Some philosophical concerns about how the VIA classifies character traits and the VIA-IS measures them

ABSTRACT

Written from the perspective of a philosopher, this paper raises a number of potential concerns with how the VIA classifies and the VIA-IS measures character traits. With respect to the 24 character strengths, concerns are raised about missing strengths, the lack of vices, conflicting character strengths, the unclear connection between character strengths and virtues, and the misclassification of some character strengths under certain virtues. With respect to the 6 virtues, concerns are raised about conflicting virtues, the absence of practical wisdom, and factor analyses that do not find a 6 factor structure. With respect to the VIA-IS, concerns are raised about its neglect of motivation and about the underlying assumptions it makes about character traits. The paper ends by sketching a significantly improved classification which omits the 6 virtues and introduces additional strengths, vices, and a conflict resolution trait.     

Targeting Item-level Nuances Leads to Small but Robust Improvements in Personality Prediction from Digital Footprints

In the past decade, researchers have demonstrated that personality can be accurately predicted from digital footprint data, including Facebook likes, tweets, blog posts, pictures, and transaction records. Such computer-based predictions from digital footprints can complement—and in some circumstances even replace—traditional self-report measures, which suffer from well-known response biases and are difficult to scale. However, these previous studies have focused on the prediction of aggregate trait scores (i.e. a person's extroversion score), which may obscure prediction-relevant information at theoretical levels of the personality hierarchy beneath the Big 5 traits. Specifically, new research has demonstrated that personality may be better represented by so-called personality nuances—item-level representations of personality—and that utilizing these nuances can improve predictive performance. The present work examines the hypothesis that personality predictions from digital footprint data can be improved by first predicting personality nuances and subsequently aggregating to scores, rather than predicting trait scores outright. To examine this hypothesis, we employed least absolute shrinkage and selection operator regression and random forest models to predict both items and traits using out-of-sample cross-validation. In nine out of 10 cases across the two modelling approaches, nuance-based models improved the prediction of personality over the trait-based approaches to a small, but meaningful degree (4.25% or 1.69% on average, depending on method). Implications for personality prediction and personality nuances are discussed. © 2020 European Association of Personality Psychology     

Why are moderators of self-other agreement difficult to establish?

Agreement between the self and other rated personality profiles was studied in two samples involving 11,096 speakers of two languages, Dutch and Estonian, who completed two different personality questionnaires, the NEO-PI-3 and HEXACO-PI-R. An outstanding agreement was achieved in the most occasions: in only 4–6% of dyadic pairs was the correlation between two randomly paired profiles higher than the actually observed correlation between true pairs. As in previous studies, we found that age and sex of participants and length of acquaintance had no significant effect on the level of self-other agreement. However, intimate knowledge helped married and unmarried couples in both samples be more accurate in their personality judgments; family members, in turn, had knowledge that made them more accurate than two people who were just acquaintances or friends. We believe that these outcomes can be explained by the contention that the judgment of another’s personality is a relatively simple task, which is accomplishable for most people most of the time. In other words, because judging another person’s personality is an easy task, we are not able to determine “good targets,” “good judges,” or “good traits.” Perhaps it is only “good information” which determines the closeness of the target-judge relationship, and which has a small but reliable impact on the level of self-other agreement. This explains why it is so difficult to find individual differences in the ability to judge another person’s personality.     

A model for personality at three levels

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.     

The relationship between personality traits and psychotic like experiences in a large non-clinical adolescent sample

ObjectiveThe relationship between personality and psychosis is well established. It has been suggested that this relationship may be partly accounted for by higher levels of depression in individuals with certain personality traits. We explored whether the link between personality and psychotic symptoms is already apparent in adolescence, and if this association would still hold when depression was controlled for.Method654 secondary school students were surveyed via self-report questionnaires measuring the Five-Factor model of personality (NEO-FFI), depression (CES-D) and psychotic-like experiences (CAPE).ResultsPositive associations were found between Neuroticism and all CAPE-subscales except Magical Thinking, which was in turn associated with all other personality traits when at high levels. Agreeableness was negatively associated with all CAPE-subscales, while Openness to Experience was only positively associated with Persecutory Ideas and Magical Thinking. After controlling for depression, many of the significant associations remained.ConclusionOur findings suggest that the chance of having psychotic like experiences is more likely for adolescents with certain personality traits. These associations are not fully explained by depression, especially when psychotic experiences are at higher levels. Future research is needed to investigate if these personality traits might put a person at risk for the development of full-blown psychosis.