Character

Human personality is 30-60% heritable according to twin and adoption studies. Hundreds of genetic variants are expected to influence its complex development, but few have been identified. We used a machine learning method for genome-wide association studies (GWAS) to uncover complex genotypic-phenotypic networks and environmental interactions. The Temperament and Character Inventory (TCI) measured the self-regulatory components of personality critical for health (i.e., the character traits of self-directedness, cooperativeness, and self-transcendence). In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified five clusters of people with distinct profiles of character traits regardless of genotype. Third, we found 42 SNP sets that identified 727 gene loci and were significantly associated with one or more of the character profiles. Each character profile was related to different SNP sets with distinct molecular processes and neuronal functions. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of 95% of the 42 SNP sets in healthy Korean and German samples, as well as their associations with character. The identified SNPs explained nearly all the heritability expected for character in each sample (50 to 58%). We conclude that self-regulatory personality traits are strongly influenced by organized interactions among more than 700 genes despite variable cultures and environments. These gene sets modulate specific molecular processes in brain for intentional goal-setting, self-reflection, empathy, and episodic learning and memory.

BackgroundOver two-thirds of UK medical schools are augmenting their selection procedures for medical students by using the United Kingdom Clinical Aptitude Test (UKCAT), which employs tests of cognitive and non-cognitive personal qualities, but clear evidence of the tests' predictive validity is lacking. This study explores whether academic performance and professional behaviours that are important in a health professional context can be predicted by these measures, when taken before or very early in the medical course.MethodsThis prospective cohort study follows the progress of the entire student cohort who entered Hull York Medical School in September 2007, having taken the UKCAT cognitive tests in 2006 and the non-cognitive tests a year later. This paper reports on the students' first and second academic years of study. The main outcome measures were regular, repeated tutor assessment of individual students' interpersonal skills and professional behaviour, and annual examination performance in the three domains of recall and application of knowledge, evaluation of data, and communication and practical clinical skills. The relationships between non-cognitive test scores, cognitive test scores, tutor assessments and examination results were explored using the Pearson product-moment correlations for each group of data; the data for students obtaining the top and bottom 20% of the summative examination results were compared using Analysis of Variance.ResultsPersonal qualities measured by non-cognitive tests showed a number of statistically significant relationships with ratings of behaviour made by tutors, with performance in each year's objective structured clinical examinations (OSCEs), and with themed written summative examination marks in each year. Cognitive ability scores were also significantly related to each year's examination results, but seldom to professional behaviours. The top 20% of examination achievers could be differentiated from the bottom 20% on both non-cognitive and cognitive measures.ConclusionsThis study shows numerous significant relationships between both cognitive and non-cognitive test scores, academic examination scores and indicators of professional behaviours in medical students. This suggests that measurement of non-cognitive personal qualities in applicants to medical school could make a useful contribution to selection and admission decisions. Further research is required in larger representative groups, and with more refined predictor measures and behavioural assessment methods, to establish beyond doubt the incremental validity of such measures over conventional cognitive assessments.

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.

The self-interest bias describes an inclination of people to evaluate transgressors morally better when the latter's actions serve the former's interests. Effective interventions to mitigate this type of self-serving bias remain underexplored. The current research investigates education and accountability as potential moderators of this bias. In preregistered Study 1 (N = 668), as predicted, educating participants about the self-interest bias eliminated its effect on their moral character judgments. However, across three preregistered accountability studies (N = 2,239), holding participants accountable for their judgments did not attenuate the bias. Similarly, in preregistered Study 5 (N = 641), we found no evidence of a combined effect of education and accountability on reducing the bias. These findings suggest that while increasing awareness through education may effectively reduce biased moral judgments, accountability, especially when lacking external scrutiny or consequences, does not. Theoretical implications, methodological limitations, and future research opportunities are discussed.