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We investigated the relationships between creative achievement, cognitive ability, temperament, and vocational interests using a large and diverse internet-based sample. Ten creative domains (visual arts, music, creative writing, dance, drama, architecture, humor, scientific discovery, inventions, culinary arts) were positively associated with higher cognitive ability, intellect and extraversion, and lower agreeableness. With regard to cognitive ability, there was no evidence for the threshold effect on achievements. With regard to age, younger individuals endorsed a greater number of low-level achievements and older individuals more high-level achievements across the 10 creative domains. Other characteristics of individual differences (e.g., vocational interests) were more domain-specific for predicting creative achievement. We also introduce a revised method for the assessment and scoring of creative achievements, and discuss suggestions for future research.

Abstract. The predictive accuracy of personality-criterion regression models may be improved with statistical learning (SL) techniques. This study introduced a novel SL technique, BISCUIT (Best Items Scale that is Cross-validated, Unit-weighted, Informative, and Transparent). The predictive accuracy and parsimony of BISCUIT were compared with three established SL techniques (the lasso, elastic net, and random forest) and regression using two sets of scales, for five criteria, across five levels of data missingness. BISCUIT’s predictive accuracy was competitive with other SL techniques at higher levels of data missingness. BISCUIT most frequently produced the most parsimonious SL model. In terms of predictive accuracy, the elastic net and lasso dominated other techniques in the complete data condition and in conditions with up to 50% data missingness. Regression using 27 narrow traits was an intermediate choice for predictive accuracy. For most criteria and levels of data missingness, regression using the Big Five had the worst predictive accuracy. Overall, loss in predictive accuracy due to data missingness was modest, even at 90% data missingness. Findings suggest that personality researchers should consider incorporating planned data missingness and SL techniques into their designs and analyses.

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirically and quantitatively derived dimensional classification system designed to describe the features of psychopathology and, ultimately, to replace categorical nosologies. Among the constructs that HiTOP organizes are "symptom components" and "maladaptive traits," but past HiTOP publications have not fully explicated the distinction between symptoms and traits. We propose working definitions of symptoms and traits and explore challenges, exceptions, and remaining questions. Specifically, we propose that the only systematic difference between symptoms and traits in HiTOP is one of time frame. Maladaptive traits are dispositional constructs that describe persistent tendencies to manifest features of psychopathology, whereas symptoms are features of psychopathology as they are manifest during any specific time period (from moments to days to months). This has the consequence that almost every HiTOP dimension, at any level of the hierarchy, can be assessed as either a trait or a symptom dimension, by adjusting the framing of the assessment. We discuss the implications of these definitions for causal models of the relations between symptoms and traits and for distinctions between psychopathology, normal personality variation, and dysfunction.

Personality is not the most popular subfield of psychology. But, in one way or another, personality psychologists have played an outsized role in the ongoing “credibility revolution” in psychology. Not only have individual personality psychologists taken on visible roles in the movement, but our field’s practices and norms have now become models for other fields to emulate (or, for those who share Baumeister’s (2016, https://doi.org/10.1016/j.jesp.2016.02.003) skeptical view of the consequences of increasing rigor, a model for what to avoid). In this article we discuss some unique features of our field that may have placed us in an ideal position to be leaders in this movement. We do so from a subjective perspective, describing our impressions and opinions about possible explanations for personality psychology’s disproportionate role in the credibility revolution. We also discuss some ways in which personality psychology remains less-than-optimal, and how we can address these flaws.

Personality traits are important predictors of health behaviors, healthcare utilization, and health outcomes. However, we know little about the role of personality traits for emergency department outcomes. The present study used data from 200 patients (effective Ns range from 84 to 191), who were being discharged from the emergency department at an urban hospital, to investigate whether the Big Five personality traits were associated with post-discharge outcomes (i.e., filling prescriptions, following up with primary care physician, making an unscheduled return to the emergency department). Using logistic regression, we found few associations among the broad Big Five domains and post-discharge outcomes. However, results showed statistically significant associations between specific Big Five items (e.g., “responsible”) and the three post-discharge outcomes. This study demonstrates the feasibility of assessing personality traits in an emergency medicine setting and highlights the utility of having information about patients’ personality tendencies for predicting post-discharge compliance.

Abstract. In pursuit of a more systematic and comprehensive framework for personality assessment, we introduce procedures for assessing personality traits at the lowest level: nuances. We argue that constructing a personality taxonomy from the bottom up addresses some of the limitations of extant top-down assessment frameworks (e.g., the Big Five), including the opportunity to resolve confusion about the breadth and scope of traits at different levels of the organization, evaluate unique and reliable trait variance at the item level, and clarify jingle/jangle issues in personality assessment. With a focus on applications in survey methodology and transparent documentation, our procedures contain six steps: (1) identification of a highly inclusive pool of candidate items, (2) programmatic evaluation and documentation of item characteristics, (3) test-retest analyses of items with adequate qualitative and quantitative properties, (4) analysis of cross-ratings from multiple raters for items with adequate retest reliability, (5) aggregation of ratings across diverse samples to evaluate generalizability across populations, (6) evaluations of predictive utility in various contexts. We hope these recommendations are the first step in a collaborative effort to identify a comprehensive pool of personality nuances at the lowest level, enabling subsequent construction of a robust hierarchy – from the bottom up.

Claude Shannon’s groundbreaking work on information theory (Shannon, 1948a) was published just as the field of psychological testing was reaching its potential. Many of the fundamental underpinnings of the psychological testing theory were proposed in this same era, and the application of these ideas over the ensuing decades has greatly informed our understanding across numerous psychological domains, including individual differences in personality, cognitive abilities, interests, and much more. While the prospect of integrating information theory into psychological assessment was initially received with great enthusiasm, it was quickly and definitively dismissed by Lee Cronbach (1955a), mainly on the grounds that it was incompatible with the practical demands of psychological testing (e.g., limited testing time, relatively small samples). In this chapter, we reconsider Cronbach’s rationale in light of recent technological advancements brought about by the “information age,” and propose that reintroducing information-theoretic approaches to psychological assessment can advance our knowledge of personality, person-perception, and personality assessment. We conclude by providing several examples of research applications that have already invoked an information theory approach to assessment.

The current study utilizes the current COVID-19 pandemic to highlight the importance of accounting for the influence of external political and economic factors in personality public-health research. We investigated the extent to which systemic factors modify the relationship between personality and pandemic response. Results shed doubt on the cross-cultural generalizability of common big-five factor models. Individual differences only predicted government compliance in autocratic countries and in countries with income inequality. Personality was only predictive of mental health outcomes under conditions of state fragility and autocracy. Finally, there was little evidence that the big five traits were associated with preventive behaviors. Our ability to use individual differences to understand policy-relevant outcomes changes based on environmental factors and must be assessed on a trait-by-trait basis, thus supporting the inclusion of systemic political and economic factors in individual differences models.

The predictive accuracy of personality-criterion regression models may be improved with statistical learning (SL) techniques. This study introduced a novel SL technique, BISCUIT (Best Items Scale that is Cross-validated, Unit-weighted, Informative and Transparent). The predictive accuracy and parsimony of BISCUIT was compared with three established SL techniques (the lasso, elastic net, and random forest) and regression using two sets of scales, for five criteria, across five levels of data missingness. BISCUIT’s predictive accuracy was competitive with other SL techniques at higher levels of data missingness. BISCUIT most frequently produced the most parsimonious SL model. The elastic net and lasso dominated other techniques in terms of predictive accuracy with complete data and in conditions with up to 50% data missingness. In terms of predictive accuracy, regression using 27 narrow traits was an intermediate choice. For most criteria and levels of data missingness, regression using the Big Five had the worst predictive accuracy. Overall, loss in predictive accuracy due to data missingness was modest, even at 90% data missingness. Findings suggest that personality researchers should consider incorporating planned data missingness and SL techniques into their designs and analyses.

Researchers have shown an interest in the aggregated Big Five personality of U.S. states, but typically they have relied on scores from a single sample (Rentfrow, Gosling, & Potter, 2008). We examine the replicability of U.S. state personality scores from two studies (Rentfrow et al., 2008; Rentfrow, Gosling, Jokela, & Stillwell, 2013) across a total of seven samples, two of them new. Same-trait correlations across samples are, on average, positive for all five traits, indicating score agreement. Additionally, three traits (Conscientiousness, Neuroticism, and Openness) show strongly consistent patterns of correlations with sociodemographic variables across samples. We find rank order stability in state personality scores for a 16-year period (1999-2015).

Background Identifying the factors that predict non-adherence to recommended preventive pediatric care is necessary for the development of successful interventions to improve compliance. Purpose Given the substantial decline in well-child visits and influenza vaccinations, we sought to examine sociodemographic (i.e., parent age, education, employment status, child age, insurance coverage, household size, race and ethnicity, income, COVID-19 incidence in state) and psychosocial (i.e., child temperament, parent mental health, parent personality traits) factors associated with preventative pediatric care (well-child visits, influenza vaccines) during the COVID-19 pandemic. Methods As part of a larger, ongoing study, 1875 parents (96% mothers, 65% age 35 or younger, 58% with a college degree) reported whether they had missed any recommended or scheduled well-child visits since the pandemic and whether they had vaccinated their child against the flu. Using data collected during fall 2020, we examine differences in these health outcomes across social/demographic factors and psychological profiles. In addition, we use lasso logistic regression models to (1) estimate the accuracy with which we can predict adherence from these characteristics and (2) identify factors most strongly, independently associated with adherence. Results Parent psychological factors were associated with outcomes above and beyond known demographic and social factors. For example, parent industriousness and orderliness were associated with greater likelihoods of attending well-child visits and vaccinating children, while parent conservatism and creativity were associated with lower rates. We also replicate prior work documenting that health insurance, income, and household size are major factors in receiving adequate pediatric care. Conclusions Adherence to preventive pediatric care varies as a function of psychological factors, suggesting that the current system of pediatric care favors some psychological profiles over others. However, the specific traits associated with non-adherence point to potentially fruitful interventions, specifically around increasing functional proximity.

We discuss methods of data collection and analysis that emphasize the power of individual personality items for predicting real world criteria (e.g., smoking, exercise, self-rated health). These methods are borrowed by analogy from radio astronomy and human genomics. Synthetic Aperture Personality Assessment (SAPA) applies a matrix sampling procedure that synthesizes very large covariance matrices through the application of massively missing at random data collection. These large covariance matrices can be applied, in turn, in Persome Wide Association Studies (PWAS) to form personality prediction scores for particular criteria. We use two open source data sets (N=4,000 and 126,884 with 135 and 696 items respectively) for demonstrations of both of these procedures. We compare these procedures to the more traditional use of “Big 5” or a larger set of narrower factors (the “little 27”). We argue that there is more information at the item level than is used when aggregating items to form factorially derived scales.

Recent findings in psychological research have begun to illuminate cognitive and neural mechanisms of imagination and mental imagery, and have highlighted its essential role for a number of important outcomes, including outcomes relevant for the study of psychopathology and psychotherapy. Scientific study of imagination, however, has been constrained by the virtue of being framed mainly as an ability for mental imagery. Here we propose that imagination is a widespread phenomenon that we all engage in, and which affects a wide range of important outcomes beyond more commonly studied constructs like creativity. Thus, the Four-Factor Imagination Scale (FFIS) focuses on features of the imaginative process, and measures imagination in terms of individual differences in those features, including frequency, complexity, emotional valence, and directedness of imagination. Study 1 consisted of construct elicitation and generation of a large pool of candidate survey items. Study 2 (N = 378) conducted exploratory quantitative analysis on the preliminary pool of candidate items in a larger sample, revealing four distinct factors of the designed items. Study 3 (N = 10,410) confirmed the structure of the preliminary items, and reported internal consistency and unidimensionality, as well as convergent and discriminant validity of the resultant scales. The FFIS confirms that imagination is multi-faceted in nature, and is better approached as a constellation of more narrowly measurable constructs.

BACKGROUND: While there has been increasing interest in patient engagement, few measures are publicly available and suitable for patients with limited health literacy. OBJECTIVE: We sought to develop a Consumer Health Activation Index (CHAI) for use among diverse patients. METHODS: Expert opinion, a systematic literature review, focus groups and cognitive interviews with patients were utilized to create and revise a potential set of items. Psychometric testing guided by item response theory was then conducted among 301 English-speaking, community-dwelling adults. This included differential item functioning analyses to evaluate item performance across participant health literacy levels. To determine construct validity, CHAI scores were compared to scales measuring similar personality constructs. Associations between the CHAI, physical and mental health established predictive validity. A second study among 9,478 adults was used to confirm CHAI associations with health outcomes. RESULTS: Exploratory factor analyses revealed a single factor solution with a 10-item scale. The CHAI showed good internal consistency (alpha=0.81) and moderate test-retest reliability (ICC=0.53). Its reading grade level was found to be at the 6(th) grade. Moderate to strong correlations were found with similar constructs (Multidimensional Health Locus of Control; r=0.38, p

article i nfo The ability to locate and orient ourselves with respect to environmental space is known as sense of direction ("SOD"). While there is considerable evidence for the predictive utility of self-report measures of this psycholog- ical construct, relatively little research has investigated the psychometric properties of the self-report scale by which it is most commonly measured - the Santa Barbara Sense of Direction scale (SBSOD, Hegarty et al., 2002) - or the broader personality correlates. The present study evaluated the factor structure of the SBSOD fol- lowing administration to 12,155 individuals and situated it among prominent sources of individual differences, specifically the Big Five personality traits and intelligence. Findings suggest that the SBSOD scale has relatively high general factor saturation, and that a considerable portion of the variance in SBSOD scores is explained by other personality traits, including Conscientiousness (r = 0.33), Intellect (r = 0.27), Emotional Stability (r = 0.26), and Extraversion (r = 0.23). Cognitive ability was less highly correlated with SBSOD scores when mea- sured at the level of general intelligence (r = 0.11) and in terms of mental rotation ability (r = .07). Recommen- dations are given for revision of the SBSOD scale based on item-level analyses.

The majority of life narrative research is performed using trained human coders. In contrast, automated linguistic analysis is oft employed in the study of verbal behaviors. These two methodological approaches are directly compared to determine the utility of automated linguistic analysis for the study of life narratives. In a study of in-person interviews (N = 158) and a second study of life stories collected online (N = 242), redemption scores are compared to the output of the Linguistic Inquiry and Word Count (Pennebaker, Francis & Booth, 2001). Additionally, patterns of language are found using exploratory principal components analysis. In both studies, redemption scores are modestly correlated with some LIWC categories and unassociated with the components. Patterns of language do not replicate across samples, indicating that the structure of language does not extend to a broader population. Redemption scores and linguistic components are independent predictors of life satisfaction up to 3 years later. These studies converge on the finding that human-coded redemption and automated linguistic analysis are complementary and nonredundant methods of analyzing life narratives, and considerations for the study of life narratives are discussed.

For all of its versatility and sophistication, the extant toolkit of cognitive ability measures lacks a public-domain method for large-scale, remote data collection. While the lack of copyright protection for such a measure poses a theoretical threat to test validity, the effective magnitude of this threat is unknown and can be offset by the use of modern test-development techniques. To the extent that validity can be maintained, the benefits of a public-domain resource are considerable for researchers, including: cost savings; greater control over test content; and the potential for more nuanced understanding of the correlational structure between constructs. The International Cognitive Ability Resource was developed to evaluate the prospects for such a public-domain measure and the psychometric properties of the first four item types were evaluated based on administrations to both an offline university sample and a large online sample. Concurrent and discriminative validity analyses suggest that the public-domain status of these item types did not compromise their validity despite administration to 97,000 participants. Further development and validation of extant and additional item types are recommended.

Two large samples were collected to evaluate the structure of traits in the temperament domain. In both samples, participants were administered random subsets of public-domain personality items from a larger pool of approximately 700 items. These data broadly cover the most widely used, public-domain measures of personality (though this breadth is not likely free of theoretical bias). When combined with a third, previously-shared dataset that used the same methodological design, the sample includes more than 125,000 participants from more than 220 countries and regions. Re-use potential includes many types of structural, correlational, and network analyses of personality and a wide range of demographic and psychographic constructs. The data are available in both rdata and csv formats.

These data were collected to evaluate the structure of personality constructs in the temperament domain. In the context of modern personality theory, these constructs are typically construed in terms of the Big Five (Conscientiousness, Agreeableness, Neuroticism, Openness, and Extraversion) though several additional constructs were included here. Approximately 24,000 individuals were administered random subsets of 696 items from 92 public-domain personality scales using the Synthetic Aperture Personality Assessment method between December 8, 2013 and July 26, 2014. The data are available in rdata format and are accompanied by documentation stored as a text file. Re-use potential include many types of structural and correlational analyses of personality.

The network perspective represents a novel contribution to personality theory by conceptualising personality traits as emerging from the mutual dependencies between fundamental and causal affective, behavioural, and cognitive components. We argue that incorporating a more nuanced biological and developmental perspective to causality and a more precise approach to affective, behavioural, cognitive and motivational components may serve to enrich the network perspective. Although the graphical approach to modelling personality is aesthetically pleasing, analytic techniques are not yet available to put network models to the (quantitative) test. Copyright © 2012 John Wiley & Sons, Ltd.

Previous research provides disparate accounts of the putative association between creativity and psychopathology, including schizotypy, psychoticism, hypomania, bipolar disorder, ADHD, and autism spectrum disorders. To examine these association, healthy, non-clinical participants completed several psychopathology-spectrum measures, often postulated to associate with creativity: the Schizotypal Personality Questionnaire, the Psychoticism scale, the Personality Inventory for DSM-5, the Hypomanic Personality Scale, the Attention Deficit/Hyperactivity Disorder scale, the Beck Depression Inventory, and the Autism-Spectrum Quotient. The goal of Study 1 was to evaluate the factor structure of these dimensional psychopathology measures and, in particular, to evaluate the case for a strong general factor(s). None of the factor solutions between 1 and 10 factors provided a strong fit with the data based on the most commonly used metrics. The goal of Study 2 was to determine whether these psychopathology scales predict, independently, two measures of creativity: 1. a measure of participants’ real-world creative achievements, and 2. divergent thinking, a laboratory measure of creative cognition. After controlling for academic achievement, psychoticism and hypomania reliably predicted real-world creative achievement and divergent thinking scored with the consensual assessment technique. None of the psychopathology-spectrum scales reliably predicted divergent thinking scored with the manual scoring method. Implications for the potential links between several putative creative processes and risk factors for psychopathology are discussed.

Personality is an abstraction used to describe and explain the coherent patterning over time and space of affect, cognition, and desire as they result in behaviour for an individual. This unique patterning or individual signature reflects a complex set of dynamic processes that can be modelled in terms of rates of growth and decay of excitation and inhibition in response to environmental cues. These processes reflect genetically based biological sensitivities that may be modelled by the differential equations of the Dynamics of Action. The important parameters within individuals reflect rates of change; the important parameters between individuals reflect average levels, frequencies and persistence. Going beyond models within and between individuals, it is also necessary to consider how individuals choose their environments. We will consider how analyses of these three levels (within individuals, between individuals, and between groups of individuals) can lead to different descriptions about the structure and processes of personality.

A prominent goal of individual differences research is the development and testing of models which predict important life outcomes. Prior work suggests that the most predictive models for many outcomes integrate multiple dimensions of individual differences and that three of the most informative dimensions are temperament, cognitive abilities and interests. Of these three, large-scale assessment of cognitive abilities has been the most problematic due to methodological constraints. Recent and ongoing development of the public-domain International Cognitive Ability Resource is intended to address these constraints. In this talk, we will describe the procedures being used to develop this resource and summarize progress to date. Then, using online data collected with synthetic aperture personality assessment (”SAPA”) methods (sapa-project.org), we compare the predictive utility of integrated individual difference models against those which use only the independent dimensions (of temperament or interests or ability) in the context of academic, occupational and health outcomes.

People differ. How and why they differ are the fundamental questions for personality psychologists. In this article we address three levels at which people differ: within individuals, between individuals, and between groups of individuals. A dynamic model of personality is considered where traits are seen as rates of change in states in response to environmental cues. Within individuals, motivational and behavioral states show inertial properties and lead to an analysis of rates of change and latencies of behavior. Between individuals, the analysis is one of frequency and duration of choices. When individuals self select into groups reflecting shared interests and abilities, the structure of these group differences reflects the consequences of the self selection. Examples of the dynamic model are given for each level of analysis.