scholarly journals Towards More Rigorous Personality Trait–Outcome Research

2016 ◽  
Vol 30 (4) ◽  
pp. 292-303 ◽  
Author(s):  
René Mõttus
Keyword(s):  
Personality Traits ◽  
Personality Trait ◽  
Outcome Research ◽  
European Association ◽  
Causal Inferences ◽  
Personality Psychology ◽  
Factor Loadings ◽  
Personality Research ◽  
Trait Level

Much of personality research attempts to identify causal links between personality traits and various types of outcomes. I argue that causal interpretations require traits to be seen as existentially and holistically real and the associations to be independent of specific ways of operationalizing the traits. Among other things, this means that, to the extents that causality is to be ascribed to such holistic traits, items and facets of those traits should be similarly associated with specific outcomes, except for variability in the degrees to which they reflect the traits (i.e. factor loadings). I argue that, before drawing causal inferences about personality trait–outcome associations, the presence of this condition should be routinely tested by, for example, systematically comparing the outcome associations of individual items or facets, or sampling different indicators for measuring the same purported traits. Existing evidence suggests that observed associations between personality traits and outcomes at least sometimes depend on which particular items or facets have been included in trait operationalizations, calling trait–level causal interpretations into question. However, this has rarely been considered in the literature. I argue that when outcome associations are specific to facets, they should not be generalized to traits. Furthermore, when the associations are specific to particular items, they should not even be generalized to facets. Copyright © 2016 European Association of Personality Psychology

Objections to the HEXACO Model of Personality Structure—and why those Objections Fail

2020 ◽  
Vol 34 (4) ◽  
pp. 492-510 ◽  
Author(s):  
Michael C. Ashton ◽  
Kibeom Lee
Keyword(s):  
Social Media ◽  
European Association ◽  
Personality Structure ◽  
Personality Psychology ◽  
Personality Research ◽  
Target Article ◽  
Social Media Platforms ◽  
Dimensional Models ◽  
Hexaco Model

The six–dimensional HEXACO model of personality structure and its associated inventory have increasingly been used in personality research. But in spite of the evidence supporting this structure and demonstrating its advantages over five–dimensional models, some researchers continue to use and promote the latter. Although there has been little overt, organized argument against the adoption of the HEXACO model, we do hear sporadic offerings of reasons for retaining the five–dimensional systems, usually in informal conversations, in manuscript reviews, on social media platforms, and occasionally in published works. In this target article, we list all of the objections to the HEXACO model that we have heard of, and we then explain why each objection fails. © 2020 European Association of Personality Psychology

A Framework for Testing Causality in Personality Research

2018 ◽  
Vol 32 (3) ◽  
pp. 254-268 ◽  
Author(s):  
Giulio Costantini ◽  
Marco Perugini
Keyword(s):  
Theoretical Model ◽  
European Association ◽  
Laboratory Research ◽  
Personality Psychology ◽  
Causal Explanations ◽  
Personality Research ◽  
Conceptual Clarity ◽  
Candidate Target ◽  
Ecological Momentary ◽  
Over Time

Causal explanations in personality require conceptual clarity about alternative causal conditions that could, even in principle, affect personality. These causal conditions crucially depend on the theoretical model of personality, each model constraining the possibility of planning and performing causal research in different ways. We discuss how some prominent models of personality allow for specific types of causal research and impede others. We then discuss causality from a network perspective, which sees personality as a phenomenon that emerges from a network of behaviours and environments over time. From a methodological perspective, we propose a three–step strategy to investigate causality: (1) identify a candidate target for manipulation (e.g. using network analysis), (2) identify and test a manipulation (e.g. using laboratory research), and (3) deliver the manipulation repeatedly for a congruous amount of time (e.g. using ecological momentary interventions) and evaluate its ability to generate trait change. We discuss how a part of these steps was implemented for trait conscientiousness and present a detailed plan for implementing the remaining steps. Copyright © 2018 European Association of Personality Psychology

scholarly journals Longitudinal Experience–Wide Association Studies—A Framework for Studying Personality Change

2020 ◽  
Vol 34 (3) ◽  
pp. 285-300 ◽  
Author(s):  
Wiebke Bleidorn ◽  
Christopher J. Hopwood ◽  
Mitja D. Back ◽  
Jaap J.A. Denissen ◽  
Marie Hennecke ◽  
...  
Keyword(s):  
Personality Traits ◽  
European Association ◽  
Association Studies ◽  
Personality Change ◽  
Life Outcomes ◽  
Personality Psychology ◽  
Research Paradigms ◽  
Methodological Approaches ◽  
Work And Health

The importance of personality for predicting life outcomes in the domains of love, work, and health is well established, as is evidence that personality traits, while relatively stable, can change. However, little is known about the sources and processes that drive changes in personality traits and how such changes might impact important life outcomes. In this paper, we make the case that the research paradigms and methodological approaches commonly used in personality psychology need to be revised to advance our understanding of the sources and processes of personality change. We propose Longitudinal Experience–Wide Association Studies as a framework for studying personality change that can address the limitations of current methods, and we discuss strategies for overcoming some of the challenges associated with Longitudinal Experience–Wide Association Studies. © 2020 European Association of Personality Psychology

Using Big Data and Machine Learning in Personality Measurement: Opportunities and Challenges

2020 ◽  
Vol 34 (5) ◽  
pp. 632-648
Author(s):  
Leo Alexander ◽  
Evan Mulfinger ◽  
Frederick L. Oswald
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
European Association ◽  
Reliability And Validity ◽  
Personality Measurement ◽  
Personality Psychology ◽  
Personality Research ◽  
The Future ◽  
Challenges And Opportunities ◽  
Conceptual Paper

This conceptual paper examines the promises and critical challenges posed by contemporary personality measurement using big data. More specifically, the paper provides (i) an introduction to the type of technologies that give rise to big data, (ii) an overview of how big data is used in personality research and how it might be used in the future, (iii) a framework for approaching big data in personality science, (iv) an exploration of ideas that connect psychometric reliability and validity, as well as principles of fairness and privacy, to measures of personality that use big data, (v) a discussion emphasizing the importance of collaboration with other disciplines for personality psychologists seeking to adopt big data methods, and finally, (vi) a list of practical considerations for researchers seeking to move forward with big data personality measurement and research. It is expected that this paper will provide insights, guidance, and inspiration that helps personality researchers navigate the challenges and opportunities posed by using big data methods in personality measurement. © 2020 European Association of Personality Psychology

Personality Neuroscience and the Five Factor Model

2016 ◽  
Author(s):  
Timothy A. Allen ◽  
Colin G. DeYoung
Keyword(s):  
Best Practices ◽  
Personality Traits ◽  
Big Five ◽  
Factor Model ◽  
Five Factor Model ◽  
Personality Psychology ◽  
Personality Research ◽  
Neuroscience Research ◽  
Behavior Motivation ◽  
Psychological Functions

Personality psychology seeks both to understand how individuals differ from one another in behavior, motivation, emotion, and cognition and to explain the causes of those differences. The goal of personality neuroscience is to identify the underlying sources of personality traits in neurobiological systems. This chapter reviews neuroscience research on the traits of the Five Factor Model (the Big Five: Extraversion, Neuroticism, Openness/Intellect, Conscientiousness, and Agreeableness). The review emphasizes the importance of theoretically informed neuroscience by framing results in light of a theory of the psychological functions underlying each of the Big Five. The chapter additionally reviews the various neuroscientific methods available for personality research and highlights pitfalls and best practices in personality neuroscience.

scholarly journals A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires

2020 ◽  
Vol 34 (6) ◽  
pp. 1095-1108 ◽  
Author(s):  
Alexander P. Christensen ◽  
Hudson Golino ◽  
Paul J. Silvia
Keyword(s):  
Personality Trait ◽  
Latent Variable ◽  
European Association ◽  
Structural Phase ◽  
External Validation ◽  
Network Models ◽  
Complementary Information ◽  
Future Directions ◽  
Personality Psychology ◽  
Structural Consistency

This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology

Different Games for Different Motives: Comment on Haesevoets, Folmer, and Van Hiel (2015)

2015 ◽  
Vol 29 (4) ◽  
pp. 506-508 ◽  
Author(s):  
Isabel Thielmann ◽  
Robert Böhm ◽  
Benjamin E. Hilbig
Keyword(s):  
Personality Traits ◽  
European Association ◽  
Personality Psychology ◽  
Economic Games ◽  
Game Theoretic

Recently, Haesevoets, Folmer, and Van Hiel (2015) strongly questioned the comparability and equivalence of different mixed–motive situations as modelled in economic games. Particularly, the authors found that different game correlated only weakly on average and loaded on two separate factors. In turn, personality traits failed to consistently account for behavioural tendencies across games. Contrary to the conclusions of Haesevoets et al., these findings are actually perfectly in line with the game–theoretic understanding of the different economic games. If one considers the variety of specific motives underlying decisions in different games, Haesevoets et al.'s findings actually support the validity of different games rather than questioning it. This, in turn, emphasizes the necessity for the plethora of different games that have been developed over decades in economics and psychology. Copyright © 2015 European Association of Personality Psychology

scholarly journals Causal Understanding in Film Viewing: The Effects of Narrative Structure and Personality Traits

2017 ◽  
Vol 37 (1) ◽  
pp. 3-31
Author(s):  
András B. Kovács ◽  
Orsolya Papp-Zipernovszky
Keyword(s):  
Problem Solving ◽  
Personality Traits ◽  
Personality Trait ◽  
Psychological Factors ◽  
Narrative Structure ◽  
Causal Inferences ◽  
Causal Understanding ◽  
Causal Connections ◽  
Causal Thinking ◽  
Film Viewing

The aim of this research was to investigate the extent to which psychological factors interfere with conscious rational problem-solving in constructing a cinematic narrative’s causal connections during film viewing. Talk-aloud protocol was used to record subjects’ verbal reactions during watching films. Viewers’ texts were analyzed to determine the type and the quantity of causal inferences. This enabled us to determine which parts of the narratives provoked high matching of causal inferences. The results demonstrate recurring correlation between causal thinking and the personality trait openness to experience. In the second study, classical and nonclassical types of narrative were compared in terms of provoking causal inferences. The results demonstrate that classical narrative provokes significantly more causal inferences than nonclassical narrative, and that classical and nonclassical narratives rely equally on personality traits in causal construction.

scholarly journals Does Neuroticism Disrupt the Psychological Benefits of Nostalgia? A Meta–analytic Test

2020 ◽  
pp. per.2276
Author(s):  
Julius Frankenbach ◽  
Tim Wildschut ◽  
Jacob Juhl ◽  
Constantine Sedikides
Keyword(s):  
European Association ◽  
Meta Analysis ◽  
The Self ◽  
Social Benefits ◽  
Individual Participant Data ◽  
Psychological Benefits ◽  
Personality Psychology ◽  
The Past ◽  
Trait Level ◽  
Individual Participant

Nostalgia, a sentimental longing or wistful affection for the past, confers self–oriented, existential, and social benefits. We examined whether nostalgic engagement is less beneficial for individuals who are high in neuroticism (i.e. emotionally unstable and prone to negative affect). Specifically, we tested whether the benefits of experimentally induced nostalgia are moderated by trait–level neuroticism. To address this issue, we conducted a high–powered individual participant data meta–analysis ( N = 3556, k = 19). We found that the benefits of nostalgia were not significantly moderated by neuroticism, as they emerged for both high and low neurotics. This finding upheld when the self–oriented, existential, and social benefits of nostalgia were analysed jointly and when they were analysed separately. Taken together, individuals high and low in neuroticism are equally likely to benefit psychologically from engagement in nostalgic reverie. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

Personality Traits Predict Smartphone Usage

2017 ◽  
Vol 31 (6) ◽  
pp. 701-722 ◽  
Author(s):  
Clemens Stachl ◽  
Sven Hilbert ◽  
Jiew–Quay Au ◽  
Daniel Buschek ◽  
Alexander De Luca ◽  
...  
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Mobile Application ◽  
European Association ◽  
Fluid Intelligence ◽  
Predictive Performance ◽  
Demographic Variables ◽  
Data Logging ◽  
Personality Psychology ◽  
Actual Behaviour

The present study investigates to what degree individual differences can predict frequency and duration of actual behaviour, manifested in mobile application (app) usage on smartphones. In particular, this work focuses on the identification of stable associations between personality on the factor and facet level, fluid intelligence, demography and app usage in 16 distinct categories. A total of 137 subjects (87 women and 50 men), with an average age of 24 ( SD = 4.72), participated in a 90–min psychometric lab session as well as in a subsequent 60–day data logging study in the field. Our data suggest that personality traits predict mobile application usage in several specific categories such as communication, photography, gaming, transportation and entertainment. Extraversion, conscientiousness and agreeableness are better predictors of mobile application usage than basic demographic variables in several distinct categories. Furthermore, predictive performance is slightly higher for single factor—in comparison with facet–level personality scores. Fluid intelligence and demographics additionally show stable associations with categorical app usage. In sum, this study demonstrates how individual differences can be effectively related to actual behaviour and how this can assist in understanding the behavioural underpinnings of personality. Copyright © 2017 European Association of Personality Psychology

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