The finer details? The predictability of life outcomes from Big Five domains, facets, and nuances

Human Values Across the Lifespan: Age-Graded Differences at Three Hierarchical Levels and What We Can Learn From Them

Personality-development research is flourishing. Here, we extend these efforts horizontally (new constructs) and vertically (new levels within the same construct) by charting out age-graded differences in Schwarz's human values across 80,814 individuals. Conducting a systematic investigation of cross-sectional age-graded differences in human values-from late teenage years to post-retirement-featuring 36 analytical model choices and 180,000 simulation-based decisions, our analyses replicate some earlier findings (e.g., increasing self- and growth-focus during adolescence and increasing security concerns during adulthood), while also highlighting complex and previously unappreciated dynamics. As such, while it is a common practice to aggregate specific values into parsimonious higher-order concepts to ease interpretation, this may risk overlooking meaningful trends in lower-order value development. Specifically, revealing unique and asynchronous patterns for value nuances, we find that aggregation (a) leads to a loss of critical information, (b) creates conflicting results when nuances diverge, and (c) significantly reduces predictive power.

Personality nuances and cognition: A multi-cohort and multi-method approach

There is substantial evidence for an association between the Five-Factor Model personality domains and cognition across adulthood. Examining the items that compose each of the five domains, known as nuances, can provide novel insight into the aspects of the traits most connected to cognitive outcomes. This study tested the association between personality nuances and cognition (memory performance, subjective memory, informant-rated cognition) in five community-based cohorts. Participants (N > 28,000, age range: 32-104 years) were administered the Midlife Development Inventory (MIDI) to assess personality nuances, immediate and recall tasks to assess memory performance, and a subjective memory measure. Ratings of cognitive functioning from a knowledgeable informant were available in two samples. There was a strong pattern of replicability between personality items and cognitive outcomes across samples and cognitive measures. Meta-analyses indicated that higher neuroticism nuances (particularly the nervous and worry items) were related to lower memory performance, worse subjective memory, and worse informant-rated cognition. Higher conscientiousness (particularly the organized and responsible items), extraversion (particularly the active item), and openness (particularly the intelligent item) nuances were consistently associated with better memory performance, better subjective memory, and better informant-rated cognition across samples. To a lesser extent, higher agreeableness nuances (helpful, warm, sympathetic) were associated with better memory and subjective memory. This research adds to the existing literature by providing novel evidence of replicable associations between personality nuances and cognition.

Using advanced machine learning algorithms to predict academic major completion: A cross-sectional study

BACKGROUND

Existing prediction methods for academic majors based on personality traits have notable gaps, including limited model complexity and generalizability.The current study aimed to utilize advanced Machine Learning (ML) algorithms with smoothing functions to predict academic majors completed based on personality subscales.

METHODS

We used reports from 59,413 individuals to perform the current study. All advanced algorithms implemented in this article were based on R software (version 4.1.3, R Core Team, 2021). All model parameters were optimized based on resampling and cross-validation (CV). In addition, pseudo-R2 as a robust metric has been used to compare the performance of models, which, unlike most studies, considers the quality of model-predicted probabilities.

RESULT

The results indicated that advanced ML models' performance on training and test data was superior to logistic regression. Pseudo-R2 and AUC results showed that advanced models such as kNN, GBE, and RF had the highest scores based on test data compared to other models. The pseudo-R2 values for the models used in this study varied across the test dataset; the lowest value belonged to the logistic regression algorithm at .022, and the highest value was recorded for the kNN algorithm at .099. The agreeableness subscale is the most influential component in predicting the completion of university education, followed by conscientiousness and emotional stability.

CONCLUSION

The potential of advanced methods to enhance the accuracy and validity of predictions is a promising development in our field. Their performance, particularly in handling large data sets with complex patterns, is a reason for optimism about the future of research in this area.

Construct Validity, Longitudinal Measurement Invariance, Incremental Validity, and Predictive Validity of the Original Grit Scale in Chinese Young Adults

Although many studies have attempted to validate grit scales because of the construct's popularity, most have considered the shorter rather than the longer Original Grit Scale (Grit-O). We examined the Grit-O's construct validity, longitudinal measurement invariance, incremental validity for academic performance, and longitudinal predictive validity for subjective well-being among young Chinese. We used a cross-sectional sample of 3,322 college students and a longitudinal sample of 1,884 college students, tested twice over 10 months. The first-order factor model fit the data better than other models and showed partial configural and metric measurement invariance over time. Grit and its two facets longitudinally predicted subjective well-being (i.e., life satisfaction, happiness, positive affect, negative affect, and depression) but had negligible incremental validity for two semesters' grades after controlling for conscientiousness. So, while the Grit-O could be a useful construct for young adults, its predictive value overlaps with a better-established construct, conscientiousness.

Co-development of general psychopathology and high-risk personality traits during adolescence

There is strong evidence for a general psychopathology dimension which captures covariance among all forms of psychopathology, yet its nature and underlying association with personality remain unclear. This study examined the co-development of general psychopathology and four high-risk personality traits: anxiety sensitivity, negative thinking, sensation seeking, and impulsivity. Data from two large Australian school-based randomised controlled trials of substance use prevention programs were analysed (N = 2,083, mean age at baseline = 13.49 years). Adolescents completed self-report measures of psychopathology symptoms and personality at baseline, one-, two-, and three-years post-baseline. Latent curve models with structured residuals, were used to examine the co-development of general psychopathology (extracted from a higher-order model) and personality traits from 13 to 16 years of age, controlling for age, sex, and cohort. Higher than usual levels of anxiety sensitivity and impulsivity were associated with higher than usual levels of general psychopathology at subsequent time points, and higher than usual levels of general psychopathology were associated with higher than usual levels of negative thinking at later time points. Sensation seeking was unrelated to general psychopathology. These findings enhance our understanding of the meaning and validity of general psychopathology, highlighting potential personality-based prevention and intervention targets.

Popularity at first sight: Dominant behaviours mediate the link between extraversion and popularity in face-to-face and virtual group interactions

Although there is robust evidence that being more extraverted is related to higher popularity, only few studies have examined which actual behaviours (e.g., verbal content, body language) might explain this association. The current study examined whether observer-rated dominant behaviours (nonverbal, paraverbal, verbal, and general cues) mediate the relationship between self-rated extraversion and its facets (assertiveness, sociability, and activity) and other-rated popularity in zero-acquaintance settings. In two studies, we analysed data from face-to-face (Study 1, N = 124) and virtual (Study 2, N = 291) group interactions where participants were videotaped while performing a task and subsequently rated each other on popularity. Across studies, extraversion and the facets assertiveness and sociability were consistently associated with higher popularity, while the role of dominant behaviours differed. In Study 1, only two nonverbal behaviours, dominant gestures and upright posture, mediated the association between extraversion and popularity. In Study 2, all four types of behavioural cues mediated the association between extraversion (facets) and popularity. We discuss how these findings provide insights into the mechanisms of attaining popularity at zero acquaintance in diverse social settings.

Personality nuances and risk of dementia: Evidence from two longitudinal studies

Personality traits are broad constructs composed of nuances, operationalized by personality items, that can provide a more granular understanding of personality associations with health outcomes. This study examined the associations between personality nuances and incident dementia and evaluated whether nuances associations replicate across two samples. Health and Retirement Study (HRS, N = 11,400) participants were assessed in 2006/2008, and the English Longitudinal Study of Ageing (ELSA, N = 7453) participants were assessed in 2010/2011 on personality and covariates. Dementia incidence was tracked for 14 years in the HRS and 8 years in ELSA. In both HRS and ELSA, higher neuroticism domain and nuances (particularly nervous and worry) were related to a higher risk of incident dementia, whereas higher conscientiousness domain and nuances (particularly responsibility and organization) were associated with a lower risk of dementia. To a lesser extent, higher extraversion (active), openness (broad-minded, curious, and imaginative), and agreeableness (helpful, warm, caring, and sympathetic) nuances were associated with a lower risk of dementia, with replicable effects across the two samples. A poly-nuance score, aggregating the effects of personality items, was associated with an increased risk of incident dementia in the HRS and ELSA, with effect sizes slightly stronger than those of the personality domains. Clinical, behavioral, psychological, and genetic covariates partially accounted for these associations. The present study provides novel and replicable evidence for specific personality characteristics associated with the risk of incident dementia.

Nuanced HEXACO: A Meta-Analysis of HEXACO Cross-Rater Agreement, Heritability, and Rank-Order Stability

Most Five-Factor Model (FFM) questionnaire items contain unique variance that is partly heritable, stable, and consensually observable, demonstrates consistent associations with age and sex, and predicts life outcomes beyond higher order factors. Extending these findings to the HEXACO model, we meta-analyzed single-item cross-rater agreement, heritability, and 2-year stability using samples from six countries. We analyzed raw item scores and their residual variance and adjusted the estimates for measurement unreliability. The median cross-rater agreement, heritability, and stability estimates were, respectively, .30, .30, and .57, for raw items and .10, .16, and .39, for item residuals. Adjusted for reliability, the respective medians were .46 and .25 for cross-rater agreement, .46 and .39 for heritability, and .87 and .94 for stability. These results are strikingly consistent with FFM-based findings, providing nondismissible evidence that single items index a partly unique level of the trait hierarchy-personality nuances-with trait properties comparable to those of higher-order traits.

Personality aspects and proenvironmental attitudes

OBJECTIVE

Climate change is a serious threat. Personality psychologists can help address this threat by understanding what kind of people tend to endorse proenvironmental attitudes and engage in sustainable behavior. Previous research supports reliable associations between proenvironmental attitudes and personality traits. However, this research has generally aggregated different kinds of attitudes into a single composite and has focused on the domain level of personality traits.

METHOD

This study explored how 10 lower-order aspects of the Big Five personality traits were related to eight different proenvironmental attitudes in three convenience samples from the United States (N = 1234; 1000) and the United Kingdom (N = 538).

RESULTS

All five trait domains were related to at least one proenvironmental attitude across all three samples. Seven of eight proenvironmental attitudes could be predicted by one or more traits in all three samples. We also found evidence that the Openness aspect of Openness to Experience was a more consistent predictor of proenvironmental attitudes than the Intellect aspect. In contrast, there was little benefit in distinguishing between the aspects of other trait domains. We did not find evidence that age or political orientation moderated the associations between proenvironmental attitudes and personality.

CONCLUSION

Results point to the need for more fine-grained research on individual differences in proenvironmental attitudes and behavior.

Self- and informant-reported personality traits and vaccination against COVID-19

As COVID-19 vaccines' accessibility has grown, so has the role of personal choice in vaccination, and not everybody is willing to vaccinate. Exploring personality traits' associations with vaccination could highlight some person-level drivers of, and barriers to, vaccination. We used self- and informant-ratings of the Five-Factor Model domains and their subtraits (a) measured approximately at the time of vaccination with the 100 Nuances of Personality (100NP) item pool (N = 56,575) and (b) measured on average ten years before the pandemic with the NEO Personality Inventory-3 (NEO-PI-3; N = 3,168). We tested individual domains' and either items' (in the 100NP sample) or facets' (in the NEO-PI-3 sample) associations with vaccination, as well as their collective ability to predict vaccination using elastic net models trained and tested in independent sample partitions. Although the NEO-PI-3 domains and facets did not predict vaccination ten years later, the domains correlated with vaccination in the 100NP sample, with vaccinated people scoring slightly higher on neuroticism and agreeableness and lower on openness, controlling for age, sex, and education. Collectively, the five domains predicted vaccination with an accuracy of r = .08. Associations were stronger at the item level. Vaccinated people were, on average, more science-minded, politically liberal, respectful of rules and authority, and anxious but less spiritual, religious, and self-assured. The 100NP items collectively predicted vaccination with r = .31 accuracy. We conclude that unvaccinated people may be a psychologically heterogeneous group and highlight some potential areas for action in vaccination campaigns.

Using sequences of life-events to predict human lives

Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event sequences. We do this by drawing on a comprehensive registry dataset, which is available for Denmark across several years, and that includes information about life-events related to health, education, occupation, income, address and working hours, recorded with day-to-day resolution. We create embeddings of life-events in a single vector space, showing that this embedding space is robust and highly structured. Our models allow us to predict diverse outcomes ranging from early mortality to personality nuances, outperforming state-of-the-art models by a wide margin. Using methods for interpreting deep learning models, we probe the algorithm to understand the factors that enable our predictions. Our framework allows researchers to discover potential mechanisms that impact life outcomes as well as the associated possibilities for personalized interventions.

Association of personality facets and cognition in the Lifelines population-based cohort study

BACKGROUND

Personality traits have been associated with cognitive functioning and risk of cognitive decline. Fewer studies have investigated how personality facets are associated with cognition in large cohorts with a prospective design.

METHODS

The association between eight personality facets and cognition (speed measures reflecting psychomotor speed and visual attention; hit rate measures reflecting visual learning and working memory) was analyzed in middle-aged adults from the Lifelines cohort (N = 79911; age 43 ± 11 years).

RESULTS

High hostility, high vulnerability, low excitement seeking, and low competence were associated with worse cognitive performance on all tasks. Impulsivity-related facets had weak and differential associations, with self-discipline negatively associated with accuracy and deliberation negatively associated with speed. These associations remained largely unchanged when accounting for lifestyle factors (smoking, alcohol consumption, physical activity). The associations with cognition were stronger in older people for impulsiveness, deliberation, and hostility, while stronger in younger people for excitement seeking, self-discipline, and vulnerability.

CONCLUSION

In a large population-based sample with a broad age range, the associations of personality facets with cognitive functioning had small effect sizes, were independent of lifestyle factors, and varied with age and among facets within the same personality domain. These findings highlight the importance of developmental stages and facet-level research in personality-cognition associations.

Social expectations as a possible mechanism for adult personality change: Limited empirical evidence for the social investment principle

OBJECTIVE

Personality traits change in both mean levels and variance across the life span but the mechanisms underlying these developmental trends remain unclear. Social Investment Principle (SIP) suggests that social expectations drive personality changes in adulthood. Accordingly, we tested whether differences between personality traits in social expectations for them can explain their different change trajectories in young adulthood.

METHODS

A pool of 257 personality items was used to measure personality traits' means and variances (N = 1096), and levels expected by friends, partners and bosses/supervisors (N = 121).

RESULTS

Raters were consistent in their expectations for how young adults should think, feel and behave. Traits under stronger expectations had higher mean levels and lower variances than traits under lower expectations; trait means and variances increased with age, but inconsistently with the SIP, these increases were unrelated to the traits' expected levels.

CONCLUSION

Our results are only partially consistent with the SIP.

The Predictive Validity of Item Effect Variables in the Satisfaction With Life Scale for Psychological and Physical Health

Although the Satisfaction with Life Scale strives to capture a single dimension, describing respondents' satisfaction with life as a whole, individual items might also capture unique aspects of life satisfaction leading to some form of multidimensionality. Such systematic item-specific variance can be viewed as a content-laden secondary trait. Information on the nomological net and predictive validity can be useful to aid the interpretation of these item-specific effects. Therefore, the present study on N = 2,543 Dutch respondents adopts revised latent state-trait theory to disentangle common construct variance, random measurement error, and person-specific item effects in the Satisfaction with Life Scale across three measurement occasions. The reported analyses not only demonstrate how to examine item-specific multidimensionality in longitudinal data but also emphasize how different identification constraints for the latent variable lead to different interpretations. Moreover, the predictive validity of item effect variables for the prediction of psychological and physical health is examined. A cross-validation with the same sample at a later measurement period and robustness checks with incomplete data, support our findings on the substantive value of a multidimensional specification of the Satisfaction with Life Scale for substantive analyses. Finally, the contributions of person-specific item effects for psychological assessments are discussed.

Studying item-effect variables and their correlation patterns with multi-construct multi-state models

Method effects on the item level can be modeled as latent difference variables in longitudinal data. These item-effect variables represent interindividual differences associated with responses to a specific item when assessing a common construct with multi-item scales. In latent variable analyses, their inclusion substantially improves model fits in comparison to classical unidimensional measurement models. More importantly, covariations between different item-effect variables and with other constructs can provide valuable insights, for example, into the structure of the studied instrument or the response process. Therefore, we introduce a multi-construct multi-state model with item-effect variables for systematic investigations of these correlation patterns within and between constructs. The implementation of this model is demonstrated using a sample of N = 2,529 Dutch respondents that provided measures of life satisfaction and positive affect at five measurement occasions. Our results confirm non-negligible item effects in two ostensibly unidimensional scales, indicating the importance of modeling interindividual differences on the item level. The correlation pattern between constructs indicated rather specific effects for individual items and no common causes, but the correlations within a construct align with the item content and support a substantive meaning. These analyses exemplify how multi-construct multi-state models allow the systematic examination of item effects to improve substantive and psychometric research.

The social, emotional, and behavioral skill antecedents to college students' volunteering during the COVID-19 pandemic

The disruptions to community functioning caused by the COVID-19 pandemic spurred individuals to action. This empirical study investigated the social, emotional, and behavioral (SEB) skill antecedents to college students' volunteering during the COVID-19 pandemic (N = 248, Mage = 20.6). We assessed eight SEB skills at the onset of a volunteering program, and students' volunteer hours were assessed 10-weeks later. Approximately 41.5% of the sample did not complete any volunteer hours. Higher levels of perspective taking skill, abstract thinking skill, and stress regulation were associated with more time spent volunteering. These results suggest that strength in particular SEB skills can prospectively predict prosocial civic behaviors.

Trait and facet personality similarity and relationship and life satisfaction in romantic couples

Previous research has shown that personality similarity plays a negligible role in explaining the life and relationship satisfaction of couples. However, similarity in more proximally measured personality (i.e., facets) might explain additional variance in partners' well-being. The current study examined if in a sample of 1294 female-male romantic couples individual and partner personality traits and facets were associated with life and relationship satisfaction in expected ways. Similarity in personality traits and facets was not robustly associated with either life or relationship satisfaction of partners. The results are discussed in the context of the predictive validity of personality facets.

Investigating general and specific psychopathology factors with nuance-level personality traits

Mental health disorders share substantial variance, prompting researchers to develop structural models that can capture both generalised psychopathology risk and disorder/symptom-specific variation. This study investigated the associations of the general and specific psychopathology factors with multiple personality trait hierarchy levels: broad domains, their facets and nuances (N = 1839 Estonian adults). A bi-factor model with a general 'p' factor and specific factors for internalising problems, thought disorders and substance use best represented psychopathology structure. Although traits' predictive accuracy varied across psychopathology factors, nuances (the lowest level personality units) provided higher predictive accuracy and higher discriminant validity than domains. For example, traits related to high vulnerability, depression and immoderation and low friendliness and achievement striving were most strongly associated with the p factor. Nuances may prove useful for predicting and understanding general and specific psychopathology forms.

Personality change through a digital-coaching intervention: Using measurement invariance testing to distinguish between trait domain, facet, and nuance change

Recent intervention research has shown that personality traits can be modified through psychological interventions. However, it is unclear whether reported effects represent changes in the trait domain or only some facets or items. Using data ( N = 552) from a recent intervention trial, the present study examined the effects of a digital-coaching intervention on self- and observer-reported personality facets and items. We focused on participants who wanted to decrease in Negative Emotionality, increase in Conscientiousness or increase in Extraversion. We used measurement invariance testing to examine which level of the trait domain hierarchy changed during the intervention. For the self-reports, we found some heterogeneity in the effects on all three trait domains, but most notably Extraversion and Conscientiousness. Specifically, participants reported to increase strongly on sociability (Extraversion), and moderately on productiveness and organization (Conscientiousness), but not on the other facets of these trait domains. Observers generally reported small but non-significant changes, with no scalar invariance violations except for Extraversion. Overall, this suggests considerable heterogeneity in intervention-related personality change that can be overlooked if only focusing on the trait domain level. We discuss the relevance of measurement invariance testing and measurement approaches for personality development and intervention research.

Negative internal working models as mechanisms that link mothers' and fathers' personality with their parenting: A short-term longitudinal study

OBJECTIVE

Research on associations between parents' personality and parenting has a long history, but mechanisms that explain them remain unsettled. We examined parents' explicit and implicit negative internal working models (IWMs) of the child, assessed at toddler age, as linking parental personality and parenting.

METHOD

Mothers and fathers from 200 community families provided personality self-reports (Neuroticism, Agreeableness, Empathy, and Anger/Hostility) when their children were infants. When children were toddlers, the explicit negative IWMs included self-reported low-mentalizing reflective functioning and resentment regarding the child. The implicit negative IWMs were coded as negative relational schemas from parental interviews. Parental positive affect, responsiveness, and power-assertive control were observed in lengthy interactions. Measures were parallel for mother- and father-child dyads.

RESULTS

Mothers' implicit IWMs linked the association between low Empathy and more power-assertive control. Fathers' explicit IWMs linked the associations between high Neuroticism and low Agreeableness and lower responsiveness. Additionally, fathers' Agreeableness and Empathy directly predicted their parenting. Two paths (Agreeableness → implicit IWMs, and explicit IWMs → responsiveness) significantly differed between mothers and fathers.

CONCLUSIONS

IWMs may link parental personality with parenting. The findings integrate and inform several bodies of literature in personality, social cognition, and developmental psychology.

Dose–response Relationship of Reported Lifetime Meditation Practice with Mental Health and Wellbeing: a Cross-sectional Study

Objectives

Meta-analyses of meditation studies have revealed mixed modest evidence of benefits across a range of outcomes. However, because this evidence-base is predominantly from brief interventions, it is unclear whether it accurately reflects how contemporary meditators practice or the dose–response relationship between amount of practice and outcome. This study sought to characterize how contemporary meditators practice, examine any possible dose–response relationships between historical practice and measures of psychological wellbeing, and explore which characteristics of practice most strongly predict favorable psychological outcomes.

Methods

One thousand six hundred and sixty-eight meditators (M = 1095 h practice, SD = 2365) responded to advertisements in meditation practice communities and social media. We explored associations between demographics, meditation practice characteristics, and outcomes including positive and negative affect, psychological distress, and life satisfaction in a cross-sectional study design.

Results

Historical meditation practice (accumulated lifetime hours) was significantly associated with favorable psychological outcomes (|r| ranging from .18 to .28). Model fit was optimized with a generalized additive model (average increase in R² = 2.22), indicating non-linear effects. The strength of association between practice time and outcomes was generally strongest for approximately the first 500 h, before plateauing. Several practice types including Vipassana (as taught by S.N. Goenka) and cultivating practices (e.g. compassion, lovingkindness) were more strongly predictive of favorable psychological outcomes.

Conclusions

Benefits of meditation accrue over time in a non-linear manner, and show variation based on practice context. These results highlight the importance of understanding how the benefits of meditation accrue over longer time durations than typical standardized programs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12671-022-01977-6.

The Behavioral, Emotional, and Social Skills Inventory (BESSI): Psychometric Properties of a German-Language Adaptation, Temporal Stabilities of the Skills, and Associations with Personality and Intelligence

Social, emotional, and behavioral (SEB) skills comprise a broad set of abilities that are essential for building and maintaining relationships, regulating emotions, selecting and pursuing goals, or exploring novel stimuli. Toward an improved SEB skill assessment, Soto and colleagues recently introduced the Behavioral, Emotional, and Social Skills Inventory (BESSI). Measuring 32 facets from 5 domains with 192 items (assessment duration: ~15 min), BESSI constitutes the most extensive SEB inventory to date. However, so far, BESSI exists only in English. In three studies, we comprehensively validated a novel German-language adaptation, BESSI-G. Moreover, we expanded evidence on BESSI in three ways by (1) assessing the psychometric properties of the 32 individual skill facets, in addition to their domain-level structure; (2) providing first insights into the temporal stabilities of the 32 facets over 1.5 and 8 months; and (3) investigating the domains' and facets' associations with intelligence, in addition to personality traits. Results show that BESSI-G exhibits good psychometric properties (unidimensionality, reliability, factorial validity). Its domain-level structure is highly similar to that of the English-language source version. The facets show high temporal stabilities, convergent validity with personality traits, and discriminant validity with fluid and crystallized intelligence. We discuss implications for research on SEB skills.

The empathic personality profile: Using personality characteristics to reveal genetic, environmental, and developmental patterns of adolescents' empathy

How do genetic and environmental processes affect empathy during early adolescence? This study illumined this question by examining the etiology of empathy with the etiology of other personality characteristics. Israeli twin adolescents rated their empathy and personality at ages 11 (N=1176) and 13 (N=821) (733 families, 51.4% females). Parents rated adolescents' emotional empathy. Adolescents performed an emotion recognition task, indicating cognitive empathy. Using a cross-validated statistical learning algorithm, this study found emotional and cognitive 'empathic personality profiles', which describe and predict self-reported empathy from nuanced Big-Five personality characteristics, or 'nuances' (i.e., individual items). These profiles predicted empathy moderately (R² =.17-.24) and were stable and robust, within each age and between ages. They also predicted empathy in a new sample of older non-twin adolescents (N=96) and were validated against non-self-report empathy measures. Both emotional and cognitive empathy were predicted by nuances representing positive attitudes toward others, trust, forgiveness, and openness to experiences. Emotional empathy was also predicted by nuances representing anxiousness and negative reactivity. Twin analyses revealed overlapping genetic and environmental influences on empathy and the empathic personality profiles and overlapping environmental influences on empathy-personality change. This study demonstrates how addressing the complexity of individuals' personalities can inform adolescents' empathy development.

A prediction-focused approach to personality modeling

In the current study, we set out to examine the viability of a novel approach to modeling human personality. Research in psychology suggests that people's personalities can be effectively described using five broad dimensions (the Five-Factor Model; FFM); however, the FFM potentially leaves room for improved predictive accuracy. We propose a novel approach to modeling human personality that is based on the maximization of the model's predictive accuracy. Unlike the FFM, which performs unsupervised dimensionality reduction, we utilized a supervised machine learning technique for dimensionality reduction of questionnaire data, using numerous psychologically meaningful outcomes as data labels (e.g., intelligence, well-being, sociability). The results showed that our five-dimensional personality summary, which we term the "Predictive Five" (PF), provides predictive performance that is better than the FFM on two independent validation datasets, and on a new set of outcome variables selected by an independent group of psychologists. The approach described herein has the promise of eventually providing an interpretable, low-dimensional personality representation, which is also highly predictive of behavior.

Facets of Personality and Risk of Cognitive Impairment: Longitudinal Findings in a Rural Community from Sardinia

Background: Few studies have examined the associations between personality facets and dementia risk and rarely included individuals from rural settings or with low education. Objective: To examine the association between personality and the risk of cognitive impairment. Methods: Participants (N = 1,668; age 50 to 94 at baseline; 56.4% women; 86.5% less than high school diploma) were from a rural region of Sardinia (Italy) who completed the Revised NEO Personality Inventory (NEO-PI-R) during the first wave (2001–2004) and the Mini-Mental State Examination (MMSE) at waves two to five (2005–2021). Cox regression was used to test personality and covariates as predictors of cognitive impairment based on MMSE education-adjusted cutoffs. Results: During the up to 18-year follow-up (M = 10.38; SD = 4.76), 187 individuals (11.2%) scored as cognitively impaired. Participants with higher neuroticism (particularly the depression facet [HR = 1.22, 95% CI = 1.06–1.40]), and lower agreeableness (particularly the modesty facet [HR = 0.83, 95% CI = 0.71–0.97]) and lower conscientiousness (particularly the dutifulness facet [HR = 0.78, 95% CI = 0.67–0.92]) were at higher risk of cognitive impairment. Lower warmth ([HR = 0.75, 95% CI = 0.65–0.87], facet of extraversion) and ideas ([HR = 0.76, 95% CI = 0.65–0.89], facet of openness) were also associated with increased risk of impairment. These associations were virtually unchanged in models that accounted for other risk factors, including smoking, depression, obesity, hypertension, diabetes, and apolipoprotein E (APOE) ɛ4 carrier status. Across the five domains, sex and the APOE variant did not moderate the associations. Conclusion: In a sample with demographic characteristics underrepresented in dementia research, this study identifies personality domains and facets most relevant to the risk of cognitive impairment.

Machine Learning and Prediction in Psychological Assessment

Abstract. Modern prediction methods from machine learning (ML) and artificial intelligence (AI) are becoming increasingly popular, also in the field of psychological assessment. These methods provide unprecedented flexibility for modeling large numbers of predictor variables and non-linear associations between predictors and responses. In this paper, we aim to look at what these methods may contribute to the assessment of criterion validity and their possible drawbacks. We apply a range of modern statistical prediction methods to a dataset for predicting the university major completed, based on the subscales and items of a scale for vocational preferences. The results indicate that logistic regression combined with regularization performs strikingly well already in terms of predictive accuracy. More sophisticated techniques for incorporating non-linearities can further contribute to predictive accuracy and validity, but often marginally.

Put your feet up: The impact of personality traits, job pressure, and social support on the need for recovery after work

The need for recovery after work (NFR) is an important warning of work-related fatigue. NFR is linked to prolonged work-related efforts and depletion of resources, creating a need for temporary respite from work demands. The aim of the current study was to investigate the relationships between NFR and the five-factor model (FFM), comprising the personality traits of emotional stability (ES), extraversion (E), agreeableness (A), conscientiousness (C), and openness to experience (O). Perceived job pressure and perceived social support were included as mediators. The study was conducted using structural equation modelling (SEM) on cross-sectional data from a sample of 681 participants from several work sectors (N females = 376, N males = 305; M age = 46.9 years; SD = 11.1). The results showed that NFR was affected both directly and indirectly by FFM traits. High ES and high O contributed directly to reduced and increased NFR, respectively. High perceived social support contributed to reduced NFR, while high perceived job pressure contributed to increased NFR. High ES contributed indirectly to reduced NFR through perceived job pressure and social support, high O contributed indirectly to increased NFR through perceived social support, and high E contributed indirectly to increased NFR through perceived job pressure. A and C were not related to NFR. The findings demonstrate that personality traits, especially ES, are firmly related to NFR and highlight the importance of incorporating personality factors into studies of work environmental factors on NFR.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-022-02950-1.