Exposure to adversity in childhood is a risk factor for lifetime mental health problems. Altered pace of biological aging, as measured through pubertal timing, is one potential explanatory pathway for this risk. This study examined whether pubertal timing mediated the association between adversity (threat and deprivation) and adolescent mental health problems (internalizing and externalizing), and whether this was moderated by sex.

Aims were examined using the Adolescent Brain and Cognitive Development study, a large community sample from the United States. Data were used from three timepoints across the ages of 9–14 years. Latent scores from confirmatory factor analysis operationalized exposure to threat and deprivation. Bayesian mixed-effects regression models tested whether pubertal timing in early adolescence mediated the relationship between adversity exposure and later internalizing and externalizing problems. Sex was examined as a potential moderator of this pathway.

Both threat and deprivation were associated with later internalizing and externalizing symptoms. Threat, but not deprivation, was associated with earlier pubertal timing, which mediated the association of threat with internalizing and externalizing problems. Sex differences were only observed in the direct association between adversity and internalizing problems, but no such differences were present for mediating pathways.

Adversity exposure had similar associations with the pace of biological aging (as indexed by pubertal timing) and mental health problems in males and females. However, the association of adversity on pubertal timing appears to depend on the dimension of adversity experienced, with only threat conferring risk of earlier pubertal timing.

To model cognitive reserve (CR) longitudinally in a neurodiverse pediatric sample using a residual index approach, and to test the criterion and construct validity of this index.

Participants were N = 115 children aged 9.5–13 years at baseline (MAge = 10.48 years, SDAge = 0.61), and n = 43 (37.4%) met criteria for ADHD. The CR index represented variance in Matrix Reasoning scores from the WASI that was unexplained by MRI-based brain variables (bilateral hippocampal volumes, total gray matter volumes, and total white matter hypointensity volumes) or demographics (age and sex).

At baseline, the CR index predicted math computation ability (estimate = 0.50, SE = 0.07, p < .001), and word reading ability (estimate = 0.26, SE = 0.10, p = .012). Longitudinally, change in CR over time was not associated with change in math computation ability (estimate = −0.02, SE = 0.03, p < .513), but did predict change in word reading ability (estimate = 0.10, SE = 0.03, p < .001). Change in CR was also found to moderate the relationship between change in word reading ability and white matter hypointensity volume (estimate = 0.10, SE = 0.05, p = .045).

Evidence for the criterion validity of this CR index is encouraging, but somewhat mixed, while construct validity was evidenced through interaction between CR, brain, and word reading ability. Future research would benefit from optimization of the CR index through careful selection of brain variables for a pediatric sample.

Undergoing puberty ahead of peers (‘earlier pubertal timing’) is an important risk factor for mental health problems during early adolescence. The current study examined pathways between pubertal timing and mental health via connectivity of neural systems implicated in emotional reactivity and regulation (specifically corticolimbic connections) in 9- to 14-year-olds.

Research questions were examined in the Adolescent Brain Cognitive Development (ABCD) Study, a large population representative sample in the United States. Linear mixed models examined associations between pubertal timing and resting-state corticolimbic connectivity. Significant connections were examined as potential mediators of the relationship between pubertal timing and mental health (withdrawn depressed and rule-breaking) problems. Exploratory analyses interrogated whether the family environment moderated neural risk patterns in those undergoing puberty earlier than their peers.

Earlier pubertal timing was related to decreased connectivity between limbic structures (bilateral amygdala and right hippocampus) and the cingulo-opercular network, left amygdala and somatomotor (mouth) network, as well as between the left hippocampus and ventral attention network and visual network. Corticolimbic connections also mediated the relationship between earlier pubertal timing and increased withdrawn depressed problems (but not rule-breaking problems). Finally, parental acceptance buffered against connectivity patterns that were implicated in withdrawn depressed problems in those undergoing puberty earlier than their peers.

Findings highlight the role of decreased corticolimbic connectivity in mediating pathways between earlier pubertal timing and withdrawn depressed problems, and we present preliminary evidence that the family environment may buffer against these neural risk patterns during early adolescence.

Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features.

Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar).

For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI −0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance.

Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.

Public responses to a future novel disease might be influenced by a subset of individuals who are either sensitized or desensitized to concern-generating processes through their lived experiences during the coronavirus disease 2019 (COVID-19) pandemic. Such influences may be critical for shaping public health messaging during the next emerging threat.

This study explored the potential outcomes of the influence of lived experiences by using a dynamic multiplex network model to simulate a COVID-19 outbreak in a population of 2000 individuals, connected by means of disease and communication layers. Then a new disease was introduced, and a subset of individuals (50% or 100% of hospitalized during the COVID-19 outbreak) was assumed to be either sensitized or desensitized to concern-generating processes relative to the general population, which alters their adoption of non-pharmaceutical interventions (social distancing).

Altered perceptions and behaviors from lived experiences with COVID-19 did not necessarily result in a strong mitigating effect for the novel outbreak. When public disease response is already strong or sensitization is assumed to be a robust effect, then a sensitized subset may enhance public mitigation of an outbreak through social distancing.

In preparing for future outbreaks, assuming an experienced and disease-aware public may compromise effective design of effective public health messaging and mitigative action.

Schizophrenia is a serious mental illness that carries a significant burden for families providing care.

The ADHES carers' survey canvassed opinions of families/friends of patients with schizophrenia across Europe.

To ascertain carer attitudes towards schizophrenia, its treatment and treatment adherence.

The survey was conducted from January-April 2011 in 16 European countries, comprising 10 questions relating to the respondents' understanding of schizophrenia, attitudes towards schizophrenia treatments, and perception of the family's/friend's role in supporting patients with schizophrenia.

Results were obtained from 138 respondents. 76% of carers recognized the importance of medication to help patients get better, improve their quality of life (77%) and relationships (74%). 67% of carers responded that they believed schizophrenia treatment damages patients' general health. Two-thirds of the carers reported that treatment adherence was a burden for the patient and over a third of carers indicated that it was a daily struggle to get patients to take their medication. 50% of carers considered the benefits offered by long-acting injectable antipsychotics as very/quite important and thus, could provide a valuable tool in improving treatment adherence. 92% of carers agreed on the importance of family support to boost treatment adherence with education/information deemed important for families and patients alike.

Carers recognize the issues they face in caring for patients with schizophrenia and their role in improving partial/non-adherence to medication, especially to avoid suboptimal treatment outcomes. The important role of family carers should be considered by healthcare professionals when treating patients with schizophrenia.

Deficits in social cognition may be among the most profound and disabling sequelae of paediatric traumatic brain injury (TBI); however, the neuroanatomical correlates of longitudinal outcomes in this domain remain unexplored. This study aimed to characterize social cognitive outcomes longitudinally after paediatric TBI, and to evaluate the use of sub-acute diffusion tensor imaging (DTI) to predict these outcomes.

The sample included 52 children with mild complex-severe TBI who were assessed on cognitive theory of mind (ToM), pragmatic language and affective ToM at 6- and 24-months post-injury. For comparison, 43 typically developing controls (TDCs) of similar age and sex were recruited. DTI data were acquired sub-acutely (mean = 5.5 weeks post-injury) in a subset of 65 children (TBI = 35; TDC = 30) to evaluate longitudinal prospective relationships between white matter microstructure assessed using Tract-Based Spatial Statistics and social cognitive outcomes.

Whole brain voxel-wise analysis revealed significantly higher mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) in the sub-acute TBI group compared with TDC, with differences observed predominantly in the splenium of the corpus callosum (sCC), sagittal stratum (SS), dorsal cingulum (DC), uncinate fasciculus (UF) and middle and superior cerebellar peduncles (MCP & SCP, respectively). Relative to TDCs, children with TBI showed poorer cognitive ToM, affective ToM and pragmatic language at 6-months post-insult, and those deficits were related to abnormal diffusivity of the sCC, SS, DC, UF, MCP and SCP. Moreover, children with TBI showed poorer affective ToM and pragmatic language at 24-months post-injury, and those outcomes were predicted by sub-acute alterations in diffusivity of the DC and MCP.

Abnormal microstructure within frontal-temporal, limbic and cerebro-cerebellar white matter may be a risk factor for long-term social difficulties observed in children with TBI. DTI may have potential to unlock early prognostic markers of long-term social outcomes.