Attachment and Political Personality are Heritable and Distinct Systems, and Both Share Genetics with Interpersonal Trust and Altruism.

The attachment and caregiving domains maintain proximity and care-giving behavior between parents and offspring, in a way that has been argued to shape people's mental models of how relationships work, resulting in secure, anxious or avoidant interpersonal styles in adulthood. Several theorists have suggested that the attachment system is closely connected to orientations and behaviors in social and political domains, which should be grounded in the same set of familial experiences as are the different attachment styles. We use a sample of Norwegian twins (N = 1987) to assess the genetic and environmental relationship between attachment, trust, altruism, right-wing authoritarianism (RWA), and social dominance orientation (SDO). Results indicate no shared environmental overlap between attachment and ideology, nor even between the attachment styles or between the ideological traits, challenging conventional wisdom in developmental, social, and political psychology. Rather, evidence supports two functionally distinct systems, one for navigating intimate relationships (attachment) and one for navigating social hierarchies (RWA/SDO), with genetic overlap between traits within each system, and two distinct genetic linkages to trust and altruism. This is counter-posed to theoretical perspectives that link attachment, ideology, and interpersonal orientations through early relational experiences.

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.

The longitudinal relationship between life events and loneliness in adolescence: A twin study.

The aim of the study was to examine associations between life events and self-assessed loneliness in adolescence. We used data from a Norwegian population-based twin sample including seven birth cohorts (N = 2,879, 56% females). The participants completed self-report questionnaires three times throughout adolescence, with 2 years in between (i.e., 12-18 years old at Wave 1). By using a random intercept cross-lagged panel model (RI-CLPM), we were able to separate stable influences in the measured constructs from the within-person changes at each measurement occasion. In addition, using data from twins allowed us to examine to what degree the associations between life events and loneliness were genetic and/or environmental in nature. The results showed moderate stability of both loneliness and aggregation scores of life events throughout adolescence. The life events were assigned to clusters based on their independence (i.e., events considered dependent or independent on a person's behavior) and desirability (i.e., positive or negative). The time-stable between-person variance in all three measures, loneliness and person-dependent positive and negative life events, could almost exclusively be accounted for by genetic factors. However, as expected, also shared environmental factors influenced person-independent life events. The associations between time-stable between-person variance in loneliness and life events were small, and nearly exclusively due to shared genetic influences. Furthermore, life events do not seem to predict changes in loneliness or vice versa. In conclusion, the self-reported levels of loneliness throughout adolescence seems to be independent of life events. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Suicide attempt risk predicts inconsistent self-reported suicide attempts: A machine learning approach using longitudinal data.

INTRODUCTION: Inconsistent self-reports of lifetime suicide attempts (LSAs) are a major obstacle for accurate assessment of suicidal behavior. This study is the first to posit that adolescents at higher risk report LSAs more consistently than those at lower risk, revealing a link between suicide attempt risk and consistent reporting. METHODS: A machine learning model was trained with 70 % of the baseline assessment data of a longitudinal sample of Norwegian adolescents (n = 10,739). The model was used to estimate the LSA risk score for the remaining 30 % of the testing dataset. The relationship between these baseline risk scores and the consistency of reporting LSAs was assessed using a 2-year follow-up reassessment of the testing dataset. RESULTS: Internalizing problems, optimism about the future, conduct problems, substance use, and disordered eating were important factors associated with suicide attempt risk. Of the participants, 63.41 % had inconsistent self-reports at the two-year follow-up. Adolescents who consistently reported LSAs had significantly higher scores of suicide attempt risk at baseline. Two logistic regression analyses confirmed an association between suicide attempt risk and inconsistent self-reported LSAs and showed that sex (being male), and lower levels of depression and conduct problems significantly predicted such inconsistencies. Those who inconsistently reported LSAs were more likely than the others to be classified by the model as false negatives at the baseline risk assessment due to their lower estimated risk scores. LIMITATIONS: Suicide attempts were measured with a single item in this study. CONCLUSION: These risk factors support the theory of adolescent suicidality (TAS) and could improve suicide attempt risk assessment. Inconsistent self-reported LSAs signal lower suicide attempt risk.

A Web-Based Intervention Using "Five Ways to Wellbeing" to Promote Well-Being and Mental Health: Randomized Controlled Trial.

BACKGROUND: Compromised well-being and mental health problems pose a significant threat to individuals and societies worldwide. Resource-intensive psychological treatments alone cannot alleviate this burden. There is a need for low-cost, evidence-based interventions aimed at preventing illness and promoting well-being. Five activity domains appear to be linked with well-being promotion across populations: connecting with others, being active, taking notice, learning, and being generous/giving. The activities mentioned are part of the Five Ways to Wellbeing framework and the web-based intervention Five Ways to Wellbeing for All (5waysA). OBJECTIVE: This randomized controlled trial aims to test the effects of the 5waysA intervention, a web-based, low-cost, well-being-promoting measure targeting the general population. To date, the Five Ways to Wellbeing framework has not been tested in this specific format. The 5waysA intervention comprises 2 webinars and SMS text message reminders delivered over a 10-week period. METHODS: In 2021, a total of 969 study participants from various regions across Norway were openly recruited through a web page. They were then randomly assigned to either an intervention group or 1 of 2 waiting list control groups, namely, active or passive. Self-reported life satisfaction (Satisfaction With Life Scale [SWLS]), flourishing (Flourishing Scale [FS]), positive emotions, anxiety, and depression symptoms (Hopkins Symptom Checklist-8 [HSCL-8]) were assessed before the intervention, at 4 weeks into the intervention, and 1-2 weeks after the intervention (over 10 weeks). Data analysis was conducted using linear mixed (multilevel) models. RESULTS: After 10 weeks, 453 participants (171 in the intervention group and 282 in the waiting list control group) were assessed on outcome variables, with a dropout rate of 53.2% (516/969). Results revealed a significantly greater increase in the intervention group compared with the controls for SWLS (b=0.13, 95% CI 0.03-0.23; P=.001), FS (b=0.19, 95% CI 0.08-0.30; P=.001), positive emotions (b=0.43, 95% CI 0.27-0.60; P<.001), and these factors combined into a global well-being measure (b=0.28, CI 0.16-0.39; P<.001). Effect sizes (Cohen d) for the well-being outcomes ranged from 0.30 to 0.49. In addition, a significant decrease in anxiety and depressive symptoms was observed (b=-0.17, 95% CI -0.30 to -0.04; P=.001) with an effect size (Cohen d) of -0.20. CONCLUSIONS: The findings suggest that the web-based 5waysA intervention could serve as an effective approach for enhancing well-being and mental health within the general population. This study offers individuals, policy makers, and local stakeholders an accessible and potentially cost-effective well-being intervention that could be easily implemented. TRIAL REGISTRATION: ClinicalTrials.gov NCT04784871; https://clinicaltrials.gov/study/NCT04784871.

Stressful life events exhibit complex patterns of associations with depressive symptoms in two population-based samples using network analysis.

BACKGROUND: Stressful life events (SLEs) constitute key risk factors for depression. However, previous studies examining associations between SLEs and depression have been limited by focusing on single events, combining events into broad categories, and/or ignoring interrelationships between events in statistical analyses. Network analysis comprises a set of statistical methods well-suited for assessing relationships between multiple variables and can help surpass several limitations of previous studies. METHODS: We applied network analysis using mixed graphical models combining two large-scale population-based samples and >34,600 randomly sampled adults to investigate the associations between SLEs and current depressive symptoms in the general population. RESULTS: Numerous SLEs were uniquely associated with specific symptoms. Strong pairwise links were observed between SLEs during the past year and individual symptoms, e.g., between having experienced illness or injury and sleeping problems, having been degraded or humiliated and feeling blue, and between financial problems and hopelessness and being worried and anxious. Several SLEs, such as financial problems, sexual abuse, and having been degraded or humiliated, were associated with symptoms across more than one timepoint. More recent SLEs were generally more strongly associated with depressive symptoms. Several life events were strongly interrelated, such as multiple forms of abuse, and financial problems, unemployment, divorce, and serious illness or injury. LIMITATIONS: Limitations include a retrospective SLE measure, cross-sectional data, a brief self-report measure of depressive symptoms, and possible attrition bias in the sample. CONCLUSIONS: Our findings may have implications for public health efforts seeking to improve population mental health.