The mental health of incarcerated individuals is a widely recognized public health issue, but little is known about the mental health status of the incarcerated individuals upon release. This study aimed to measure the prevalence of psychiatric disorders and substance use disorders (SUDs) among incarcerated men scheduled to be released from jail soon.

We conducted a cross-sectional national survey from September 2020 to September 2022 across 26 jails (selected at random) in France. Each participant was interviewed within 30 days prior to their release via a structured questionnaire, including the Mini International Neuropsychiatric Interview.

A total of 579 individuals were included in the analysis (participation rate: 66.2%). The prevalence of mood disorders, anxiety disorders, post-traumatic stress disorder, and psychotic episodes were 30.7% (95% confidence interval [CI]: 27.1%–34.6%), 28.7% (95% CI: 25.1%–32.5%), 11.1% (95% CI: 8.8%–13.9%), and 10.5% (95% CI: 8.3%–13.3%), respectively. Additionally, almost half of the individuals had an SUD, and dual disorders were identified in 21.9% (95% CI: 18.8%–25.5%) of the cases. The analysis of mental health care pathways raised questions about access to certain types of care, such as full-time psychiatric hospitalization while in prison, as well as questions about the continuity of care upon release.

This study shows that the mental health of incarcerated men who are scheduled to be released soon is precarious. Complex mental health problems, particularly dual disorders, are common and require better coordination between mental health care systems in prisons and the community.

Schizotypy represents an index of psychosis-proneness in the general population, often associated with childhood trauma exposure. Both schizotypy and childhood trauma are linked to structural brain alterations, and it is possible that trauma exposure moderates the extent of brain morphological differences associated with schizotypy.

We addressed this question using data from a total of 1182 healthy adults (age range: 18–65 years old, 647 females/535 males), pooled from nine sites worldwide, contributing to the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Schizotypy working group. All participants completed both the Schizotypal Personality Questionnaire Brief version (SPQ-B), and the Childhood Trauma Questionnaire (CTQ), and underwent a 3D T1-weighted brain MRI scan from which regional indices of subcortical gray matter volume and cortical thickness were determined.

A series of multiple linear regressions revealed that differences in cortical thickness in four regions-of-interest were significantly associated with interactions between schizotypy and trauma; subsequent moderation analyses indicated that increasing levels of schizotypy were associated with thicker left caudal anterior cingulate gyrus, right middle temporal gyrus and insula, and thinner left caudal middle frontal gyrus, in people exposed to higher (but not low or average) levels of childhood trauma. This was found in the context of morphological changes directly associated with increasing levels of schizotypy or increasing levels of childhood trauma exposure.

These results suggest that alterations in brain regions critical for higher cognitive and integrative processes that are associated with schizotypy may be enhanced in individuals exposed to high levels of trauma.

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.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Patients with psychiatric disorders are exposed to high risk of COVID-19 and increased mortality. In this study, we set out to assess the clinical features and outcomes of patients with current psychiatric disorders exposed to COVID-19.

This multi-center prospective study was conducted in 22 psychiatric wards dedicated to COVID-19 inpatients between 28 February and 30 May 2020. The main outcomes were the number of patients transferred to somatic care units, the number of deaths, and the number of patients developing a confusional state. The risk factors of confusional state and transfer to somatic care units were assessed by a multivariate logistic model. The risk of death was analyzed by a univariate analysis.

In total, 350 patients were included in the study. Overall, 24 (7%) were transferred to medicine units, 7 (2%) died, and 51 (15%) patients presented a confusional state. Severe respiratory symptoms predicted the transfer to a medicine unit [odds ratio (OR) 17.1; confidence interval (CI) 4.9–59.3]. Older age, an organic mental disorder, a confusional state, and severe respiratory symptoms predicted mortality in univariate analysis. Age >55 (OR 4.9; CI 2.1–11.4), an affective disorder (OR 4.1; CI 1.6–10.9), and severe respiratory symptoms (OR 4.6; CI 2.2–9.7) predicted a higher risk, whereas smoking (OR 0.3; CI 0.1–0.9) predicted a lower risk of a confusional state.

COVID-19 patients with severe psychiatric disorders have multiple somatic comorbidities and have a risk of developing a confusional state. These data underline the need for extreme caution given the risks of COVID-19 in patients hospitalized for psychiatric disorders.

Investing in stricter biodiversity conservation and wildlife protection to reduce the number of emerging diseases and, consequently, the risk of pandemics such as coronavirus disease-19 (COVID-19), must integrate a social-ecological perspective. Biodiversity conservation, in order to be effective as disease prevention, requires consideration of people's needs, knowledge and institutions within their locally specific contexts. To meet this goal, future biodiversity research and conservation policy should apply six social-ecological principles for shaping future practices of co-existence of societies and nature.

The COVID-19 pandemic, presumably originating in a spillover event from natural wildlife reservoirs into the human population, sets a new benchmark for the indirect cost of biodiversity exploitation. To reverse the trend of increasing pandemic risk, biodiversity conservation and wildlife protection must be strengthened globally. In this paper, we argue that such preventive measures explicitly need to employ a social-ecological approach. In particular, attention must be paid to the societal relations to nature to avoid falling for simplistic solutions that neglect regional and local particularities of both, biodiversity and local communities. We emphasize the importance of avoiding a Western-biased view and acknowledging the factors and causations of infectious disease emergence in industrialized countries. To reduce the emergence of zoonotic and vector-borne diseases in their specific contexts, we propose applying a social-ecological systems approach by integrating plural local knowledge and values, established practices, formal and informal institutions, as well as technology. We further introduce six social-ecological principles for shaping transformations in the Anthropocene to maintain and build more resilient and sustainable communities. By operationalizing these inter- and transdisciplinary principles, biodiversity conservation can be effectively implemented as infectious disease prevention.

A social-ecological approach to biodiversity conservation can pave the way for an effective and socially just reduction of future pandemic risks.

Catatonia is a frequent, complex and severe identifiable syndrome of motor dysregulation. However, its pathophysiology is poorly understood.

We aimed to provide a systematic review of all brain imaging studies (both structural and functional) in catatonia.

We identified 137 case reports and 18 group studies representing 186 individual patients with catatonia. Catatonia is often associated with brain imaging abnormalities (in more than 75% of cases). The majority of the case reports show diffuse lesions of white matter, in a wide range of brain regions. Most of the case reports of functional imaging usually show frontal, temporal, or basal ganglia hypoperfusion. These abnormalities appear to be alleviated after successful treatment of clinical symptoms. Structural brain magnetic resonance imaging studies are very scarce in the catatonia literature, mostly showing diffuse cerebral atrophy. Group studies assessing functional brain imaging after catatonic episodes show that emotional dysregulation is related to the GABAergic system, with hypoactivation of orbitofrontal cortex, hyperactivation of median prefrontal cortex, and dysconnectivity between frontal and motor areas.

In catatonia, brain imaging is abnormal in the majority of cases, and abnormalities more frequently diffuse than localised. Brain imaging studies published so far suffer from serious limitations and for now the different models presented in the literature do not explain most of the cases. There is an important need for further studies including a better clinical characterisation of patients with catatonia, functional imaging with concurrent catatonic symptoms and the use of novel brain imaging techniques.

Hospital-based health technology assessment (HB-HTA) needs to consider all relevant data to help decision-making, including patients’ preferences. In this study, we comprehensively describe the process of identification, refinement and selection of attributes and levels for a discrete choice experiment (DCE).

A mixed-methods design was used to identify attributes and levels explaining low back pain (LBP) patients’ choice for a non-surgical treatment. This design combined a systematic literature review with a patients’ focus group, one-on-one interactions with experts and patients, and discussions with stakeholder committee members. Following the patient's focus group, ranking exercises were conducted. A consensus about the attributes and levels was researched during discussions with committee members.

The literature review yielded 40 attributes to consider in patients’ treatment choice. During the focus group, one additional attribute emerged. The ranking exercises allowed selecting eight attributes for the DCE. These eight attributes and their levels were discussed and validated by the committee members who helped reframe two levels in one of the attributes and delete one attribute. The final seven attributes were: treatment modality, pain reduction, onset of treatment efficacy, duration of efficacy, difficulty in daily living activities, sleep problem, and knowledge about their body and pain.

This study is one of the few to comprehensively describe the selection process of attributes and levels for a DCE. This may help ensure transparency and judge the quality of the decision-making process. In the context of a HB-HTA unit, this strengthens the legitimacy to perform a DCE to better inform decision-makers in a patient-centered care approach.