A Longitudinal Study of Parental Depressive Symptoms and Coparenting in the First 18 Months.

Although the negative impact of postpartum depression on parenting behaviors has been well established-albeit separately-for mothers and fathers, the respective and joint impact of both parents' mood on family-group interactive behaviors, such as coparenting support and conflict behaviors between the parents, have not yet been investigated. The aim of this study was to examine the association between parental depressive symptoms and coparenting behaviors in a low-risk sample of families with infants, exploring reciprocity between the variables, as well as gender differences between mothers and fathers regarding these links. At 3 (T1), 9 (T2), and 18 months postpartum (T3), we assessed both parents' depressive symptoms with a self-report questionnaire and observed coparenting support and conflict during triadic mother-father-child interactions. The results revealed that higher maternal depressive symptoms at T1 were associated with lower support at T1 and T2. Conflict at T3 was associated with higher maternal depressive symptoms at T3 and, more surprisingly, with less depressive symptoms in mothers at T2 and fathers at T3. Cross-lagged associations suggested that parental depressive symptoms were more likely to influence coparenting than the reverse. Moreover, maternal depressive symptoms were more likely to be linked to coparenting behaviors than were paternal depressive symptoms. These results confirm that parental-mostly maternal-depressive symptoms, even of mild intensity, may jeopardize the development of healthy family-level relations, which previous research has shown to be crucial for child development

Longitudinal Relationships Between Reflective Functioning, Empathy, and Externalizing Behaviors During Adolescence and Young Adulthood

Reflective functioning (RF) refers to the understanding of one’s own and others’ behaviors in terms of mental states, whereas empathy entails the abilities to understand (cognitive empathy) and to share (affective empathy) the emotions of others. Low RF and low empathy have been previously related to externalizing behaviors, such as aggression and rule breaking. However, few longitudinal studies have simultaneously examined the relationships between these variables during adolescence. The aim of the present study is to investigate the longitudinal effects of both RF and empathy on potential changes in externalizing behaviors over time, in a group of 103 adolescents and young adults from the general population assessed repeatedly up to four times. We conducted multilevel analysis in order to examine the effects of RF and empathy on the initial levels and the trajectories of externalizing behaviors over time, while accounting for other variables previously associated with externalizing behaviors, such as age, gender, internalizing problems, and cognitive abilities. The results suggest that the ability to reflect on behaviors in terms of mental states predicted a sharper decrease in externalizing behaviors over time. Moreover, externalizing behaviors at the first assessment were associated with RF impairments and low affective empathy. Age, gender, cognitive abilities, and cognitive empathy were not associated with externalizing behaviors. We discuss how our results, based on a typically developing population, might inform primary or indicated prevention strategies for externalizing behaviors by focusing on socio-cognitive processes such as RF and affective empathy

Psychological Distress and Well-Being among Students of Health Disciplines: The Importance of Academic Satisfaction

Background: Research on the mental health of students in health disciplines mainly focuses on psychological distress and nursing and medical students. This study aimed to investigate the psychological well-being and distress and related factors among undergraduate students training in eight different health-related tracks in Geneva, Switzerland. Methods: This cross-sectional study used established self-filled scales for anxiety, depression, stress, psychological well-being, and study satisfaction. Descriptive statistics and hierarchical regression analyses were applied. Results: In October 2019, out of 2835 invited students, 915 (32%) completed the survey. Lower academic satisfaction scores were strongly associated with depression (β = −0.26, p < 0.001), anxiety (β = −0.27, p < 0.001), and stress (β = −0.70, p < 0.001), while higher scores were associated with psychological well-being (β = 0.70, p < 0.001). Being female was strongly associated with anxiety and stress but not with depression or psychological well-being. Increased age was associated with enhanced psychological well-being. The nature of the academic training had a lesser impact on mental health and the academic year had none. Conclusion: Academic satisfaction strongly predicts depression, anxiety, stress, and psychological well-being. Training institutions should address the underlying factors that can improve students’ satisfaction with their studies while ensuring that they have access to psychosocial services that help them cope with mental distress and enhance their psychological well-bein

Meta-analysis of generalized additive models in neuroimaging studies

Contains fulltext : 231772.pdf (publisher's version ) (Open Access)Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated

Today’s older adults are cognitively fitter than older adults were 20 years ago, but when and how they decline is no different than in the past

History-graded increases in older adults' levels of cognitive performance are well documented, but little is known about historical shifts in within-person change: cognitive decline and onset of decline. We combined harmonized perceptual-motor speed data from independent samples recruited in 1990 and 2010 to obtain 2,008 age-matched longitudinal observations (M = 78 years, 50% women) from 228 participants in the Berlin Aging Study (BASE) and 583 participants in the Berlin Aging Study II (BASE-II). We used nonlinear growth models that orthogonalized within- and between-person age effects and controlled for retest effects. At age 78, the later-born BASE-II cohort substantially outperformed the earlier-born BASE cohort (d = 1.20; 25 years of age difference). Age trajectories, however, were parallel, and there was no evidence of cohort differences in the amount or rate of decline and the onset of decline. Cognitive functioning has shifted to higher levels, but cognitive decline in old age appears to proceed similarly as it did two decades ago

Healthy minds 0-100 years: Optimising the use of European brain imaging cohorts ("Lifebrain").

The main objective of "Lifebrain" is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.This research is funded by the EU Horizon 2020 Grant: ‘Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (“Lifebrain”)’. Grant agreement number: 732592. Call: Societal challenges: Health, demographic change and well-bein

Five views of a secret: does cognition change during middle adulthood?

This study examined five aspects of change (or stability) in cognitive abilities in middle adulthood across a 12-year period. Data come from the Interdisciplinary Study on Adult Development. The sample consisted of N = 346 adults (43.8 years on average, 48.6% female). In total, 11 cognitive tests were administered to assess fluid and crystallized intelligence, memory, and processing speed. In a first series of analyses, strong measurement invariance was established. Subsequently, structural stability, differential stability, stability of divergence, absolute stability, and the generality of changes were examined. Factor covariances were shown to be equal across time, implying structural stability. Stability coefficients were around .90 for fluid and crystallized intelligence, and speed, indicating high, yet not perfect differential stability. The coefficient for memory was .58. Only in processing speed the variance increased across time, indicating heterogeneity in interindividual development. Significant mean-level changes emerged, with an increase in crystallized intelligence and decline in the other three abilities. A number of correlations among changes in cognitive abilities were significant, implying that cognitive change

People's interest in brain health testing: Findings from an international, online cross-sectional survey

Brain health entails mental wellbeing and cognitive health in the absence of brain disorders. The past decade has seen an explosion of tests, cognitive and biological, to predict various brain conditions, such as Alzheimer's Disease. In line with these current developments, we investigated people's willingness and reasons to—or not to—take a hypothetical brain health test to learn about risk of developing a brain disease, in a cross-sectional multilanguage online survey. The survey was part of the Global Brain Health Survey, open to the public from 4th June 2019 to 31st August 2020. Respondents were largely recruited via European brain councils and research organizations. 27,590 people responded aged 18 years or older and were predominantly women (71%), middle-aged or older (>40 years; 83%), and highly educated (69%). Responses were analyzed to explore the relationship between demographic variables and responses. Results: We found high public interest in brain health testing: over 91% would definitely or probably take a brain health test and 86% would do so even if it gave information about a disease that cannot be treated or prevented. The main reason for taking a test was the ability to respond if one was found to be at risk of brain disease, such as changing lifestyle, seeking counseling or starting treatment. Higher interest in brain health testing was found in men, respondents with lower education levels and those with poor self-reported cognitive health. Conclusion: High public interest in brain health and brain health testing in certain segments of society, coupled with an increase of commercial tests entering the market, is likely to put pressure on public health systems to inform the public about brain health testing in years to come.publishedVersio

No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy

Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration—which is shorter than current recommendations