Despite the recognised importance of mental disorders and social disconnectedness for mortality, few studies have examined their co-occurrence.

To examine the interaction between mental disorders and three distinct aspects of social disconnectedness on mortality, while taking into account sex, age and characteristics of the mental disorder.

This cohort study included participants from the Danish National Health Survey in 2013 and 2017 who were followed until 2021. Survey data on social disconnectedness (loneliness, social isolation and low social support) were linked with register data on hospital-diagnosed mental disorders and mortality. Poisson regression was applied to estimate independent and joint associations with mortality, interaction contrasts and attributable proportions.

A total of 162 497 individuals were followed for 886 614 person-years, and 9047 individuals (5.6%) died during follow-up. Among men, interaction between mental disorders and loneliness, social isolation and low social support, respectively, accounted for 47% (95% CI: 21–74%), 24% (95% CI: −15 to 63%) and 61% (95% CI: 35–86%) of the excess mortality after adjustment for demographics, country of birth, somatic morbidity, educational level, income and wealth. In contrast, among women, no excess mortality could be attributed to interaction. No clear trends were identified according to age or characteristics of the mental disorder.

Mortality among men, but not women, with a co-occurring mental disorder and social disconnectedness was substantially elevated compared with what was expected. Awareness of elevated mortality rates among socially disconnected men with mental disorders could be of importance to qualify and guide prevention efforts in psychiatric services.

A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.

We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.

We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723–0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.

We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

The longitudinal course of late-life depression remains under-studied.

To describe transitions along the depression continuum in old age and to identify factors associated with specific transition patterns.

We analysed 15-year longitudinal data on 2745 dementia-free persons aged 60+ from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression (minor and major) was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; subsyndromal depression (SSD) was operationalised as the presence of ≥2 symptoms without depression. Multistate survival models were used to map depression transitions, including death, and to examine the association of psychosocial (social network, connection and support), lifestyle (smoking, alcohol consumption and physical activity) and clinical (somatic disease count) factors with transition patterns.

Over the follow-up, 19.1% had ≥1 transitions across depressive states, while 6.5% had ≥2. Each additional somatic disease was associated with a higher hazard of progression from no depression (No Dep) to SSD (hazard ratio 1.09; 1.07–1.10) and depression (Dep) (hazard ratio 1.06; 1.04–1.08), but also with a lower recovery (HRSSD−No Dep 0.95; 0.93–0.97 [where ‘HR’ refers to ‘hazard ratio’]; HRDep−No Dep 0.96; 0.93–0.99). Physical activity was associated with an increased hazard of recovery to no depression from SSD (hazard ratio 1.49; 1.28–1.73) and depression (hazard ratio 1.20; 1.00–1.44), while a richer social network was associated with both higher recovery from (HRSSD−No Dep 1.44; 1.26–1.66; HRDep−No Dep 1.51; 1.34–1.71) and lower progression hazards to a worse depressive state (HRNo Dep−SSD 0.81; 0.70–0.94; HRNo Dep−Dep 0.58; 0.46–0.73; HRSSD−Dep 0.66; 0.44–0.98).

Older people may present with heterogeneous depressive trajectories. Targeting the accumulation of somatic diseases and enhancing social interactions may be appropriate for both depression prevention and burden reduction, while promoting physical activity may primarily benefit recovery from depressive disorders.

Concern that self-harm and mental health conditions are increasing in university students may reflect widening access to higher education, existing population trends and/or stressors associated with this setting.

To compare population-level data on self-harm, neurodevelopmental and mental health conditions between university students and non-students with similar characteristics before and during enrolment.

This cohort study linked electronic records from the Higher Education Statistics Agency for 2012–2018 to primary and secondary healthcare records. Students were undergraduates aged 18 to 24 years at university entry. Non-students were pseudo-randomly selected based on an equivalent age distribution. Logistic regressions were used to calculate odds ratios. Poisson regressions were used to calculate incidence rate ratios (IRR).

The study included 96 760 students and 151 795 non-students. Being male, self-harm and mental health conditions recorded before university entry, and higher deprivation levels, resulted in lower odds of becoming a student and higher odds of drop-out from university. IRRs for self-harm, depression, anxiety, autism spectrum disorder (ASD), drug use and schizophrenia were lower for students. IRRs for self-harm, depression, attention-deficit hyperactivity disorder, ASD, alcohol use and schizophrenia increased more in students than in non-students over time. Older students experienced greater risk of self-harm and mental health conditions, whereas younger students were more at risk of alcohol use than non-student counterparts.

Mental health conditions in students are common and diverse. While at university, students require person-centred stepped care, integrated with local third-sector and healthcare services to address specific conditions.

Individuals with schizophrenia face high mortality risks. The effects of lipid-modifying agents on this risk remain understudied.

This study was conducted to investigate the effects of lipid-modifying agents on mortality risk in people with schizophrenia.

This nationwide cohort study collected the data of people with schizophrenia from Taiwan's National Health Insurance Research Database for the period between 1 January 2001 and 31 December 2019. Multivariable Cox proportional hazards regression with a time-dependent model was used to estimate the hazard ratio for mortality associated with each lipid-modifying agent.

This study included 110 300 people with schizophrenia. Of them, 22 528 died (19 754 from natural causes and 1606 from suicide) during the study period, as confirmed using data from Taiwan's national mortality database. The use of lipid-modifying agents was associated with reduced risks of all-cause (adjusted hazard ratio [aHR]:0.37; P < 0.001) and natural (aHR:0.37; P < 0.001) mortality during a 5-year period. Among the lipid-modifying agents, statins and fibrates were associated with reduced risks of all-cause mortality (aHRs:0.37 and 0.39, respectively; P < 0.001 for both) and natural mortality (aHRs: 0.37 and 0.42, respectively; P < 0.001 for both). Notably, although our univariate analysis indicated an association between the use of lipid-modifying agents and a reduced risk of suicide mortality, the multivariate analysis revealed no significant association.

Lipid-modifying agents, particularly statins and fibrates, reduce the risk of mortality in people with schizophrenia. Appropriate use of lipid-modifying agents may bridge the mortality gap between these individuals and the general population.

Urbanisation is taking place worldwide and rates of mental illness are rising. There has been increasing interest in ‘nature’ and how it may benefit mental health and well-being.

To understand how the literature defines nature; what the characteristics of the nature intervention are; what mental health and well-being outcomes are being measured; and what the evidence shows, in regard to how nature affects the mental health and well-being of children and adolescents.

A meta-review was conducted, searching three databases for relevant primary and secondary studies, using key search terms including ‘nature’ and ‘mental health’ and ‘mental well-being’. Inclusion criteria included published English-language studies on the child and adolescent population. Authors identified the highest quality evidence from studies meeting the inclusion criteria. Data were extracted and analysed using descriptive content analysis.

Sixteen systematic reviews, two scoping reviews and five good quality cohort studies were included. ‘Nature’ was conceptualised along a continuum (the ‘nature research framework’) into three categories: a human-designed environment with natural elements; a human-designed natural environment; and a natural environment. The nature ‘intervention’ falls into three areas (the ‘nature intervention framework’): access, exposure and engagement with nature, with quantity and quality of nature relevant to all areas. Mental health and well-being outcomes fit along a continuum, with ‘disorder’ at one end and ‘well-being’ at the other. Nature appears to have a beneficial effect, but we cannot be certain of this.

Nature appears to have a beneficial effect on mental health and well-being of children and adolescents. Evidence is lacking on clinical populations, ethnically diverse populations and populations in low- and middle-income countries. Our results should be interpreted considering the limitations of the included studies and confidence in findings.