adequacy. This is done by formalizing the empirical phenomena in terms of the model, and assessing whether the model indeed reproduces them. Fifth, the theorist studies the overall adequacy of the theory by evaluating whether phenomena are indeed reproduced faithfully, whether explanatory principles are parsimonious and substantively plausible, and whether the theory implies new predictions to promote further research. We illustrate TCM with an example taken from the intelligence literature (the mutualism model of intelligence), discuss the place of TCM in the larger scheme of scientific research, and propose an outline for a university curriculum that can systematically educate psychologists in the process of theory formation.

A team of 37 researchers (Many Labs 4; Klein et al., 2019) has recently reported that it has failed to replicate the effect of mortality salience on worldview defense – a classic finding from terror management theory (TMT). This collaborative project (21 labs, N = 2220) has the potential to provide useful information regarding the robustness of an often-replicated and influential empirical finding. However, Klein et al. (2019) deviated from their preregistered plan by including smaller samples than specified in their pre-registration. This undisclosed deviation from their plan is problematic because it undermines the potential benefits of pre-registration; indeed, the negative results of their meta-analyses appear to be predominantly driven by small studies. We reanalyzed the Many Labs 4 data after excluding studies that did not meet the preregistered minimum sample size (40 participants per cell). Results showed that the data actually do replicate the original study. This successful replication emerged only in the expert advice variation of these studies, which addresses one of the purposes of this study by showing that replication is more likely to occur when researchers follow the advice of researchers with considerable experience in this domain. We discuss the importance of following preregistered plans to avoid misleading conclusions and potential issues involved with literal replications of effects that may depend on societal zeitgeist at the time data are collected.

The last decade has brought reforms to improve methodological practices, with the goal to increase the reliability and replicability of effects. However, explanations of effects remain scarce, and a growing chorus of scholars argues that the replicability crisis has distracted from a crisis of theory. In the same decade, the empirical literature using factor and network models has grown rapidly. I discuss three ways in which this literature falls short of theory building and testing. First, statistical and theoretical models are conflated, leading to invalid inferences such as the existence of psychological constructs based on factor models, or recommendations for clinical interventions based on network models. I demonstrate this inferential gap in a simulation study on statistical equivalence: excellent model fit does little to corroborate a theory, regardless of quality or quantity of data. Second, researchers fail to explicate theories about psychological constructs, but use implicit causal beliefs to guide inferences. These latent theories have led to problematic best practices in psychological research where inferences are drawn based on one specific causal model that is assumed, but not explicated. Third, explicated theories are often weak theories: narrative and imprecise descriptions vulnerable to hidden assumptions and unknowns. They fail to make clear predictions, and it remains unclear whether statistical effects corroborate such theories or not. Weak theories are immune to refutation or revision. I argue that these three challenges to theory building and testing are common and harmful, and impede theory formation, failure, and reform. A renewed focus on theoretical psychology and formal models offers a way forward.

Classic perspectives on mindfulness emphasize engagement with life’s challenges. In contrast, contemporary mainstream approaches to mindfulness in psychology chiefly focus on stress reduction. We contrast classic and contemporary approaches, outlining conceptual and methodological shortcomings of mindfulness research. Existing mindfulness measures fail to adequately capture engagement or relief aspects of the construct due to assessment primarily through negatively-worded items, discordant definitions, confusion of outcomes with processes, and a lack of contextual sensitivity. Empirical evidence shows that the dimensions of mindfulness are not only negatively correlated with each other, but also with variables they should be similarly linked to. Further, modern measures of mindfulness are positively related to outcomes that are antithetical to mindfulness-as-engagement (e.g., emotional suppression), suggesting that current measures may be biased towards relief rather than engagement outcomes. We outline several ways to overcome conceptual and methodological challenges, highlighting the need for a deeper understanding of classic contemplative roots of mindfulness and a rigorous psychometric and culturally-sensitive analysis, in hopes to guide researchers towards capturing mindfulness as a regulatory process that involves actively working through life’s challenges.

Human cognition is characterized by its complexity and multidimensionality. Adaptive and appropriate behavior in the here and now requires a system which integrates sensorimotor information from multiple modalities, the individual’s personal experience, and possible future events. Nevertheless, measuring such complexity has proven difficult, at best. Classical laboratory experiments have been crucial to informing models of brain functioning. These types of experiments, nevertheless, generally do not capture the experiences of the real world and therefore lack ecological validity. This is mostly a methodological -not necessarily epistemic- limitation. The first section of this article will address the theoretical assumptions underlying the Mobile Brain/Body Imaging approach, which -we argue- are best understood from the Embodied, Embedded, Extended and Enactive approach to cognition. Later, we briefly review the technological advances that have enabled MoBI implementation. Finally, a discussion of MoBI’s strengths and limitations for the study of cognition within the 4E framework is presented with an emphasis in the Chilean context.

In this article (in press, Perspectives in Psychological Science) I generalize the notion of multiple self-aspects to create a descriptive framework in which lives are partitioned into containers of activities called strands. Strands are nearly-decomposable life-modules, structured, stable, and concurrent longitudinal streams of extended duration whose momentary cross-sections constitute self- aspects. They are differentiated by five features: (a) the person’s role, (b) the cast, (c) the setting, (d) norms and values, and (e) habits and routines. Strands contain projects, and episodes, and are replete with narrative. Each strand is continuous (i.e., strands persist when a person moves between them), and for the most part strands are mutually asynchronous. From a first-person perspective, the strands are continuous and concurrent but only one strand is in the foreground at a given time, i.e., transitions between strands are akin to a figure-ground reversal. Furthermore, a life is different from the sum of its strands: it is a nonlinear system that can take on configurations not predictable from a comprehensive description of the individual strands. Two such examples are the achievement of greatness despite severe handicaps and instances of extreme self-sacrifice. I also discuss the research potential of a proposed smartphone app called LifeMaps.

Much of the characteristic symptomatology of schizophrenia can be understood as resulting from a pervasive sense of disembodiment. The body is experienced as an external machine that needs to be controlled with explicit intentional commands, which in turn leads to severe difficulties in interacting with the world in a fluid and intuitive manner. In consequence, there is a characteristic dissociality: Others become problems to be solved by intellectual effort and no longer present opportunities for spontaneous interpersonal alignment. This dissociality goes hand in hand with a progressive loss of the socially extended mind, which normally affords opportunities for co-regulation of cognitive and affective processes. However, at times people with schizophrenia report that they are confronted by the opposite of this dissociality, namely an unusual fluidity of the self-other boundary as expressed in experiences of ambiguous body boundaries, intrusions, and even merging with others. Here the person has not lost access to the socially extended mind but has instead become lost in it, possibly due to a weakened sense of self. We argue that this neglected aspect of schizophrenic social dysfunction can be usefully approached via the concept of genuine intersubjectivity: We normally participate in a shared experience with another person by implicitly co-regulating how our interaction unfolds. This co-regulation integrates our respective experience’s dynamical bases into one interpersonal process and gives the interaction an ambiguous second-person character. The upshot is that reports of abnormal self-other fluidity are not indicative of hallucinations without any basis in reality, but of a heightened sensitivity and vulnerability to processes of interpersonal alignment and mutual incorporation that form the normal basis of social life. We conclude by discussing implications of this view for both the science of consciousness as well as approaches to intervention and therapy.

In recent years, there are severe concerns about the replicability and reproducibility crisis of psychological research. In this special issue, as one of the remedies to improve this situation as much as possible, we practiced "pre-review of pre-registration" of direct replication of previous research. In this paper, I summarized our practice, which was performed for the first time in Japan, through a progress report and comments by the reviewers, and provided some perspectives for the future.

For the past 25 years, the field of social and political psychology has embraced the idea that humans possess a special system justification motivation which causes even members of disadvantaged groups to support societal systems that ostensibly operate against their personal and group interests. Recently, this system justification motive explanation has been challenged, based on mounting empirical evidence to the contrary. However, the potential demise of this dominant perspective invites explanations for the system justification phenomenon, especially amongst the disadvantaged. Existing interest-based accounts, such as the social identity model of system attitudes have tried to fill this gap, but have generally focused on system rationalisation processes within dyadic systems that pitch disadvantaged groups against their privileged counterparts alone. The current contribution extends the existing interest-based accounts by explaining system justification effects in multi-stratified social systems. Based on the triadic social stratification theory, we propose that system justification among the disadvantaged may result from favourable inter-status comparisons within a multi-stratified social system.

Scientists, for the most part, want to get it right. However, the social structures that govern their work undermine that aim, and this leads to nonreplicable findings in many fields. Because the social structure of science is a decentralized system, it is difficult to intervene. In this article, I discuss how we might do so, focusing on self-corrective-labor schemes (i.e., ways of distributing replication efforts within the scientific community). First, I argue that we need to implement a scheme that makes replication work outcome independent, systematic, and sustainable. Second, I use these three criteria to evaluate extant proposals, which place the responsibility for replication on original researchers, consumers of their research, students, or many labs. Third, on the basis of a philosophical analysis of the reward system of science and the benefits of the division of cognitive labor, I propose a scheme that satisfies the criteria better: the professional scheme. This scheme has two main components. First, the scientific community is organized into two groups: discovery researchers, who produce new findings, and confirmation researchers, whose primary function is to do confirmation work (i.e., replication, reproduction, meta-analysis). Second, a distinct reward system is established for confirmation researchers so that their career advancement is separated from whether they obtain positive experimental results.

In contemporary identity research Erik Erikson is seldom associated with work on culture, race, and ethnicity. What is ironic about this lack of association is that not only did Erikson consider these factors, but that they figured prominently into his theorizing. The purpose of this article is to provide an analysis of Erikson’s views that is more accurate than is what is typically represented by: 1) reviewing a brief history of empirical research on identity development since Erikson, 2) providing a broad summary of Erikson’s writing on how identity is shaped by culture, race, and ethnicity, 3) arguing that Erikson’s work suggests that historical trauma serves as an ideological setting for the identity development of marginalized groups, and 4) describing how historical trauma is associated with threats to temporal identity integration, or self-continuity.

The analysis of longitudinal neuroimaging data within the massively univariate framework provides the opportunity to study empirical questions about neurodevelopment. Missing outcome data are an all-to-common feature of any longitudinal study, a feature that, if handled improperly, can reduce statistical power and lead to biased parameter estimates. The goal of this paper is to provide conceptual clarity of the issues and non-issues that arise from analyzing incomplete data in longitudinal studies with particular focus on neuroimaging data. This paper begins with a review of the hierarchy of missing data mechanisms and their relationship to likelihood-based methods, a review that is necessary not just for likelihood-based methods, but also for multiple-imputation methods. Next, the paper provides a series of simulation studies with designs common in longitudinal neuroimaging studies to help illustrate missing data concepts regardless of interpretation. Finally, two applied examples are used to demonstrate the sensitivity of inferences under different missing data assumptions and how this may change the substantive interpretation. The paper concludes with a set of guidelines for analyzing incomplete longitudinal data that can improve the validity of research findings in developmental neuroimaging research. Keywords: Neuroimaging, Missing data, Likelihood, Longitudinal data

García Coll et al.'s (1996) integrative model was a landmark article for developmental science, and for psychology more broadly, in outlining the multitude of social and cultural factors at play when seeking to understand the development of racial/ethnic minority children. The time is ripe to not only take stock of those advances but also evaluate the integrative model in the context of present-day research practice within developmental psychology, and psychology more broadly. The purpose of this article is to bring a systemic perspective to developmental science through a discussion of current practices in the field. To do so, we examine invisibility, or how dominant practices serve to overlook, silence, or dismiss knowledge produced by and for racial/ethnic minority populations. Guided by the interpretive framework of intersectionality (Crenshaw, 1991), we discuss three key questions: From whose vantage point is research conducted? What types of questions are valued? And who gets left out? We then conclude with recommendations for changes in practices for individuals, institutions, and the field at large. Importantly, although our analysis is largely grounded in research and practices in developmental psychology, it is also highly relevant to psychological science as a whole. (PsycINFO Database Record

Over the years, researchers in psychological science have documented and investigated a host of powerful cognitive fallacies, including hindsight bias and confirmation bias. Researchers themselves may not be immune to these fallacies and may unwittingly adjust their statistical analysis to produce an outcome that is more pleasant or better in line with prior expectations. To shield researchers from the impact of cognitive fallacies, several methodologists are now advocating preregistration—that is, the creation of a detailed analysis plan before data collection or data analysis. One may argue, however, that preregistration is out of touch with academic reality, hampering creativity and impeding scientific progress. We provide a historical overview to show that the interplay between creativity and verification has shaped theories of scientific inquiry throughout the centuries; in the currently dominant theory, creativity and verification operate in succession and enhance one another’s effectiveness. From this perspective, the use of preregistration to safeguard the verification stage will help rather than hinder the generation of fruitful new ideas.

The ability to generate novel hypotheses is an important problem solving capacity of humans. This ability is vital for making sense of the complex and unfamiliar world we live in. Often, this capacity is characterized as an inference to the best explanation—selecting the ‘best’ explanation from a given set of candidate hypotheses. However, it remains unclear where these candidate hypotheses originate from. In this paper we contribute to computationally explaining these origins by providing the contours of the computational problem solved when humans generate hypotheses.The origin of hypotheses, otherwise known as abduction proper, is hallmarked by six properties: (1) isotropy (anything is potentially relevant), (2) open-ended (the set of hypotheses can contain each hypothesis that a person can in principle generate), (3) novel (it can contain hypotheses that a person has never generated before), (4) grounded (each candidate hypothesis must be related to perception), (5) sensible (each candidate hypothesis must be able to explain the observation) and (6) constrained (the set must be constrained in psychologically relevant ways). In this paper we provide a computational-level model of abduction proper that unifies all six properties. We conjecture that abduction proper is best seen as a process of deep analogical inference.

This is a preprint of the editorial for special issue “The new style of psychological research: CHANGE we can believe in” of Japanese Psychological Review.

In light of the “replication crisis,” some (e.g., Nelson, Simmons, & Simonsohn, 2018) advocate for greater policing and transparency in research methods. Others (Baumeister, 2016; Finkel, Eastwick, & Reis, 2017; Goldin-meadow, 2016; Levenson, 2017) argue against rigid requirements that may inadvertently restrict discovery. We embrace both positions and argue that proper understanding and implementation of the well-established paradigm of Exploratory Data Analysis (EDA; Tukey, 1977) is necessary to push beyond the replication crisis. Unfortunately, many don’t realize EDA exists (Goldin-Meadow, 2016), fail to understand the philosophy and proper tools for exploration (Baumeister, 2016), or reject EDA as unscientific (Lindsay, 2015). EDA’s mistreatment is unfortunate, and is usually based on misunderstanding the nature and goal of EDA. We develop an expanded typology that situates EDA, CDA, and rough CDA in the same framework with fishing, p-hacking, and HARKing, and argue that most, if not all, questionable research practices (QRPs) would be resolved by understanding and implementing the EDA/CDA gradient. We argue most psychological research is “rough CDA,” which has often and inadvertently used the wrong tools. We conclude with guidelines about how these typologies can be integrated into a cumulative research program that is necessary to move beyond the replication crisis.