This paper presents five studies on the development and validation of a scale of intellectual humility. This scale captures cognitive, affective, behavioral, and motivational components of the construct that have been identified by various philosophers in their conceptual analyses of intellectual humility. We find that intellectual humility has four core dimensions: Open-mindedness (versus Arrogance), Intellectual Modesty (versus Vanity), Corrigibility (versus Fragility), and Engagement (versus Boredom). These dimensions display adequate self-informant agreement, and adequate convergent, divergent, and discriminant validity. In particular, Open-mindedness adds predictive power beyond the Big Six for an objective behavioral measure of intellectual humility, and Intellectual Modesty is uniquely related to Narcissism. We find that a similar factor structure emerges in Germanophone participants, giving initial evidence for the model’s cross-cultural generalizability.

It has become clear that there are multiple “moralities”: diverse bases that guide people’s judgments of right and wrong. The widely known Moral Foundations Theory stipulates that there are at least five such moralities, measurable via questionnaire, and tends to assume that these distinct foundations are rooted deep in humanity’s evolutionary past. Were this true, we should find that the structure of five foundations is cross-culturally generalizable. Such assumptions are best tested in a diverse range of global populations with no built-in Western bias. Here, we test the measurement invariance of the short-form Moral Foundations Questionnaire across 27 countries spanning the five largest continents. We find that it is difficult to specify Moral Foundations Questionnaire items in a quantitative five-factor model that will converge nonproblematically across a wide variety of populations.

Contemporary structural models of personality, like the Big Five, are rooted in natural-language lexicons in which socially important individual-differences concepts are sedimented. But key studies of these lexicons have been narrow in scope and mainly sought confirmatory evidence for one model of interest, rather than the maximum number of meaningful dimensions obtainable from the lexicon. Here, building on established methods for determining the appropriate number of factors, and comparing various methods of data-treatment and factor-rotation, analyses allowed higher-dimensionality structures to emerge from the same data. Factor-number-determination methods always recommended well more than 5 or 6 factors. In data using the largest 1,710-term set, we compared 18 candidate-structures derived from different method-combinations, identifying 15-, 21-, and 28-factor structures as most robust and promising. Among these, in a larger sample using a smaller 540-term set, the factors related to the 21-dimensional structure were most advantageously robust. Robustness-comparisons in an even larger sample with a 449-term subset of the original 1,710 converged on a similar number of factors. Though such a high-dimensionality model is slightly less robust than the Big Five across method-variations, we were able to confirm its clearly superior predictive capacity. And as comprehensiveness would imply, one can readily identify a low-dimensionality structure like the Big Five from within this higher-dimensionality structure, but one cannot generate this structure from the Big Five. A high-dimensionality structure can function as an improved scientific framework for cataloging trait variables and dimensions, including those that fall outside popular classifications involving only 5 or 6 factors.

We know that there are cross-cultural differences in psychological variables, such as individualism/collectivism. But it has not been clear which of these variables show relatively the greatest differences. The Survey of World Views project operated from the premise that such issues are best addressed in a diverse sampling of countries representing a majority of the world’s population, with a very large range of item-content. Data were collected online from 8,883 individuals (almost entirely college students based on local publicizing efforts) in 33 countries that constitute more than two third of the world’s population, using items drawn from measures of nearly 50 variables. This report focuses on the broadest patterns evident in item data. The largest differences were not in those contents most frequently emphasized in cross-cultural psychology (e.g., values, social axioms, cultural tightness), but instead in contents involving religion, regularity-norm behaviors, family roles and living arrangements, and ethnonationalism. Content not often studied cross-culturally (e.g., materialism, Machiavellianism, isms dimensions, moral foundations) demonstrated moderate-magnitude differences. Further studies are needed to refine such conclusions, but indications are that cross-cultural psychology may benefit from casting a wider net in terms of the psychological variables of focus.

Prediction of outcomes is an important way of distinguishing, among personality models, the best from the rest. Prominent previous models have tended to emphasize multiple internally consistent "facet" scales subordinate to a few broad domains. But such an organization of measurement may not be optimal for prediction. Here, we compare the predictive capacity and efficiency of assessments across two types of personality-structure model: conventional structures of facets as found in multiple platforms, and new high-dimensionality structures emphasizing those based on natural-language adjectives, in particular lexicon-based structures of 20, 23, and 28 dimensions. Predictions targeted 12 criterion variables related to health and psychopathology, in a sizeable American community sample. Results tended to favor personality-assessment platforms with (at least) a dozen or two well-selected variables having minimal intercorrelations, without sculpting of these to make them function as indicators of a few broad domains. Unsurprisingly, shorter scales, especially when derived from factor analyses of the personality lexicon, were shown to take a more efficient route to given levels of predictive capacity. Popular 20 th-century personality-assessment models set out influential but suboptimal templates, including one that first identifies domains and then facets, which compromise the efficiency of measurement models, at least from a comparative-prediction standpoint.