Social cohesion is defined as the sense of belonging, solidarity and shared values within a group. Although the terms "social capital" and "social cohesion" are sometimes used interchangeably, strictly speaking the former refers to the resources embedded in social relations - such as trust and norms of cooperation - which then create social cohesion. Social cohesion has been studied as a predictor of mental health in residential communities, schools and workplaces. Taking a life-course perspective, this paper reviews the empirical evidence linking social cohesion to common mental disorders, psychosis, suicidality and substance misuse. Consistent evidence is found for a protective association between social cohesion and common mental disorders, suicidality and substance misuse. Findings are mixed for psychosis. Hypothetical pathways explaining the link between social cohesion and mental health include that: a) living in a cohesive community promotes neighborly interactions which may reduce residents' risk of becoming socially isolated; b) social cohesion buffers the deleterious effects of adversity; and c) social cohesion lowers crime and increases safety perceptions. Important gaps remain in the literature, including the need for improved measurement (greater consistency in the use of indicators to measure social cohesion, developing measures to capture bridging social capital, and enhancing the validity of multi-item instruments via application of item-response theory); the need to strengthen causal inference; and the need for participatory intervention studies that demonstrate how social cohesion can be intentionally generated, and for whom it can be beneficial. Investing in the strengthening of social cohesion represents an asset-based approach to mental health promotion. In contrast to a deficits-based approach (such as efforts targeting loneliness or social isolation), increased attention to social cohesion can be viewed as targeting an upstream driver of both social isolation and loneliness, as well as an independent determinant of population mental health.
Anxiety disorders are the most prevalent mental health conditions worldwide. While their burden in terms of excess mortality is known to be high, a quantitative systematic evaluation of all-cause and cause-specific mortality and suicide attempt risks in people with anxiety or stress-related disorders is lacking. We performed a systematic review and random effects meta-analysis, in which co-primary outcomes were risk ratios (RRs) for all-cause and suicide-related mortality, and secondary outcomes were natural-cause mortality, other cause-specific mortality, and risk of suicide attempt. Sensitivity and meta-regression analyses were conducted. Overall, 165 studies encompassing 7,395,722 people with any anxiety or stress-related disorder and 135,059,023 controls, from 27 different countries across all continents, were included. Compared with the general population, a higher risk of all-cause mortality was associated with any anxiety or stress-related disorder (n=42, RR=1.54, 95% CI: 1.14-2.08, p=0.005), generalized anxiety disorder (n=9, RR=1.48, 95% CI: 1.23-1.78, p<0.001), and post-traumatic stress disorder (PTSD) and other stress-related disorders (n=21, RR=1.39, 95% CI: 1.15-1.67, p<0.001), but not with panic disorder, phobias, and mixed anxiety or stress-related disorders. Suicide mortality was increased in people with any anxiety or stress-related disorder (n=39, RR=2.88, 95% CI: 2.13-3.89, p<0.001), panic disorder (n=3, RR=3.58, 95% CI: 1.39-9.25, p<0.008), mixed anxiety or stress-related disorders (n=27, RR=2.77, 95% CI: 1.89-4.07, p<0.001), PTSD and other stress-related disorders (n=11, RR=3.13, 95% CI: 1.85-5.28, p<0.001), and generalized anxiety disorder (n=3, RR=1.93, 95% CI: 1.17-3.17, p<0.01). Suicide attempt risk was higher than in the general population in people with all anxiety or stress-related disorders, ranging from RR=6.33 (95% CI: 4.08-9.82, n=5) in panic disorder to RR=2.74 (95% CI: 1.72-4.35, n=5) in phobias. Natural-cause mortality was increased in any anxiety or stress-related disorder (n=19, RR=1.25, 95% CI: 1.09-1.44, p=0.002), generalized anxiety disorder (n=5, RR=1.55, 95% CI: 1.19-2.02, p=0.001), mixed anxiety or stress-related disorders (n=8, RR=1.26, 95% CI: 1.02-1.56, p=0.033), and PTSD and other stress-related disorders (n=9, RR=1.17, 95% CI: 1.03-1.33, p=0.019), but not in panic disorder. Cardiovascular-related deaths were increased in any and mixed anxiety or stress-related disorders and in generalized anxiety disorder, while cancer mortality was increased only in generalized anxiety disorder. When analyzing people with vs. without anxiety disorders with samples being matched by comorbid physical or mental disorders, results remained significant for all-cause mortality in generalized anxiety disorder and panic disorder, but not in any or mixed anxiety or stress-related disorders, and in PTSD and stress-related disorders. When compared with other mental disorders, no difference in co-primary outcomes emerged from more than two studies. Publication bias was present across several analyses, but sensitivity analyses largely confirmed the main findings. In meta-regression analyses, more recent data collection mitigated all-cause mortality, while schizophrenia-spectrum and bipolar disorder comorbidity mitigated suicide mortality risk, possibly driven by underlying treatment. This meta-analysis documents a higher all-cause, suicide and natural-cause mortality, and a higher risk of suicide attempt, in people with anxiety or stress-related disorders compared to the general population. Given the high prevalence and the recognized global treatment gap for these disorders, this finding is of great public health concern, and calls for appropriate prevention, screening and treatment strategies. More studies are needed to fill the publication bias gap and to identify modifiable risk or mitigating factors.
Most research into the clinical high risk for psychosis (CHR-P) state has focused on predicting transition to psychosis in the short term, and largely in research samples that are not representative of real-world preventive care. However, CHR-P individuals experience a broad range of poor long-term clinical outcomes in real-world settings, such as hospitalization for psychiatric reasons, initiation of a new antipsychotic treatment, or suicide. Improving the detection of individuals at greater risk of these long-term poor outcomes is critical to advance preventive care in real-world clinical settings. This study aims to develop and internally validate a personalized clinical prediction model for real-world, long-term poor outcomes beyond transition risk in CHR-P individuals. This RECORD-compliant, real-world, long-term prospective cohort study included electronic health records (EHR) data from all CHR-P individuals receiving preventive care from the Outreach and Support in South London (OASIS) service in South London and Maudsley National Health Service Foundation Trust in the UK from 2001 to 2024. The primary outcome was the long-term cumulative risk of first real-world poor outcome, operationalized by pragmatic parameters informing clinical practice: transition to psychosis, receiving a first antipsychotic treatment at a dosage necessary to treat first-episode psychosis, receiving a first voluntary or compulsory hospitalization for psychiatric reasons, or dying by suicide. A clinical prediction model (regularized Cox regression) was developed and validated using internal-external cross-validation to predict long-term poor outcomes, utilizing real-world predictors available in routine care. Model performance was indexed by discrimination (Harrell's C), calibration (slope, intercept), overall performance (Brier score), and potential clinical utility (decision curve analysis). One thousand CHR-P OASIS patients were included (mean age: 22.51±4.99 years; 53.60% males, 44.73% White) and followed up to a maximum of 21 years. The cumulative risk of real-world poor outcome was 0.644 (95% CI: 0.547-0.742) at 14-18 years. The validated clinical prediction model showed statistically significant discrimination (C=0.69; 95% CI: 0.63-0.74), calibration (slope = 1.61, 95% CI: 0.74-2.48; intercept = -0.03, 95% CI: -0.62 to 0.55) and overall performance (Brier score = 0.18; 95% CI: 0.13-0.22). Decision curve analysis demonstrated that the model was associated with greater net benefit than the clinical alternatives at risk thresholds from 0% to 50%. These data suggest that most CHR-P individuals have long-term poor outcomes, beyond transition to psychosis, in real-world care, which should become the focus of a new generation of research. The clinical prediction model presented here can identify these individuals and facilitate the personalized provision of preventive care, thereby improving outcomes in this population. CHR-P services should extend their duration of care to address the substantial long-term clinical outcomes experienced by young individuals.
It is estimated that, globally, the mean point prevalence of diagnosable mental disorders in children and adolescents is higher than 11%, and around half of cases of major mental disorders have their onset before the age of 18. Mental disorders with onset in childhood or adolescence have an enormous impact on the developing brain, body and personal identity, as well as on the short- and long-term social, educational and functional capacity of individuals. Child and adolescent psychiatry - as a discipline, profession, academic field, and network of clinical services - is still relatively young, with its formal evolution beginning in the 20th century. Therefore, it is not surprising that there are currently many challenges, but also opportunities and expected future developments, in this area. In this paper, we identify and address the core challenges, possible solutions, opportunities, and future directions of child and adolescent psychiatry. In the first part of the paper, challenges and possible solutions are discussed regarding diagnostic issues, stigma, access to care, shortage of mental health professionals, evidence-based treatments, treatment adherence, parental participation/engagement, integration with schools, digital influences and cyberbullying, and war/forced displacement. In the second part, opportunities and developments are addressed that relate to early identification and intervention, resilience, interdisciplinary collaborations, integration with primary care, community-based approaches, use of digital technologies, precision child and adolescent psychiatry, artificial intelligence and related ethical issues, and cultural diversity and competences. Despite the significance and impact of mental disorders in children and adolescents, clinical delivery and research on these conditions remain underfunded and underprioritized, even in high-income countries, with clinical services and prevention/early intervention research receiving minimal investment. Addressing mental health in children and young people requires multi-level strategies beyond individual treatment, including tackling structural and socioeconomic barriers and creating opportunities for strengthening resilience and well-being. A well-trained workforce, adequate policies, and increased public awareness are crucial. Overall, the current gaps demand urgent action and global funding rebalancing to more adequately meet the critical needs of children and young people challenged by mental illness.
We sought to clarify the inter-relationships among a range of psychiatric and substance use disorders by employing two-dimensional genetic maps, with axes defined by family genetic risk for major depression (MD) and drug use disorder (DUD). Using comprehensive Swedish national register data, we located cases of 12 disorders within this space and examined how their genetic risk profiles varied as a function of sex, age at onset, and level of recurrence. Disorders segregated robustly into two clusters. Internalizing disorders were characterized by moderate genetic liability for MD and low liability for DUD, while externalizing disorders displayed substantial risk for both genetic dimensions. These patterns were replicated across regions of Sweden. Post-traumatic stress disorder (PTSD) grouped with the internalizing cluster, whereas borderline personality disorder aligned with the externalizing group. Sex differences in genetic liability were common and frequently involved both axes: typically, the sex with the lower disorder prevalence carried higher genetic risk, with the most striking contrasts observed for alcohol use disorder (AUD) and DUD. Across most disorders, earlier age at onset was associated with elevated genetic liability, with particularly strong effects for AUD, MD and PTSD. Similarly, high level of recurrence consistently indexed increased genetic risk, often spanning both axes, with notable prominence for AUD, DUD, MD and PTSD. Taken together, these findings suggest that the genetic liabilities underlying psychiatric and substance use disorders are not fixed entities but vary systematically with key clinical features. Considering multiple genetic risks simultaneously provides an informative framework for understanding cross-disorder relationships between psychiatric disorders.
