The effect of mindfulness training on resting-state networks in pre-adolescent children with sub-clinical anxiety related attention impairments.

Mindfulness training has been associated with improved attention and affect regulation in preadolescent children with anxiety related attention impairments, however little is known about the underlying neurobiology. This study sought to investigate the impact of mindfulness training on functional connectivity of attention and limbic brain networks in pre-adolescents. A total of 47 children with anxiety and/or attention issues (aged 9-11 years) participated in a 10-week mindfulness intervention.

Social Connectedness, Cyberbullying, and Well-Being: Preliminary Findings from the Longitudinal Adolescent Brain Study.

Social connectedness is well established as an important aspect of adolescence, with higher levels typically resulting in positive mental health and well-being. Cyberbullying is a prevalent concern during adolescence and is a significant contributor to poor mental health outcomes during this important phase of life. Research shows that social connectedness may act as a protective factor for mental health and well-being when young people experience cyberbullying.

Can measures of sleep quality or white matter structural integrity predict level of worry or rumination in adolescents facing stressful situations? Lessons from the COVID-19 pandemic.

Introduction: COVID-19 has resulted in major life changes to the majority of the world population, particularly adolescents, with social-distancing measures such as home-based schooling likely to impact sleep quality. Increased worry is also likely considering the substantial financial, educational and health concerns accompanying COVID-19. White matter (WM) integrity has been shown to be associated with anxiety and depression symptoms, including worry, as well being closely associated with sleep quality.

A novel, complex systems approach to modelling risk of psychological distress in young adolescents.

Adolescence is a period of significant anatomical and functional brain changes, and complex interactions occur between mental health risk factors. The Longitudinal Adolescent Brain Study commenced in 2018, to monitor environmental and psychosocial factors influencing mental health in 500 adolescents, for 5 years. Participants are recruited at age 12 from the community in Australia's Sunshine Coast region.

Short strides to important findings: A short interval longitudinal study of sleep quality, psychological distress and microstructure changes to the uncinate fasciculus in early adolescents.

Background: Developmental studies have shown adolescence is a period of ongoing white matter (WM) development, reduced sleep quality and the onset of many mental disorders. Findings indicate the WM development of the uncinate fasciculus (UF), a WM tract suggested to play a key role in mental disorders, continues throughout adolescence. While these studies provide valuable information, they are limited by long intervals between scans (1 to 4 years) leaving researchers and clinicians to infer what may be occurring between time-points.

Associations between sleep quality and psychological distress in early adolescence.

Although numerous studies have reported an association between sleep quality and mental health, few have focused on this association exclusively in early adolescence. Targeting this age group is vital as many mental illnesses first emerge during adolescence and remain a significant burden throughout life. In the current study = 60 participants aged 12 years completed the Pittsburgh Sleep Quality Index (PSQI) and Kessler Psychological Distress Scale (K10).

Using measures of intrinsic homeostasis and extrinsic modulation to evaluate mental health in adolescents: Preliminary results from the longitudinal adolescent brain study (LABS).

Adolescence is a period when complex interactions occur between mental health risk factors. The Longitudinal Adolescent Brain Study (LABS) commenced in 2018, to monitor environmental and psychosocial factors thought to influence mental health in 500 young people. Participants commence at 12 years of age, via a community-based recruitment model, and data is collected at 15 time-points over five years.

Associations between Facial Emotion Recognition and Mental Health in Early Adolescence.

Research shows that adolescents with mental illnesses have a bias for processing negative facial emotions, and this may play a role in impaired social functioning that often co-exists with a mental health diagnosis. This study examined associations between psychological and somatic problems and facial emotion recognition in early adolescence; as any processing biases in this age-group may be an early indicator of later mental illnesses. A community sample of 40 12-year-olds self-rated their symptoms of anxiety, depression, and somatization via two mental health screeners.

Subcortical Volume Correlates of Psychological Distress in Early Adolescence.

The hippocampus and amygdala have justifiably been the focus of much mental health research due to their putative roles in top-down processing control of emotion, fear, and anxiety. However, understanding the causal relationship between these regions and mental illness has been limited as current literature is lacking in the observation of neuro-structural changes preceding first episodes. Here, we report whole and sub-structural hippocampal and amygdala volume correlates of psychological distress in early adolescence.

Utility of Bayesian networks in QMRA-based evaluation of risk reduction options for recycled water.

Background: Quantitative microbial risk assessment (QMRA), the current method of choice for evaluating human health risks associated with disease-causing microorganisms, is often constrained by issues such as availability of required data, and inability to incorporate the multitude of factors influencing risk. Bayesian networks (BNs), with their ability to handle data paucity, combine quantitative and qualitative information including expert opinions, and ability to offer a systems approach to characterisation of complexity, are increasingly recognised as a powerful, flexible tool that overcomes these limitations.

Objectives: We present a QMRA expressed as a Bayesian network (BN) in a wastewater reuse context, with the objective of demonstrating the utility of the BN method in health risk assessments, particularly for evaluating a range of exposure and risk mitigation scenarios.

Modelling microbial health risk of wastewater reuse: A systems perspective.

There is a widespread need for the use of quantitative microbial risk assessment (QMRA) to determine reclaimed water quality for specific uses, however neither faecal indicator levels nor pathogen concentrations alone are adequate for assessing exposure health risk. The aim of this study was to build a conceptual model representing factors contributing to the microbiological health risks of reusing water treated in maturation ponds. This paper describes the development of an unparameterised model that provides a visual representation of theoretical constructs and variables of interest.

Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.

Background: Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.