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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. Public Significance Statement: This study suggests that life events do not influence levels of loneliness in adolescence. The weak associations between life events and loneliness were mainly due to shared genetic influences. Additionally, the results showed that levels of loneliness are moderately stable throughout this period of life, mainly due to genetic influences. Importantly, the study highlights the need of using genetically informative designs, also when studying the effects of assumed "environmental" measures. [ABSTRACT FROM AUTHOR]

Although previous studies have identified negative relationships between cognitive ability and emotional problems (EP), mechanism explaining these relationships remained unclear. This study evaluated two explanatory models using bivariate moderation model-fitting analysis in a twin design. The resilience model suggests that high cognitive ability decreases the risk of EP in adverse settings, and the scarring model suggests that EP symptoms lead to persistent cognitive deficits following onset. The Standard Progressive Matrices Plus (SPM) and EP scale were administered to a sample of 3,202 twins (mean age = 14.62 ± 1.74 years) attending public schools in Nigeria. The results of bivariate moderation model-fitting analyses only supported the resilience model. Moderation effects were not significant in the scarring model when genetic and environmental influences were incorporated. The best-fitting bivariate moderation model assuming the resilience model yielded a genetic correlation of − 0.57 (95% CI = − 0.40, − 0.84) with no significant environmental correlations. Moreover, the SPM moderated the environmental, not genetic, influences on EP, such that environmental influences were strong when protective factors were absent (low SPM) and weak when these were present (high SPM). These results indicate the need to develop targeted prevention and intervention strategies for EP in adolescents displaying low cognitive ability in deprived settings. [ABSTRACT FROM AUTHOR]

Background: Stress is a universal phenomenon and one of the most common precipitants of insomnia. However, not everyone develops insomnia after experiencing a stressful life event. This study aims to test aspects of Spielman's '3P model of insomnia' (during adolescence) by exploring the extent to which: (a) insomnia symptoms are predicted by polygenic scores (PGS); (b) life events predict insomnia symptoms; (c) the interaction between PGS and life events contribute to the prediction of insomnia symptoms; (d) gene–environment interaction effects remain after controlling for sex. Methods: The sample comprised 4,629 twins aged 16 from the Twin Early Development Study who reported on their insomnia symptoms and life events. PGS for insomnia were calculated. In order to test the main hypothesis of this study (a significant interaction between PGS and negative life events), we fitted a series of mixed effect regressions. Results: The best fit was provided by the model including sex, PGS for insomnia, negative life events, and their interactions (AIC = 26,158.7). Our results show that the association between insomnia symptoms and negative life events is stronger for those with a higher genetic risk for insomnia. Conclusions: This work sheds light on the complex relationship between genetic and environmental factors implicated for insomnia. This study has tested for the first time the interaction between genetic predisposition (PGS) for insomnia and environmental stressors (negative life events) in adolescents. This work represents a direct test of components of Spielman's 3P model for insomnia which is supported by our results. [ABSTRACT FROM AUTHOR]