Childhood adversity is associated with anxiety and depression in older adults: A cumulative risk and latent class analysis.

BACKGROUND: The long-lasting influence of childhood adversity on mental health is well documented; however empirical research examining how this association extends into older adults is limited. This study operationalises adversity using cumulative risk and latent class analysis (LCA) models to assess how adversity exposure and typologies may predict anxiety and depression in older adults. METHODS: Data came from the Personality and Total Health (PATH) Through Life Project (N = 2551, age 60-66). Participants retrospectively reported their childhood experiences of domestic adversity on a 17-item scale. Mental health was measured using four validated questionnaires of depression and anxiety. RESULTS: Linear and generalised additive models (GAM) indicated a dose-response relationship, where a greater number of cumulative adversities were associated with poorer scores on all four mental health measures. LCA identified a four-class solution; with high adversity and high parental dysfunction being associated with poorer mental health outcomes while moderate parental dysfunction and low adversity groups scored at healthy levels. Women reported higher overall anxiety than men, but no notable interactions between ACEs and gender were observed. Patterns revealed by LCA were similar to patterns shown by the cumulative risk model. LIMITATIONS: There is a large time gap from childhood to assessment, making our study susceptible to recall bias. Also, our findings were based on cross-sectional data, limiting causal inferences. CONCLUSION: Childhood adversity had independent and additive contributions to depression and anxiety in older adulthood, and both cumulative risk and person-centred approaches captured this relationship.

Ab Initio Investigation of the Na3[Ln(ODA)3]·2NaClO4·6H2O (Ln = Ce-Yb; ODA = Oxydiacetate) Series.

In this work, the Na3[Ln(ODA)3]·2NaClO4·6H2O (Ln = Ce-Yb; ODA = oxydiacetate) series was analyzed with the ab initio ligand field theory (AILFT) module of the ORCA computational suite. The results were discussed within the framework of the angular overlap model (AOM) and compared to literature data. We find that the structural changes observed across the series exemplifies the effects of the lanthanide contraction also manifesting in the value of the AOM parameters. It is also shown that the complete active space self-consistent field (CASSCF) methodology is sufficient to describe the ligand field interactions in mononuclear lanthanide complexes, and the effects of dynamic correlation, through n-electron valence state perturbation theory (NEVPT2), are discussed. The calculated ligand field parameters of the present work are compared to the experimentally derived values from the literature.

Cumulative risk, factor analysis, and latent class analysis of childhood adversity data in a nationally representative sample.

BACKGROUND: Childhood adversity is a multifaceted construct that is in need of comprehensive operationalisation. OBJECTIVE: The aim of this study was to explore the optimal method to operationalise a scale of adverse childhood experiences (ACEs). PARTICIPANTS AND SETTING: Data were from Wave 1 of the Personality and Total Health (PATH) Through Life Project (N = 7485, 51% women). Participants from three age groups (20-25, 40-45, 60-65) retrospectively reported their childhood experiences of domestic adversity on a 17-item scale (e.g., physical abuse, verbal abuse, neglect, poverty). METHODS: We compared three approaches to operationalising the 17-item scale: a cumulative risk approach, factor analysis, and latent class analysis (LCA). The cumulative risk and dimensional models were represented by a unidimensional and two-dimensional model respectively using confirmatory factor analysis (CFA). RESULTS: The cumulative risk approach and LCA were viable approaches to operationalising ACE data in PATH. CFA of the dimensional model produced latent factors of threat and deprivation that were highly correlated, potentially leading to problems with multicollinearity when estimating associations. LCA revealed six classes of ACEs: high adversity, low adversity, low affection, authoritarian upbringing, high parental dysfunction, and moderate parental dysfunction. CONCLUSION: Our study found multiple latent classes within a 17-item questionnaire assessing domestic adversity. Using both the cumulative method and latent class approach may be a more informative approach when examining the relationship between ACEs and later health outcomes. Future ACE studies may benefit by considering multi-dimensional approaches to operationalising adversity.

Misogynistic Tweets Correlate With Violence Against Women.

How online social behavior covaries with real-world outcomes remains poorly understood. We examined the relationship between the frequency of misogynistic attitudes expressed on Twitter and incidents of domestic and family violence that were reported to the Federal Bureau of Investigation. We tracked misogynistic tweets in more than 400 areas across 47 American states from 2013 to 2014. Correlation and regression analyses found that misogynistic tweets were related to domestic- and family-violence incidents in those areas. A cross-lagged model showed that misogynistic tweets positively predicted domestic and family violence 1 year later; however, this effect was small. Results were robust to several known predictors of domestic violence. Our findings identify geolocated online misogyny as co-occurring with domestic and family violence. Because the longitudinal relationship between misogynistic tweets and domestic and family violence was small and conducted at the societal level, more research with multilevel data might be useful in the prediction of future violence.