When problems just bounce back: about the relation between resilience and academic success in German tertiary education

While in the past the concept of resilience was used to explain psychological well-being in extreme situations like enduring poverty, abuse, or war, it has now found broad application in numerous fields of research. It can also be applied to examine how everyday challenges and problems are dealt with, for example in the educational and university context. This raises the question of whether resilience and academic success are correlated. Using German longitudinal data including university and university of applied sciences students in their first four years (2010–2015) we investigate how resilience and various measurements of success (satisfaction, intention to drop out, grades) are correlated using multilevel growth-curve models. We demonstrate that resilient individuals have consistently more positive academic trajectories, have lower dropout intentions, report better grades and are more satisfied with their lives. The effects are exceptionally stable over time, statistically highly significant and of considerable magnitude. This demonstrates that resilience is associated with better outcomes in university students under control of a large number of potential confounding factors and influences.

Living Arrangements, Electronic Communication Use, and Psychological Functioning

Older people who live alone may benefit more from using electronic communication than those who live with others. Although living alone has been linked to a higher risk of depression and social isolation, few studies examined the effect of using electronic communication separately by living arrangements. The current study examines the effect of electronic communication use by living arrangements for people aged 65 and older. Using the 2011-2018 National Health and Aging Trends Study (NHATS), we examine how the frequency of emails/texts is associated with changes in psychological well-being and depressive symptoms accounting for sociodemographic, health, social network characteristics (N=6,897). Multilevel growth curve models showed that those living alone or with others were more likely to have fewer depressive symptoms at baseline if they used electronic communication, but the use did not affect their trajectory of depression. Those living alone or with others who used electronic communication did not have higher psychological well-being at baseline, nor did it affect their trajectory. The overall findings raise a question on the effectiveness of promoting electronic communication technology as a substitute for in person interaction for older adults living alone in the community.

Trajectories of Depressive Symptoms and Neighborhood Changes from Adolescence to Adulthood: Latent Class Growth Analysis and Multilevel Growth Curve Models

The role of neighborhood socioeconomic status (SES) and racial/ethnic composition on depression has received considerable attention in the United States. This study examines associations between trajectory patterns of neighborhood changes and depressive symptoms using data from Waves I-IV of the National Longitudinal Study of Adolescent to Adult Health. We used latent class growth analysis to determine the number and distribution of person-centered trajectories for neighborhood characteristics, and multilevel growth curve models to examine how belonging to each class impacted depression trajectories from ages 13 to 32 among non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics, and non-Hispanic Others (NHO). The distribution of neighborhood SES classes across racial/ethnic groups suggests significant levels of economic inequality, but had no effect on depressive symptoms. A more complex picture emerged on the number and distribution of racial/ethnic composition latent class trajectories. Compared to NHB peers who lived in predominantly NHW neighborhoods from adolescence to adulthood, NHBs in more diverse neighborhoods had lower risk for depressive symptoms. Conversely, Hispanics living in neighborhoods with fewer NHWs had higher risk for depressive symptoms. Among NHOs, living in neighborhoods with a critical mass of other NHOs had a protective effect against depressive symptoms.

The Effectiveness of Neurofeedback in an Outpatient Setting: A Multilevel Modeling Approach

Purpose: Neurofeedback is an increasingly common therapeutic intervention for mental disorders. Most of the existent neurofeedback via electroencephalography (EEG-nf) research uses controlled studies to examine whether EEG-nf is an efficacious treatment for attention deficit hyperactivity disorder (ADHD). Less is known regarding the effectiveness of EEG-nf in clinical settings for symptoms other than ADHD. The purpose of this study was to examine whether EEG-nf sessions were associated with a reduction in hyperactivity, emotional dysregulation, anxiety, and depression symptoms. Method: Multilevel growth curve models were used to analyze secondary data from 83 EEG-nf patients from an outpatient clinic. Results: EEG-nf sessions were associated with a decrease in mental disorder symptoms generally, but this trend slowed over time. Discussion: Findings suggest that practitioners should adhere to a relatively brief (approximately 30 sessions) EEG-nf protocol. Findings also encourage more research dedicated to examining the effectiveness of EEG-nf on a variety of mental health symptoms treated in community settings.

Can green space quantity and quality help prevent postpartum weight gain? A longitudinal study

BackgroundPostpartum weight gain is a well-known challenge for many mothers, but associations with green space quantity and quality have not been investigated.MethodsThis longitudinal study used data on 3843 mothers living in Australia tracked biennially for 15 years post partum from 2004 onwards. Multilevel growth curve models adjusted for confounding were used to examine the patterning of body mass index (BMI) in relation to green space quantity, measured by percentage land use, and green space quality, measured by self-report. Two-way interaction terms were fitted to investigate time-contingent associations between BMI and green space.ResultsCompared with mothers in areas with ≤5% green space, adjusted BMI coefficients were −0.43 kg/m2 (SE 0.37), −0.69 kg/m2 (SE 0.32) −0.86 kg/m2 (SE 0.33) and −0.80 kg/m2 (SE 0.41) among mothers in areas with 6%–10%, 11%–20%, 21%–40% and ≥41% green space, respectively. There were no independent associations between BMI and green space quality. Evidence suggested mothers living in areas with 21%–40% green space had the lowest BMI, whether they agreed that local parks were good quality (−0.89 kg/m2 (SE 0.34)) or not (−0.93 kg/m2 (SE 0.35)). Mothers in the greenest areas only had statistically significantly lower BMI if they perceived local parks as high quality (−0.89 kg/m2 (SE 0.41)). There was limited evidence that these associations varied with respect to the number of years post partum.ConclusionThese findings may suggest that urban greening strategies to achieve a threshold of at least 21% or more green space in an area may help reduce, but not fully prevent postpartum weight gain. Potential mechanisms warrant investigation.

Identifying Critical Points of Trajectories of Depressive Symptoms From Childhood to Young Adulthood: Evidence of Sex Differences from the Avon Longitudinal Study of Parents and Children (ALSPAC)

Depression is a common mental illness associated with increased substance misuse and risk of suicide. Potential risk factors for depression include sex and depressive symptoms in early life, however the mechanisms responsible are not yet understood. Research has focused on late childhood and adolescence as this developmental period may be a modifiable risk factor that prevents or reduces depression at a later stage. It is also important to establish at what ages the level of depression is changing as this will help identify critical points to intervene with treatment. We used multilevel growth-curve models to explore adolescent trajectories of depressive symptoms in the Avon Longitudinal Study of Parents and Children, a UK based pregnancy cohort. Using data from 9301 individuals, trajectories of depressive symptoms were constructed for males and females between 10.6 and 22.8 years old. We calculated the age of peak velocity for depressive symptoms (the age at which depressive symptoms increases most rapidly) and the age of maximum depressive symptoms. Adjusted results suggested that being female was associated with a steeper trajectory compared to being male (per 1 year increase in relation to depressive symptoms: 0.128, SE = 0.035, [95% CI: 0.059, 0.198]; p <0.001). We found evidence suggesting that females had an earlier age of peak velocity of depressive symptoms (females 13.7 years old, SE = 0.321, [95% CI: 12.9, 14.4] and males 16.4 years old, SE = 0.096, [95% CI: 16.2, 16.6]; p <0.001), but weak evidence of an earlier age of maximum depressive symptoms (p = 0.125). Possible mechanisms that underlie this sex difference include the roles of pubertal development and timing. Using multilevel growth curve models to estimate the age of peak velocity and maximum depressive symptoms for different population subgroups may provide useful knowledge for treating and preventing later depression.