Opioid use disorder (OUD) is a medical condition associated with problematic opioid use, leading to addiction and severe life impairments. This research delivers an in-depth evaluation of OUD burden and trends at global, regional and national levels.

This study analysed the global burden of OUD from 1990 to 2021 using data from the 2021 Global Burden of Diseases, Injuries, and Risk Factors Study. Key metrics included age-standardized prevalence, incidence, mortality and disability-adjusted life years (DALYs), disaggregated by gender, age, region, country and socio-demographic index (SDI) quintiles. The average annual percentage change described trends, while the age-period-cohort model evaluated age, period and cohort effects. A Bayesian Age-period-cohort model predicted future OUD trends from 2022 to 2040.

In 2021, the global burden of OUD remained substantial, with a total of 16,164,876 cases and a prevalence of 154.59 cases per 100,000 population (95% uncertainty interval [UI]: 131.06–181.26). In 2021, the global incidence of OUD reached 1,942,525 cases (95% UI: 1,643,342–2,328,363), and its global mortality reached 99,555 deaths (95% UI: 92,948–108,050), with DALYs amounting to 11,218,519 (95% UI: 9,188,658–13,159,551). Regionally, high SDI regions, particularly in the High-income North America, exhibited the greatest burden. Among countries, the United States faced the most severe burden and increase, with the highest prevalence (2014.62 per 100,000), incidence (151.84 per 100,000), mortality (15.37 per 100,000) and DALYs (1594.63 per 100,000), and all APPC values exceeding 5%. Males aged 20–39 years were the most affected demographic. However, forecasts indicate that the OUD burden among females will significantly increase over the next 20 years, with the prevalence and incidence expected to rise by 39% and 49%, respectively.

The global burden of OUD has statistically significantly increased from 1990 to 2021. There are marked disparities across regions, countries and SDI levels. High-SDI regions, particularly High-income North America, bear the heaviest burden, with young males (aged 20–39 years) being the most affected groups. However, caution should be exercised regarding the female population, as the number of affected individuals is rapidly increasing.

Previous studies have estimated the lifetime incidence, age of onset and prevalence of mental disorders, but none have used nationwide data covering both primary and secondary care, even though mental disorders are commonly treated in primary care. We aimed to determine lifetime incidence, age-specific incidence, age of onset and service utilization for diagnosed mental disorders.

This register-based cohort study followed the entire population of Finland from 2000 to 2020. We estimated the cumulative incidence of diagnosed mental disorders with the Aalen–Johansen estimator, accounting for competing risks such as death and emigration. We also calculated age-specific incidence and 12-month service utilization as of 31 December 2019, providing diagnosis-, age- and gender-specific estimates.

We followed 6.4 million individuals for 98.5 million person-years. By age 100, lifetime incidence of any diagnosed mental disorder was 76.7% (95% CI, 76.6–76.7) in women and 69.7% (69.6–69.8) in men; in psychiatric secondary care, it was 39.7% (39.6–39.8) and 31.5% (31.4–31.6). At age 75, stricter estimates for non-organic disorders (ICD-10: F10–F99) were 65.6% (65.5–65.7) for women and 60.0% (59.9–60.1). Anxiety disorders (F40–F48) had the highest cumulative incidence. Median age of onset of non-organic mental disorders was 24.1 (interquartile range, 14.8–43.3 years) in women and 20.0 (interquartile range, 7.3–42.2 years) in men. Service utilization within 12 months was 9.0% for women and 7.7% for men.

Most, though not all, individuals experience at least one type of mental disorder, often during youth. Capturing the overall occurrence of mental disorders requires including both primary and secondary care data.

The literature on persistent antidepressant withdrawal symptoms is sparse. This systematic review is the first to examine the prevalence, duration, severity, risk/protective factors and treatment strategies for post-acute withdrawal syndrome (PAWS) following the discontinuation of antidepressant medications.

We searched PubMed, Web of Science and PsycInfo, focusing on newer-generation antidepressants. The electronic database search was complemented with handsearching reference lists of pivotal studies. We included original studies in adults reporting on PAWS and providing data about epidemiology and clinical management of withdrawal symptoms persisting for at least 6 weeks.

The literature search yielded 1286 results, with 26 records assessed for eligibility, and seven studies fulfilled our selection criteria. Prevalence data were sparse, with one small cohort study reporting a 15% prevalence rate for PAWS in patients with panic disorder and agoraphobia. The duration of PAWS varied considerably across studies, ranging from 1.5 to 166 months. Long-term paroxetine use emerged as a potential risk factor for the development of PAWS. There was no reliable evidence to support the effectiveness of various treatment strategies, including the reinstatement of antidepressant medication, the use of benzodiazepines and the provision of cognitive-behavioral therapy.

The current evidence on PAWS is sparse and predominantly of low certainty. The presence of withdrawal symptoms, lasting several months and possibly even years in some patients, underscores the need for further research with rigorous methodology. Large prospective cohort studies are needed to assess the epidemiology of PAWS, while randomized controlled trials are quired to test the efficacy of clinical interventions to treat PAWS.

CRD42023461793

Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs using data from a large prospective cohort of Spanish HCWs and (2) identify the most important variables in terms of contribution to the model’s predictive accuracy.

This is a prospective, multicentre cohort study of Spanish HCWs active during the COVID-19 pandemic. A total of 8,996 HCWs participated in the web-based baseline survey (May–July 2020) and 4,809 in the 4-month follow-up survey. A total of 219 predictor variables were derived from the baseline survey. The outcome variable was any STB at the 4-month follow-up. Variable selection was done using an L1 regularized linear Support Vector Classifier (SVC). A random forest model with 5-fold cross-validation was developed, in which the Synthetic Minority Oversampling Technique (SMOTE) and undersampling of the majority class balancing techniques were tested. The model was evaluated by the area under the Receiver Operating Characteristic (AUROC) curve and the area under the precision–recall curve. Shapley’s additive explanatory values (SHAP values) were used to evaluate the overall contribution of each variable to the prediction of future STBs. Results were obtained separately by gender.

The prevalence of STBs in HCWs at the 4-month follow-up was 7.9% (women = 7.8%, men = 8.2%). Thirty-four variables were selected by the L1 regularized linear SVC. The best results were obtained without data balancing techniques: AUROC = 0.87 (0.86 for women and 0.87 for men) and area under the precision–recall curve = 0.50 (0.55 for women and 0.45 for men). Based on SHAP values, the most important baseline predictors for any STB at the 4-month follow-up were the presence of passive suicidal ideation, the number of days in the past 30 days with passive or active suicidal ideation, the number of days in the past 30 days with binge eating episodes, the number of panic attacks (women only) and the frequency of intrusive thoughts (men only).

Machine learning-based prediction models for STBs in HCWs during the COVID-19 pandemic trained on web-based survey data present high discrimination and classification capacity. Future clinical implementations of this model could enable the early detection of HCWs at the highest risk for developing adverse mental health outcomes.

NCT04556565

Multimorbidity, especially physical–mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical–mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.

A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18–65years) residing in Liaoning Province, China, to evaluate the occurrence of physical–mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical–mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.

Physical–mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical–mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.

The physical–mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.

HOPE (National Institute for Health and Care Research Global Health Research Group on Homelessness and Mental Health in Africa) aims to develop and evaluate interventions that address the unmet needs of people who are homeless and have severe mental illness (SMI) living in three African countries in ways that are rights-based, contextually grounded, scalable and sustainable.

We will work in the capital city (Addis Ababa) in Ethiopia, a regional city (Tamale) in Ghana, and the capital city (Nairobi) and a rural county (Makueni) in Kenya to understand different approaches to intervention needed across varied settings.

We will be guided by the MRC/NIHR framework on complex interventions and implementation frameworks and emphasise co-production. Formative work will include synthesis of global evidence (systematic review, including grey literature, and a Delphi consensus exercise) on interventions and approaches to homelessness and SMI. We will map contexts; conduct focused ethnography to understand lived experiences of homelessness and SMI; carry out a cross-sectional survey of people who are homeless (n = 750 Ghana/Ethiopia; n = 350 Kenya) to estimate prevalence of SMI and identify prioritised needs; and conduct in-depth interviews and focus group discussions with key stakeholders to understand experiences, challenges and opportunities for intervention. This global and local evidence will feed into Theory of Change (ToC) workshops with stakeholders to establish agreement about valued primary outcomes, map pathways to impact and inform selection and implementation of interventions. Intervention packages to address prioritised needs will be co-produced, piloted and optimised for feasibility and acceptability using participatory action research. We will use rights-based approaches and focus on community-based care to ensure sustainability. Realist approaches will be employed to analyse how contextual variation affects mechanisms and outcomes to inform methods for a subsequent evaluation of larger scale implementation. Extensive capacity-strengthening activities will focus on equipping early career researchers and peer researchers. People with lived experience of SMI and policymakers are an integral part of the research team. Community engagement is supported by working closely with multisectoral Community Advisory Groups.

HOPE will develop evidence to support action to respond to the needs and preferences of people experiencing homelessness and SMI in diverse settings in Africa. We are creating a new partnership of researchers, policymakers, community members and people with lived experience of SMI and homelessness to enable African-led solutions. Key outputs will include contextually relevant practice and policy guidance that supports achievement of inclusive development.

A systematic review and meta-analysis was conducted to investigate the prevalence and antecedents/outcomes of loneliness and social isolation among individuals with severe mental disorders (SMD), such as schizophrenia, schizoaffective disorder, bipolar disorder or major depressive disorder.

Five well-known electronic databases (PubMed, PsycINFO, CINAHL, Web of Science and Scopus) were searched (plus a hand search). Observational studies that report the prevalence and, if available, antecedents and consequences of loneliness/isolation among individuals with SMD were included. Key characteristics were extracted, and a meta-analysis was performed. Our systematic review was preregistered on PROSPERO (ID: CRD42024559043). The PRISMA guidelines were followed. The Joanna Briggs Institute (JBI) standardized critical appraisal tool developed for prevalence studies was applied to assess the quality of the included studies.

The initial search yielded 4506 records, and after duplicate removal and screening, a total of 10 studies were finally included. The studies included used data from Europe, Asia, North America, and Oceania. Two studies employed a longitudinal design, while all other studies had a cross-sectional design. Most of the studies included between 100 and 500 individuals with SMD. All studies involved both male and female participants, with women typically comprising about 40% of the sample. The average age of participants often ranged from approximately 30 to 40 years. The estimated prevalence of loneliness was 59.1% (95% CI: 39.6% to 78.6%, I2 = 99.3, P < .001) among individuals with any diagnosis of SMD. Furthermore, the estimated prevalence of objective social isolation was 63.0% (95% CI: 58.6% to 67.4%) among individuals with schizophrenia or schizophrenia spectrum disorder. The quality of the studies was moderate to good. Subjective well-being and depressive symptoms in particular were found to contribute to loneliness in the included studies.

The present systematic review with meta-analysis identified high levels of loneliness and objective social isolation among those with SMD. These findings stress the importance of monitoring and addressing social needs in this vulnerable group, which may have a positive effect on the life quality of individuals with SMD. Future research in neglected regions (e.g. South America and Africa) is recommended. Different diagnoses within severe mental disorders should be distinguished in future studies. Furthermore, additional longitudinal studies are required to explore the antecedents and consequences of loneliness and social isolation among individuals with SMD.

Only little empirical evidence exists on mental health in LGBTIQ+ refugees. In the present study, trauma exposure, experiences of sexual violence and current treatment needs for physical and mental health were investigated in association with symptoms of anxiety, depression, post-traumatic stress disorder (PTSD) and somatic symptom burden in LGBTIQ+ asylum-seekers resettled in Germany and seeking psychosocial support.

Data was collected in cooperation with a counselling centre for LGBTIQ+ asylum-seekers between Mai 2018 and March 2024, with a total of 120 completed questionnaires of adult clients. The questionnaire (11 different languages) included sociodemographic and flight-related questions as well as standardized instruments for assessing PTSD (PCL-5), depression (PHQ-9), somatic symptom burden (SSS-8), and anxiety (HSCL-25). Prevalence rates were calculated according to the cut-off scores of each questionnaire. Four logistic regression analyses were conducted to test for potential associations between being screened positive for anxiety, depression, somatic symptom burden or PTSD and the number of traumatic events, experiences of sexual violence as well as current treatment needs for physical and mental health.

The great majority, 74.2% (95% CI: 66–82) of the respondents, screened positive for at least one of the mental disorders investigated, with 45% (95% CI: 36–54) suffering from somatic symptom burden, 44.2% (95% CI: 35–53) from depression, 58.3% (95% CI: 50–67) from PTSD, and 62.5% (95% CI: 54–71) from anxiety; 69.5% participants reported having been exposed to sexual violence. Current treatment needs for physical health problems were reported by 47% and for mental health problems by 56.7%. Participants with experiences of sexual violence were more likely to be screened positive for depression (OR: 6.787, 95% CI: 1.45–31.65) and PTSD (OR: 6.121, 95% CI: 1.34–27.95).

The study provides initial insights on mental health and associated factors in a highly burdened and hard-to-reach population. The findings are important for healthcare systems and political authorities in terms of assuring better protection and healthcare for LGBTIQ+ refugees and asylum-seekers.

Aims. Parental postpartum depressive symptoms have been extensively studied, but the combined longitudinal depression trajectories of parents and their long-term development beyond the postpartum period remain largely underexplored. We identified dyadic longitudinal depressive symptom trajectories in new parents, followed over an 11-year period, and compared parental characteristics, as well as child temperament and mental health factors, across different parental trajectory classes.

Methods. A prenatal cohort of 5,518 couples was studied. Depressive symptoms were measured using the Edinburgh Postnatal Depression Scale at eight time points: in the prenatal stage, in the newborn stage, and at 6 months, 18 months, 3 years, 5 years, 7 years and 11 years after the birth of the child.

Results. Dyadic Latent Class Growth Modelling identified five classes of couples: (1) mother has elevated depressive symptoms, father is non-depressed (24%); (2) both mother and father have elevated depressive symptoms (20%); (3) both mother and father are constantly non-depressed (42%); (4) both mother and father are constantly depressed (5%); and (5) mother is constantly depressed, father has elevated depressive symptoms (9%). Relationship maintenance (particularly being married or separated) was the most strongly associated with the classes. Socio-economic resources, emotional well-being, health, obstetric history and parental background also served as meaningful covariates. Child temperament and mental health showed weak correlations with parental trajectory classes.

Conclusions. Parents with postpartum depressive symptoms often experience depressive symptoms long-term. Separated parents are particularly vulnerable to adverse depressive trajectories. Our findings underscore the importance of dyadic methods in estimating unique combinations of parental depression trajectories.

Mental health problems in adolescence are increasingly prevalent and have tremendous impacts on life-long health and mortality. Although household poverty is a known risk factor for adolescent mental health, evidence of the timing hypothesis is scarce. We aimed to examine the longitudinal associations of poverty across childhood with mental health in adolescence, focusing on the timing of exposure.

We used the data of 5,671 children from a Japanese population-based longitudinal cohort, which recruited the first graders (aged 6–7 years) and followed biannually until eighth grade (aged 13–14 years) in Adachi, Tokyo. Household poverty was defined as households having any of the following experiences: annual income less than Japanese yen 3 million, payment difficulties and material deprivations, measured in first, second, fourth, sixth and eighth grades. Adolescent mental health included parent-report internalizing and externalizing problems (the Strengths and Difficulties Questionnaire), self-report depression (the Patient Health Questionnaire-9) and self-esteem (the Japanese version Children’s Perceived Competence Scale) in eighth grade. We applied g-estimation of structural nested mean modelling to account for time-varying confounders.

If adolescents were exposed to household poverty at any grade across childhood, on average, they would report more severe depressive symptoms (ψ = 0.32 [95% CI 0.13; 0.51]) and lower self-esteem (ψ = −0.41 [−0.62; −0.21]) in eighth grade. There were also average associations of household poverty at any grade with more internalizing (ψ = 0.19 [0.10; 0.29]) and externalizing problems (ψ = 0.10 [0.002; 0.19]). Although the associations between household poverty and mental health were stronger in younger ages (e.g., poverty in the second grade → depression: ψ = 0.54 [−0.12; 1.19] vs. poverty in the eighth grade → depression: ψ = −0.01 [−0.66; 0.64]), overlapping 95% CIs indicated no statistically significantly different associations by the timing of exposure.

We found the average effect of exposure to household poverty at any grade on mental health outcomes in eighth grade, failing to support the timing hypothesis. The findings indicate that the effects of household poverty accumulate over time in childhood and impact adolescent mental health (cumulative hypothesis) rather than the effects differ by the timing of exposure. While cumulative effects suggest a persistent intervention in poor households across childhood, we highlight intervention at any timing in childhood may be effective in alleviating adolescent mental health problems.

Developing integrated mental health services focused on the needs of children and young people is a key policy goal in England. The THRIVE Framework and its implementation programme, i-THRIVE, are widely used in England. This study examines experiences of staff using i-THRIVE, estimates its effectiveness, and assesses how local system working relationships influence programme success.

This evaluation uses a quasi-experimental design (10 implementation and 10 comparison sites.) Measurements included staff surveys and assessment of ‘THRIVE-like’ features of each site. Additional site-level characteristics were collected from health system reports. The effect of i-THRIVE was evaluated using a four-group propensity-score-weighted difference-in-differences model; the moderating effect of system working relationships was evaluated with a difference-in-difference-in-differences model.

Implementation site staff were more likely to report using THRIVE and more knowledgeable of THRIVE principles than comparison site staff. The mean improvement of fidelity scores among i-THRIVE sites was 16.7, and 8.8 among comparison sites; the weighted model did not find a statistically significant difference. However, results show that strong working relationships in the local system significantly enhance the effectiveness of i-THRIVE. Sites with highly effective working relationships showed a notable improvement in ‘THRIVE-like’ features, with an average increase of 16.41 points (95% confidence interval: 1.69–31.13, P-value: 0.031) over comparison sites. Sites with ineffective working relationships did not benefit from i-THRIVE (−2.76, 95% confidence interval: − 18.25–12.73, P-value: 0.708).

The findings underscore the importance of working relationship effectiveness in the successful adoption and implementation of multi-agency health policies like i-THRIVE.

The study assessed the interactions and the impact of specialist mobile community care teams (assertive outreach teams or AOTs) implemented in the mental health (MH) system of Bizkaia (Spain) using a methodology derived from an ecosystem perspective.

First, the experts assessed the system’s services and codified them according to an international classification system. Second, following an iterative methodology for expert-knowledge elicitation, a clients’ flow diagram showing the inter-dependencies of the system’s components was developed. It included variables and their relationships represented in a causal model. Third, the system elements where the AOTs had a major impact (stress nodes) were identified. Fourth, three scenarios (variable combinations representing the ‘stress points’ of the system) were modelled to assess its relative technical efficiency (technical performance indicator).

The classification system identified the lack of fidelity of the AOTs to the original assertive community treatment model, categorizing them as non-acute low-intensity mobile care. The causal model identified the following elements of the system as ‘stress nodes’ in relation to AOT: users’ families; social services (outside of the healthcare system); acute hospitals; non-acute residential facilities and, to a lesser extent, acute hospital day care services. When the stress nodes inside the healthcare system were modelled separately, acute and non-acute hospital care services resulted in a large deterioration in the system performance, while acute day hospital care had only a small impact.

The development of the expert-knowledge-based causal model from an ecosystem perspective was helpful in combining information from different levels, from nano to macro, to identify the components in the system likely to be most affected by a potential policy intervention, such as the closure of AOTs. It was also able to illustrate the interaction between the MH system components over time and the impact of the potential changes on the technical performance of the system. Such approaches have potential future application in assisting with service planning and decision-making in other health systems and socio-economic contexts.

To examine the risk of perinatal mental illness, including new diagnoses and recurrent use of mental healthcare, comparing women with and without traumatic brain injury (TBI), and to identify injury-related factors associated with these outcomes among women with TBI.

We conducted a population-based cohort study in Ontario, Canada, of all obstetrical deliveries to women in 2012–2021, excluding those with mental healthcare use in the year before conception. The cohort was stratified into women with no remote mental illness history (to identify new mental illness diagnoses between conception and 365 days postpartum) and those with a remote mental illness history (to identify recurrent illnesses). Modified Poisson regression generated adjusted relative risks (aRRs) (1) comparing women with and without TBI and (2) according to injury-related variables (i.e., number, severity, timing, mechanism and intent) among women with TBI.

There were n = 12,724 women with a history of TBI (mean age: 27.6 years [SD, 5.5]) and n = 786,317 without a history of TBI (mean age: 30.6 years [SD, 5.0]). Women with TBI were at elevated risk of a new mental illness diagnosis in the perinatal period compared to women without TBI (18.5% vs. 12.7%; aRR: 1.31, 95% confidence interval [CI]: 1.24–1.39), including mood and anxiety disorders. Women with a TBI were also at elevated risk for recurrent use of mental healthcare perinatally (35.5% vs. 27.8%; aRR: 1.18, 95% CI: 1.14–1.22), including mood and anxiety, psychotic, substance use and other mental health disorders. Among women with a history of TBI, the number of TBI-related healthcare encounters was positively associated with an elevated risk of new-onset mental illness.

These findings demonstrate the need for providers to be attentive to the risk for perinatal mental illness in women with a TBI. This population may benefit from screening and tailored mental health supports and treatment options.

Epidemiological evidence shows a concerning rise in youth mental health difficulties over the past three decades. Most evidence, however, comes from countries in Europe or North America, with far less known about changes in other global regions. This study aimed to compare adolescent mental health across two population-based cohorts in the UK, and two population-based cohorts in Pelotas, Brazil.

Four population-based cohorts with identical mental health measures were compared. In Brazil, these included the 1993 Pelotas Birth Cohort and the 2004 Pelotas Birth Cohort. In the UK, cohorts included the Avon Longitudinal Study of Parents and Children, and the Millennium Cohort Study. Mental health was measured in all cohorts using identical, parent-rated scores from the Strengths and Difficulties Questionnaire (SDQ). This was assessed in both countries over approximately the same time periods, when adolescents were aged 11 (2004 vs 2015 in Brazil, and 2003 vs 2012 in the UK), with follow-up analyses focused on outcomes in later adolescence.

Mental health problems were higher in the UK for adolescents born in the early 2000s compared to those born in the early 1990s. In Pelotas, the opposite was found, whereby problems were lower for adolescents born in the early 2000s compared to those born in the early 1990s. Despite these promising reductions in mental health problems in Pelotas over time, SDQ scores remained higher in Pelotas compared to the UK.

Our study represents the first to compare two population-based cohorts in the UK, and two population-based cohorts in Pelotas, Brazil, to understand how mental health problems have changed over time across the two settings. Our findings provide the most up-to-date insight into population-level rates of youth mental health problems in Pelotas, and shed novel insight into how these have changed over the last two decades in comparison to the UK. In doing so, our study provides a tentative first step towards understanding youth mental health over time at a more global scale, and presents a valuable opportunity to examine putative contributors to differences across time.

The high level of psychological distress in young people is a growing concern. However, there are few national surveys that describe the trajectories of mental health and wellbeing through adolescence into early adulthood. Further, existing research has largely focused exclusively on mental ill-health, with little focus on positive mental health. This study provides the first national profile of the mental health and wellbeing of Australians aged 12–25 years.

Participants completed the National Youth Mental Health survey in 2018 (n1 = 3832), 2020 (n2 = 974) or 2022 (n3 = 961). We applied Keyes’ Complete Mental Health (CMH) framework to derive categories of mental health and wellbeing, and examine rates of CMH over time, by age and gender.

While approximately half of those surveyed reported flourishing (high wellbeing without mental illness), rates of flourishing declined between 2018 and 2022. Rates of flourishing generally decreased with age, and flourishing was more prevalent amongst males than females.

The findings provide a unique contrast of youth mental health pre-, during and post- the COVID-19 pandemic. While rates of psychological distress are consistently high, the proportion of youth reporting flourishing highlights the need to consider all aspects of psychological functioning to accurately understand and respond to the mental health needs of young people.

The comparability between self-reports and clinician-rated scales for measuring depression following treatment has been a long-standing debate, with studies finding mixed results. While the use of self-reports in psychotherapy trials is very common, it has been widely assumed that these tools pose a validity threat when masking of participants is not possible. We conducted a meta-analysis across randomized controlled trials (RCTs) of psychotherapy for depression to examine if treatment effect estimates obtained via self-reports differ from clinician-rated outcomes.

We identified studies from a living database of psychotherapies for depression (updated to 1 January 2023). We included RCTs measuring depression at post-treatment with both a self-report and a clinician-rated scale. As our main model, we ran a multilevel hierarchical meta-analysis, resulting in a pooled differential effect size (Δg) between self-reports and clinician ratings. Moderators of this difference were explored through multimodel inference analyses.

A total of 91 trials (283 effect sizes) were included. In our main model, we found that self-reports produced smaller effect size estimates compared to clinician-rated instruments (Δg = 0.12; 95% CI: 0.03–0.21). This difference was very similar when only including trials with masked clinicians (Δg = 0.10; 95% CI: 0.00–0.20). However, it was more pronounced for unmasked clinical ratings (Δg = 0.20; 95% CI: −0.03 to 0.43) and when trials targeted specific population groups (e.g., perinatal depression) (Δg = 0.20; 95% CI: 0.08–0.32). Effect sizes between self-reports and clinicians were identical in trials targeting general adults (Δg = 0.00; 95% CI: −0.14 to 0.14).

Self-report instruments did not overestimate the effects of psychotherapy for depression and were generally more conservative than clinician assessments. Patients’ perception of improvement should not be considered less valid by default, despite the inherent challenge of masking in psychotherapy.

Increasing evidence has established a strong association between social anxiety disorder and suicidal behaviours, including suicidal ideation and suicide attempts. However, the association between social anxiety disorder and suicide mortality remains unclear.

This study analysed data from 15,776 patients with social anxiety disorder, extracted from a nationwide Taiwanese cohort between 2003 and 2017. Two unexposed groups without social anxiety disorder, matched by birth year and sex in 1:4 and 1:10 ratios, respectively, were used for comparison. Suicide deaths during the same period were examined. Psychiatric comorbidities commonly associated with social anxiety disorder, including schizophrenia, bipolar disorder, major depression, alcohol use disorder (AUD), substance use disorder (SUD), obsessive-compulsive disorder, autism, and attention deficit hyperactivity disorder, were identified.

Time-dependent Cox regression models, adjusted for demographic factors and psychiatric comorbidities, revealed that individuals with social anxiety disorder had an increased risk of suicide (hazard ratio: 3.49 in the 1:4 matched analysis and 2.84 in the 1:10 matched analysis) compared with those without the disorder. Comorbidities such as schizophrenia, bipolar disorder, major depression, AUD, and SUD further increased the risk of suicide in patients with social anxiety disorder.

Social anxiety disorder is an independent risk factor for suicide death. Additional psychiatric comorbidities, including schizophrenia, major affective disorders, and AUD, further increased social anxiety disorder-related suicide risk. Therefore, mental health officers and clinicians should develop targeted suicide prevention strategies for individuals with social anxiety disorder.