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Temporal information-processing is critical for adaptive behavior and goal-directed action. It is thus crucial to understand how the temporal distance between behaviorally relevant events is encoded to guide behavior. However, research on temporal representations has yielded mixed findings as to whether organisms utilize relative versus absolute judgments of time intervals. To address this fundamental question about the timing mechanism, we tested mice in a duration discrimination procedure in which they learned to correctly categorize tones of different durations as short or long. After being trained on a pair of target intervals the mice transferred to conditions in which cue durations and corresponding response locations were systematically manipulated. Specifically, responses and/or durations of cues were switched in different experimental phases so that either the relative or absolute mapping remained constant. The findings indicate that the transfer occurred most readily when relative relationships of durations and response locations were preserved. In contrast, when the animals had to re-map these relative relations, their temporal discrimination ability was impaired, and they required extensive training to re-establish temporal control. However, preserving the response location of one of the cue durations in such conditions was found to help with initial transfer. These results demonstrate that mice can represent experienced durations both as having a certain magnitude (absolute representation) and as being shorter or longer of the two durations (an ordinal relation to other cue durations), with relational control having a greater influence in temporal discriminations.

Theories of hate date back several thousand years, yet very few experiments have examined the psychological structure of hate. We investigated whether any differences in the psychological experience of hate and dislike were a matter of degree (i.e. hate falls on the end of the continuum of dislike) or kind (i.e. hate is imbued with distinct cognitive, emotional, or motivational components that distinguish it from dislike). In a series of experiments, participants reported disliked and hated attitude objects and rated each on dimensions including valence, attitude strength, morality, and emotional content. Quantitative and qualitative measures provided convergent evidence that hated attitude objects were not only more negative than disliked attitude objects but also more likely to be associated with moral beliefs and emotions (Study 1). Further, differences in kind (i.e., moral beliefs and emotions) held even after statistically adjusting for differences in degree (i.e., negativity). Subsequent research confirmed that hate not only differs from dislike but also from extreme dislike—providing a more stringent test of a difference in kind (Study 2)—and this difference was observed for both person and concept attitude objects (Study 3). A content analysis of online websites found that the language used on hate websites also differed in kind (i.e., moral content), but not degree (i.e., negativity), from complaint forums (Study 4). Thus, across quantitative and qualitative indices from the lab and the field, hated attitude objects were more likely to be associated with morality than disliked objects.

We introduce the Category Abstraction Learning (CAL) model, a cognitive framework formally describing category learning built on similarity-based generalization, dissimilarity-based abstraction, two attention learning mechanisms, error-driven knowledge structuring, and stimulus memorization. Our hypotheses draw on an array of empirical and theoretical insights connecting reinforcement and category learning. The key novelty of the model is its explanation of how rules are learned from scratch based on three central assumptions. (a) Category rules emerge from two processes of stimulus generalization (similarity) and its direct inverse (category contrast) on independent dimensions. (b) Two attention mechanisms guide learning by focusing on rules, or on the contexts in which they produce errors. (c) Knowing about these contexts inhibits executing the rule, without correcting it, and consequently leads to applying partial rules in different situations. The model is designed to capture both systematic and individual differences in a broad range of learning paradigms. We illustrate the model's explanatory scope by simulating several benchmarks, including the classic Six Problems, the 5-4 problem, and linear separability. Beyond the common approach of predicting average response probabilities, we also propose explanations for more recently studied phenomena that challenge existing learning accounts, regarding task instructions, individual differences in rule extrapolation in three different tasks, individual attention shifts to stimulus features during learning, and other phenomena. We discuss CAL's relation to different models, and its potential to measure the cognitive processes regarding attention, abstraction, error detection, and memorization from multiple psychological perspectives. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

How do humans learn, through social interaction, whom to depend on in different situations? We compared the extent to which inferred trait attributes—as opposed to learned reward associations previously examined in feedback-based learning contexts—could adaptively inform cross-context social decision making. In four experiments, participants completed a novel task in which they chose to “hire” other players to solve math and verbal questions for money. These players varied in their trait-level competence across these contexts, and, independently, in the monetary rewards they offered to participants across contexts. Results revealed that participants chose partners primarily based on context-specific traits, as opposed to either global (e.g., cross-context) trait impressions or material rewards. When making choices in novel contexts—including determining who to choose for social and emotional support—participants generalized trait knowledge from past contexts that required similar traits. Reward-based learning, by contrast, demonstrated significantly weaker context-sensitivity and generalization. These findings suggest that people form context-dependent trait impressions from interactive feedback and use this knowledge to make flexible social decisions. These results support a novel theoretical account of how interaction-based social learning can support context-specific impression formation and adaptive decision making.

Contending with sexism is associated with negative affective outcomes, including increased anger, anxiety, and depression. Prior research demonstrates that the use of emotion-regulation strategies, such as self-distanced reappraisal, when contending with general negative interpersonal experiences, can help people manage their emotions, attenuating the associated negative affect. The present research considers whether the affective benefits of reappraisal extend to past experiences of discrimination. Specifically, we examine whether using self-distanced reappraisal (Studies 1 and 2) or positive reappraisal (Study 2) when contending with sexism yields more positive and less negative affective outcomes, relative to engaging in self-immersion. Contrary to previous research examining more general negative interpersonal experiences, we find limited evidence that self-distanced reappraisal is an effective emotion-regulation strategy for women contending with sexism (N = 1,236). The present work offers preliminary evidence, however, that positive reappraisal may be a promising emotion-regulation strategy that reduces the negative affective consequences associated with reliving past instances of sexism, compared with either self-immersion or self-distanced reappraisal. We discuss the implications of these findings for understanding the efficacy of different emotion-regulation strategies in the context of discrimination. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Research on tempo perception has shown that it is effectively modeled by tactus rate (musical pulse), and aligns with the theory of metrical hierarchy. This research typically draws from common-practice music (music from the Western European tradition, ca. 1750-1900), and therefore does not address traits found in other repertoire that may contend with these claims. The current study investigated the impact of the backbeat, a ubiquitous rhythmic feature of popular music, on tempo perception. The experiment asked listeners to compare the tempos of pairs of excerpts with the same tactus rate. Pairs of excerpts were always presented with different backbeats, shifting to either half-time or double-time. Results indicated that half-time trials were perceived to be slower, and double-time trials were perceived to be faster, despite identical tactus rates and metrical hierarchies. The findings provide empirical support for the idea that established theories of tempo perception and metrical hierarchy may not entirely extend to other musical styles, and that the backbeat may be a metrical feature of popular music, rather than simply a rhythmic one.

An increasing number of studies in the Human and Social Sciences and Information and Communication Technologies and Sciences are conducted in virtual reality. Many of them use 3D human-like computer-generated characters in order to study social interactions in healthy participants, or the effect mental illness or neurological disorder on social cognition. However, free access to virtual characters is still not straightforward with often a lack of psychological evaluation of available characters. We present here the ATHOS database composed of 48 Caucasian male and female virtual characters with non-emotional facial expression available in the FBX file format. For each of them, we provide an evaluation in terms of valence, reliability, sympathy and sociability. Concerning these evaluations, inter-rater reliability analysis revealed a good degree of agreement among raters (between 0.85 and 0.98) and a cluster analysis highlighted a division of the virtual characters into three groups (low, medium and high evaluation scores). The ATHOS database of virtual characters, available in open access, can be used for many different purposes including the development of social immersive virtual environments, cognitive assessments or even rehabilitation programs in the health domain.

© 2020 American Psychological Association. The development of creativity in young children has been studied extensively, but relatively few studies have examined the period of adolescence and emerging adulthood in relation to creative potential. The present study uses a combination of frequentist and Bayesian analyses to evaluate the impact of individual factors (e.g., IQ) and contextual factors (e.g., pursuit of creative hobbies) on creative ideation in three cohorts of young people aged 14-20 years. Measures of divergent thinking, specifically the Alternate Uses Task (AUT) and the Overcoming Knowledge Constraints Task, were used to this end. Openness to aesthetic and imaginative experience was the strongest predictor of creative potential for the 3 AUT measures. Moreover, Bayesian hypothesis testing revealed that the best predictive model for AUT ideational fluency and AUT overall originality was one that included only Openness, whereas the best predictive model for AUT peak originality, or the propensity to generate highly original responses, included Openness, as well as IQ and Engagement in Creative Hobbies. No group differences in creative potential were found between the three age cohorts (aged 14-15, 16-17, and 18-20). The study not only confirms the importance of openness to aesthetic and imaginative experience as a predictor of creative potential in adolescents and young adults, but also indicates the necessity to consider the combined and differentiated impact of individual and contextual factors in different facets of creative ideation.

Parents are known to provide a lasting basis for their children's social development. Understanding parent-driven socialization is particularly relevant in adolescence, as an increasing social independence is developed. However, the relationship between key parenting styles of care and control and the microlevel expression of daily-life social interactions has been insufficiently studied. Adolescent and young adult twins and their nontwin siblings (N = 635; mean age = 16.6; age range = 14.2-21.9; 58.6% female; 79.5% in or having completed higher secondary/tertiary education; 2.8% speaking language other than Dutch at home) completed the Parental Bonding Instrument (PBI) on parental care and control. Participants also completed a 6-day experience sampling period (10 daily beeps, mean compliance = 68.0%) to assess daily-life social interactions. Higher overall parental bonding quality (of both parents) related to more positive social experiences in daily life (e.g., belonging in company), but not to more social behaviors (e.g., being with others). Factor analysis indicated a three-factor structure of the PBI, with care, denial of psychological autonomy, and encouragement of behavioral freedom. Paternal care was uniquely predictive of better social experiences. These findings demonstrate how parenting styles may be uniquely associated with how adolescents experience their social world, with a potentially important role for fathers in particular. This complements the long-held idea of socialization through parenting by bringing it into the context of daily life and implies how both conceptualizations of social functioning and interventions aimed at alleviating social dysfunction might benefit from a stronger consideration of day-to-day social experiences. (PsycInfo Database Record (c) 2022 APA, all rights reserved). ispartof: DEVELOPMENTAL PSYCHOLOGY vol:58 issue:4 pages:792-805 ispartof: location:United States status: published

Reliability is a crucial concept in psychometrics. Although it is typically estimated as a single fixed quantity, previous work suggests that reliability can vary across persons, groups, and covariates. We propose a novel method for estimating and modeling case-specific reliability without repeated measurements or parallel tests. The proposed method employs a “Reliability Factor” that models the error variance of each case across multiple indicators, thereby producing case-specific reliability estimates. Additionally, we use Gaussian process modeling to a estimate non-linear, non-monotonic function between the latent factor itself and the reliability of the measure, providing an analogue to test information functions in item response theory. The reliability factor model is a new tool for examining latent regions with poor conditional reliability, and correlates thereof, in a classical test theory framework.

People presumably strive to maximize their own benefit whenever possible, so it is puzzling when they vote for leaders who may not have their best interest at heart. We tested whether support for a political leader is diminished when supporters learn they are financially disadvantaged by the leader’s policies. In a pre-registered, two-stage experiment (Time 1 n = 601, Time 2 n = 343), Trump voters predicted their expected tax refund (or payment), and then reported their tax outcome immediately after the filing deadline. Afterwards, we confronted half of the participants with the discrepancy between their actual and predicted tax outcome. Having lower-than-expected tax outcomes was not associated with reduced support for Trump either on its own, or in combination with being reminded of this outcome. However, it led participants who were dissatisfied with their tax outcome to downgrade the importance of lowering taxes, possibly in an effort to reduce cognitive dissonance and justify continued support for Trump. Subjective tax outcome satisfaction, on the other hand, did predict Trump support, but was dwarfed in magnitude by other variables such as system justification and political orientation. Overall, we find little evidence that economic self-interest played a role in support for Trump.

A growing number of publications focus on estimating Gaussian graphical models (GGM, networks of partial correlation coefficients). At the same time, generalizibility and replicability of these highly parameterized models are debated, and sample sizes typically found in datasets may not be sufficient for estimating the underlying network structure. In addition, while recent work emerged that aims to compare networks based on different samples, these studies do not take potential cross-study heterogeneity into account. To this end, this paper introduces methods for estimating GGMs by aggregating over multiple datasets. We first introduce a general maximum likelihood estimation modeling framework in which all discussed models are embedded. This modeling framework is subsequently used to introduce meta-analytic Gaussian network aggregation (MAGNA). We discuss two variants: fixed-effects MAGNA, in which heterogeneity across studies is not taken into account, and random-effects MAGNA, which models sample correlations and takes heterogeneity into account. We assess the performance of MAGNA in large-scale simulation studies. Finally, we exemplify the method using four datasets of post-traumatic stress disorder (PTSD) symptoms, and summarize findings from a larger meta-analysis of PTSD symptom.

When people encounter others emotions, they engage multiple brain systems, including parts of sensorimotor cortex associated with motor simulation. Simulation-related brain activity is commonly described as a "low-level" component of empathy and social cognition. As such, it has been studied predominantly using simple, non-naturalistic tasks, such as viewing facial expressions or biological motion. This leaves unclear whether and how sensorimotor simulation contributes to more complex empathic judgments. Here we explore this phenomenon by combining a naturalistic social paradigm with a reliable index of sensorimotor cortex-based simulation: EEG suppression of oscillatory activity in the mu (8-13 Hz) frequency band. We recruited participants to watch naturalistic video clips of people ("targets") describing emotional events in their lives. Participants viewed these clips (i) with both video and sound, (ii) with only video, or (iii) with only sound. Participants provided continuous ratings of how they believed the target in the video felt. We calculated participants empathic accuracy as the correlation between their inferences and targets self-report. Across all conditions, right-lateralized mu suppression tracked empathic accuracy. This was true when examining accuracy for videos as a whole, as well as when examining accuracy over 3-second intervals within each video. Our results provide novel evidence that motor representations—as measured through mu suppression—play an important role not only in low-level motor simulation, but also in higher-level inferences about others emotions.

Students' academic achievement is a key predictor of various life outcomes and is commonly used for selection as well as for educational monitoring and accountability. With regard to achievement indicators, a differentiation has traditionally been drawn between grades and standardized tests. There is initial, albeit inconclusive, evidence that these indicators might differentially reflect students' personality as encapsulated in the Big Five personality traits as well as measures of cognitive abilities. In this article, we propose the personality-achievement saturation hypothesis (PASH) as an overarching model that describes the association between achievement indicators and personality. The PASH suggests that the differentiation between grades and tests is too simplistic and that associations between personality and achievement instead vary across five main features of the achievement measures that are used: level of standardization, relevance for the student, curricular validity, instructional sensitivity, and cognitive ability saturation. On the basis of findings from prior studies, we focused in particular on conscientiousness and openness to test the PASH. We used data from three large-scale studies (total N = 14,953) and aggregated our findings across these studies. In line with the PASH, the Big Five trait of conscientiousness was most strongly related to measures that were less standardized and less saturated with cognitive ability but higher on curriculum validity, relevance, and instructional sensitivity. In addition, openness was most strongly related to measures that were higher on standardization and cognitive ability saturation but lower on relevance, curriculum validity, and instructional sensitivity in English.Educational Impact and Implications Statement Achievement measures are of central importance for student selection, employment, and educational policy, and according to a widely shared belief, they involve intellectual abilities as well as aspects of personality such as effort and persistence. Up to now, prior research has remained rather inconclusive about why achievement measures vary in their degree of personality saturation. In this study, we developed and successfully tested a new framework (the PASH), which categorizes achievement measures along five main features and thereby contributes to a better explanation of differential associations between personality traits and different achievement measures.

Objective: The Shift-of-Strategy (SoS) approach is an extension of the Strategic Use of Evidence technique. In the SoS approach, interviewers influence suspects’ strategies to encourage suspects to become more forthcoming with information by challenging discrepancies between their statements and the available evidence, in a non-accusatory manner. Our aim was to test the effectiveness of two variations of the SoS approach, one in which the interviewer responded immediately to any discrepancies with the evidence (Reactive) and one in which the interviewer only responded to severe discrepancies (Selective). Hypotheses: We generally predicted that the SoS approach conditions would be more effective at eliciting new information from mock suspects, compared to direct questioning. Method: In a laboratory experiment, N = 300 mock suspects committed a simulated crime and were interviewed using one of the two versions of the SoS approach or with an interviewing approach that did not involve the presentation of evidence. We coded the transcribed interviews to assess how much information about the mock crime participants disclosed. Results: The Reactive version of the SoS approach was more effective than direct questioning at eliciting new information from mock suspects. The Reactive technique also appeared to prompt participants to change their strategies during the interview. Conclusions: The present experiment provides initial support for the core principles of the SoS approach.

Experimental tests of interventions need to have sufficient sample size to constitute a robust test of the intervention's effectiveness with reasonable precision and power. To estimate the required sample size adequately, researchers are required to specify an effect size. But what effect size should be used to plan the required sample size? Various inroads into selecting the a priori effect size have been suggested in the literature-including using conventions, prior research, and theoretical or practical importance. In this paper, we first discuss problems with some of the proposed methods of selecting the effect size for study planning. We then lay out a method for intervention researchers that provides a way out of many of these problems. The proposed method requires setting a meaningful change definition, it is specifically suited for applied researchers interested in planning tests of intervention effectiveness. We provide a hands-on walk through of the method and provide easy-to-use R functions to implement it.

The functioning of groups and societies requires that individuals cooperate on public goods such as healthcare and state defense. While psychological science has addressed cooperation and public good provision, it has largely ignored situations in which individuals face multiple public goods and must choose on which to cooperate. Such decisions can be difficult when public goods are attractive on one dimension (e.g., being ‘efficient’ in providing comparatively high returns) and unattractive on another (e.g., providing unequal rather than equal returns to group members). Here we examined (expectations about) cooperation in multiple-public good provision problems using four incentivized and preregistered experiments (N = 774). Participants simultaneously faced two public goods that varied in efficiency and (in)equality of returns. Results showed more cooperation on the comparatively efficient public good (Exp. 1) and on the equal-return (vs. unequal-return) public good. Crucially, however, when the unequal-returns public good was also the most efficient, individuals cooperated comparatively more on this unequal-but-efficient public good when they themselves benefitted the most from inequality (Exp. 2—4). Low beneficiaries largely ignored public good efficiency and preferentially cooperated on equal- rather than unequal-returns public goods. Consequently, groups encountering multiple-public good provision problems including an unequal-but-efficient-returns public good were most cooperative. Expectations (Exp. 2—4) as well as preferences for revising the multiple-public good provision problems’ choice architecture (Exp. 3—4) echoed these cooperation patterns. We discuss implications for theory and policy on cooperation.

Dominance perceptions play an important role in social interactions. Although many researchers have proposed that shape masculinity is an important facial cue for dominance perceptions, evidence for this claim has come almost exclusively from studies that assessed perceptions of experimentally manipulated face images using forced-choice paradigms. Consequently, we investigated the role of masculine shape characteristics in perceptions of men’s facial dominance (1) using the forced-choice method and (2) when unmanipulated face images were rated for dominance and shape masculinity was measured from face images. Although we observed large positive effects of masculinity on dominance perceptions when we used the forced-choice method (Cohen’s ds = 2.51 and 3.28), the effect of masculinity on dominance perceptions was considerably smaller when unmanipulated face images were rated and shape masculinity measured from face images (Cohen’s ds = 0.44 and 0.62). This same pattern was observed when faces were rated separately for physical and social dominance and was seen for two different sets of stimuli. Collectively, these results suggest that previous research using the forced-choice method overstated the importance of face-shape masculinity for dominance perceptions and that shape masculinity is less important for dominance assessments of unmanipulated face images than previous research suggested. This research was supported by ESRC grant ES/X000249/1 awarded to BCJ, by ZintegrUJ travel grant POWR.03.05.00-00-Z309/17-00 awarded to UMM, and a University of Strathclyde Global Research Award to JD. For the purpose of Open Access, the authors have applied a Creative Commons Attribution (CC BY) to any Author Accepted Manuscript (AAM) version arising from this submission.

Perceptions of the trustworthiness of faces predict important social outcomes, including economic exchange and criminal sentencing decisions. However, the specific facial characteristics that drive trustworthiness perceptions remain poorly understood. Here we investigated this issue by exploring possible relationships between ratings of the trustworthiness of face images and objective assessments of two aspects of face shape that researchers have previously suggested are important for perceptions of trustworthiness: distinctiveness and sexual dimorphism. We found that faces with more distinctive shapes were rated as less trustworthy. By contrast, sexual dimorphism of face shape was not significantly correlated with trustworthiness ratings. These results suggest that distinctiveness of face shape plays a more important role in trustworthiness perceptions than does sexual dimorphism and suggest that perceptions of trustworthiness may stem, at least in part, from the ‘anomalous-is-bad’ stereotype. This research was supported by ESRC grant ES/X000249/1 awarded to BCJ and a University of Strathclyde Global Research Award Studentship awarded to KL. For the purpose of Open Access, the authors have applied a Creative Commons Attribution (CC BY) to any Author Accepted Manuscript (AAM) version arising from this submission.This research was supported by ESRC grant ES/X000249/1 awarded to BCJ. For the purpose of Open Access, the authors have applied a Creative Commons Attribution (CC BY) to any Author Accepted Manuscript (AAM) version arising from this submission.

That American and European participants are overrepresented in psychological studies has been previously established. In addition, researchers also often tend to be similarly homogenous. This continues to be alarming, especially given that this research is being used to inform policies across the world. In the face of a global pandemic where behavioral scientists propose solutions, we ask who is conducting research and on what samples. Forty papers on COVID-19 published in PsyArxiV were analyzed; the nationalities of the authors and the samples they recruited were assessed. Findings suggest that an overwhelming majority of the samples recruited were from the US and the authors were based in US and German institutions. Next, men constituted a large proportion of primary and sole authors. The implications of these findings are discussed.

In classical statistics, there is a close link between null hypothesis significance testing (NHST) and parameter estimation via confidence intervals. However, for the Bayesian counterpart, a link between null hypothesis Bayesian testing (NHBT) and Bayesian estimation via a posterior distribution is less straightforward, but does exist, and has recently been reiterated by Rouder, Haaf, and Vandekerckhove (2018). It hinges on a combination of a point mass probability and a probability density function as prior (denoted as the spike-and-slab prior). In the present paper, it is first carefully explained how the spike-and-slab prior is defined, and how results can be derived for which proofs were not given in Rouder, Haaf, and Vandekerckhove (2018). Next, it is shown that this spike-and-slab prior can be approximated by a pure probability density function with a rectangular peak around the center towering highly above the remainder of the density function. Finally, we will indicate how this ‘hill-and-chimney’ prior may in turn be approximated by fully continuous priors. In this way, it is shown that NHBT results can be approximated well by results from estimation using a strongly peaked prior, and it is noted that the estimation itself offers more than merely the posterior odds on which NHBT is based. Thus, it complies with the strong APA requirement of not just mentioning testing results but also offering effect size information. It also offers a transparent perspective on the NHBT approach employing a prior with a strong peak around the chosen point null hypothesis value.

The potential for the design of artificial intelligence (AI) conversational agents to reinforce gender-based stereotypes was recently highlighted in a UNESCO (United Nations Educational, Scientific and Cultural Organization) report. Addressing this issue requires knowledge of how male and female conversational agents’ voices are perceived. Consequently, we investigated whether male and female conversational agents’ voices are perceived differently for a range of traits commonly investigated in studies of natural human stimuli (trustworthy, emotionally stable, responsible, sociable, caring, attractive, intelligent, confident, weird, unhappy, mean, aggressive, dominant, competent, old, masculine, feminine). Male voices were rated as significantly more aggressive, dominant, mean, and masculine than female voices and were also rated significantly older. Female voices were rated as significantly more feminine than male voices. These differences in how male and female conversational agents’ voices are perceived may be usefully applied to the design of conversational agents to reduce their effects on gender-based stereotypes. This research was supported by the EPSRC grant ‘Designing Conversational Assistants to Reduce Gender Bias’ (EP/T023783/1), awarded to Benedict Jones. For the purpose of Open Access, the authors have applied a Creative Commons Attribution (CC BY) to any Author Accepted Manuscript (AAM) version arising from this submission.

We integrate Rawls’ (1971/2009, 1993, 2001) concept of primary goods with self-determination theory (SDT; Ryan & Deci, 2017), to examine the link between people’s perceptions of primary goods (i.e., views of society as just and fair), basic psychological need satisfaction, and well-being. In Study 1 (N=762, countries = Australia, the United States, South Africa, India, and the Philippines) and Study 2 (N=1479, groups = ethnic minority, sexual minority, political group, religious group), we used partial least squares structural equation modelling (PLS-SEM) to assess associations between perceptions of primary goods and wellness, and the intermediary role of basic psychological needs. Perceptions of primary goods linked positively to well-being (average effect size = 0.48), and negatively to ill-being (average effect size = -0.46). These associations were strongly mediated by basic psychological needs (average percentage mediated: 53% Study 1 and 68% Study 2). Results signify the importance of primary goods’ perceptions to wellness.

Cognitive science invokes semantic networks to explain diverse phenomena, from memory retrieval to creativity. Research in these areas often assumes a single underlying semantic network that is shared across individuals. Yet, recent evidence suggests that content, size, and connectivity of semantic networks are experience-dependent, implying sizable individual and age-related differences. Here, we investigate individual and age differences in the semantic networks of younger and older adults by deriving semantic networks from both fluency and similarity rating tasks. Crucially, we use a megastudy approach to obtain thousands of similarity ratings per individual to allow us to capture the characteristics of individual semantic networks. We find that older adults possess lexical networks with smaller average degree and longer path lengths relative to those of younger adults, with older adults showing less interindividual agreement and thus more unique lexical representations relative to younger adults. Furthermore, this approach shows that individual and age differences are not evenly distributed but, rather, are related to weakly connected, peripheral parts of the networks. All in all, these results reveal the interindividual differences in both the content and the structure of semantic networks that may accumulate across the life span as a function of idiosyncratic experiences.

Measurement reliability is a fundamental concept in psychology. It is traditionally considered a stable property of a questionnaire, measurement device, or experimental task. Although intraclass correlation coefficients (ICC) are often used to assess reliability in repeated measure designs, their descriptive nature depends upon the assumption of a common within-person variance. This work focuses on the presumption that each individual is adequately described by the average within-person variance in hierarchical models. And thus whether reliability generalizes to the individual level, which leads directly into the notion of individually varying ICCs. In particular, we introduce a novel approach, using the Bayes factor, wherein a researcher can directly test for homogeneous within-person variance in hierarchical models. Additionally, we introduce a membership model that allows for classifying which (and how many) individuals belong to the common variance model. The utility of our methodology is demonstrated on cognitive inhibition tasks. We find that heterogeneous within-person variance is a defining feature of these tasks, and in one case, the ratio between the largest to smallest within-person variance exceeded 20. This translates into a tenfold difference in person-specific reliability! We also find that few individuals belong to the common variance model, and thus traditional reliability indices are potentially masking important individual variation. We discuss the implications of our findings and possible future directions. The methods are implemented in the R package vICC

The current study used latent class analysis to identify subgroups of collegiate Christian evangelicals and to compare them on a range of cross-sectional and longitudinal indicators of personal attitudes and campus climate. Items from the Interfaith Diversity Experiences and Attitudes Longitudinal Survey (IDEALS) formed the basis of this study. We identified three subgroups who differed in terms of their appreciation of outside groups, knowledge of other groups, and ratings of campus climate. Our results provide insight into the evangelical experience in higher education and provide additional support for the argument that “evangelical” should be viewed as a heterogeneous population.

Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequisite for drawing valid inferences when studying dynamics of psychological factors in intensive longitudinal data. To conveniently evaluate this invariance, latent Markov factor analysis (LMFA) was proposed. LMFA combines a latent Markov model with mixture factor analysis: The Markov model captures changes in MMs over time by clustering subjects' observations into a few states and state-specific factor analyses reveal what the MMs look like. However, to estimate the model, Vogelsmeier, Vermunt, van Roekel, and De Roover (2019) introduced a one-step (full information maximum likelihood; FIML) approach that is counterintuitive for applied researchers and entails cumbersome model selection procedures in the presence of many covariates. In this paper, we simplify the complex LMFA estimation and facilitate the exploration of covariate effects on state memberships by splitting the estimation in three intuitive steps: (1) obtain states with mixture factor analysis while treating repeated measures as independent, (2) assign observations to the states, and (3) use these states in a discrete- or continuous-time latent Markov model taking into account classification errors. A real data example demonstrates the empirical value. ispartof: MULTIVARIATE BEHAVIORAL RESEARCH vol:58 issue:2 ispartof: location:United States status: published

Missing data are ubiquitous in psychological research. They may come about as an unwanted result of coding or computer error, participants' non-response or absence, or missing values may be intentional, as in planned missing designs. We discuss the effects of missing data on χ²-based goodness-of-fit indices in Structural Equation Modeling (SEM), specifically on the Root Mean Squared Error of Approximation (RMSEA). We use simulations to show that naive implementations of the RMSEA have a downward bias in the presence of missing data and, thus, overestimate model goodness-of-fit. Unfortunately, many state-of-the-art software packages report the biased form of RMSEA. As a consequence, the scientific community may have been accepting a much larger fraction of models with non-acceptable model fit. We propose a bias-correction for the RMSEA based on information-theoretic considerations that take into account the expected misfit of a person with fully observed data. The corrected RMSEA is asymptotically independent of the proportion of missing data for misspecified models. Importantly, results of the corrected RMSEA computation are identical to naive RMSEA if there are no missing data.

UNLABELLED: A child's socio-economic environment can profoundly affect their development. While existing literature focusses on simplified metrics and pair-wise relations between few variables, we aimed to capture complex interrelationships between several relevant domains using a broad assessment of 519 children aged 7-9 years. Our analyses comprised three multivariate techniques that complimented each other, and worked at different levels of granularity. First, an exploratory factor analysis (principal component analysis followed by varimax rotation) revealed that our sample varied along continuous dimensions of cognition, attitude and mental health (from parallel analysis); with potentially emerging dimensions speed and socio-economic status (passed Kaiser's criterion). Second, k-means cluster analysis showed that children did not group into discrete phenotypes. Third, a network analysis on the basis of bootstrapped partial correlations (confirmed by both cross-validated LASSO and multiple comparisons correction of binarised connection probabilities) uncovered how our developmental measures interconnected: educational outcomes (reading and maths fluency) were directly related to cognition (short-term memory, number sense, processing speed, inhibition). By contrast, mental health (anxiety and depression symptoms) and attitudes (conscientiousness, grit, growth mindset) showed indirect relationships with educational outcomes via cognition. Finally, socio-economic factors (neighbourhood deprivation, family affluence) related directly to educational outcomes, cognition, mental health, and even grit. In sum, cognition is a central cog through which mental health and attitude relate to educational outcomes. However, through direct relations with all components of developmental outcomes, socio-economic status acts as a great 'unequaliser'. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-021-02232-2.

The concept of emotion disposition is proposed as an important dimension of individual differences. It refers to a stable tendency to experience certain emotions more or less frequently or intensely for similar classes of situations or events in daily experience than the majority of other people. In contrast to classic "trait affect" traditions, the theoretical framework described here proposes a specific mechanism based on the notion of appraisal bias, that is, the evaluation of events or situations in biased, often unrealistic, fashion. The bias toward internal versus external causal attribution is a classic example. It is suggested that such biases can affect virtually all appraisal criteria (e.g., novelty/expectedness, (un)pleasantness, goal conduciveness/obstruction, causation, control, power, and norm compliance), creating a disposition to experience specific emotions more frequently. In some cases, this process may lead to the development of affective disorders. Two studies are herein reported: (a) administering an emotion disposition assessment instrument to several thousand adults in personnel assessment contexts (N = 3,012), demonstrating the existence and intensity of emotion dispositions and identifying potential individual difference correlates; and (b) using an updated version of the instrument in a representative survey panel study (N = 190), assessing both emotion dispositions and appraisal biases, allowing analysis of their relationships (in addition to examining the effect of correlates). The results confirm the viability of the underlying theoretical assumptions as well as of the scenario method used for the assessment and provide leads for further research, particularly in the areas of emotional competence and affective disorders. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The use of statistical inference in linguistics and related areas like psychology typically involves a binary decision: either reject or accept some null hypothesis using statistical significance testing. When statistical power is low, this frequentist data-analytic approach breaks down: null results are uninformative, and effect size estimates associated with significant results are overestimated. Using an example from psycholinguistics, several alternative approaches are demonstrated for reporting inconsistencies between the data and a theoretical prediction. The key here is to focus on committing to a falsifiable prediction, on quantifying uncertainty statistically, and learning to accept the fact that – in almost all practical data analysis situations – we can only draw uncertain conclusions from data, regardless of whether we manage to obtain statistical significance or not. A focus on uncertainty quantification is likely to lead to fewer excessively bold claims that, on closer investigation, may turn out to be not supported by the data.

With mental health being a field that is becoming progressively more familiar and researched in depth, an important subject of interest that should be addressed is child mental health, and the different factors that can influence it. In this paper, we use a dataset from the Substance Abuse and Mental Health Data Archive to analyze the impacts of child-mentor relationships on child mental health. Previous studies have come to similar conclusions: positive parent-student and teacher-student relationships often lead to signs of positive mental health in children. To expand upon these past findings, we used different measures of mental health and relationship qualities to create a predictive model. We conducted classification and coefficient weight analyses to see how strong of an impact different variables representing indicators of healthy relationships had on different aspects of child mental health. This information was used to create predictions of future cases. Like previous studies, we found that there was a general pattern that showed that good child-mentor relationships, defined specifically by the frequency of praise and fights, had an overall positive impact on child mental health, specifically when it came to symptoms of depression. Furthermore, parents seemed to have stronger impacts on child mental health than teachers did. Limitations include possibly biased respondents who may not be representative of the greater population, as well as the specificity of the variables that were chosen. Going forward, further steps to analyze different datasets and deepen the scope of the research will be helpful in finding patterns and developing more detailed conclusions.

This study was designed to assess the psychological factors influencing life satisfaction of undergraduates. The instruments used were Perceived Stress Scale (PSS), Wong and Law Emotional Intelligence Scale (WLEIS), Rosenberge Self-esteem Scale (RSS), and Satisfaction with Life Scale (SWLS). A total number of 190 participants were purposively selected across various faculties in Ekiti State University. Four hypotheses were tested using Independent t-test to find the effects of perceived stress, emotional intelligence, and self-esteem on life satisfaction. Multiple regression was used to find the joint and individual influences of these variables. The results showed that there is no significant influence of perceived stress on life satisfaction (t (75) = 1.23, p = .22, 95% CI [-1.14, 4.83). There is no significant influence of self-esteem on life satisfaction (t (51) = -1.31, p = .20, 95% CI [-5.28, 1.11), and there is no significant joint influence of perceived stress, emotional intelligence and self-esteem on life satisfaction (F (3,187) = 1.79, p = .15, R2 =.03). Additionally, perceived stress (β = .07, p = .33), emotional intelligence (β = .14, p = 054) and self-esteem (β = .02, p = .83) did not have independent influences on life satisfaction. Implications of the present findings for future research are discussed, as well as potential interventions for improving life satisfaction.

Selection for statistical significance is a well-known factor that distorts the published literature and challenges the cumulative progress in science. Recent replication failures have fueled concerns that many published results are false-positives. Brunner and Schimmack (2020) developed z-curve, a method for estimating the expected replication rate (ERR) – the predicted success rate of exact replication studies based on the mean power after selection for significance. This article introduces an extension of this method, z-curve 2.0. The main extension is an estimate of the expected discovery rate (EDR) – the estimate of a proportion that the reported statistically significant results constitute from all conducted statistical tests. This information can be used to detect and quantify the amount of selection bias by comparing the EDR to the observed discovery rate (ODR; observed proportion of statistically significant results). In addition, we examined the performance of bootstrapped confidence intervals in simulation studies. Based on these results, we created robust confidence intervals with good coverage across a wide range of scenarios to provide information about the uncertainty in EDR and ERR estimates. We implemented the method in the zcurve R package (Bartoš & Schimmack, 2020).

Sustaining finite public resources presents a dilemma between acting in self-interest for present benefit versus working toward long-term collective gain. Given gratitude's links to prosociality and self-control, the present studies investigated whether gratitude would promote sustainable resource extraction under conditions of rapidly depleting resources. In Study 1 (N = 155), participants were randomly assigned to experience an emotional state (gratitude or neutral) prior to playing a resource dilemma game in which the common pool was manipulated to indicate either a sustained or depleting resource status. Neutral participants increased their point taking when the pool was depleting compared with when it was sustained; however, this pattern was not observed for grateful participants. Study 2 (N = 224) replicated these findings while also showing the effect of gratitude to be distinct from happiness. These findings show that gratitude, as opposed to a general positive emotional state, buffers against overtaking in resource dilemmas and suggests that this emotion may be useful in promoting sustainable behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Objective Everyday speech understanding frequently occurs in perceptually demanding environments, for example, due to background noise and normal age-related hearing loss. The resulting degraded speech signals increase listening effort, which gives rise to negative downstream effects on subsequent memory and comprehension, even when speech is intelligible. In two experiments, we explored whether the presentation of realistic assistive text captioned speech offsets the negative effects of background noise and hearing impairment on multiple measures of speech memory. Design In Experiment 1, young normal-hearing adults (N = 48) listened to sentences for immediate recall and delayed recognition memory. Speech was presented in quiet or in two levels of background noise. Sentences were either presented as speech only or as text captioned speech. Thus, the experiment followed a 2 (caption vs no caption) × 3 (no noise, +7 dB signal-to-noise ratio, +3 dB signal-to-noise ratio) within-subjects design. In Experiment 2, a group of older adults (age range: 61 to 80, N = 31), with varying levels of hearing acuity completed the same experimental task as in Experiment 1. For both experiments, immediate recall, recognition memory accuracy, and recognition memory confidence were analyzed via general(ized) linear mixed-effects models. In addition, we examined individual differences as a function of hearing acuity in Experiment 2. Results In Experiment 1, we found that the presentation of realistic text-captioned speech in young normal-hearing listeners showed improved immediate recall and delayed recognition memory accuracy and confidence compared with speech alone. Moreover, text captions attenuated the negative effects of background noise on all speech memory outcomes. In Experiment 2, we replicated the same pattern of results in a sample of older adults with varying levels of hearing acuity. Moreover, we showed that the negative effects of hearing loss on speech memory in older adulthood were attenuated by the presentation of text captions. Conclusions Collectively, these findings strongly suggest that the simultaneous presentation of text can offset the negative effects of effortful listening on speech memory. Critically, captioning benefits extended from immediate word recall to long-term sentence recognition memory, a benefit that was observed not only for older adults with hearing loss but also young normal-hearing listeners. These findings suggest that the text captioning benefit to memory is robust and has potentially wide applications for supporting speech listening in acoustically challenging environments.

Here, we take a computational approach to understand the mechanisms underlying face perception biases in depression. Thirty participants diagnosed with major depressive disorder and 30 healthy control participants took part in three studies involving recognition of identity and emotion in faces. We used signal detection theory to determine whether any perceptual biases exist in depression aside from decisional biases. We found lower sensitivity to happiness in general, and lower sensitivity to both happiness and sadness with ambiguous stimuli. Our use of highly-controlled face stimuli ensures that such asymmetry is truly perceptual in nature, rather than the result of studying expressions with inherently different discriminability. We found no systematic effect of depression on the perceptual interactions between face expression and identity. We also found that decisional strategies used in our task were different for people with depression and controls, but in a way that was highly specific to the stimulus set presented. We show through simulation that the observed perceptual effects, as well as other biases found in the literature, can be explained by a computational model in which channels encoding positive expressions are selectively suppressed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Imaginative resistance refers to cases in which one’s otherwise flexible imaginative capacity is constrained by an unwillingness or inability to imaginatively engage with a given claim. In three studies, we explored which specific imaginative demands engender resistance when imagining morally deviant worlds and whether individual differences in emotion predict the degree of this resistance. Participants read narratives containing either no harmful actions, harmful actions, or harmful actions with evaluative statements that the harms were morally justified, after which measures of moral judgment and imaginative resistance were assessed. In Study 1 (N = 176), participants resisted the notion that harmful actions could be morally acceptable in the world of a narrative regardless of the author’s claims about these actions but did not resist imagining that a perpetrator of harm could believe their actions to be morally acceptable. In Study 2 (N = 167) we replicated the findings of Study 1 and showed that imaginative resistance is greatest among participants who experience more negative affect in response to imagining harm and are lower in either trait anxiety or trait psychopathy. In Study 3 (N = 210) we show that this is the case even when the harms assessed include both low-severity (i.e., emotional harm) and high-severity (i.e., killing) cases. These findings suggest that people’s moral beliefs constrain their ability to imagine hypothetical moral alternatives, although this ability systematically varies on the basis of stable individual differences in emotion.

Evaluating other people's sincerity is a ubiquitous and important part of social interactions. Fourteen experiments (total N = 7,565; 10 preregistered; 11 in the main article, three in the online supplemental materials; with U.S. American and British members of the public, and French students) show that response speed is an important cue on which people base their sincerity inferences. Specifically, people systematically judged slower (vs. faster) responses as less sincere for a range of scenarios from trivial daily conversations to high stakes situations such as police interrogations. Our findings suggest that this is because slower responses are perceived to be the result of the responder suppressing automatic, truthful thoughts, and fabricating a novel answer. People also seem to have a rich lay theory of response speed, which takes into account a variety of situational factors. For instance, the effect of response delay on perceived sincerity is smaller if the response is socially undesirable, or if it can be attributed to mental effort. Finally, we showed that explicit instructions to ignore response speed can reduce the effect of response speed on judgments on sincerity. Our findings not only help ascertain the role of response speed in interpersonal inference making processes, but also carry important practical implication. In particular, the present study highlights the potential effects that may be observed in judicial settings, because the response speed of innocent suspects may mislead people to judge them as insincere and hence guilty. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Contains fulltext : 227546.pdf (Publisher’s version ) (Open Access) We predict how our actions will influence the world around us. Prevailing models in the action control literature propose that we use these predictions to suppress or "cancel" perception of expected action outcomes, to highlight more informative surprising events. However, contrasting normative Bayesian models in sensory cognition suggest that we are more, not less, likely to perceive what we expect - given that what we expect is more likely to occur. Here we adjudicated between these models by investigating how expectations influence perceptual decisions about action outcomes in a signal detection paradigm. Across three experiments, participants performed one of two manual actions that were sometimes accompanied by brief presentation of expected or unexpected visual outcomes. Contrary to dominant cancellation models but consistent with Bayesian accounts, we found that observers were biased to report the presence of expected action outcomes. There were no effects of expectation on sensitivity. Computational modeling revealed that the action-induced bias reflected a sensory bias in how evidence was accumulated rather than a baseline shift in decision circuits. Expectation effects remained in Experiments 2 and 3 when orthogonal cues indicated which finger was more likely to be probed (i.e. task-relevant). These biases toward perceiving expected action outcomes are suggestive of a mechanism that would enable generation of largely veridical representations of our actions and their consequences in an inherently uncertain sensory world. 12 p.

Flake, Pek, and Hehman (2017) recently demonstrated that metrics of structural validity are severely underreported in social and personality psychology. We apply their recommendations for the comprehensive assessment of structural validity to a uniquely large and varied dataset (N = 144496 experimental sessions) to investigate the psychometric properties of some of the most widely used self-report measures (k = 15 questionnaires, 26 subscales) in social and personality psychology. When assessed using the modal practice of considering only their internal consistency, 89% of scales appeared to possess good validity. Yet, when validity was assessed comprehensively (via internal consistency, immediate and delayed test-retest reliability, factor structure, and measurement invariance for median age and gender) only 4% demonstrated good validity. Furthermore, the less commonly a test is reported in the literature, the more likely it was to be failed (e.g., measurement invariance). This suggests that the pattern of under- reporting in the field may represent widespread hidden invalidity of the measures we use, and therefore pose a threat to many research findings. We highlight the degrees of freedom afforded to researchers in the assessment and reporting of structural validity. Similar to the better-known concept of p-hacking, we introduce the concept of validity hacking (v-hacking) and argue that it should be acknowledged and addressed.

The Taylor Aggression Paradigm (TAP) is a frequently-used laboratory measure of aggression. However, the flexibility inherent in its implementation and analysis can undermine its validity. To test whether the TAP is a valid aggression measure irrespective of this flexibility, we conducted two preregistered studies (Study 1 N = 177, Study 2 N = 167) of a standardized version of the TAP. Across both studies, TAP scores showed agreement with other laboratory aggression measures, were magnified by an experimental provocation manipulation, and were associated with traits typically linked to aggressive behavior. Mixed evidence was found for the external and discriminant validity of the task. Individual responses largely loaded onto a single component, suggesting that the aggregate scoring approach accurately represents the underlying data structure. These results provide preliminary support for the internal validity of this TAP approach and highlight the utility of preregistration in psychometric research.

The Combined Cognitive Bias Hypothesis proposes that emotional information processing biases associate with each other and may interact to conjointly influence mental health. Yet, little is known about the interrelationships amongst cognitive biases, particularly in adolescence. We used data from the CogBIAS longitudinal study (Booth et al. 2017), including 451 adolescents who completed measures of interpretation bias, memory bias, and a validated measure of general mental health in a typical population. We used a moderated network modelling approach to examine positive mental health related moderation of the cognitive bias network. Mental health was directly connected to positive and negative memory biases, and positive interpretation biases, but not negative interpretation biases. Further, we observed some mental health related moderation of the network structure. Network connectivity decreased with higher positive mental health scores. Network approaches allow us to model complex relationships amongst cognitive biases and develop novel hypotheses for future research.

The umbrella-term ‘executive functions’ (EF) includes various domain-general, goal-directed cognitive abilities responsible for behavioral self-regulation. The influential unity and diversity model of EF posits the existence of three correlated yet separable executive domains: inhibition, shifting and updating. These domains may be influenced by factors such as socioeconomic status (SES) and culture, possibly due to the way EF tasks are devised and to biased choice of stimuli, focusing on first-world testees. Here, we propose a FREE (Free Research Executive Function Evaluation) test battery that includes two open-access tasks for each of the three abovementioned executive domains to allow latent variables to be obtained. The tasks were selected from those that have been shown to be representative of each domain, that are not copyrighted and do not require special hardware/software to be administered. These tasks were adapted for use in populations with varying SES/schooling levels by simplifying tasks/instructions and using easily recognized stimuli such as pictures. Items are answered verbally and tasks are self-paced to minimize interference from individual differences in psychomotor and perceptual speed, to better isolate executive from other cognitive abilities. We tested these tasks on 146 early adolescents (aged 9–15 years) of both sexes and varying SES, because this is the age group in which the executive domains of interest become distinguishable and in order to confirm that SES effects were minimized. Performance was determined by Rate Correct Scores (correct answers divided by total time taken to complete blocks/trial), which consider speed-accuracy trade-offs. Scores were sensitive to the expected improvement in performance with age and rarely/inconsistently affected by sex and SES, as expected, with no floor or ceiling effects, or skewed distribution, thus suggesting their adequacy for diverse populations in these respects. Using structural equation modeling, evidence based on internal structure was obtained by replicating the three correlated-factor solution proposed by the authors of the model. We conclude that the FREE test battery, which is open access and described in detail, holds promise as a tool for research that can be adapted for a wide range of populations, as well as altered and/or complemented in coming studies., Fil: Zanini, Gislaine A. V. Departamento de Psicobiologia. Universidade Federal de São Paulo; Brazil., Fil: Miranda, Monica C. Programa de Pós Graduação em Psicologia-Psicossomática. Universidade Ibirapuera; Brazil., Fil: Cogo-Moreira, Hugo. School of Public Health. Li Ka Shing Faculty of Medicine, The University of Hong Kong; China., Fil: Nouri, Ali. Department of Education Studies, Faculty of Humanities. Malayer University; Iran., Fil: Fernández, Alberto Luis. Universidad Católica de Córdoba. Facultad de Filosofía y Humanidades; Argentina., Fil: Pompéia, Sabine. Departamento de Psicobiologia. Universidade Federal de São Paulo; Brazil.

A label’s entrenchment, its degree of use by members of a community, affects its perceived explanatory value even if the label provides no substantive information (Hemmatian & Sloman, 2018). The repository contains the data and materials related to three experiments that show the susceptibility of laypersons and mental health professionals to the entrenchment effect for diagnostic categories. Participants saw entrenched psychiatric and non-psychiatric diagnostic labels as better explanations than non-entrenched labels even if they are circular. Using scenarios involving experts who discuss unfamiliar diagnostic categories, we show that this preference is not due to violations of conversational norms, lack of reflectiveness or attentiveness, and the characters’ familiarity or unfamiliarity with the label. In Experiment 1, whether a label provided novel symptom information or not had no impact on lay responses, while its entrenchment enhanced ratings of explanation quality. The effect persisted in Experiment 2 for causally incoherent categories and regardless of direct provision of mechanistic information. The effect of entrenchment was partly related to induced causal beliefs about the category, even when they contradict explicitly provided information. Most participants in both experiments did not report any effect of entrenchment and the effect was present for those who did not. In Experiment 3, mental health professionals showed the effect using diagnoses that were mere shorthands for symptoms, despite a tendency to rate all explanations as unsatisfactory. The data suggest that bringing experts’ attention to the manipulation eliminates the effect. This pre-registration relates to the fourth experiment in this series, which attempts to disambiguate the social and epistemic utility of labels, and to provide additional controls.

According to the lexical quality hypothesis (Perfetti, 2007), differences in the orthographic, semantic, and phonological representations of words will affect individual reading performance. Whilst several studies have focused on orthographic precision and semantic coherence, few have considered phonological precision. The present study used a suite of individual difference measures to assess which components of lexical quality contributed to competition resolution in a masked priming experiment. The experiment measured form priming for word and pseudoword targets with dense and sparse neighbourhoods in 84 university students. Individual difference measures of language and cognitive skills were also collected and a principal component analysis was used to group these data into components. The data showed that phonological precision and NHD interacted with form priming. In participants with high phonological precision, the direction of priming for word targets with sparse neighbourhoods was facilitatory, while the direction for those with dense neighbourhoods was inhibitory. In contrast, people with low phonological precision showed the opposite pattern, but the interaction was non-significant. These results suggest that the component of phonological precision is linked to lexical competition for word recognition and that access to the mental lexicon during reading is affected by differing levels of phonological processing.

How do we decide what to say to ensure our meanings will be understood? The Rational Speech Act model (RSA, Frank & Goodman, 2012) asserts that speakers plan what to say by comparing the informativity of words in a particular context. We present the first example of an RSA model of sentence level (who-did-what-to-whom) meanings. In these contexts, the set of possible messages must be abstracted from entities in common ground (people and objects) to possible events (Jane eats the apple, Marco peels the banana), with each word contributing unique semantic content. How do speakers accomplish the transformation from context to compositional, informative messages? In a communication game, participants described transitive events (e.g. Jane pets the dog), with only two words, in contexts where two words either were or were not enough to uniquely identify an event. Adults chose utterances matching the predictions of the RSA even when there was no possible fully 'successful' utterance. Thus we show that adults’ communicative behavior can be described by a model that accommodates informativity in context, beyond the set of possible entities in common ground. This study provides the first evidence that adults' language production is affected, at the level of argument structure, by the graded informativity of possible utterances in context, and suggests that full- blown natural speech may result from speakers who model and adapt to the listener’s needs.

Many psychological theories predict U-shaped relationships: The effect of x is positive for low values of x, but negative for high values, or vice versa. Despite implying merely a change of sign, hypotheses about U-shaped functions are tested almost exclusively via quadratic regressions, an approach that imposes an arbitrary functional-form assumption that in some scenarios can lead to a 100% rate of false positives (e.g., the incorrect conclusion that y = log( x) is U shaped). Estimating two regression lines, one for low and one for high values of x, allows testing for a sign change without a functional-form assumption. I introduce the Robin Hood algorithm as a way to set the break point between the lines. This algorithm delivers higher power to detect U shapes than all the other break-point-setting alternatives I compared with it. The article includes simulations demonstrating the performance of the two-lines test and reanalyses of published results using this test. An app for running the two-lines test is available at http://webstimate.org/twolines .

Most people want to change some aspects of their personality, but does this phenomenon extend to moral character and to close others? Targets ( n = 800) rated their personality traits and reported how much they wanted to change on each trait; well-acquainted informants ( n = 958) rated targets’ personality traits and how much they wanted the targets to change on those same traits. Targets and informants reported a lower desire to change more morally relevant traits (e.g., honesty, compassion, fairness) compared with less morally relevant traits (e.g., anxiety, sociability, productiveness)—even after we controlled for current trait levels. Moreover, although targets generally wanted to improve more on traits that they had less desirable levels of, and informants wanted their targets to improve more on those traits as well, targets’ moral change goals were less calibrated to their current trait levels. Finally, informants wanted targets to change in similar ways, but to a lesser extent, than targets themselves did. These findings suggest that moral considerations take a back seat when it comes to self-improvement.

Individualism appears to have increased over the past several decades, yet most research documenting this shift has been limited to the study of a handful of highly-developed countries. Is the world becoming more individualistic as a whole? If so, why? To address these questions, here we examine 51 years of data on individualistic practices and values across 77 countries. Our findings suggest that individualism is indeed rising in most of societies we tested. Despite dramatic shifts towards greater individualism around the world, cultural differences remain sizeable. Moreover, cultural differences are primarily linked to changes in socioeconomic development, and to a lesser extent to shifts in pathogen prevalence, disaster frequency, and climatic stress.