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Abstract Cyberbullying is associated with various mental health concerns in adolescents, including body dissatisfaction and disordered eating behaviours. However, there is a significant research gap concerning the unique effects of appearance-related cyberbullying (ARC) on adolescent mental health. This study examined the prevalence and psychological consequences of ARC among middle to late adolescent females (aged 14–19 years, M age = 15.98, N = 336). Participants completed an online survey regarding their experiences of ARC, body image variables, and eating disorder symptomology. Findings indicate the widespread occurrence of ARC among adolescent females, with body shape and size emerging as predominant targets. Experiences of ARC-victimisation positively correlated with increased concerns about body shape, body shame, and eating disorder symptomology. Conversely, experiences of ARC-victimisation were negatively correlated with body esteem and body appreciation. Finally, appearance-related cybervictimisation was significantly associated with adolescent females’ desire to pursue appearance alterations through methods such as dieting and exercising, altering self-presentation, and undergoing cosmetic procedures due to perceived experiences of ARC. These findings highlight the urgent need for preventative measures, such as age-appropriate social media policies and health promotion programs that encourage positive online behaviour, and strategies to address the impacts of ARC to protect the mental well-being of adolescent females.

ABSTRACT Introduction Subanesthetic doses of ketamine are a promising novel treatment for suicidality; however, the evidence for predictive biomarkers is sparse. Recently, measures of complexity, including Lempel–Ziv complexity (LZC) and multiscale entropy (MSE), have been implicated in ketamine's therapeutic action. We evaluated electroencephalogram (EEG)‐derived LZC and MSE differences between responders and nonresponders to oral ketamine treatment. Methods A total of 31 participants received six single, weekly (titrated) doses of oral racemic ketamine (0.5–3 mg/kg) and underwent EEG scans at baseline (Week 0), post‐treatment (Week 6), and follow‐up (Week 10). Resting‐state (eyes closed and open) recordings were processed in EEGLAB, and complexity metrics were extracted using the Neurokit2 package. Participants were designated responders or nonresponders by clinical response (Beck Suicide Scale [BSS] score reduction of ≥ 50% from baseline to the respective timepoint or score ≤ 6) and then compared in terms of complexity across resting‐state conditions and time. Results Employing a Bayesian mixed effects model, we found strong evidence that LZC was higher in the eyes‐open compared to eyes‐closed condition, as were MSE scales 1–3. At a global level, responders displayed elevated eyes‐open baseline complexity compared to nonresponders, with these values decreasing from baseline to post‐treatment (Week 6) in responders only. Exploratory analyses revealed that the elevated baseline eyes‐open LZC in responders was spatially localized to the left frontal lobe (F1, AF3, FC1, and F3). Conclusion EEG‐complexity metrics may be sensitive biomarkers for evaluating and predicting oral ketamine treatment response, with the left prefrontal cortex bein a possible treatment response region.

IntroductionNutrition, sleep and physical activity are termed the “big three” health enhancing behaviors (HEB) associated with psychological distress and wellbeing. This study sought to understand differential associations between an expanded group of HEB (nutrition, sleep, physical activity, mindfulness, social connectedness) and psychological distress/wellbeing in early adolescents.MethodsCorrelational and regression analyses were conducted in N=103 (51% females) adolescents (12.6 ± 0.3 years of age) recruited from the Longitudinal Adolescent Brain Study.ResultsHigher scores on sleep, social connectedness and mindfulness scales were significantly associated with lower psychological distress scores. While higher scores on social connectedness and mindfulness scales were significantly associated with higher wellbeing scores. When adjusting for sex, nutrition, sleep, social connectedness and mindfulness accounted for a significant proportion of variance in the psychological distress model whereas physical activity and social connectedness accounted for a significant proportion of the variance in the wellbeing model.DiscussionsOverall findings make a strong case for expansion of the “big three” HEB to include mindfulness and social connectedness, especially given social connectedness emerged as the strongest predictor of both psychological distress and wellbeing. In addition, this research suggests that early adolescent nutrition, sleep quality, and mindfulness should be prioritized in efforts to reduce risk of difficulties, and physical activity prioritized as a protective factor for wellbeing in this population. Findings have implications for interventions, emphasizing the importance of addressing HEB factors comprehensively and tailoring strategies to the unique needs of early adolescents to foster positive mental health outcomes.

Abstract Background Existing treatments for young people with severe depression have limited effectiveness. The aim of the Study of Ketamine for Youth Depression (SKY-D) trial is to determine whether a 4-week course of low-dose subcutaneous ketamine is an effective adjunct to treatment-as-usual in young people with major depressive disorder (MDD). Methods SKY-D is a double-masked, randomised controlled trial funded by the Australian Government’s National Health and Medical Research Council (NHMRC). Participants aged between 16 and 25 years (inclusive) with moderate-to-severe MDD will be randomised to receive either low-dose ketamine (intervention) or midazolam (active control) via subcutaneous injection once per week for 4 weeks. The primary outcome is change in depressive symptoms on the Montgomery-Åsberg Depression Rating Scale (MADRS) after 4 weeks of treatment. Further follow-up assessment will occur at 8 and 26 weeks from treatment commencement to determine whether treatment effects are sustained and to investigate safety outcomes. Discussion Results from this trial will be important in determining whether low-dose subcutaneous ketamine is an effective treatment for young people with moderate-to-severe MDD. This will be the largest randomised trial to investigate the effects of ketamine to treat depression in young people. Trial registration Australian and New Zealand Clinical Trials Registry ID: ACTRN12619000683134. Registered on May 7, 2019. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377513 .

Neurodevelopment during early childhood and adolescence are recognised as critical periods, with potential life-long lasting impacts on mental health and wellbeing. The time-frame of these neurodevelopmental changes also correspond to one in five individuals aged 9–17 years old being diagnosed with a mental health condition. Furthermore, sex-based differences in the diagnosed prevalence of mental health conditions are also well characterised and can be leveraged to differentiate development of brain structures between sexes throughout childhood and adolescence. During adolescence, early observed mental health symptoms, alongside measures of brain development, may provide utility toward understanding both the onset timing of various mental conditions, and a neurobiological explanation for disproportionate prevalence's among sexes. This study aims to determine sex differences in psychological distress levels and structural brain volume relationships in early adolescents. To address this question, we first present and then utilise the ‘first hundred brains’ (FHB) cohort, a multimodal dataset of 12-to-13 year-olds individuals enrolled in the Longitudinal Adolescent Brain Study (LABS). The FHB dataset consists of 101 unique individuals (47 female), aged 13.01 ± 0.55 years. Psychological distress was measured using the Kessler-10, a self-report questionnaire probing recent experiences of anxiety and depression symptoms. All participants underwent 3T MRI brain scans. T1-weighted structural scans were processed using FreeSurfer's Sequence Adaptive Multimodal segmentation pipeline, with volume measurements from 39 regions of interest included in the analyses. Findings revealed that compared to age matched males, early adolescent females have significantly higher psychological distress as well as significantly larger hippocampi and ventral diencephalon, bilaterally. Correlational analyses revealed a significant positive association between psychological distress scores and right amygdala volumes for males, but not in females, or the combined cohort. In this initial analysis of the FHB dataset, we have identified significant sex differences in psychological distress, brain volumes, and the relationships between these two metrics. With the peak age-of-onset for many psychiatric disorders occurring during adolescence, research focused on youth mental health vulnerability and opportunity for early detection, prevention and improvement is vitally important.

Abstract Aims The needs of young people attending mental healthcare can be complex and often span multiple domains (e.g., social, emotional and physical health factors). These factors often complicate treatment approaches and contribute to poorer outcomes in youth mental health. We aimed to identify how these factors interact over time by modelling the temporal dependencies between these transdiagnostic social, emotional and physical health factors among young people presenting for youth mental healthcare. Methods Dynamic Bayesian networks were used to examine the relationship between mental health factors across multiple domains (social and occupational function, self-harm and suicidality, alcohol and substance use, physical health and psychiatric syndromes) in a longitudinal cohort of 2663 young people accessing youth mental health services. Two networks were developed: (1) ‘initial network’, that shows the conditional dependencies between factors at first presentation, and a (2) ‘transition network’, how factors are dependent longitudinally. Results The ‘initial network’ identified that childhood disorders tend to precede adolescent depression which itself was associated with three distinct pathways or illness trajectories; (1) anxiety disorder; (2) bipolar disorder, manic-like experiences, circadian disturbances and psychosis-like experiences; (3) self-harm and suicidality to alcohol and substance use or functioning. The ‘transition network’ identified that over time social and occupational function had the largest effect on self-harm and suicidality, with direct effects on ideation (relative risk [RR], 1.79; CI, 1.59–1.99) and self-harm (RR, 1.32; CI, 1.22–1.41), and an indirect effect on attempts (RR, 2.10; CI, 1.69–2.50). Suicide ideation had a direct effect on future suicide attempts (RR, 4.37; CI, 3.28–5.43) and self-harm (RR, 2.78; CI, 2.55–3.01). Alcohol and substance use, physical health and psychiatric syndromes (e.g., depression and anxiety, at-risk mental states) were independent domains whereby all direct effects remained within each domain over time. Conclusions This study identified probable temporal dependencies between domains, which has causal interpretations, and therefore can provide insight into their differential role over the course of illness. This work identified social, emotional and physical health factors that may be important early intervention and prevention targets. Improving social and occupational function may be a critical target due to its impacts longitudinally on self-harm and suicidality. The conditional independence of alcohol and substance use supports the need for specific interventions to target these comorbidities.

Various methods have been developed to combine inference across multiple sets of results for unsupervised clustering, within the ensemble clustering literature. The approach of reporting results from one ‘best’ model out of several candidate clustering models generally ignores the uncertainty that arises from model selection, and results in inferences that are sensitive to the particular model and parameters chosen. Bayesian model averaging (BMA) is a popular approach for combining results across multiple models that offers some attractive benefits in this setting, including probabilistic interpretation of the combined cluster structure and quantification of model-based uncertainty. In this work we introduce clusterBMA, a method that enables weighted model averaging across results from multiple unsupervised clustering algorithms. We use clustering internal validation criteria to develop an approximation of the posterior model probability, used for weighting the results from each model. From a combined posterior similarity matrix representing a weighted average of the clustering solutions across models, we apply symmetric simplex matrix factorisation to calculate final probabilistic cluster allocations. In addition to outperforming other ensemble clustering methods on simulated data, clusterBMA offers unique features including probabilistic allocation to averaged clusters, combining allocation probabilities from ‘hard’ and ‘soft’ clustering algorithms, and measuring model-based uncertainty in averaged cluster allocation. This method is implemented in an accompanying R package of the same name. We use simulated datasets to explore the ability of the proposed technique to identify robust integrated clusters with varying levels of separation between subgroups, and with varying numbers of clusters between models. Benchmarking accuracy against four other ensemble methods previously demonstrated to be highly effective in the literature, clusterBMA matches or exceeds the performance of competing approaches under various conditions of dimensionality and cluster separation. clusterBMA substantially outperformed other ensemble methods for high dimensional simulated data with low cluster separation, with 1.16 to 7.12 times better performance as measured by the Adjusted Rand Index. We also explore the performance of this approach through a case study that aims to identify probabilistic clusters of individuals based on electroencephalography (EEG) data. In applied settings for clustering individuals based on health data, the features of probabilistic allocation and measurement of model-based uncertainty in averaged clusters are useful for clinical relevance and statistical communication.

Abstract Numerous studies have demonstrated that low‐dose subanesthetic intravenous ketamine infusion treatment leads to rapid improvement of treatment‐resistant depression. The following case report describes the use of a very low‐dose subcutaneous ketamine as a form of maintenance in a patient with severe treatment‐resistant depression using a retrospective chart review.

We provided the dataset of brain connectome matrices, their similarities measures to self and others longitudinally, and Kessler's psychological distress scales (K10) including the response to each question. The dataset can be used to replicate the results of the manuscript titled “A longitudinal study of functional connectome uniqueness and its association with psychological distress in adolescence”. The functional connectome (whole-brain and 13 networks) matrices were calculated from the resting-state functional MRIs (rs-fMRIs). We collected rs-fMRI and Kessler's psychological distress scale (K10) in 77 adolescents longitudinally up to 9 times from 12 years of age every four months. After removal of data with excessive motion, 262 functional connectome matrices were provided with this paper. The 300 regions of interest (ROIs) were defined using the Greene lab brain atlas. The functional connectome matrices were calculated as correlations between time series from any pair of ROIs extracted from pre-processed fMRIs. This dataset could be potentially used to 1. Understand developmental changes in the functional brain connectivity, 2. As a normal control database of functional connectome matrices, 3. Develop and validate connectome and network-related analysing methods.

Abstract Improving our understanding of the causes of functional impairment in young people is a major global challenge. Here, we investigated the relationships between self-reported days out of role and the total quantity and different patterns of self-reported somatic, anxious-depressive, psychotic-like, and hypomanic symptoms in a community-based cohort of young adults. We examined self-ratings of 23 symptoms ranging across the four dimensions and days out of role in >1900 young adult twins and non-twin siblings participating in the “19Up” wave of the Brisbane Longitudinal Twin Study. Adjusted prevalence ratios (APR) and 95% confidence intervals (95% CI) quantified associations between impairment and different symptom patterns. Three individual symptoms showed significant associations with days out of role, with the largest association for impaired concentration. When impairment was assessed according to each symptom dimension, there was a clear stepwise relationship between the total number of somatic symptoms and the likelihood of impairment, while individuals reporting ≥4 anxious-depressive symptoms or five hypomanic symptoms had greater likelihood of reporting days out of role. Furthermore, there was a stepwise relationship between the total number of undifferentiated symptoms and the likelihood of reporting days out of role. There was some suggestion of differences in the magnitude and significance of associations when the cohort was stratified according to sex, but not for age or twin status. Our findings reinforce the development of early intervention mental health frameworks and, if confirmed, support the need to consider interventions for subthreshold and/or undifferentiated syndromes for reducing disability among young people.

Abstract 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. In this baseline, cross-sectional study of N = 64 participants, we draw on the network perspective, conceptualising mental disorders as causal systems of interacting entities, to propose a Bayesian network (BN) model of lifestyle and psychosocial variables influencing chances of individuals being psychologically well or experiencing psychological distress. Sensitivity analysis of network priors revealed that psychological distress (Kessler-10) was most affected by eating behaviour. Unhealthy eating increased the chance of moderate psychological distress by 600%. Low social connectedness increased the chance of severe psychological disorder by 200%. Certainty for psychological wellness required 33% decrease in unhealthy eating behaviours, 11% decrease in low social connectedness, and 9% reduction in less physical activity. BN can augment clinician judgement in mental disorders as probabilistic decision support systems. The full potential of BN methodology in a complex systems approach to psychopathology has yet to be realised.

Abstract Recently, low-dose ketamine has been proposed as a rapid-acting treatment option for suicidality. The majority of studies to date have utilised intravenous (IV) ketamine, however, this route of administration has limitations. On the other hand, oral ketamine can be administered in a range of settings, which is important in treating suicidality, although studies as to safety and feasibility are lacking. n = 32 adults (aged 22–72 years; 53% female) with chronic suicidal thoughts participated in the Oral Ketamine Trial on Suicidality (OKTOS), an open-label trial of sub-anaesthetic doses of oral ketamine over 6 weeks. Participants commenced with 0.5 mg/kg of ketamine, which was titrated to a maximum 3.0 mg/kg. Follow-up assessments occurred at 4 weeks after the final dose. The primary outcome measure was the Beck Scale for Suicide Ideation (BSS) and secondary measures included scales for suicidality and depressive symptoms, and measures of functioning and well-being. Mean BSS scores significantly reduced from a high level of suicidal ideation at the pre-ketamine (week 0) timepoint to below the clinical threshold at the post-ketamine (week 6) timepoint. The proportion of participants that achieved clinical improvement within the first 6 weeks was 69%, whereas 50% achieved a significant improvement by the follow-up (week 10) timepoint. Six weeks of oral ketamine treatment in participants with chronic suicidality led to significant reduction in suicidal ideation. The response observed in this study is consistent with IV ketamine trials, suggesting that oral administration is a feasible and tolerable alternative treatment for chronic suicidality.

Abstract Background The glutamatergic modulator ketamine has been shown to result in rapid reductions in both suicidal ideation (SI) and depressive symptoms in clinical trials. There is a practical need for identification of pre-treatment predictors of ketamine response. Previous studies indicate links between treatment response and body mass index (BMI), depression symptoms and previous suicide attempts. Our aim was to explore the use of clinical and demographic factors to predict response to serial doses of oral ketamine for chronic suicidal ideation. Methods Thirty-two participants completed the Oral Ketamine Trial on Suicidality (OKTOS). Data for the current study were drawn from pre-treatment and follow-up time-points of OKTOS. Only clinical and sociodemographic variables were included in this analysis. Data were used to create a proof of concept Bayesian network (BN) model of variables predicting prolonged response to oral ketamine, as defined by the Beck Scale for Suicide Ideation (BSS). Results The network of potential predictors of response was evaluated using receiver operating characteristic (ROC) curve analyses. A combination of nine demographic and clinical variables predicted prolonged ketamine response, with strong contributions from BMI, Social and Occupational Functioning Assessment Scale (SOFAS), Montgomery-Asberg Depression Rating Scale (MADRS), number of suicide attempts, employment status and age. We evaluated and optimised the proposed network to increase the area under the ROC curve (AUC). The performance evaluation demonstrated that the BN predicted prolonged ketamine response with 97% accuracy, and AUC = 0.87. Conclusions At present, validated tools to facilitate risk assessment are infrequently used in psychiatric practice. Pre-treatment assessment of individuals’ likelihood of response to oral ketamine for chronic suicidal ideation could be beneficial in making more informed decisions about likelihood of success for this treatment course. Clinical trials registration number ACTRN12618001412224, retrospectively registered 23/8/2018.

Abstract Background Since the 1990s, neuroimaging has been utilised to study Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a debilitating illness with unknown aetiology. While brain abnormalities in ME/CFS have been identified, relatively little is known regarding which specific abnormalities are consistently observed across research groups and to what extent the observed abnormalities are reproducible. Method To identify consistent and inconsistent neuroimaging observations in ME/CFS, this retrospective and systematic review searched for studies in which neuroimaging was used to investigate brain abnormalities in ME/CFS in Ovid MEDLINE, PubMed (NCBI), and Scopus from January 1988 to July 2018. A qualitative synthesis of observations was performed to identify brain abnormalities that were consistently and inconsistently reported. Results 63 full-text articles were included in the synthesis of results from 291 identified papers. Additional brain area recruitment for cognitive tasks and abnormalities in the brain stem are frequent observations in 11 and 9 studies using different modalities from different research teams respectively. Also, sluggish blood oxygenation level-dependent (BOLD) signal responses to tasks, reduced serotonin transporters, and regional hypometabolism are consistent observations by more than two research teams. Single observations include abnormal brain tissue properties, regional metabolic abnormalities, and association of brain measures with ME/CFS symptoms. Reduced resting cerebral blood flow and volumetric brain changes are inconsistent observations across different studies. Conclusion Neuroimaging studies of ME/CFS have frequently observed additional brain area recruitment during cognitive tasks and abnormalities in the brain stem. The frequent observation of additional brain area recruitment and consistent observation of sluggish fMRI signal response suggest abnormal neurovascular coupling in ME/CFS.

Abstract Background Subthreshold/attenuated syndromes are established precursors of full-threshold mood and psychotic disorders. Less is known about the individual symptoms that may precede the development of subthreshold syndromes and associated social/functional outcomes among emerging adults. Methods We modeled two dynamic Bayesian networks (DBN) to investigate associations among self-rated phenomenology and personal/lifestyle factors (role impairment, low social support, and alcohol and substance use) across the 19Up and 25Up waves of the Brisbane Longitudinal Twin Study. We examined whether symptoms and personal/lifestyle factors at 19Up were associated with (a) themselves or different items at 25Up, and (b) onset of a depression-like, hypo-manic-like, or psychotic-like subthreshold syndrome (STS) at 25Up. Results The first DBN identified 11 items that when endorsed at 19Up were more likely to be reendorsed at 25Up (e.g., hypersomnia, impaired concentration, impaired sleep quality) and seven items that when endorsed at 19Up were associated with different items being endorsed at 25Up (e.g., earlier fatigue and later role impairment; earlier anergia and later somatic pain). In the second DBN, no arcs met our a priori threshold for inclusion. In an exploratory model with no threshold, >20 items at 19Up were associated with progression to an STS at 25Up (with lower statistical confidence); the top five arcs were: feeling threatened by others and a later psychotic-like STS; increased activity and a later hypo-manic-like STS; and anergia, impaired sleep quality, and/or hypersomnia and a later depression-like STS. Conclusions These probabilistic models identify symptoms and personal/lifestyle factors that might prove useful targets for indicated preventative strategies.

The role of gender and the associated brain activation when witnessing cyberbullying requires investigation. The current study aimed to determine whether brain responses to cyberbullying differ according to gender and level of wellbeing. We hypothesised that females and males would activate different regions of the brain when witnessing cyberbullying, and that this would be influenced by wellbeing levels and prior cyberbullying experiences. Blood-oxygenation-level-dependent (BOLD) responses were examined in participants (N = 32, aged 18–25 years; 66% female) whilst observing cyberbullying versus neutral stimuli during a functional MRI. Results revealed significant correlations between BOLD signal and achievement scores among males, but not females, with previous experiences of cyberbullying, in regions including the cerebellum, the superior and inferior frontal gyrus, and the precuneus. Furthermore, males who previously cyberbullied others, with higher scores in achievement (a wellbeing sub-category), activated brain regions associated with executive function, social cognition, and self-evaluation, when viewing the cyberbullying stimuli. In addition, despite gender, BOLD signal in the cingulate gyrus was negatively correlated with cyberbullying scores, and BOLD signal in the left dorsal caudate and the cerebellum was independently and positively correlated with achievement scores. Taken together, these findings provide insights into brain responses to cyberbullying scenarios and emphasize that there are some significant variations according to gender. The overall finding that males activated brain regions linked to varying aspects of cognition, whereas females more often activated regions linked to emotion processing and empathy is important for future research in this area.

Background The schizophrenia polygenic risk score (SCZ-PRS) is an emerging tool in psychiatry. Aims We aimed to evaluate the utility of SCZ-PRS in a young, transdiagnostic, clinical cohort. Method SCZ-PRSs were calculated for young people who presented to early-intervention youth mental health clinics, including 158 patients of European ancestry, 113 of whom had longitudinal outcome data. We examined associations between SCZ-PRS and diagnosis, clinical stage and functioning at initial assessment, and new-onset psychotic disorder, clinical stage transition and functional course over time in contact with services. Results Compared with a control group, patients had elevated PRSs for schizophrenia, bipolar disorder and depression, but not for any non-psychiatric phenotype (for example cardiovascular disease). Higher SCZ-PRSs were elevated in participants with psychotic, bipolar, depressive, anxiety and other disorders. At initial assessment, overall SCZ-PRSs were associated with psychotic disorder (odds ratio (OR) per s.d. increase in SCZ-PRS was 1.68, 95% CI 1.08–2.59, P = 0.020), but not assignment as clinical stage 2+ (i.e. discrete, persistent or recurrent disorder) (OR = 0.90, 95% CI 0.64–1.26, P = 0.53) or functioning (R = 0.03, P = 0.76). Longitudinally, overall SCZ-PRSs were not significantly associated with new-onset psychotic disorder (OR = 0.84, 95% CI 0.34–2.03, P = 0.69), clinical stage transition (OR = 1.02, 95% CI 0.70–1.48, P = 0.92) or persistent functional impairment (OR = 0.84, 95% CI 0.52–1.38, P = 0.50). Conclusions In this preliminary study, SCZ-PRSs were associated with psychotic disorder at initial assessment in a young, transdiagnostic, clinical cohort accessing early-intervention services. Larger clinical studies are needed to further evaluate the clinical utility of SCZ-PRSs, especially among individuals with high SCZ-PRS burden.

Identifying biomarkers of developing mental disorder is crucial to improving early identification and treatment—a key strategy for reducing the burden of mental disorders. Cross-frequency coupling between two different frequencies of neural oscillations is one such promising measure, believed to reflect synchronization between local and global networks in the brain. Specifically, in adults phase–amplitude coupling (PAC) has been shown to be involved in a range of cognitive processes, including working and long-term memory, attention, language, and fluid intelligence. Evidence suggests that increased PAC mediates both temporary and lasting improvements in working memory elicited by transcranial direct-current stimulation and reductions in depressive symptoms after transcranial magnetic stimulation. Moreover, research has shown that abnormal patterns of PAC are associated with depression and schizophrenia in adults. PAC is believed to be closely related to cortico-cortico white matter (WM) microstructure, which is well established in the literature as a structural mechanism underlying mental health. Some cognitive findings have been replicated in adolescents and abnormal patterns of PAC have also been linked to ADHD in young people. However, currently most research has focused on cross-sectional adult samples. Whereas initial hypotheses suggested that PAC was a state-based measure due to an early focus on cognitive, task-based research, current evidence suggests that PAC has both state-based and stable components. Future longitudinal research focusing on PAC throughout adolescent development could further our understanding of the relationship between mental health and cognition and facilitate the development of new methods for the identification and treatment of youth mental health.

Whilst it is well documented that cyberbullying is linked to poor mental health outcomes, limited research has examined how cyberbullying may influence brain development adolescents, and the influence of each of these factors. The article’s primary objective was to develop an understanding of research to date that addresses any relationship between adolescent brain development and cyberbullying. The current article reviews any existing literature regarding the impact of cyberbullying on adolescent brain development, paying particular attention to research using magnetic resonance imaging (MRI) techniques. Whilst brain studies have examined neural mechanisms associated with conduct disorders, antisocial behavior, and aggression in young people; there is a paucity of research examining these factors specifically in relation to cyberbullying. In particular, little research has examined how MRI research could help understand how the brain is affected by cyberbullying, not only in bullies and victims but also bystanders. This article highlights the gaps in the cyberbullying field in relation to neuroscience research, and the need for further, longitudinal research examining cyberbullying and how it may affect brain development in young people. This article concludes by suggesting a framework for future research, and highlights the importance of future findings for developing interventions and understanding short and long term effects.

BackgroundNeurocognitive impairments robustly predict functional outcome. However, heterogeneity in neurocognition is common within diagnostic groups, and data-driven analyses reveal homogeneous neurocognitive subgroups cutting across diagnostic boundaries.AimsTo determine whether data-driven neurocognitive subgroups of young people with emerging mental disorders are associated with 3-year functional course.MethodModel-based cluster analysis was applied to neurocognitive test scores across nine domains from 629 young people accessing mental health clinics. Cluster groups were compared on demographic, clinical and substance-use measures. Mixed-effects models explored associations between cluster-group membership and socio-occupational functioning (using the Social and Occupational Functioning Assessment Scale) over 3 years, adjusted for gender, premorbid IQ, level of education, depressive, positive, negative and manic symptoms, and diagnosis of a primary psychotic disorder.ResultsCluster analysis of neurocognitive test scores derived three subgroups described as ‘normal range’ (n = 243, 38.6%), ‘intermediate impairment’ (n = 252, 40.1%), and ‘global impairment’ (n = 134, 21.3%). The major mental disorder categories (depressive, anxiety, bipolar, psychotic and other) were represented in each neurocognitive subgroup. The global impairment subgroup had lower functioning for 3 years of follow-up; however, neither the global impairment (B = 0.26, 95% CI −0.67 to 1.20; P = 0.581) or intermediate impairment (B = 0.46, 95% CI −0.26 to 1.19; P = 0.211) subgroups differed from the normal range subgroup in their rate of change in functioning over time.ConclusionsNeurocognitive impairment may follow a continuum of severity across the major syndrome-based mental disorders, with data-driven neurocognitive subgroups predictive of functional course. Of note, the global impairment subgroup had longstanding functional impairment despite continuing engagement with clinical services.

Background: Community Care Units (CCUs) are a model of community-based residential rehabilitation support available in Australia that assists people affected by severe and persistent mental illness to enhance their independent living skills and community involvement. These services have been subject to limited evaluation, and available descriptions of consumer cohorts lack relevance to the understanding of their rehabilitation needs.Method: A clinical assessment battery covering a broad range of relevant domains was completed with consumers commencing at three CCUs in Queensland, Australia, between December 2014 and December 2017 (N = 145). The cohort was described based on demographic, diagnostic, treatment-related variables, and the assessment battery. The comparability of included sites was assessed. This contemporary cohort was also compared to the pooled cohort of Australian community-based residential rehabilitation services emerging from a previous systematic review. Additionally, cluster analysis (CA) was completed in two stages based on the clinician-rated assessments: hierarchical CA (Wards method) to identify the optimal number of clusters, followed by K-means clustering.Results: Dominant features of the cohort were male sex and the primary diagnoses of schizophrenia spectrum disorders. The average consumer age was 31.4 years. Most consumers were referred from the community, had been living with family, and were not subject to involuntary treatment orders. No site-based differences were observed on demographic, diagnostic and treatment-related variables. However, some site-based variation in levels of symptoms and functional impairment emerged. Overall, the cohort was comparable with the Transitional Residential Rehabilitation (TRR) cohort defined in a previous systematic review. Through CA, a three-cluster solution emerged: Cluster 1 (15%) was characterised by higher levels of substance use comorbidity; Cluster 2 (39%) was characterised by higher levels of disability and symptoms; and Cluster 3 (46%) was distinguished by lower levels of general psychiatric symptoms.Conclusions: The cohort was generally comparable to the TRR cohort. Site-based variability in the characteristics of admitted consumers was minimal. The CA solution suggested that three different sub-groups of consumers are admitted to CCUs, which have implications for adapting the approach to rehabilitation. Recommendations include ensuring early availability of interventions to address co-morbidities and pacing rehabilitation expectations to consumers stage of recovery.

Background: Agomelatine is a melatonin agonist and 5HT antagonist developed for the treatment of major depressive disorder which also has some effects on the circadian system. Since circadian dysfunctions are thought to play a role in the pathophysiology of depression, some of the mechanism of action of this drug may relate to improvements in circadian rhythms.Objective: This proof of concept open-label study sought to determine if improvements in depressive symptoms following an adjunctive multimodal intervention including agomelatine intake are associated with the magnitude of circadian realignment. This was investigated in young people with depression, a subgroup known to have high rates of delayed circadian rhythms.Methods: Young people with depression received a psychoeducation session about sleep and circadian rhythms, were asked to progressively phase advance their wake up time, and completed an 8 weeks course of agomelatine (25–50 mg). Participants underwent semi-structured psychological assessments, ambulatory sleep-wake monitoring and measurement of melatonin circadian phase before and after the intervention.Results: Twenty-four young adults with depression (17–28 years old; 58% females) completed the study. After the intervention, depressive symptoms were significantly reduced [t(23) = 6.9, p < 0.001] and, on average, the timing of dim light melatonin onset (DLMO) shifted 3.6 h earlier [t(18) = 4.4, p < 0.001]. On average, sleep onset was phase shifted 28 min earlier [t(19) = 2.1, p = 0.047] and total sleep time increased by 24 min [t(19) = –2.6, p = 0.018]. There was no significant change in wake-up times. A strong correlation (r = 0.69, p = 0.001) was found between the relative improvements in depression severity and the degree of phase shift in DLMO.Conclusion: Although this needs to be replicated in larger randomized controlled trials, these findings suggest that the degree of antidepressant response to a multimodal intervention including psychoeducation and agomelatine intake may be associated with the degree of change in evening melatonin release in young people with depression. This offers promising avenues for targeted treatment based on the prior identification of objective individual characteristics.

Background: Cognitive impairments contribute significantly to disease burden in young individuals presenting with major psychiatric disorders. The capacity to encode the consequences of one's actions may be of particular importance for real-world functioning due to its fundamental role in goal-directed behavior. Methods: Here, we investigated a dimensional measure of causal awareness during a probabilistic learning task in 92 young individuals with an admixture of major mood and psychotic illnesses, at early and more established stages. Using automated gray matter segmentation of T1-weighted images, we estimated the volume and shapes of major subcortical structures and investigated their association with causal awareness. Results: The low causal awareness (LCA) group (n = 35) reported increased social disability (p = .004) and reduced right pallidal size, specifically within the dorsolateral surfaces (p = .02), relative to the unimpaired high causal awareness (HCA) patients (n = 57). In early-stage illness, LCA had a smaller right thalamus (p = .002) relative to HCA. Exploratory investigations suggested that in developed psychotic syndromes, causal awareness was correlated with left hippocampal size (p = .006) whereas, in more persistent affective disorders, causal awareness was correlated with left amygdala size (p = .013), specifically within the anterior aspect. Discussion: Low causal awareness occurs across diagnoses and stages of illness and is associated with poor functional outcomes. Our results suggest that there may be shared neural underpinnings of its dysfunction in the early course of mood and psychotic disorders, however in more established illness, there is greater neurobiological divergence in causal awareness correlates between diagnoses.

Binge drinking has significant effects on memory, particularly with regards to the transfer of information to long-term storage. Partial or complete blocking of memory formation is known as blackout. Youth represents a critical period in brain development that is particularly vulnerable to alcohol misuse. Animal models show that the adolescent brain is more vulnerable to the acute and chronic effects of alcohol compared with the adult brain. This mini-review addresses the neurobiological underpinnings of binge drinking and associated memory loss (blackout) in the adolescent and young adult period. Although the extent to which there are pre-existing versus alcohol-induced neurobiological changes remains unclear, it is likely that repetitive binge drinking in youth has detrimental effects on cognitive and social functioning. Given its role in learning and memory, the hippocampus is a critical region with neuroimaging research showing notable changes in this structure associated with alcohol misuse in young people. There is a great need for earlier identification of biological markers associated with alcohol-related brain damage. As a means to assess in vivo neurochemistry, magnetic resonance spectroscopy (MRS) has emerged as a particularly promising technique since changes in neurometabolites often precede gross structural changes. Thus, the current paper addresses how MRS biomarkers of neurotransmission (glutamate, GABA) and oxidative stress (indexed by depleted glutathione) in the hippocampal region of young binge drinkers may underlie propensity for blackouts and other memory impairments. MRS biomarkers may have particular utility in determining the acute versus longer-term effects of binge drinking in young people.

Myo-inositol, a second messenger glucose isomer and glial marker, is potentiated by melatonin. In addition to common abnormalities in melatonin regulation, depressive disorders have been associated with reduced myo-inositol in frontal structures. This study examined associations between myo-inositol in the anterior cingulate cortex and the timing of evening melatonin release. Forty young persons with unipolar depression were recruited from specialized mental health services (20.3 ± 3.8 years old). Healthy controls were recruited from the community (21.7 ± 2.6 years old). The timing of dim light melatonin onset (DLMO) was estimated using salivary melatonin sampling. Myo-inositol concentrations (MI/CrPCr ratio) in the anterior cingulate cortex were obtained using proton magnetic resonance spectroscopy. After controlling for age, sex, and CrPCr concentration the depression group had significantly lower MI/CrPCr ratios than healthy controls [F(4, 75) = 11.4, p = 0.001]. In the depression group, later DLMO correlated with lower MI/CrPCr ratio (r = −0.48, p = 0.014). These findings suggest that neurochemical changes in the frontal cortex are associated with circadian disruptions in young persons with depression.