Development of personality in early and middle adulthood: set like plaster or persistent change?

Different theories make different predictions about how mean levels of personality traits change in adulthood. The biological view of the Five-factor theory proposes the plaster hypothesis: All personality traits stop changing by age 30. In contrast, contextualist perspectives propose that changes should be more varied and should persist throughout adulthood. This study compared these perspectives in a large (N = 132,515) sample of adults aged 21-60 who completed a Big Five personality measure on the Internet. Conscientiousness and Agreeableness increased throughout early and middle adulthood at varying rates; Neuroticism declined among women but did not change among men. The variety in patterns of change suggests that the Big Five traits are complex phenomena subject to a variety of developmental influences.     

The do re mi's of everyday life: the structure and personality correlates of music preferences

The present research examined individual differences in music preferences. A series of 6 studies investigated lay beliefs about music, the structure underlying music preferences, and the links between music preferences and personality. The data indicated that people consider music an important aspect of their lives and listening to music an activity they engaged in frequently. Using multiple samples, methods, and geographic regions, analyses of the music preferences of over 3,500 individuals converged to reveal 4 music-preference dimensions: Reflective and Complex, Intense and Rebellious, Upbeat and Conventional, and Energetic and Rhythmic. Preferences for these music dimensions were related to a wide array of personality dimensions (e.g., Openness), self-views (e.g., political orientation), and cognitive abilities (e.g., verbal IQ).     

The precarious couple effect: verbally inhibited men + critical, disinhibited women = bad chemistry

When critical, verbally disinhibited women are paired with verbally inhibited men, relationship quality suffers, rendering the relationship precarious. This effect theoretically emerges when (a). verbally disinhibited women pair with relatively inhibited men (man-more-inhibited couples) and (b). the disinhibition of women in man-more-inhibited couples amplifies women's criticalness and alienates men. Three studies (Ns=437, 300, and 564) provided evidence that relationship quality suffered in man-more-inhibited couples; a 4th study (N=168) showed that the criticalness of women in man-more-inhibited couples did indeed undermine relationship quality. Implications for understanding the impact of gender expectations on relationships and for integrating behavioral and personological approaches to close relationships are discussed.     

Tree thinking: a new paradigm for integrating comparative data in psychology

Over the past 15 years, several important theoretical and methodological developments have emerged from evolutionary biology. These developments--collectively dubbed tree thinking--are now well known in evolutionary biology but have yet to be incorporated into mainstream psychology. Tree thinking has revolutionized evolutionary biology and has the potential to do the same for how comparative data are integrated into psychology. Tree thinking holds that explanations (or narratives) for adaptations must be based on an understanding of the adaptations' history (or chronicle) over evolutionary time. This tenet of tree thinking requires researchers to consider hitherto neglected patterns of data. The authors present the ideas and methods behind tree thinking, examining their implications for psychology.     

Normal perception of Mooney faces in developmental prosopagnosia: Evidence from the N170 component and rapid neural adaptation

Individuals with developmental prosopagnosia (DP) have a severe difficulty recognizing the faces of known individuals in the absence of any history of neurological damage. These recognition problems may be linked to selective deficits in the holistic/configural processing of faces. We used two‐tone Mooney images to study the processing of faces versus non‐face objects in DP when it is based on holistic information (or the facial gestalt) in the absence of obvious local cues about facial features. A rapid adaptation procedure was employed for a group of 16 DPs. Naturalistic photographs of upright faces were preceded by upright or inverted Mooney faces or by Mooney houses. DPs showed face‐sensitive N170 components in response to Mooney faces versus houses, and N170 amplitude reductions for inverted as compared to upright Mooney faces. They also showed the typical pattern of N170 adaptation effects, with reduced N170 components when upright naturalistic test faces were preceded by upright Mooney faces, demonstrating that the perception of Mooney and naturalistic faces recruits shared neural populations. Our findings demonstrate that individuals with DP can utilize global information about face configurations for categorical discriminations between faces and non‐face objects, and suggest that face processing deficits emerge primarily at more fine‐grained higher level stages of face perception.     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.     

Personality Correlates of Self-Esteem

The current study examined the relation between self-esteem and the Big Five personality dimensions. Data were collected over the Internet from a large heterogeneous sample of individuals who ranged in age from 9 to 90 years (N = 326,641). Collectively, the Big Five accounted for 34% of the variance in self-esteem. High self-esteem individuals were emotionally stable, extraverted, and conscientious and were somewhat agreeable and open to experience. Despite an extensive search for potential mediators and moderators of this general pattern, the relations between self-esteem and the Big Five largely cut across age, sex, social class, ethnicity, and nationality (United States vs non-United States). High self-esteem individuals tended to ascribe socially desirable traits to themselves, and this tendency partially mediated relations between the Big Five and self-esteem. Discussion focuses on interpreting the social desirability effects, limitations of the study, and directions for future research.