The Basel Face Database: A validated set of photographs reflecting systematic differences in Big Two and Big Five personality dimensions.
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ABSTRACT:
SUBMITTER: Walker M
PROVIDER: S-EPMC5873939 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Individual differences in basal leukocyte gene expression profiles as a function of Big 5 personality dimensions
2015-01-28 | GSE60491 | GEO
Project description:Individual differences in basal leukocyte gene expression profiles as a function of Big 5 personality dimensions Gene expression profiling was carried out on peripheral blood mononuclear cell RNA samples collected from 119 healthy adults measured for the 5 major dimensions of human personality (Neuroticism, Extraversion, Openness, Agreeableness, Conscientiousness) using the NEO-FFI 60-item personality inventory. Personality measures are z-score standardized. Analyses control for major demographic characteristics (age, sex, Caucasian vs Non-Caucasian race) as well as Body Mass Index (BMI), smoking (CigDay), alcohol consumption (AlcDay), and physical activity (ExerDay, hours per day). Additional secondary analyses controlled for the presence of minor physical symptoms (MinorSymptom, e.g.,hayfever, headache), medication use (BirthControl, Antidepressant, OtherMedication), and negative affective states (NegativeAffect, standardized values of PANAS Negative Affect scale). Experiment type: Risk prediction
2015-01-28 | E-GEOD-60491 | biostudies-arrayexpress
Project description:Introduction Openness, conscientiousness, extroversion, agreeableness and neuroticism are known as the Big Five personality traits (BFPT). They are theoretical building blocks of the personality and comprise wide and interconnected spectra. Artificial intelligence (AI) could help to grasp their complexity. Objectives To investigate whether AI could predict the BFPT from themselves. Methods Data from 2,697 questionnaires were analysed using an AI. The short form of the International Personality Item Pool was used to assess the BFPT. Four of the BFPT scores were employed to predict the fifth one and the procedure was repeated for all of them alternatively. The AI was conservatively tuned to maximize the one-way random intraclass correlation coefficient (ICC) between predicted and real values. Their Pearson’s r was calculated too. The free and open source programming language R was used for all the analyses. Dataset source: Hansson, Isabelle; Berg, Anne Ingeborg; Thorvaldsson, Valgeir (2018), “Can personality predict longitudinal study attrition? Evidence from a population-based sample of older adults”, Mendeley Data, V1, doi: 10.17632/g3jx8zt2t9.1 Results Openness, conscientiousness, extroversion, agreeableness and neuroticism predictions obtained ICC of 0.219, 0.146, 0.306, 0.354, 0.121 and Pearson’s r of 0.254, 0.149, 0.393, 0.446, 0.122 respectively. The results for extroversion and agreeableness were indicative of fair performance. Conclusions AI might be useful to predict personality traits, mainly extroversion and agreeableness. This could be utile in many situations, such as dealing with missing data or deciding whether to formally test someone. Finally, the AI used in this study is freely available, allowing anyone to experiment.
| S-EPMC9475767 | biostudies-literature
Project description:Personality traits are summarized by five broad dimensions with pervasive influences on major life outcomes, strong links to psychiatric disorders and clear heritable components. To identify genetic variants associated with each of the five dimensions of personality we performed a genome-wide association (GWA) scan of 3972 individuals from a genetically isolated population within Sardinia, Italy. On the basis of the analyses of 362 129 single-nucleotide polymorphisms we found several strong signals within or near genes previously implicated in psychiatric disorders. They include the association of neuroticism with SNAP25 (rs362584, P=5 x 10(-5)), extraversion with BDNF and two cadherin genes (CDH13 and CDH23; Ps<5 x 10(-5)), openness with CNTNAP2 (rs10251794, P=3 x 10(-5)), agreeableness with CLOCK (rs6832769, P=9 x 10(-6)) and conscientiousness with DYRK1A (rs2835731, P=3 x 10(-5)). Effect sizes were small (less than 1% of variance), and most failed to replicate in the follow-up independent samples (N up to 3903), though the association between agreeableness and CLOCK was supported in two of three replication samples (overall P=2 x 10(-5)). We infer that a large number of loci may influence personality traits and disorders, requiring larger sample sizes for the GWA approach to confidently identify associated genetic variants.
| S-EPMC2874623 | biostudies-literature
Project description:Backgrounds Accelerated cellular ageing, which can be examined by telomere length (TL), may be an overarching mechanism underlying the association between personality and adverse health outcomes. This 6-year longitudinal study examined the relation between personality and leukocyte telomere length (LTL) across time among adults with a wide age-range.MethodsData from the Netherlands Study of Depression and Anxiety were used and included patients with a depression and/or anxiety disorder and healthy controls. Overall, 2936 persons (18-65 years, 66% female) had data on LTL at baseline and 1883 persons had LTL at 6-year follow-up. The Big Five personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) and Type D personality were assessed.ResultsNeuroticism was negatively (B = -2.11, p = 0.03) and agreeableness was positively (B = 3.84, p = 0.03) related to LTL measured across two time points, which became just non-significant after adjusting for somatic health, lifestyle factors, and recent life stress (B = -1.99, p = 0.06; and B = 3.01, p = 0.10). Type D personality was negatively (B = -50.16, p < 0.01) related to LTL across two time points, which still remained statistically significant after full adjustment (B = -47.37, p = 0.01). Associations did not differ by age, gender, and current psychiatric status.ConclusionsThe Big Five traits high neuroticism and low agreeableness, and Type D personality were associated with shorter LTL measured across a 6-year period. Associations with the Big Five traits became non-significant after controlling for somatic health, lifestyle factors, and recent life stress, yet similar trends were observed. Type D personality remained independently associated with shorter LTL after full adjustment.
| S-EPMC5851042 | biostudies-literature
Project description:We used a new theory of the biological basis of the Big Five personality traits to generate hypotheses about the association of each trait with the volume of different brain regions. Controlling for age, sex, and whole-brain volume, results from structural magnetic resonance imaging of 116 healthy adults supported our hypotheses for four of the five traits: Extraversion, Neuroticism, Agreeableness, and Conscientiousness. Extraversion covaried with volume of medial orbitofrontal cortex, a brain region involved in processing reward information. Neuroticism covaried with volume of brain regions associated with threat, punishment, and negative affect. Agreeableness covaried with volume in regions that process information about the intentions and mental states of other individuals. Conscientiousness covaried with volume in lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. These findings support our biologically based, explanatory model of the Big Five and demonstrate the potential of personality neuroscience (i.e., the systematic study of individual differences in personality using neuroscience methods) as a discipline.
| S-EPMC3049165 | biostudies-literature
Project description:Can personality traits be measured and interpreted reliably across the world? While the use of Big Five personality measures is increasingly common across social sciences, their validity outside of western, educated, industrialized, rich, and democratic (WEIRD) populations is unclear. Adopting a comprehensive psychometric approach to analyze 29 face-to-face surveys from 94,751 respondents in 23 low- and middle-income countries, we show that commonly used personality questions generally fail to measure the intended personality traits and show low validity. These findings contrast with the much higher validity of these measures attained in internet surveys of 198,356 self-selected respondents from the same countries. We discuss how systematic response patterns, enumerator interactions, and low education levels can collectively distort personality measures when assessed in large-scale surveys. Our results highlight the risk of misinterpreting Big Five survey data and provide a warning against naïve interpretations of personality traits without evidence of their validity.
| S-EPMC6620089 | biostudies-other
Project description:There is ample evidence that morphological and social cues in a human face provide signals of human personality and behaviour. Previous studies have discovered associations between the features of artificial composite facial images and attributions of personality traits by human experts. We present new findings demonstrating the statistically significant prediction of a wider set of personality features (all the Big Five personality traits) for both men and women using real-life static facial images. Volunteer participants (N = 12,447) provided their face photographs (31,367 images) and completed a self-report measure of the Big Five traits. We trained a cascade of artificial neural networks (ANNs) on a large labelled dataset to predict self-reported Big Five scores. The highest correlations between observed and predicted personality scores were found for conscientiousness (0.360 for men and 0.335 for women) and the mean effect size was 0.243, exceeding the results obtained in prior studies using 'selfies'. The findings strongly support the possibility of predicting multidimensional personality profiles from static facial images using ANNs trained on large labelled datasets. Future research could investigate the relative contribution of morphological features of the face and other characteristics of facial images to predicting personality.
| S-EPMC7244587 | biostudies-literature
Project description:The Diagnostic and Statistical Manual of Mental Disorders (DSM; 5th ed.) reassignment of gambling disorder as an addictive disorder alongside the substance-related addictive disorders encourages research into their shared etiologies. The aims of this study were to examine: (a) the associations of Big Five personality dimensions with alcohol, nicotine, cannabis, and gambling disorders, (b) the comorbidity between these disorders, (c) the extent to which common personality underpinnings explain comorbidity, (d) whether results differed for men and women, and (e) the magnitude of personality differences corresponding to the 4 disorders. Participants were 3,785 twins and siblings (1,365 men, 2,420 women; Mage = 32 years, range = 21-46 years) from the Australian Twin Registry who completed psychiatric interviews and Big Five personality inventories. The personality profile of high neuroticism, low agreeableness, and low conscientiousness was associated with all 4 addictive disorders. All but 1 of the pairwise associations between the disorders were significant. After accounting for Big Five traits, the associations were attenuated to varying degrees but remained significant. The results were generally similar for men and women. The results suggest that the Big Five traits of neuroticism, agreeableness, and conscientiousness are associated with the general propensity to develop an addictive disorder and may in part explain their co-occurrence; however, they may be more broadly associated with the propensity for any psychiatric disorder. The effect sizes of the personality associations suggest that the diagnosis of gambling disorder as operationalized by the DSM may be more severe than the other addictive disorders. Calibration of the diagnosis of gambling disorder to the other addictive disorders may be warranted. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Project description:Based on Eysenck's biopsychological trait theory, brain arousal has long been considered to explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. However, most published results have been derived from small samples and, despite inherent limitations, EEG alpha power has usually served as an exclusive indicator for brain arousal. To overcome these problems, we here selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and brain arousal by using the validated EEG- and EOG-based analysis tool VIGALL. Our analyses revealed that participants who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of brain arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained the strongest evidence for neuroticism facet 'impulsivity' and reduced brain arousal. In line with this, both impulsivity and openness have previously been conceptualized as aspects of extraversion. We regard our findings as well in line with the postulations of Eysenck and consistent with the recently proposed 'arousal regulation model'. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large (collaborative) studies.
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