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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.

Some people use healthcare services more than others. Identifying factors associated with healthcare use has the potential to improve the effectiveness, efficiency, and equity of healthcare. In line with the Andersen behavioral model of healthcare utilization and initial empirical findings, personality traits may be key predisposing factors associated with healthcare use. Across 15 samples, the present study examined cross-sectional and prospective associations between Big Five personality traits and the likelihood of dental visits, general medical practitioner visits, and hospitalizations. Using coordinated data analysis, we estimated models within each of 15 samples individually (sample Ns ranged from 516 to 305,762), and then calculated weighted mean effect sizes using random effects meta-analysis across samples (total N = 358,803). According to the synthesized results, people higher in conscientiousness, agreeableness, extraversion, and openness, and lower in neuroticism were more likely to visit the dentist; people higher in neuroticism were more likely to visit general medical practitioners; and people lower in conscientiousness and agreeableness and higher in neuroticism were more likely to be hospitalized. Associations tended to be small with odds ratios around 1.20 (rs ≈ .05). These findings provide evidence across 15 international samples for small but consistent associations between personality traits and healthcare use and demonstrate that personality-healthcare associations differ by type of care. We discuss directions for future research, including examining more specific personality facets (e.g., productiveness vs. responsibility) as well as important dimensions of healthcare (e.g., preventative vs. reactive care; acute vs. chronic care).

The relationship between life outcomes and an individual's standing in the social and economic hierarchy of society is an important topic across the social sciences. Foundational to this work is assessing an individual’s standing in this hierarchy, often referred to as socioeconomic status (SES). One component of an individual’s SES, often overlooked in the psychological literature, is occupational prestige – the amount of status accorded to them based on their occupational role. In this research, we collected and validated a new index of occupational prestige for 1029 specific occupations, including all jobs in the US Department of Labor's O*NET database and 22 broader occupational families. In Study 1, we collected a comprehensive set of occupational prestige ratings and demonstrated their high reliability. In Study 2, we developed a crosswalk between the ratings collected in Study 1 and prior ratings of occupations listed in the US Census and show convergent validity with previous indices. In Studies 3 and 4 we used additional data to evaluate the construct validity of occupational prestige more broadly. In Study 3, we established convergent and discriminant validity with other indicators of SES: income and educational attainment. In Study 4, we use the O*NET database to identify the characteristics of occupations most strongly associated with prestige. These results support the validity of the index and suggest occupations with high prestige require skills traditionally emphasized in liberal arts education (e.g., critical thinking, reading comprehension).

These are the Supplementary Materials to "Deep Lexical Hypothesis: Identifying personality structure in natural language." In addition to extensive analytic code with comments and output for the 3 studies reported in the primary manuscript, this supplement includes sections on prior findings about personality structure and the rationale for choosing the Saucier and Goldberg (1996) dataset as the historical frame of reference. An open-access preprint of the primary manuscript can be viewed at https://psyarxiv.com/gdm5v/.

Some scholars have presented models of the United States as a set of “nations” with distinct settlement histories and contemporary cultures. We examined personality differences in one such model, that of Colin Woodard, using data from over 75,000 respondents. Four nations were particularly distinct: The Deep South, Left Coast, New Netherland, and the Spanish Caribbean. Differences between nations at the level of the individual person were typically small, but were larger at the level of community, revealing how aggregation can contribute to differences in the lived experience of places in nations such as Yankeedom or Greater Appalachia. We represented effects in a three-dimensional model defined by Authoritarian conventionalism (which differentiated ‘Red’ and ‘Blue’ nations) as well as Cognitive resilience and Competitiveness (which differentiated among the Blue nations). Finally, we adjusted Woodard’s model to better fit the data, and found that nations largely maintained their boundaries, with the most drastic changes occurring on the East Coast.

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.

The measurement of individual differences in cognitive ability has a long and important history in psychology, but it has been impeded by the proprietary nature of most assessment measures. With the development of validated open-source measures of ability (collected in the International Cognitive Ability Resource, or ICAR, available at ICAR-project.com ), it is now possible for many researchers to assess ability in large surveys or small, lab-based studies without the expenses associated with proprietary measures. We review the history of ability measurement and discuss how the growing set of items included in ICAR allows ability assessments to be more generally available to all researchers.

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. This study introduces a newly developed public-domain multilingual automatic item generator that creates propositional reasoning (PR) items belonging to 15 item families by using various inference rules. Psychometric properties of the resulting written PR test were investigated in three diverse samples in English, simplified Chinese, and German, respectively. Internal consistency was good to excellent across samples. The ICAR16 short form test of cognitive abilities ( Condon & Revelle, 2014 ) was used to evaluate construct validity. Correlations of ICAR16 scores and PR scores were high. Furthermore, items within families appeared to be equivalent, with only minor differential item functioning between the Chinese- and English-speaking samples. Performance on the PR test was shown to be reasonably stable over the course of 1 week. Differences of total scores between test forms (pen and paper vs. computerized administration) were not detected. Findings suggest that the automatically generated PR test is a valuable instrument for the assessment of propositional reasoning ability.

Reliability is a fundamental problem for measurement in all of science. Although defined in multiple ways, and estimated in even more ways, the basic concepts seem straightforward and need to be understood by practitioners as well as methodologists. Reliability theory is not just for the psychometrician estimating latent variables, it is for everyone who wants to make inferences from measures of individuals or of groups. For the case of a single test administration, we consider multiple measures of reliability, ranging from the worst (β) to average (α, λ3) to best (λ4) split half reliabilities, and consider why model-based estimates (ωh, ωt) should be reported. We also address the utility of test-retest and alternate form reliabilities. The advantages of immediate versus delayed retests to decompose observed score variance into specific, state, and trait scores are discussed. But reliability is not just for test scores, it is also important when evaluating the use of ratings. Estimates that may be applied to continuous data include a set of intraclass correlations while discrete categorical data needs to take advantage of the family of κ statistics. Examples of these various reliability estimates are given using state and trait measures of anxiety given with different delays and under different conditions. An online supplemental materials is provided with more detail and elaboration. The online supplemental materials is also used to demonstrate applications of open source software to examples of real data, and comparisons are made between the many types of reliability. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

To evaluate the influence of recall periods on the assessment of physical function, we compared, in cancer and general population samples, the standard administration of PROMIS Physical Function items without a recall period to administrations with 24-hour and 7-day recall periods. We administered 31 items from the PROMIS Physical Function v2.0 item bank to 2400 respondents (n = 1001 with cancer; n = 1399 from the general population). Respondents were randomly assigned to one of three recall conditions (no recall, 24-hours, or 7-days) and one of two “reminder” conditions (with recall periods presented only at the start of the survey or with every item). We assessed items for potential differential item functioning (DIF) by recall time period. We then tested recall and reminder effects with analysis of variance controlling for demographics, English fluency, and co-morbidities. Based on conservative pre-set criteria, no items were flagged for recall time period-related DIF. Using analysis of variance, each condition was compared to the standard PROMIS administration for Physical Function (no recall period). There was no evidence of significant differences among groups in the cancer sample. In the general population sample, only the 24-hour recall condition with reminders was significantly different from the “no recall” PROMIS standard. At the item level, for both samples, the number of items with non-trivial effect size differences across conditions was minimal. Compared to no recall, the use of a recall period has little to no effect upon PROMIS physical function responses or scores. We recommend that PROMIS Physical Function be administered with the standard PROMIS “no recall” period.

BACKGROUND: The All of Us Research Program is building a national longitudinal cohort and collecting data from multiple information sources (e.g., biospecimens, electronic health records (EHRs), and mobile/wearable technologies) to advance precision medicine. Participant-provided information, collected via surveys, will complement and augment these information sources. We report the process used to develop and refine the initial three surveys for this program. METHODS: The All of Us survey development process included: (1) prioritization of domains for scientific needs, (2) examination of existing validated instruments, (3) content creation, (4) evaluation and refinement via cognitive interviews and online testing, (5) content review by key stakeholders, and (6) launch in the All of Us electronic participant portal. All content was translated into Spanish. RESULTS: We conducted cognitive interviews in English and Spanish with 169 participants, and 573 individuals completed online testing. Feedback led to over 40 item content changes. Lessons learned included: (1) validated survey instruments performed well in diverse populations reflective of All of Us; (2) parallel evaluation of multiple languages can ensure optimal survey deployment; (3) recruitment challenges in diverse populations required multiple strategies; and (4) key stakeholders improved integration of surveys into larger Program context. CONCLUSIONS: This efficient, iterative process led to successful testing, refinement, and launch of three All of Us surveys. Reuse of All of Us surveys, available at http://researchallofus.org, may facilitate large consortia targeting diverse populations in English and Spanish to capture participant-provided information to supplement other data, such as genetic, physical measurements, or data from EHRs.

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.

Fluctuations in the average daily personality of the United States capture both meaningful affective responses to world events (e.g., changes in anxiety or well-being) and broader psychological responses. We estimate the change in national personality in the months following the onset of the COVID-19 pandemic and investigate fluctuations in personality states during the year 2020 using data from an ongoing personality assessment project. We find significant and meaningful change in personality traits since the beginning of the pandemic, as well as evidence of instability in personality states. When evaluating changes from the first few months of 2020 to the period of social distancing related to COVID-19 restrictions, the social traits reflected an unexpected “deprivation” effect such that mean self-ratings increased in the wake of restricted opportunities for social interaction. Changes in mean levels of the affective traits were not significant over the same months, but they did differ significantly from the average levels of prior years when looking at shorter time intervals (rolling 7-day averages) around prominent national events. This instability may reflect meaningful fluctuations in national personality, as we find that daily personality states are associated with other indices of national health, including daily COVID-19 cases and the S&P index. Overall, the use of personality measures to capture responses to global events offers a more holistic picture of the U.S. psyche and of personality change at the national level.

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.

We argue that it is useful to distinguish between three key goals of personality science—description, prediction and explanation—and that attaining them often requires different priorities and methodological approaches. We put forward specific recommendations such as publishing findings with minimum a priori aggregation and exploring the limits of predictive models without being constrained by parsimony and intuitiveness but instead maximizing out-of-sample predictive accuracy. We argue that naturally occurring variance in many decontextualized and multidetermined constructs that interest personality scientists may not have individual causes, at least as this term is generally understood and in ways that are human-interpretable, never mind intervenable. If so, useful explanations are narratives that summarize many pieces of descriptive findings rather than models that target individual cause–effect associations. By meticulously studying specific and contextualized behaviours, thoughts, feelings and goals, however, individual causes of variance may ultimately be identifiable, although such causal explanations will likely be far more complex, phenomenon-specific and person-specific than anticipated thus far. Progress in all three areas—description, prediction and explanation—requires higher dimensional models than the currently dominant ‘Big Few’ and supplementing subjective trait-ratings with alternative sources of information such as informant-reports and behavioural measurements. Developing a new generation of psychometric tools thus provides many immediate research opportunities. © 2020 European Association of Personality Psychology

We argue that it is useful to distinguish between three key goals of personality science – description, prediction and explanation – and that attaining them often requires different priorities and methodological approaches. We put forward specific recommendations such as publishing findings with minimum a priori aggregation and exploring the limits of predictive models without being constrained by parsimony and intuitiveness but instead maximising out-of-sample predictive accuracy. We argue that naturally-occurring variance in many decontextualized and multi-determined constructs that interest personality scientists may not have individual causes, at least as this term is generally understood and in ways that are human-interpretable, never mind intervenable. If so, useful explanations are narratives that summarize many pieces of descriptive findings rather than models that target individual cause-effect associations. By meticulously studying specific and contextualized behaviours, thoughts, feelings and goals, however, individual causes of variance may ultimately be identifiable, although such causal explanations will likely be far more complex, phenomenon-specific and person-specific than anticipated thus far. Progress in all three areas – description, prediction, and explanation – requires higher-dimensional models than the currently-dominant “Big Few” and supplementing subjective trait-ratings with alternative sources of information such as informant-reports and behavioural measurements. Developing a new generation of psychometric tools thus provides many immediate research opportunities.

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.

Personality consists of stable patterns of cognitions, emotions, and behaviors, yet personality psychologists rarely study behaviors. Even when examined, behaviors typically are considered to be validation criteria for traditional personality items. In the current study (N = 332,489), we conceptualize (self-reported, yearlong) behavioral frequencies as measures of personality. We investigate whether behavioral frequencies have incremental validity over traditional personality items in correlating personality with six outcome criteria. We use BISCUIT, a statistical learning technique, to find the optimal number of items for each criterion’s model, across three pools of items: traditional personality items (k = 696), behavioral frequencies (k = 425), and a combined pool. Compared to models using only traditional personality items, models using the combined pool are more strongly correlated to four criteria. We find mixed evidence of congruence between the type of criterion and the type of personality items that are most strongly correlated with it (e.g., behavioral criteria are most strongly correlated to behavioral frequencies). Findings suggest that behavioral frequencies are measures of personality that offer a unique effect in describing personality-criterion relationships beyond traditional personality items. We provide an updated, public-domain item pool of behavioral frequencies: the BARE (Behavioral Acts, Revised and Expanded) Inventory.

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.

Background Over the past decade, public interest in managing health-related information for personal understanding and self-improvement has rapidly expanded. This study explored aspects of how patient-provided health information could be obtained through an electronic portal and presented to inform and engage patients while also providing information for healthcare providers. Methods We invited participants using ResearchMatch from 2 cohorts: (1) self-reported healthy volunteers (no medical conditions) and (2) individuals with a self-reported diagnosis of anxiety and/or depression. Participants used a secure web application (dashboard) to complete the PROMIS® domain survey(s) and then complete a feedback survey. A community engagement studio with 5 healthcare providers assessed perspectives on the feasibility and features of a portal to collect and display patient provided health information. We used bivariate analyses and regression analyses to determine differences between cohorts. Results A total of 480 participants completed the study (239 healthy, 241 anxiety and/or depression). While participants from the tw2o cohorts had significantly different PROMIS scores (p Conclusions Our findings demonstrated a strong desire among healthy people, patients with chronic diseases, and healthcare providers for a self-assessment portal that can collect patient-reported outcome metrics and deliver personalized feedback.

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.

A shared experience among many graduate students is the dawning realization that the vaunted privilege of having one's scholarly work accepted for publication is also a fleecing. The exact terms of this fleecing depend on a number of different factors – so many, in fact, that it can get a bit confusing – but it's quite common for researchers to pay several thousand dollars to make their work available for others to read. And these are not the expenses incurred to complete their scholarly work. It's merely the cost of having one's work posted on the website of an academic publisher!

PURPOSE: To evaluate the influence of recall periods on the assessment of physical function, we compared, in cancer and general population samples, the standard administration of PROMIS Physical Function items without a recall period to administrations with 24-hour and 7-day recall periods. METHODS: We administered 31 items from the PROMIS Physical Function v2.0 item bank to 2400 respondents (n = 1001 with cancer; n = 1399 from the general population). Respondents were randomly assigned to one of three recall conditions (no recall, 24-hours, or 7-days) and one of two “reminder” conditions (with recall periods presented only at the start of the survey or with every item). We assessed items for potential differential item functioning (DIF) by recall time period. We then tested recall and reminder effects with analysis of variance controlling for demographics, English fluency, and co-morbidities. RESULTS: Based on conservative pre-set criteria, no items were flagged for recall time period-related DIF. Using analysis of variance, each condition was compared to the standard PROMIS administration for Physical Function (no recall period). There was no evidence of significant differences among groups in the cancer sample. In the general population sample, only the 24-hour recall condition with reminders was significantly different from the “no recall” PROMIS standard. At the item level, for both samples, the number of items with non-trivial effect size differences across conditions was minimal. CONCLUSIONS: Compared to no recall, the use of a recall period has little to no effect upon PROMIS physical function responses or scores. We recommend that PROMIS Physical Function be administered with the standard PROMIS “no recall” period.

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 There is a need for valid self-report measures of core health-related quality of life (HRQoL) domains. Objective To derive brief, reliable and valid health profile measures from the Patient Reported Outcomes Measurement Information System® (PROMIS®) item banks. Methods Literature review, investigator consensus process, item response theory (IRT) analysis, and expert review of scaling results from multiple PROMIS data sets. We developed 3 profile measures ranging in length from 29 to 57 questions. These profiles assess important HRQoL domains with highly informative subsets of items from respective item banks and yield reliable information across mild-to-severe levels of HRQoL experiences. Each instrument assesses the domains of pain interference, fatigue, depression, anxiety, sleep disturbance, physical function, and social function using 4-, 6-, and 8-item short forms for each domain, and an average pain intensity domain score, using a 0-10 numeric rating scale. Results With few exceptions, all domain short forms within the profile measures were highly reliable across at least 3 standard deviation (30 T-score) units and were strongly correlated with the full bank scores. Construct validity with ratings of general health and quality of life was demonstrated. Information to inform statistical power for clinical and general population samples is also provided. Conclusions Although these profile measures have been used widely, with summary scoring routines published, description of their development, reliability, and initial validity has not been published until this article. Further evaluation of these measures and clinical applications are encouraged.

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.

Although the measurement of intelligence is important, researchers sometimes avoid using them in their studies due to their history, cost, or burden on the researcher. To encourage the use of cognitive ability items in research, we discuss the development and validation of the International Cognitive Ability Resource (ICAR), a growing set of items from 19 different subdomains. We consider how these items might benefit open science in contrast to more established proprietary measures. A short summary of how these items have been used in outside studies is provided in addition to ways we would love to see the use of public-domain cognitive ability items grow.

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.

Lievens (2017) makes a case for SJTs in personnel selection, a recommendation with which we agree. In particular, we like the emphasis on branching out from current methodologies and using new techniques such as SJTs not only in I/O or personnel selection research but also in basic personality research. Despite our enthusiasm, we point out some flaws, most notably lack a time dimension to SJTs.

BACKGROUND: There is a need for valid self-report measures of core health-related quality of life (HRQoL) domains. OBJECTIVE: To derive brief, reliable and valid health profile measures from the Patient Reported Outcomes Measurement Information System® (PROMIS®) item banks. METHODS: Literature review, investigator consensus process, item response theory (IRT) analysis, and expert review of scaling results from multiple PROMIS data sets. We developed 3 profile measures ranging in length from 29 to 57 questions. These profiles assess important HRQoL domains with highly informative subsets of items from respective item banks and yield reliable information across mild-to-severe levels of HRQoL experiences. Each instrument assesses the domains of pain interference, fatigue, depression, anxiety, sleep disturbance, physical function, and social function using 4-, 6-, and 8-item short forms for each domain, and an average pain intensity domain score, using a 0–10 numeric rating scale. RESULTS: With few exceptions, all domain short forms within the profile measures were highly reliable across at least 3 standard deviation (30 T-score) units and were strongly correlated with the full bank scores. Construct validity with ratings of general health and quality of life was demonstrated. Information to inform statistical power for clinical and general population samples is also provided. CONCLUSIONS: Although these profile measures have been used widely, with summary scoring routines published, description of their development, reliability, and initial validity has not been published until this article. Further evaluation of these measures and clinical applications are encouraged.