Making cities mental health friendly for adolescents and young adults.

Urban life shapes the mental health of city dwellers, and although cities provide access to health, education and economic gain, urban environments are often detrimental to mental health1,2. Increasing urbanization over the next three decades will be accompanied by a growing population of children and adolescents living in cities3. Shaping the aspects of urban life that influence youth mental health could have an enormous impact on adolescent well-being and adult trajectories4. We invited a multidisciplinary, global group of researchers, practitioners, advocates and young people to complete sequential surveys to identify and prioritize the characteristics of a mental health-friendly city for young people. Here we show a set of ranked characteristic statements, grouped by personal, interpersonal, community, organizational, policy and environmental domains of intervention. Life skills for personal development, valuing and accepting young people's ideas and choices, providing safe public space for social connection, employment and job security, centring youth input in urban planning and design, and addressing adverse social determinants were priorities by domain. We report the adversities that COVID-19 generated and link relevant actions to these data. Our findings highlight the need for intersectoral, multilevel intervention and for inclusive, equitable, participatory design of cities that support youth mental health.

Smartphones and the Neuroscience of Mental Health.

Improvements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal data sets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness.

Mental health concerns during the COVID-19 pandemic as revealed by helpline calls.

Mental health is an important component of public health, especially in times of crisis. However, monitoring public mental health is difficult because data are often patchy and low-frequency1-3. Here we complement established approaches by using data from helplines, which offer a real-time measure of 'revealed' distress and mental health concerns across a range of topics4-9. We collected data on 8 million calls from 19 countries, focusing on the COVID-19 crisis. Call volumes peaked six weeks after the initial outbreak, at 35% above pre-pandemic levels. The increase was driven mainly by fear (including fear of infection), loneliness and, later in the pandemic, concerns about physical health. Relationship issues, economic problems, violence and suicidal ideation, however, were less prevalent than before the pandemic. This pattern was apparent both during the first wave and during subsequent COVID-19 waves. Issues linked directly to the pandemic therefore seem to have replaced rather than exacerbated underlying anxieties. Conditional on infection rates, suicide-related calls increased when containment policies became more stringent and decreased when income support was extended. This implies that financial relief can allay the distress triggered by lockdown measures and illustrates the insights that can be gleaned from the statistical analysis of helpline data.

Sex and mental health are related to subcortical brain microstructure.

Some mental health problems such as depression and anxiety are more common in females, while others such as autism and attention deficit/hyperactivity (AD/H) are more common in males. However, the neurobiological origins of these sex differences are poorly understood. Animal studies have shown substantial sex differences in neuronal and glial cell structure, while human brain imaging studies have shown only small differences, which largely reflect overall body and brain size. Advanced diffusion MRI techniques can be used to examine intracellular, extracellular, and free water signal contributions and provide unique insights into microscopic cellular structure. However, the extent to which sex differences exist in these metrics of subcortical gray matter structures implicated in psychiatric disorders is not known. Here, we show large sex-related differences in microstructure in subcortical regions, including the hippocampus, thalamus, and nucleus accumbens in a large sample of young adults. Unlike conventional T1-weighted structural imaging, large sex differences remained after adjustment for age and brain volume. Further, diffusion metrics in the thalamus and amygdala were associated with depression, anxiety, AD/H, and antisocial personality problems. Diffusion MRI may provide mechanistic insights into the origin of sex differences in behavior and mental health over the life course and help to bridge the gap between findings from experimental, epidemiological, and clinical mental health research.

The causal effect of mental health on labor market outcomes: The case of stress-related mental disorders following a human-made disaster.

As disasters increase due to climate change, population density, epidemics, and technology, information is needed about postdisaster consequences for people's mental health and how stress-related mental disorders affect multiple spheres of life, including labor-market attachment. We tested the causal hypothesis that individuals who developed stress-related mental disorders as a consequence of their disaster exposure experienced subsequent weak labor-market attachment and poor work-related outcomes. We leveraged a natural experiment in an instrumental variables model, studying a 2004 fireworks factory explosion disaster that precipitated the onset of stress-related disorders (posttraumatic stress disorder, anxiety, and depression) among individuals in the local community (N = 86,726). We measured labor-market outcomes using longitudinal population-level administrative data: sick leave, unemployment benefits, early retirement pension, and income from wages from 2007 to 2010. We found that individuals who developed a stress-related disorder after the disaster were likely to go on sickness benefit, both in the short- and long-term, were likely to use unemployment benefits and to lose wage income in the long term. Stress-related disorders did not increase the likelihood of early retirement. The natural experiment design minimized the possibility that omitted confounders biased these effects of mental health on work outcomes. Addressing the mental health and employment needs of survivors after a traumatic experience may improve their labor-market outcomes and their nations' economic outputs.

Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.

Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.

Generational differences in mental health trends in the twenty-first century.

Given the observed deterioration in mental health among Australians over the past decade, this study investigates to what extent this differs in people born in different decades-i.e., possible birth cohort differences in the mental health of Australians. Using 20 y of data from a large, nationally representative panel survey (N = 27,572), we find strong evidence that cohort effects are driving the increase in population-level mental ill-health. Deteriorating mental health is particularly pronounced among people born in the 1990s and seen to a lesser extent among the 1980s cohort. There is little evidence that mental health is worsening with age for people born prior to the 1980s. The findings from this study highlight that it is the poorer mental health of Millennials that is driving the apparent deterioration in population-level mental health. Understanding the context and changes in society that have differentially affected younger people may inform efforts to ameliorate this trend and prevent it continuing for emerging cohorts.

Differential spatial-social accessibility to mental health care and suicide.

In recent years, the United States has been experiencing historically high suicide rates. In the face of mental health care provider shortages that leave millions needing to travel longer to find providers with schedule openings, if any are available at all, the inaccessibility of mental health care has become increasingly central in explaining suicidality. To examine the relationship between access to care and suicide, we leverage a dataset mapping all licensed US psychiatrists and psychotherapists (N= 711,214), as of early 2020, and employ real-world transportation data to model patients' mobility barriers. We find a strong association between reduced mental health care provider spatial-social accessibility and heightened suicide risk. Using a machine learning approach to condition on a host of 22 contextual factors known to be implicated in suicide (e.g., race, education, divorce, gun shop prevalence), we find that in locales where individuals seeking care can access fewer mental health care providers, already more likely to be saturated by demand, suicide risk is increased (3.2% for each reduced SD of psychiatrist accessibility; 2.3% for psychotherapists). Additionally, we observe that local spatial-social accessibility inequalities are associated with further heightened risk of suicide, underscoring the need for research to account for the highly localized barriers preventing many Americans from accessing needed mental health services.

Fostering Psychological Safety and Supporting Mental Health Among Cardiovascular Health Care Workers: A Science Advisory From the American Heart Association.

The psychological safety of health care workers is an important but often overlooked aspect of the rising rates of burnout and workforce shortages. In addition, mental health conditions are prevalent among health care workers, but the associated stigma is a significant barrier to accessing adequate care. More efforts are therefore needed to foster health care work environments that are safe and supportive of self-care. The purpose of this brief document is to promote a culture of psychological safety in health care organizations. We review ways in which organizations can create a psychologically safe workplace, the benefits of a psychologically safe workplace, and strategies to promote mental health and reduce suicide risk.

Gene copy number variation and pediatric mental health/neurodevelopment in a general population.

We assessed the relationship of gene copy number variation (CNV) in mental health/neurodevelopmental traits and diagnoses, physical health and cognition in a community sample of 7100 unrelated children and youth of European or East Asian ancestry (Spit for Science). Clinically significant or susceptibility CNVs were present in 3.9% of participants and were associated with elevated scores on a continuous measure of attention-deficit/hyperactivity disorder (ADHD) traits (P = 5.0 × 10-3), longer response inhibition (a cognitive deficit found in several mental health and neurodevelopmental disorders; P = 1.0 × 10-2) and increased prevalence of mental health diagnoses (P = 1.9 × 10-6, odds ratio: 3.09), specifically ADHD, autism spectrum disorder anxiety and learning problems/learning disorder (P's < 0.01). There was an increased burden of rare deletions in gene-sets related to brain function or expression in brain associated with more ADHD traits. With the current mental health crisis, our data established a baseline for delineating genetic contributors in pediatric-onset conditions.

Promoting good mental health over the menopause transition.

The potential risk for mental health conditions over the menopause transition shapes women's expectations and informs putative physiological mechanisms regulating women's mental health. We review evidence from prospective studies reporting on associations between mental health conditions and the menopause transition. Major depressive disorder and the more prevalent subthreshold depressive symptoms are the most common conditions studied. We reviewed 12 prospective studies reporting depressive symptoms, major depressive disorder, or both over the menopause transition and found no compelling evidence for a universal increased risk for either condition. However, specific subgroups of participants, primarily defined by menopause-related risk factors (ie, vasomotor symptoms that are severe or disturb sleep, a long duration of the transition, or reproductive hormone dynamics) and psychosocial risk factors (eg, stressful life events), were vulnerable to depressive symptoms. The increased risk of major depressive disorder over the menopause transition appears predominantly in individuals with previous major depressive disorder. Greater focus on recognising risk factors in primary care is warranted. On the basis of scarce data, we found no compelling evidence that risk of anxiety, bipolar disorder, or psychosis is universally elevated over the menopause transition. Potential misattribution of psychological distress and psychiatric disorders to menopause could harm women by delaying accurate diagnosis and the initiation of effective psychotropic treatments, and by creating negative expectations for people approaching menopause. A paradigm shift is needed. We conclude with recommendations for the detection and treatment of depressive symptoms or major depressive disorder and strategies to promote good mental health over the menopause transition, while responsibly preparing and supporting those at risk.

Prevalence of adolescent mental disorders in Kenya, Indonesia, and Viet Nam measured by the National Adolescent Mental Health Surveys (NAMHS): a multi-national cross-sectional study.

BACKGROUND: Mental disorders are the leading global cause of health burden among adolescents. However, prevalence data for mental disorders among adolescents in low-income and middle-income countries are scarce with often limited generalisability. This study aimed to generate nationally representative prevalence estimates for mental disorders in adolescents in Kenya, Indonesia, and Viet Nam. METHODS: As part of the National Adolescent Mental Health Surveys (NAMHS), a multinational cross-sectional study, nationally representative household surveys were conducted in Kenya, Indonesia, and Viet Nam between March and December, 2021. Adolescents aged 10-17 years and their primary caregiver were interviewed from households selected randomly according to sampling frames specifically designed to elicit nationally representative results. Six mental disorders (social phobia, generalised anxiety disorder, major depressive disorder, post-traumatic stress disorder, conduct disorder, and attention-deficit hyperactivity disorder) were assessed with the Diagnostic Interview Schedule for Children, Version 5. Suicidal behaviours and self-harm in the past 12 months were also assessed. Prevalence in the past 12 months and past 4 weeks was calculated for each mental disorder and collectively for any mental disorder (ie, of the six mental disorders assessed). Prevalence of suicidal behaviours (ie, ideation, planning, and attempt) and self-harm in the past 12 months was calculated, along with adjusted odds ratios (aORs) to show the association with prevalence of any mental disorder in the past 12 months. Inverse probability weighting was applied to generate national estimates with corresponding 95% CIs. FINDINGS: Final samples consisted of 5155 households (ie, adolescent and primary caregiver pairs) from Kenya, 5664 households from Indonesia, and 5996 households from Viet Nam. In Kenya, 2416 (46·9%) adolescents were male and 2739 (53·1%) were female; in Indonesia, 2803 (49·5%) adolescents were male and 2861 (50·5%) were female; and in Viet Nam, 3151 (52·5%) were male and 2845 (47·4%) were female. Prevalence of any mental disorder in the past 12 months was 12·1% (95% CI 10·9-13·5) in Kenya, 5·5% (4·3-6·9) in Indonesia, and 3·3% (2·7-4·1) in Viet Nam. Prevalence in the past 4 weeks was 9·4% (8·3-10·6) in Kenya, 4·4% (3·4-5·6) in Indonesia, and 2·7% (2·2-3·3) in Viet Nam. The prevalence of suicidal behaviours in the past 12 months was low in all three countries, with suicide ideation ranging from 1·4% in Indonesia (1·0-2·0) and Viet Nam (1·0-1·9) to 4·6% (3·9-5·3) in Kenya, suicide planning ranging from 0·4% in Indonesia (0·3-0·8) and Viet Nam (0·2-0·6) to 2·4% (1·9-2·9) in Kenya, and suicide attempts ranging from 0·2% in Indonesia (0·1-0·4) and Viet Nam (0·1-0·3) to 1·0% (0·7-1·4) in Kenya. The prevalence of self-harm in the past 12 months was also low in all three countries, ranging from 0·9% (0·6-1·3) in Indonesia to 1·2% (0·9-1·7) in Kenya. However, the prevalence of suicidal behaviours and self-harm in the past 12 months was significantly higher among those with any mental disorder in the past 12 months than those without (eg, aORs for suicidal ideation ranged from 7·1 [3·1-15·9] in Indonesia to 14·7 [7·5-28·6] in Viet Nam). INTERPRETATION: NAMHS provides the first national adolescent mental disorders prevalence estimates for Kenya, Indonesia, and Viet Nam. These data can inform mental health and broader health policies in low-income and middle-income countries. FUNDING: The University of Queensland in America (TUQIA) through support from Pivotal Ventures, a Melinda French Gates company.

Clinical effectiveness of the psychological therapy Mental Health Intervention for Children with Epilepsy in addition to usual care compared with assessment-enhanced usual care alone: a multicentre, randomised controlled clinical trial in the UK.

BACKGROUND: Mental health difficulties are common in children and young people with chronic health conditions, but many of those in need do not access evidence-based psychological treatments. The study aim was to evaluate the clinical effectiveness of integrated mental health treatment for children and young people with epilepsy, a common chronic health condition known to be associated with a particularly high rate of co-occurring mental health difficulties. METHODS: We conducted a parallel group, multicentre, open-label, randomised controlled trial of participants aged 3-18 years, attending epilepsy clinics across England and Northern Ireland who met diagnostic criteria for a common mental health disorder. Participants were randomised (1:1; using an independent web-based system) to receive the Mental Health Intervention for Children with Epilepsy (MICE) in addition to usual care, or assessment-enhanced usual care alone (control). Children and young people in both groups received a full diagnostic mental health assessment. MICE was a modular psychological intervention designed to treat common mental health conditions in children and young people using evidence-based approaches such as cognitive behaviour therapy and behavioural parenting strategies. Usual care for mental health disorders varied by site but typically included referral to appropriate services. Participants, along with their caregivers, and clinicians were not masked to treatment allocation but statisticians were masked until the point of analysis. The primary outcome, analysed by modified intention-to-treat, was the parent-report Strengths and Difficulties Questionnaire (SDQ) at 6 months post-randomisation. The study is complete and registered with ISRCTN (57823197). FINDINGS: 1401 young people were potentially deemed eligible for study inclusion. Following the exclusion of 531 young people, 870 participants were assessed for eligibility and completed the SDQ, and 480 caregivers provided consent for study inclusion between May 20, 2019, and Jan 31, 2022. Between Aug 28, 2019, and Feb 21, 2022, 334 participants (mean ages 10·5 years [SD 3·6] in the MICE group vs 10·3 [4·0] in control group at baseline) were randomly assigned to an intervention using minimisation balanced by age, primary mental health disorder, diagnosis of intellectual disability, and autistic spectrum disorder at baseline. 168 (50%) of the participants were female and 166 (50%) were male. 166 participants were randomly assigned to the MICE group and 168 were randomly assigned to the control group. At 6 months, the mean SDQ difficulties for the 148 participants in the MICE group was 17·6 (SD 6·3) and 19·6 (6·1) for the 148 participants in the control group. The adjusted effect of MICE was -1·7 (95% CI -2·8 to -0·5; p=0·0040; Cohen's d, 0·3). 14 (8%) patients in the MICE group experienced at least one serious adverse event compared with 24 (14%) in the control group. 68% percent of serious adverse events (50 events) were admission due to seizures. INTERPRETATION: MICE was superior to assessment-enhanced usual care in improving symptoms of emotional and behavioural difficulties in young people with epilepsy and common mental health disorders. The trial therefore shows that mental health comorbidities can be effectively and safely treated by a variety of clinicians, utilising an integrated intervention across ages and in the context of intellectual disability and autism. The evidence from this trial suggests that such a model should be fully embedded in epilepsy services and serves as a model for other chronic health conditions in young people. FUNDING: UK National Institute for Health Research Programme Grants for Applied Research programme and Epilepsy Research UK Endeavour Project Grant.

A Bayesian nonparametric approach for multiple mediators with applications in mental health studies.

Mediation analysis with contemporaneously observed multiple mediators is a significant area of causal inference. Recent approaches for multiple mediators are often based on parametric models and thus may suffer from model misspecification. Also, much of the existing literature either only allow estimation of the joint mediation effect or estimate the joint mediation effect just as the sum of individual mediator effects, ignoring the interaction among the mediators. In this article, we propose a novel Bayesian nonparametric method that overcomes the two aforementioned drawbacks. We model the joint distribution of the observed data (outcome, mediators, treatment, and confounders) flexibly using an enriched Dirichlet process mixture with three levels. We use standardization (g-computation) to compute all possible mediation effects, including pairwise and all other possible interaction among the mediators. We thoroughly explore our method via simulations and apply our method to a mental health data from Wisconsin Longitudinal Study, where we estimate how the effect of births from unintended pregnancies on later life mental depression (CES-D) among the mothers is mediated through lack of self-acceptance and autonomy, employment instability, lack of social participation, and increased family stress. Our method identified significant individual mediators, along with some significant pairwise effects.

The role of environmental sensitivity in the mental health of Syrian refugee children: a multi-level analysis.

Individuals with high environmental sensitivity have nervous systems that are disproportionately receptive to both the protective and imperilling aspects of the environment, suggesting their mental health is strongly context-dependent. However, there have been few consolidated attempts to examine putative markers of sensitivity, across different levels of analysis, within a single cohort of individuals with high-priority mental health needs. Here, we examine psychological (self-report), physiological (hair hormones) and genetic (polygenic scores) markers of sensitivity in a large cohort of 1591 Syrian refugee children across two waves of data. Child-caregiver dyads were recruited from informal tented settlements in Lebanon, and completed a battery of psychological instruments at baseline and follow-up (12 months apart). Univariate and multivariate Bayesian linear mixed models were used to examine a) the interrelationships between markers of sensitivity and b) the ability of sensitivity markers to predict anxiety, depression, post-traumatic stress disorder, and externalising behaviour. Self-reported sensitivity (using the Highly Sensitive Child Scale) significantly predicted a higher burden of all forms of mental illness across both waves, however, there were no significant cross-lagged pathways. Physiological and genetic markers were not stably predictive of self-reported sensitivity, and failed to similarly predict mental health outcomes. The measurement of environmental sensitivity may have significant implications for identifying and treating mental illness, especially amongst vulnerable populations, but clinical utility is currently limited to self-report assessment.