The COVID-19 pandemic has led to an increased psychological strain on public mental health and may impact behavioural, mental, and physical health, presumably with effects on patients with severe mental disorders.

This study examines pandemic-related physical and mental health and (compensatory) behavioural changes, in patients with BD as compared to healthy control individuals.

Physical and mental health and self-reported changes in daily structure and behaviour due to pandemic were assessed using a self-constructed questionnaire and the brief symptom inventory (BSI) from outpatient clinics in Germany, Austria, and Denmark in individuals with BD and a healthy control group.

The present study included 118 individuals with BD and 215 healthy controls. Individuals with BD reported statistically significant higher physical risk burden, increased weight gain, more physical comorbidities, and a decrease in physical activity and they further reported higher rate of COVID-19 testing, had more worries concerning health and experienced more anxiety but less social distancing.

The COVID-19 pandemic seems to have a greater impact on physical health in individuals with BD than in healthy controls. Individuals with BD appear to be having more difficulties compensating their behaviour due to the pandemic which could amplify the effect of risk factors associated with poorer physical health. This highlights the necessity for optimising and targeting the overall treatment of both mental and physical health in patients with BD during periods with far-reaching changes such as COVID-19 pandemic.

No significant relationships.

To quantify perceptions of tap water among low-income mothers with young children residing in Michigan and examine associations between perceptions of tap water, mothers’ and young children’s beverage intake, and mothers’ infant feeding practices.

Cross-sectional study.

Online survey.

Medicaid-insured individuals who had given birth at a large Midwestern US hospital between fall 2016 and fall 2020 were invited by email to complete a survey in winter 2020 (N 3881); 15·6 % (N 606) completed eligibility screening, 550 (90·8 %) were eligible to participate, and 500 (90·9 %) provided valid survey data regarding perceptions of tap water, self and child beverage intake, and infant feeding practices.

Two-thirds (66·2 %) of mothers reported that their home tap water was safe to drink without a filter, while 21·6 % were unsure about the safety of their home tap water. Mothers’ perceptions of their home tap water were associated with their own tap and bottled water intake and their young children’s tap water and bottled water intake. Mothers with more negative perceptions of tap water in general, independent of their perceptions about their home tap water, consumed more bottled water and sugar-sweetened beverages, and their young children drank bottled water and fruit drinks more frequently. Few associations were observed between mothers’ perceptions of tap water and infant feeding practices.

Uncertainty about tap water safety and negative perceptions of tap water are common among low-income Michigan mothers. These beliefs may contribute to less healthful and more costly beverage intake among mothers and their young children.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

The purpose of this study was to pilot safety and tolerability of a 1-week aerobic exercise program during the post-acute phase of concussion (14–25 days post-injury) by examining adherence, symptom response, and key functional outcomes (e.g., cognition, mood, sleep, postural stability, and neurocognitive performance) in young adults.

A randomized, non-blinded pilot clinical trial was performed to compare the effects of aerobic versus non-aerobic exercise (placebo) in concussion patients. The study enrolled three groups: 1) patients with concussion/mild traumatic brain injury (mTBI) randomized to an aerobic exercise intervention performed daily for 1-week, 2) patients with concussion/mTBI randomized to a non-aerobic (stretching and calisthenics) exercise program performed daily for 1-week, and 3) non-injured, no intervention reference group.

Mixed-model analysis of variance results indicated a significant decrease in symptom severity scores from pre- to post-intervention (mean difference = −7.44, 95% CI [−12.37, −2.20]) for both concussion groups. However, the pre- to post-change was not different between groups. Secondary outcomes all showed improvements by post-intervention, but no differences in trajectory between the groups. By three months post-injury, all outcomes in the concussion groups were within ranges of the non-injured reference group.

Results from this study indicate that the feasibility and tolerability of administering aerobic exercise via stationary cycling in the post-acute time frame following post-concussion (14–25 days) period are tentatively favorable. Aerobic exercise does not appear to negatively impact recovery trajectories of neurobehavioral outcomes; however, tolerability may be poorer for patients with high symptom burden.

We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.

A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.

How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.

COVID-19 altered research in Clinical and Translational Science Award (CTSA) hubs in an unprecedented manner, leading to adjustments for COVID-19 research.

CTSA members volunteered to conduct a review on the impact of CTSA network on COVID-19 pandemic with the assistance from NIH survey team in October 2020. The survey questions included the involvement of CTSAs in decision-making concerning the prioritization of COVID-19 studies. Descriptive and statistical analyses were conducted to analyze the survey data.

60 of the 64 CTSAs completed the survey. Most CTSAs lacked preparedness but promptly responded to the pandemic. Early disruption of research triggered, enhanced CTSA engagement, creation of dedicated research areas and triage for prioritization of COVID-19 studies. CTSAs involvement in decision-making were 16.75 times more likely to create dedicated diagnostic laboratories (95% confidence interval [CI] = 2.17–129.39; P < 0.01). Likewise, institutions with internal funding were 3.88 times more likely to establish COVID-19 dedicated research (95% CI = 1.12–13.40; P < 0.05). CTSAs were instrumental in securing funds and facilitating establishment of laboratory/clinical spaces for COVID-19 research. Workflow was modified to support contracting and IRB review at most institutions with CTSAs. To mitigate chaos generated by competing clinical trials, central feasibility committees were often formed for orderly review/prioritization.

The lessons learned from the COVID-19 pandemic emphasize the pivotal role of CTSAs in prioritizing studies and establishing the necessary research infrastructure, and the importance of prompt and flexible research leadership with decision-making capacity to manage future pandemics.

The National Neuropsychology Network (NNN) is a multicenter clinical research initiative funded by the National Institute of Mental Health (NIMH; R01 MH118514) to facilitate neuropsychology’s transition to contemporary psychometric assessment methods with resultant improvement in test validation and assessment efficiency.

The NNN includes four clinical research sites (Emory University; Medical College of Wisconsin; University of California, Los Angeles (UCLA); University of Florida) and Pearson Clinical Assessment. Pearson Q-interactive (Q-i) is used for data capture for Pearson published tests; web-based data capture tools programmed by UCLA, which serves as the Coordinating Center, are employed for remaining measures.

NNN is acquiring item-level data from 500–10,000 patients across 47 widely used Neuropsychology (NP) tests and sharing these data via the NIMH Data Archive. Modern psychometric methods (e.g., item response theory) will specify the constructs measured by different tests and determine their positive/negative predictive power regarding diagnostic outcomes and relationships to other clinical, historical, and demographic factors. The Structured History Protocol for NP (SHiP-NP) helps standardize acquisition of relevant history and self-report data.

NNN is a proof-of-principle collaboration: by addressing logistical challenges, NNN aims to engage other clinics to create a national and ultimately an international network. The mature NNN will provide mechanisms for data aggregation enabling shared analysis and collaborative research. NNN promises ultimately to enable robust diagnostic inferences about neuropsychological test patterns and to promote the validation of novel adaptive assessment strategies that will be more efficient, more precise, and more sensitive to clinical contexts and individual/cultural differences.

Aggressive behaviour is a prevalent and harmful phenomenon in patients with borderline personality disorder (BPD). However, no short-term, low-cost programme exists that specifically focuses on aggression.

Attuning therapy modules to pathogenetic mechanisms that underlie reactive aggression in BPD, we composed a 6 week mechanism-based anti-aggression psychotherapy (MAAP) approach for the group setting, which we tested against a non-specific supportive psychotherapy (NSSP).

A cluster-randomised two-arm parallel-group phase II trial of N = 59 patients with BPD and overt aggressive behaviour was performed (German Registry for Clinical Trials, DRKS00009445). The primary outcome was the externally directed overt aggression score of the Modified Overt Aggression Scale (M-OAS) post-treatment (adjusted for pre-treatment overt aggression). Secondary outcomes were M-OAS irritability, M-OAS response rate and ecological momentary assessment of anger post-treatment and at 6 month follow-up, as well as M-OAS overt aggression score at follow-up.

Although no significant difference in M-OAS overt aggression between treatments was found post-treatment (adjusted difference in mean 3.49 (95% CI −5.32 to 12.31, P = 0.22), the MAAP group showed a clinically relevant decrease in aggressive behaviour of 65% on average (versus 33% in the NSSP group), with particularly strong improvement among those with the highest baseline aggression. Most notably, significant differences in reduction in overt aggression between MAAP and NSSP were found at follow-up.

Patients with BPD and aggressive behaviour benefited from a short group psychotherapy, with improvements particularly visible at 6 month follow-up. Further studies are required to show whether these effects are specific to MAAP.