The genetic underpinnings of right-wing authoritarianism and social dominance orientation explain political attitudes beyond Big Five personality

Objective: Political attitudes are predicted by the key ideological variables of right-wing authoritarianism (RWA) and social dominance orientation (SDO), as well as some of the Big Five personality traits. Past research indicates that personality and ideological traits are correlated for genetic reasons. A question that has yet to be tested concerns whether the genetic variation underlying the ideological traits of RWA and SDO has distinct contributions to political attitudes, or if genetic variation in political attitudes is subsumed under the genetic variation underlying standard Big Five personality traits. Method: We use data from a sample of 1987 Norwegian twins to assess the genetic and environmental relationships between the Big Five personality traits, RWA, SDO, and their separate contributions to political policy attitudes. Results: RWA and SDO exhibit very high genetic correlation (r = 0.78) with each other and some genetic overlap with the personality traits of openness and agreeableness. Importantly, they share a larger genetic substrate with political attitudes (e.g., deporting an ethnic minority) than do Big Five personality traits, a relationship that persists even when controlling for the genetic foundations underlying personality traits. Conclusion: Our results suggest that the genetic foundations of ideological traits and political attitudes are largely non-overlapping with the genetic foundations of Big Five personality traits

Emotional problems in preadolescents in Norway: the role of gender, ethnic minority status, and home- and school-related hassles

<p>Abstract</p> <p>Background</p> <p>"The gender gap" refers to a lifelong higher rate of emotional problems in girls, as compared to boys, that appears during adolescence. The gender gap is a well-replicated finding among older adolescents and is assumed to be a cross-cultural phenomenon. However, these cross-cultural studies have not investigated the gender gap in ethnic minorities but sampled ethnic majority adolescents in different countries. Some studies that investigated the gender gap across ethnic groups indirectly (by presenting emotional problem scores stratified by gender and ethnic group) indicate that the gender gap is less prominent or even absent among minorities. The aims of this study were to assess whether the gender gap is found in both majority and minority preadolescents, and to investigate whether a possible (gender and ethnic) group difference can be accounted for by differences in home or school hassles.</p> <p>Methods</p> <p>Participants were 902 preadolescent students (aged 10 to 12) from two cities in Norway. We collected self-report measures of emotional problems and home and school hassles. Using mediated moderation analysis we tested whether the interaction effect between gender and ethnic minority background on emotional problems was mediated by home or school hassles.</p> <p>Results</p> <p>The gender gap in emotional problems was restricted to ethnic majority preadolescents. School hassles but not home hassles accounted in part for this effect.</p> <p>Conclusions</p> <p>The absence of the gender gap among minority as opposed to majority preadolescents may indicate that social circumstances may postpone or hamper the emergence and magnitude of the gender gap in ethnic minority preadolescents. In this study, school hassles partly accounted for the combined gender and ethnic group differences on emotional problems. This indicates that school hassles may play a role in the higher levels of emotional problems in preadolescent minority boys and consequently the absence of a gender gap found in our minority sample.</p

Familial confounding or measurement error? How to interpret findings from sibling control studies.

Epidemiological researchers often examine associations between risk factors and health outcomes in non-experimental designs. Observed associations may be causal or confounded by unmeasured factors. Sibling and co-twin control studies account for familial confounding by comparing exposure levels among siblings (or twins). If the exposure-outcome association is causal, the siblings should also differ regarding the outcome. However, such studies may sometimes introduce more bias than they alleviate. Measurement error in the exposure may bias results and lead to erroneous conclusions that truly causal exposure-outcome associations are confounded by familial factors. The current study used Monte Carlo simulations to examine bias due to measurement error in sibling control models when the observed exposure-outcome association is truly causal. The results showed that decreasing exposure reliability and increasing sibling-correlations in the exposure led to deflated exposure-outcome associations and inflated associations between the family mean of the exposure and the outcome. The risk of falsely concluding that causal associations were confounded was high in many situations. For example, when exposure reliability was 0.7 and the observed sibling-correlation was r = 0.4, about 30–90% of the samples (n = 2,000) provided results supporting a false conclusion of confounding, depending on how p-values were interpreted as evidence for a family effect on the outcome. The current results have practical importance for epidemiological researchers conducting or reviewing sibling and co-twin control studies and may improve our understanding of observed associations between risk factors and health outcomes. We have developed an app (SibSim) providing simulations of many situations not presented in this paper

Maternal perinatal and concurrent depressive symptoms and child behavior problems:a sibling comparison study

Background: Previous studies have found significant associations between maternal prenatal and postpartum depression and child behavior problems (CBP). The present study investigates whether associations remain in a prospective, longitudinal design adjusted for familial confounding. Methods: The sample comprised 11,599 families including 17,830 siblings from the Norwegian Mother and Child Cohort study. Mothers reported depressive symptoms at gestational weeks 17 and 30, as well as 6 months, 1.5, 3, and 5 years postpartum. Fathers’ depression was measured at gestational week 17. At the last three time-points, child internalizing and externalizing problems were concurrently assessed. We performed multilevel analyses for internalizing and externalizing problems separately, using parental depression as predictors. Analyses were repeated using a sibling comparison design to adjust for familial confounding. Results: All parental depressive time-points were significantly and positively associated with child internalizing and externalizing problems. After sibling comparison, however, only concurrent maternal depression was significantly associated with internalizing [estimate = 2.82 (1.91–3.73, 95% CI)] and externalizing problems [estimate = 2.40 (1.56–3.23, 95% CI)]. The effect of concurrent maternal depression on internalizing problems increased with child age. Conclusions: Our findings do not support the notion that perinatal maternal depression is particularly detrimental to children's psychological development, as the most robust effects were found for maternal depression occurring during preschool years

The p factor of psychopathology and personality in middle childhood : genetic and gestational risk factors

A correction has been issued for this article: DOI: https://doi.org/10.1017/S0033291723000879BackgroundA joint, hierarchical structure of psychopathology and personality has been reported in adults but should also be investigated at earlier ages, as psychopathology often develops before adulthood. Here, we investigate the joint factor structure of psychopathology and personality in eight-year-old children, estimate factor heritability and explore external validity through associations with established developmental risk factors. MethodsPhenotypic and biometric exploratory factor analyses with bifactor rotation on genetically informative data from the Norwegian Mother, Father, and Child Cohort (MoBa) study. The analytic sub-sample comprised 10 739 children (49% girls). Mothers reported their children's symptoms of depression (Short Moods and Feelings Questionnaire), anxiety (Screen for Anxiety Related Disorders), attention-deficit/hyperactivity disorder inattention and hyperactivity, oppositional-defiant disorder, conduct disorder (Parent/Teacher Rating Scale for Disruptive Behavior Disorders), and Big Five personality (short Hierarchical Personality Inventory for Children). Developmental risk factors (early gestational age and being small for gestational age) were collected from the Medical Birth Registry. ResultsGoodness-of-fit indices favored a p factor model with three residual latent factors interpreted as negative affectivity, positive affectivity, and antagonism, whereas psychometric indices favored a one-factor model. ADE solutions fitted best, and regression analyses indicated a negative association between gestational age and the p factor, for both the one- and four-factor solutions. ConclusionCorrelations between normative and pathological traits in middle childhood mostly reflect one heritable and psychometrically interpretable p factor, although optimal fit to data required less interpretable residual latent factors. The association between the p factor and low gestational age warrants further study of early developmental mechanisms.Peer reviewe

Insights into the accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models