Journal of Intelligence

What are consequential world problems? As “grand societal challenges”, one might define them as problems that affect a large number of people, perhaps even the entire planet, including problems such as climate change, distributive justice, world peace, world nutrition, clean air and clean water, access to education, and many more. The “Sustainable Development Goals”, compiled by the United Nations, represent a collection of such global problems. From my point of view, these problems can be seen as complex. Such complex problems are characterized by the complexity, connectivity, dynamics, intransparency, and polytely of their underlying systems. These attributes require special competencies for dealing with the uncertainties of the given domains, e.g., critical thinking. My position is that it is not IQ, but complex problem-solving competencies for dealing with complex and dynamic situations, that is important for handling consequential global problems. These problems require system competencies, i.e., competencies that go beyond analytical intelligence, and comprise systems understanding as well as systems control. Complex problem solving is more than analytic intelligence. Full article

One of the best-established findings in intelligence research is the pattern of positive correlations among various intelligence tests. Although this so-called positive manifold became the conceptual foundation of many theoretical accounts of intelligence, the very nature of it has remained unclear. Only recently, Process Overlap Theory (POT) proposed that the positive manifold originated from overlapping domain-general, executive processes. To test this assumption, the functional relationship between different aspects of executive attention and the positive manifold was investigated by re-analyzing an existing dataset (N = 228). Psychometric reasoning, speed, and memory performance were assessed by a short form of the Berlin Intelligence Structure test. Two aspects of executive attention (sustained and selective attention) and speed of decision making were measured by a continuous performance test, a flanker task, and a Hick task, respectively. Traditional structural equation modeling, representing the positive manifold by a g factor, as well as network analyses, investigating the differential effects of the two aspects of executive attention and speed of decision making on the specific correlations of the positive manifold, suggested that selective attention, sustained attention, and speed of decision making explained the common but not the unique portions of the positive manifold. Thus, we failed to provide evidence for POT’s assumption that the positive manifold is the result of overlapping domain-general processes. This does not mean that domain-general processes other than those investigated here will not be able to show the pattern of results predicted by POT. Full article

In 1990, Salovey and Mayer introduced emotional intelligence (EI). Thirty-one years later, a proliferation of interventions to improve people’s EI has taken place. A literature review of studies focused on enhancing the EI of college students revealed a notable gap. When educational material for training sessions included all of the skills in an EI model, researchers usually utilized lengthy durations (i.e., 11–56 h). Few successful investigations employed an ultra-brief (i.e., ≤1 h) approach. The present study examined the feasibility of training using a minimalistic timeframe and a sample of freshmen; their transitional challenges from high school to college mark them as an appropriate target population. Employing a quasi-experimental one-group pretest–posttest design, the recruited participants (n = 75) experienced an ultra-brief intervention highlighting the complete skill-set in the Ability Emotional Intelligence model. Findings from a one-way repeated measures MANOVA indicated improvement transpired in two of four MSCEIT scores (i.e., perception and facilitation). The merit of the present study is delineated using Orsmond and Cohn’s five objectives for feasibility investigations. In addition, implications of the results and possible applications are proposed. Full article

The Woodcock-Johnson IV Tests of Cognitive Abilities (WJ IV COG) is a comprehensive assessment battery designed to assess broad and narrow cognitive abilities, as defined by the Cattell-Horn-Carroll (CHC) theory of intelligence. Previous studies examined the invariance of the WJ assessments across sex and age groups using factor analytic methods. Psychometric network modeling is an alternative methodology that can address both direct and indirect relationships among the observed variables. In this study, we employed psychometric network modeling to examine the invariance of the WJ IV COG across sex and age groups. Using a normative sample (n = 4212 participants) representative of the United States population, we tested the extent to which the factorial structure of the WJ IV COG aligned with CHC theory for the school-aged sample. Next, we used psychometric network modeling as a data-driven method to investigate whether the network structure of the WJ IV COG remains similar across different sex and age (age 6 to 19, inclusively) groups. Our results showed that the WJ IV COG maintained the same network structure across all age and sex groups, although the network structure at younger ages indicated weaker relationships among some subtests. Overall, the results provide construct validity evidence for the WJ IV COG, based on both theoretical and data-driven methods. Full article

Process overlap theory (POT) is a new theoretical framework designed to account for the general factor of intelligence (g). According to POT, g does not reflect a general cognitive ability. Instead, g is the result of multiple domain-general executive attention processes and multiple domain-specific processes that are sampled in an overlapping manner across a battery of intelligence tests. POT explains several benchmark findings on human intelligence. However, the precise nature of the executive attention processes underlying g remains unclear. In the current paper, we discuss challenges associated with building a theory of individual differences in attention and intelligence. We argue that the conflation of psychological theories and statistical models, as well as problematic inferences based on latent variables, impedes research progress and prevents theory building. Two studies designed to illustrate the unique features of POT relative to previous approaches are presented. In Study 1, a simulation is presented to illustrate precisely how POT accounts for the relationship between executive attention processes and g. In Study 2, three datasets from previous studies are reanalyzed (N = 243, N = 234, N = 945) and reveal a discrepancy between the POT simulated model and the unity/diversity model of executive function. We suggest that this discrepancy is largely due to methodological problems in previous studies but also reflects different goals of research on individual differences in attention. The unity/diversity model is designed to facilitate research on executive function and dysfunction associated with cognitive and neural development and disease. POT is uniquely suited to guide and facilitate research on individual differences in cognitive ability and the investigation of executive attention processes underlying g. Full article

This article introduces a 6P framework for understanding intelligence, as well as the theories and tests that are derived from it. The 6Ps in the framework are purpose, press, problems, persons, processes, and products underlying intelligence. Each of the 6Ps is considered in turn. We argue that although the purpose of intelligence is culturally universal, the other Ps can vary at least somewhat over time and space. A single theory or test of intelligence represents a particular configuration of the 6Ps, but other configurations of the 6Ps might yield different theories and different tests. Full article

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain–behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5–18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role ‘between’ brain and behavior. We discuss implications and possible avenues for future studies. Full article

Fully developing the talents of all students is a fundamental goal for personal well-being and development and ultimately for global societal innovation and flourishing. However, in this paper we focus on what we believe is an often neglected and underdeveloped population, that of the gifted. We draw from the cognitive aptitude and gifted education research literatures to make the case that solutions to consequential real-world problems can be greatly enhanced by more fully developing the talents of the intellectually gifted population, which we operationalize in this paper as roughly the top 5% of cognitive talent. Should well-supported high achievers choose to solve them, these problems span health, science, economic growth, and areas unforeseen. We draw from longitudinal research on intellectually precocious students and retrospective research on leaders and innovators in society, showing that mathematical, verbal, and spatial aptitudes are linked to societal innovation. We then discuss two remaining fundamental challenges: the identification of disadvantaged and marginalized groups of students who have traditionally been neglected in selection for gifted programming suited to their current developmental needs, and the building of skills beyond academic ones, specifically in the related areas of open-minded thinking and intellectual humility. Full article

The study of socio-cognitive abilities emerged from intelligence research, and their specificity remains controversial until today. In recent years, the psychometric structure of face cognition (FC)—a basic facet of socio-cognitive abilities—was extensively studied. In this review, we summarize and discuss the divergent psychometric structures of FC in easy and difficult tasks. While accuracy in difficult tasks was consistently shown to be face-specific, the evidence for easy tasks was inconsistent. The structure of response speed in easy tasks was mostly—but not always—unitary across object categories, including faces. Here, we compare studies to identify characteristics leading to face specificity in easy tasks. The following pattern emerges: in easy tasks, face specificity is found when modeling speed in a single task; however, when modeling speed across multiple, different easy tasks, only a unitary factor structure is reported. In difficult tasks, however, face specificity occurs in both single task approaches and task batteries. This suggests different cognitive mechanisms behind face specificity in easy and difficult tasks. In easy tasks, face specificity relies on isolated cognitive sub-processes such as face identity recognition. In difficult tasks, face-specific and task-independent cognitive processes are employed. We propose a descriptive model and argue for FC to be integrated into common taxonomies of intelligence. Full article

When meeting someone at zero acquaintance, we make assumptions about each other that encompass emotional states, personality traits, and even cognitive abilities. Evidence suggests individuals can accurately detect psychopathic personality traits in strangers based on short video clips or photographs of faces. We present an in-depth examination of this ability. In two studies, we investigated whether high psychopathy traits are perceivable and whether other traits affect ratings of psychopathic traits in the sense of a halo effect. On the perceiver’s end, we additionally examined how cognitive abilities and personality traits of the responders affect these ratings. In two studies (n₁ = 170 community adults from the USA, n₂ = 126 students from Australia), participants rated several targets on several characteristics of psychopathy, as well as on attractiveness, masculinity, sympathy, trustworthiness, neuroticism, intelligence, and extraversion. Results show that responders were generally able to detect psychopathy. Responders generally came to a consensus in their ratings, and using profile similarity metrics, we found a weak relation between ratings of psychopathy and the targets’ psychopathy level as determined by the Psychopathy Checklist: Short Version. Trait ratings, though, were influenced by the ratings of other traits like attractiveness. Finally, we found accuracy in the perception of psychopathy was positively related to fluid intelligence but unrelated to emotion perception ability. Full article

This paper presents a meta-analysis of the links between intelligence test scores and creative achievement. A three-level meta-analysis of 117 correlation coefficients from 30 studies found a correlation of r = .16 (95% CI: .12, .19), closely mirroring previous meta-analytic findings. The estimated effects were stronger for overall creative achievement and achievement in scientific domains than for correlations between intelligence scores and creative achievement in the arts and everyday creativity. No signs of publication bias were found. We discuss theoretical implications and provide recommendations for future studies. Full article

When faced with the task of trying to “read” a stranger’s thoughts, what cues can perceivers use? We explore two predictors of empathic accuracy (the ability to accurately infer another person’s thoughts): use of stereotypes about the target’s group, and use of the target’s own words. A sample of 326 White American undergraduate students were asked to infer the dynamic thoughts of Middle Eastern male targets, using Ickes’ (Ickes et al. 1990) empathic accuracy paradigm. We predicted use of stereotypes would reduce empathic accuracy because the stereotypes would be negative and inaccurate. However, more stereotypical inferences about the target’s thoughts actually predicted greater empathic accuracy, a pattern in line with past work on the role of stereotypes in empathic accuracy (Lewis et al. 2012), perhaps because the stereotypes of Middle Easterners (collected from a sample of 60 participants drawn from the same population) were less negative than expected. In addition, perceivers who inferred that the targets were thinking thoughts that more closely matched what the target was saying out loud were more empathically accurate. Despite the fact that words can be used intentionally to obscure what a target is thinking, they appear to be a useful cue to empathic accuracy, even in tricky contexts that cross cultural lines. Full article

In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research. Full article

Individual differences in understanding other people’s emotions have typically been studied with recognition tests using prototypical emotional expressions. These tests have been criticized for the use of posed, prototypical displays, raising the question of whether such tests tell us anything about the ability to understand spontaneous, non-prototypical emotional expressions. Here, we employ the Emotional Accuracy Test (EAT), which uses natural emotional expressions and defines the recognition as the match between the emotion ratings of a target and a perceiver. In two preregistered studies (N_total = 231), we compared the performance on the EAT with two well-established tests of emotion recognition ability: the Geneva Emotion Recognition Test (GERT) and the Reading the Mind in the Eyes Test (RMET). We found significant overlap (r > 0.20) between individuals’ performance in recognizing spontaneous emotions in naturalistic settings (EAT) and posed (or enacted) non-verbal measures of emotion recognition (GERT, RMET), even when controlling for individual differences in verbal IQ. On average, however, participants reported enjoying the EAT more than the other tasks. Thus, the current research provides a proof-of-concept validation of the EAT as a useful measure for testing the understanding of others’ emotions, a crucial feature of emotional intelligence. Further, our findings indicate that emotion recognition tests using prototypical expressions are valid proxies for measuring the understanding of others’ emotions in more realistic everyday contexts. Full article

In this article, we provide preliminary evidence for the ‘hypersensitivity hypothesis’, according to which Emotional Intelligence (EI) functions as a magnifier of emotional experience, enhancing the effect of emotion and emotion information on thinking and social perception. Measuring ability EI, and in particular Emotion Understanding, we describe an experiment designed to determine whether, relative to those low in EI, individuals high in EI were more affected by the valence of a scenario describing a target when making an affective social judgment. Employing a sample of individuals from the general population, high EI participants were found to provide more extreme (positive or negative) impressions of the target as a function of the scenario valence: positive information about the target increased high EI participants’ positive impressions more than it increased low EI participants’ impressions, and negative information increased their negative impressions more. In addition, EI affected the amount of recalled information and this led high EI individuals to intensify their affective ratings of the target. These initial results show that individuals high on EI may be particularly sensitive to emotions and emotion information, and they suggest that this hypersensitivity might account for both the beneficial and detrimental effects of EI documented in the literature. Implications are discussed. Full article

This paper provides a meta-analytic update on the relationship between intelligence and divergent thinking (DT), as research on this topic has increased, and methods have diversified since Kim’s meta-analysis in 2005. A three-level meta-analysis was used to analyze 849 correlation coefficients from 112 studies with an overall N = 34,610. The overall effect showed a significant positive correlation of r = .25. This increase of the correlation as compared to Kim’s prior meta-analytic findings could be attributed to the correction of attenuation because a difference between effect sizes prior-Kim vs. post-Kim was non-significant. Different moderators such as scoring methods, instructional settings, intelligence facets, and task modality were tested together with theoretically relevant interactions between some of these factors. These moderation analyses showed that the intelligence–DT relationship can be higher (up to r = .31–.37) when employing test-like assessments coupled with be-creative instructions, and considering DT originality scores. The facet of intelligence (g vs. g_f vs. g_c) did not affect the correlation between intelligence and DT. Furthermore, we found two significant sample characteristics: (a) average sample age was positively associated with the intelligence–DT correlation, and (b) the intelligence–DT correlation decreased for samples with increasing percentages of females in the samples. Finally, inter-moderator correlations were checked to take potential confounding into account, and also publication bias was assessed. This meta-analysis provides a comprehensive picture of current research and possible research gaps. Theoretical implications, as well as recommendations for future research, are discussed. Full article

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests. Similarly, some scholars argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach. Full article

Working memory capacity (WMC) and fluid intelligence (Gf) are highly correlated, but what accounts for this relationship remains elusive. Process-overlap theory (POT) proposes that the positive manifold is mainly caused by the overlap of domain-general executive processes which are involved in a battery of mental tests. Thus, executive processes are proposed to explain the relationship between WMC and Gf. The current study aims to (1) achieve a relatively purified representation of the core executive processes including shifting and inhibition by a novel approach combining experimental manipulations and fixed-links modeling, and (2) to explore whether these executive processes account for the overlap between WMC and Gf. To these ends, we reanalyzed data of 215 university students who completed measures of WMC, Gf, and executive processes. Results showed that the model with a common factor, as well as shifting and inhibition factors, provided the best fit to the data of the executive function (EF) task. These components explained around 88% of the variance shared by WMC and Gf. However, it was the common EF factor, rather than inhibition and shifting, that played a major part in explaining the common variance. These results do not support POT as underlying the relationship between WMC and Gf. Full article

This study examined the unfolding in real time of original ideas during divergent thinking (DT) in five- to six-year-olds and related individual differences in DT to executive functions (EFs). The Alternative Uses Task was administered with verbal prompts that encouraged children to report on their thinking processes while generating uses for daily objects. In addition to coding the originality of each use, the domain-specific DT processes memory retrieval and mental operations were coded from children’s explanations. Six EF tasks were administered and combined into composites to measure working memory, shifting, inhibition, and selective attention. The results replicated findings of a previous study with the same children but at age four years: (1) there was a serial order effect of the originality of uses; and (2) the process mental operations predicted the originality of uses. Next, the results revealed that both domain-general EFs and domain-specific executive processes played a role in the real-time unfolding of original ideas during DT. Particularly, the DT process mental operations was positively related to the early generation of original ideas, while selective attention was negatively related to the later generation of original ideas. These findings deepen our understanding of how controlled executive processes operate during DT. Full article