Hospital Emergency Departments are increasingly playing a role in the care of young people experiencing suicidal crisis. Autistic young people, who already experience elevated rates of suicidal thoughts and death by suicide, may face particular difficulties in such environments.

This retrospective medical records review explored patterns of Emergency Department attendance for suicidal crisis among young people (aged 8-16 years) attending a UK paediatric hospital between 2019 and 2021. Anonymised clinical records from 338 young people were analysed using descriptive and exploratory statistics.

35.8% of attendees were autistic and 62.0% of those were female. Autistic young people were attending at significantly younger ages than non-autistic young people, and were significantly more likely to be known to mental health services and to have attended the Emergency Department previously for suicide ideation.

Findings indicate that autistic young people, and in particular autistic females, were over-represented in crisis presentations, despite previous attempts to seek help. Further research is needed to understand what could help prevent autistic young people from reaching crisis, and what support may be beneficial in the Emergency Department to de-escalate crises, improve wellbeing, and prevent re-attendance.

To analyse suicide mortality trends in Andalusia, Spain (2000-2024) through age-period-cohort (APC) decomposition, identify trend change-points, and quantify pandemic-associated excess mortality.

This population-based study used Spanish National Statistics Institute data (INE; heading 098, ICD-10 × 60-X84). Age-standardised rates (European Standard Population 2013) were computed by sex. Methods comprised joinpoint regression, Prais-Winsten modelling, an APC model (intrinsic estimator), and a log-linear counterfactual projecting the 2000-2019 trend onto 2020-2024, with quasi-Poisson and age-range sensitivity analyses.

18,350 suicide deaths were recorded (77.4% male). Crude rates remained stable (EAPC = - 0.12%, p = 0.615) whereas age-standardised rates declined significantly (EAPC = - 0.96%, p < 0.001), revealing demographic masking. Joinpoint regression identified a single change-point reversing the long-term decline, at 2018 for both sexes (EAPC - 1.67% to + 2.65%) and 2019 for men (- 2.01% to + 3.84%); neither post-reversal segment reached significance. The APC model (adults aged 40-84; deviance R² = 0.983) showed an ascending age gradient, a period nadir in 2015-2019, and declining cohort risk. The counterfactual estimated 783 excess deaths during 2020-2024 (O/E = 1.23, 95% CI 1.20-1.27; p < 0.001), concentrated among those aged 15-64.

The age-standardised decline reached its nadir around 2018-2019 and reversed thereafter; relative to the projected pre-pandemic trend, the pandemic period (2020-2024) showed a sustained excess without attenuation over the five years observed. These findings support age-targeted prevention; provincial heterogeneity warrants formal subnational analyses before recommending geographically differentiated strategies.

to understand the family management experience of mental disorders in adolescents in light of the Family Management Style Framework.

a qualitative case study was conducted with six families between July and November 2022. The interviews were analyzed using a hybrid thematic analysis model, with the support of NVivo® 15.

families understand mental illness as a condition marked by stigma and daily challenges. Adolescents' identity oscillates between normality and vulnerability, guiding care towards safety and well-being. Changes in routine reflect the effort to cope with unpredictability, while future expectations value adolescents' autonomy and mental health.

the study provides support for interventions that promote resilience and family functionality, based on psychoeducation, problem-solving, reinforcement of strengths, and mitigation of problematic aspects of family management.

To identify and map the relationship between nursing work environments and patient safety for older adults ≥ 65.

Scoping review and consultation exercise.

Systematic searches of five databases were conducted in 2022, 2024 and 2026. Two reviewers independently screened titles/abstracts and subsequently by full-text review. Data was extracted using an extraction form with knowledge users involved throughout.

Eighty-four studies were included. The data were presented with three main categories: (1) study characteristics; (2) core constructs; (3) the relationship between nursing work environments and patient safety, including theoretical frameworks and knowledge users' insights.

The relationship between nursing work environments and patient safety for older adults is intricate. Work environment factors, such as staffing, skill mix and education, influence patient safety, which is defined through outcomes like mortality, readmissions and healthcare-associated complications.

Increased awareness of how the work environment influences patient safety can support prioritisation of nursing practice, staffing, skill mix and increase level of education to reduce errors.

The findings provide an overview of the ways in which work environment factors shape safety for older adults and highlight gaps in measurement and conceptual clarity. The results have implications for healthcare policy, organisational decision-making and clinical practice. The review was conducted in accordance with the EQUATOR guidelines for PRISMA-ScR.

Emphasises the role of supportive work environments in enhancing care quality globally. Provides insight for policy and improvements to benefit patient safety. Clarifies the scope of research on nursing work environments and patient safety in older adults.

Patients and members of the public were involved in designing the study, collecting data and interpreting the findings. Their contributions included reviewing concepts, co-creating research questions, providing feedback on methodology, inclusion/exclusion, findings and practice implications.

Antidepressants such as venlafaxine and sertraline pose high risks to water ecosystems. As depressive disorders and other mental health conditions become increasingly prevalent worldwide, prescription and environmental presence of these pharmaceuticals continue to rise. This study explores the practical viability of a new framework for prescribing antidepressants-integrating safety, efficacy and environmental impact. This same approach could be applied in the future for reviewing prescription of other drug classes commonly found as pollutants in water.

To assess whether environmental risks could be reduced by prioritizing less polluting active substances, shifts in prescribing practices were simulated: For sertraline, shifts were directed towards citalopram and/or escitalopram, whereas for venlafaxine, the alternative was left unspecified due to the lack of equivalent options; a cost analysis was conducted to research economic feasibility of such an implementation.

Shifting away from sertraline towards citalopram and/or escitalopram would reduce the risk class of sertraline without increasing that of citalopram and escitalopram; the cost of such shifts would increase SSRI expenditure between 0.65% and 8.22% for Italy and reduce it between 3.53% and 12.72% in Germany. Conversely, no change in risk category is observed when the quantity of prescribed venlafaxine is reduced.

In the future, clinical guidelines could be adjusted to favour first-line substances with lower environmental impact but comparable efficacy, as for citalopram and escitalopram compared with sertraline. Together with strengthened implementation of non-pharmacological strategies, these measures could be an active step in fighting environmental pollution and climate change, increasing global health.

Autistic children and young people receiving eating disorder focused family therapy (FT-ED) for anorexia nervosa (AN) are more likely than their non-Autistic peers to require longer and more intensive treatment. Qualitative evidence suggests that Autistic young people and their parents struggle with a perceived inflexible delivery of FT-ED that can be mis-attuned to autistic needs. Clinicians delivering this care report a lack of confidence when adapting FT-ED to this population, and there is limited guidance on how to do this. This paper describes evidence‑informed and coproduced guidelines, developed via a series of workshops with Autistic people with lived experience of an eating disorder, parents and carers, clinicians, researchers, and third‑sector representatives. The intention of these guidelines is to support clinicians in the adaptation of FT-ED for Autistic young people with AN and their families, with the aim of delivering more appropriate and effective care. Young people and their parents or carers may also find these guidelines helpful when advocating for autism-affirming care within FT-ED.

Formic acid is widely used in rubber latex coagulation, especially in semiurban and rural industrial settings. Its unregulated handling poses significant occupational health hazards. The objectives of the case series are to document the clinical, toxicological, and autopsy findings in six fatal cases of formic acid poisoning among rubber industry workers in Tripura, India. To document the clinical, toxicological, and autopsy findings in six fatal cases of formic acid poisoning among rubber industry workers in Tripura, India. This retrospective case series analyzed clinical records, autopsy findings, histopathology, and toxicology reports of six deceased individuals exposed to formic acid through ingestion or inhalation. All victims were rubber factory or plantation workers; five deaths were suicidal and one accidental. Common features included metabolic acidosis, gastrointestinal corrosion, pulmonary edema, and multi-organ failure. Histopathology revealed acute tubular necrosis, gastric mucosal necrosis, and alveolar edema. Toxicology confirmed lethal levels of formic acid. These cases highlight critical gaps in occupational safety, chemical handling practices, and mental health support in industrial environments handling corrosive agents like formic acid.

The aim of the study was to analyze the influence of various pipelines for preprocessing raw functional magnetic resonance imaging (fMRI) data on the accuracy of classification of subjects into schizophrenia patients and healthy controls using machine learning methods, and to give recommendations for optimizing the data preprocessing pipeline for this task.

The study used fMRI data from 72 subjects acquired on a Siemens Magnetom Verio 3T MRI scanner (Siemens Healthineers, Germany) at the National Research Centre "Kurchatov Institute". Seven different preprocessing pipelines were used on each dataset. Feature vectors for classification were constructed from each preprocessed dataset. We applied the following three algorithms for feature vector construction: ReHo, FCM, and FHR. Classification was performed using 15 machine learning methods from the scikit-learn package for each feature set and each preprocessing pipeline. The final accuracy was determined as the maximum accuracy among all machine learning methods.

No single optimal preprocessing pipeline for all feature vector construction algorithms was found. Smoothing increased accuracy for the voxel metrics ReHo and FHR, but not for the regional metric FCM. Spatial smoothing was the only preprocessing step that affected classification accuracy for the FHR method. The FHR feature set without smoothing demonstrated accuracy close to chance level. The steps of frequency filtering and median normalization substantially increased the accuracy for both the ReHo and FCM methods, both with and without smoothing. The steps of inhomogeneity correction and slice timing correction did not increase accuracy for the FCM feature set but did improve it by several percent for the ReHo feature set. Application of ICA filtering changed accuracy within a range of 5%, in either a positive or negative direction.

Based on the obtained results, the following recommendations can be given for fMRI data preprocessing pipelines for binary classification of subjects into schizophrenia patients and healthy controls using machine learning methods and taking into account the feature vector construction algorithm. The most suitable for the ReHo metric pipeline includes motion correction, normalization, inhomogeneity correction, slice timing correction, frequency filtering, median normalization, and spatial smoothing. The most suitable for the FCM metric pipeline includes motion correction, normalization, inhomogeneity correction, slice timing correction, frequency filtering, and median normalization. Spatial smoothing is the most important factor for the FHR metric. The ICA filtering step does not provide a clear benefit and should therefore be applied with caution.

Micro- and nano-plastics (MNPs) can enter the human body through inhalation, ingestion, contact with consumer products, and iatrogenic routes. The clinical relevance of MNP exposure should be interpreted at three levels: barrier interaction, cellular stress, and system-level disruption, with key mechanisms including oxidative stress, mitochondrial dysfunction, and chronic inflammation.

The gut microbiota significantly influences mental health through the gut-brain axis, modulating mood, cognition, and emotional regulation. While probiotics and prebiotics have been widely studied for their psychobiotic effects, postbiotics-metabolic byproducts of probiotics-represent an underexplored area with potential therapeutic applications. Understanding the role of postbiotics in mental health disorders, such as depression, psychosis, and mania, could lead to novel treatment strategies. This review examines the psychobiotic potential of postbiotics and their mechanisms of action.

A systematic literature review was conducted to evaluate the effects of postbiotics on mental health conditions. We searched PubMed, Medline, EMBASE, and the Cochrane Library for English-language articles published between January 1, 2015, and January 1, 2025, using keywords such as "postbiotic," "paraprobiotic," "depression," "anxiety," and "psychosis." A manual search supplemented the electronic search to ensure comprehensive coverage. Studies focusing on postbiotic effects on mood regulation, neuroinflammation, and neurotransmitter modulation were included.

Postbiotics demonstrate promising psychobiotic effects in depression, psychosis, and mania. They modulate neurotransmitter levels, including serotonin and gamma-aminobutyric acid (GABA), and reduce neuroinflammation, contributing to improved mood and cognitive function. Additionally, postbiotics influence the hypothalamic-pituitary-adrenal (HPA) axis, enhancing stress response and emotional regulation. These findings suggest that postbiotics may serve as effective therapeutic agents for mental health disorders.

Postbiotics offer significant potential as novel interventions for mental health conditions, with mechanisms involving neurotransmitter modulation and neuroinflammation reduction. Further empirical research is needed to elucidate their clinical applications and optimize therapeutic protocols. This review highlights the importance of postbiotics in advancing innovative strategies to improve mental health outcomes and well-being.