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.

There has been concern about violent acts and other criminal behaviour by people with a possible history of mental health problems. We therefore assessed the effects of community treatment orders (CTOs) on self-, third-party-, and agency-reported criminal behaviour when compared to voluntary treatment.

A systematic search of PubMed/Medline, Embase, PsycINFO and criminal justice bibliographic databases for observational or randomised controlled trials (RCTs) comparing CTO cases with controls receiving voluntary psychiatric treatment. Relevant outcomes were reports of violence and aggression or contacts with the criminal justice system such as arrests and court appearances.

Thirteen papers from 11 studies met inclusion criteria. Nine papers came from the United States and four from Australia. Two papers were of RCTs. Results for all outcomes were non-significant, the effect size declining as study design improved from non-randomised data on self-reported criminal behaviour, through third party criminal justice records and finally to RCTs. Similarly, there was no significant finding in the subgroup analysis of serious criminal behaviour.

On the limited available evidence, CTOs may not address aggression or criminal behaviour in people with mental illness. This is possibly because the risk of violence is increased by comorbid or nonclinical variables, which are beyond the scope of CTOs. These include substance use, a history of victimisation or maltreatment, and the wider environment. The management of risk should therefore focus on the whole person and their community through social and public health interventions, not solely legislative control.

While the cross-sectional relationship between internet gaming disorder (IGD) and depression is well-established, whether IGD predicts future depression remains debated, and the underlying mechanisms are not fully understood. This large-scale, three-wave longitudinal study aimed to clarify the predictive role of IGD in depression and explore the mediating effects of resilience and sleep distress.

A cohort of 41,215 middle school students from Zigong City was assessed at three time points: November 2021 (T1), November 2022 (T2) and November 2023 (T3). IGD, depression, sleep distress and resilience were measured using standardized questionnaires. Multiple logistic regression was used to examine the associations between baseline IGD and both concurrent and subsequent depression. Mediation analyses were conducted with T1 IGD as the predictor, T2 sleep distress and resilience as serial mediators and T3 depression as the outcome. To test the robustness of the findings, a series of sensitivity analyses were performed. Additionally, sex differences in the mediation pathways were explored.

(1) IGD was independently associated with depression at baseline (T1: adjusted odds ratio [AOR] = 4.76, 95% confidence interval [CI]: 3.79–5.98, p < 0.001), 1 year later (T2: AOR = 1.42, 95% CI: 1.16–1.74, p < 0.001) and 2 years later (T3: AOR = 1.24, 95% CI: 1.01–1.53, p = 0.042); (2) A serial multiple mediation effect of sleep distress and resilience was identified in the relationship between IGD and depression. The mediation ratio was 60.7% in the unadjusted model and 33.3% in the fully adjusted model, accounting for baseline depression, sleep distress, resilience and other covariates. The robustness of our findings was supported by various sensitivity analyses; and (3) Sex differences were observed in the mediating roles of sleep distress and resilience, with the mediation ratio being higher in boys compared to girls.

IGD is a significant predictor of depression in adolescents, with resilience and sleep distress serving as key mediators. Early identification and targeted interventions for IGD may help prevent depression. Intervention strategies should prioritize enhancing resilience and improving sleep quality, particularly among boys at risk.

The association between a pregnant mother’s vitamin D status and depressive symptoms has yielded inconsistent results. It is possible that other factors play a role in this association, as depression can have multiple causes. Recognizing the significance of the husband’s participation in antenatal care, this study aimed to examine whether the husband’s involvement moderates the link between the mother’s vitamin D status and depressive symptoms during pregnancy.

A total of 2983 Chinese married pregnant women, in their 25–35 weeks of pregnancy, completed questionnaires to assess their levels of depressive symptoms and the involvement of their husbands in their antenatal care appointments. Additionally, their serum levels of vitamin D were measured.

After adjusting for maternal age, parity, and socio-economic status, the husband’s involvement in antenatal care moderated the association between maternal vitamin D status and depressive symptoms during pregnancy (β = 2.03, p = 0.035). Specifically, when their husbands were not regularly present for antenatal care appointments, mothers with suboptimal vitamin D levels experienced more depressive symptoms than those with optimal levels. However, there were no noticeable differences in depressive symptoms between vitamin D groups for mothers whose husbands attended all antenatal care appointments.

Pregnant women who have suboptimal vitamin D levels and lack support from their spouses are most vulnerable to experiencing depression. It is crucial to holistically assess the social and physiological needs of expectant mothers to reduce their risk of antenatal depression.

Digital peer support interventions have the potential to promote healthy lifestyles and better mental health. This systematic review and meta-analysis synthesizes evidence on the effectiveness of digital peer support interventions for enhancing physical and mental health in healthy individuals rather than those diagnosed with a clinical condition.

First, we evaluated the impact of digital peer support interventions on physical and mental health outcomes by attending to sources of peer support (informal, naturally occurring peer support; formal support from trained peers), effectiveness demonstrated through different study designs (pre–post comparison vs. well-controlled experimental conditions) and long-term effects of interventions. Second, we examined whether features of digital peer support interventions – specifically, dosage, uptake and platform affordances – moderated intervention effectiveness. Third, we considered moderating effects of individual differences (age and existing health conditions) and country.

Using random-effects modelling, which included 47 studies with 76 effect sizes on physical health, and 73 studies with 118 effect sizes on mental health, we found a moderate effect of digital peer support in improving physical health (standardized mean difference (SMD) = 0.35, p < 0.001; 95% CI: 0.30–0.41) and a large effect in enhancing mental health (standardized mean difference(SMD) = 0.53, p < 0.001; 95% CI: 0.46–0.61), which were similar across ages and individuals with varying degree of existing health conditions. Different sources of peer support demonstrated similar effects on physical health, but informal, naturally occurring peer support was more effective in bolstering mental health than formal support from trained peers, producing large effects that were comparable to online professional support. Positive effects on physical health were sustained over follow-up assessments, but weakened for mental health over time. Greater dosages of intervention had decreased effectiveness, but uptake of intervention did not moderate the effects on health. Interventions delivered on platforms that afford greater interactivity (apps, social networking sites and video conferencing) were more effective than those with lower interactivity (forums, websites and emails). Digital peer support interventions had stronger effects on improving physical health in Western countries than Eastern countries, but stronger effects on improving mental health in Eastern than Western countries.

Our findings contribute to the nascent conceptual models of digital peer support, lend credence to digital peer support as a scalable preventive intervention with real-world benefits in bolstering individuals’ physical and mental health and provide important insights into best practices.

Prompt initial contact with a treatment provider is a critical first step in seeking help for a mental or substance use disorders (SUDs). The aim of the current study was to provide estimates of patterns and predictors of delay in making initial treatment contact based on the recently completed Australian National Survey of Mental Health and Wellbeing.

Data came a nationally representative epidemiological survey of n = 15,893 Australians. Measures included DSM-IV lifetime diagnoses of mood (MD), anxiety (AD) and SUDs; age of disorder onset; and age of first treatment contact. Correlates of treatment delay were examined.

SUDs exhibited the lowest lifetime treatment rate (27%), compared to MD (94%) and ADs (85%). Individuals with AD experienced the longest delay in seeking treatment (Mdn = 11 years), followed by those with SUDs (Mdn = 8 years) and MDs (Mdn = 3 years). Females had higher odds of seeking treatment for MD and AD but lower odds for SUDs. Recent birth cohorts showed increased treatment seeking across disorders, and higher education was associated with increased treatment seeking for MD and AD. Age of onset, country of birth and co-occurring disorders had mixed associations with treatment seeking.

The study reveals stark disparities in treatment-seeking behaviour and delays across mental and substance use disorders, with a pronounced underutilization of services for SUDs. Additionally, attention should be directed towards early intervention for individuals with earlier symptom onset, those from earlier cohorts and those with co-occurring SUDs.

Although individuals with lower socio-economic position (SEP) have a higher prevalence of mental health problems than others, there is no conclusive evidence on whether mental healthcare (MHC) is provided equitably. We investigated inequalities in MHC use among adults in Stockholm County (Sweden), and whether inequalities were moderated by self-reported psychological distress.

MHC use was examined in 31,433 individuals aged 18–64 years over a 6-month follow-up period, after responding to the General Health Questionnaire-12 (GHQ-12) in 2014 or the Kessler Six (K6) in 2021. Information on their MHC use and SEP indicators, education, and household income, were sourced from administrative registries. Logistic and negative binomial regression analyses were used to estimate inequalities in gained MHC access and frequency of outpatient visits, with psychological distress as a moderating variable.

Individuals with lower education or income levels were more likely to gain access to MHC than those with high SEP, irrespective of distress levels. Education-related differences in gained MHC access diminished with increasing distress, from a 74% higher likelihood when reporting no distress (odds ratio, OR = 1.74 [95% confidence interval, 95% CI: 1.43–2.12]) to 30% when reporting severe distress (OR = 1.30 [0.98–1.72]). Comparable results were found for secondary care but not primary care i.e., lower education predicted reduced access to primary care in moderate-to-severe distress groups (e.g., OR = 0.63 [0.45–0.90]), and for physical but not digital services. Income-related differences in gained MHC access remained stable or increased with distress, especially for secondary care and physical services.

Among MHC users, we found marginal socio-economic differences in the frequency of outpatient visits, and these differences decreased with increasing distress. Yet, having only primary education with severe distress was associated with fewer outpatient visits compared with having post-secondary education (rate ratio, RR = 0.82; 95% CI: 0.67–1.00). These inequities were especially evident among women and for visits to psychologists, counsellors, or psychotherapists.

Although lower-income groups used services more than others, they still had higher odds of not using services when reporting distress (i.e., those not in contact with services despite scoring ≥3 on the GHQ-12 or ≥8 on the K6; OR = 1.27; 95% CI: 1.15–1.40).

Overall, individuals with lower education and income used MHC services more than their counterparts with higher socio-economic status; however, low-educated individuals faced inequities in primary care and underutilized non-physician services such as visits to psychologists.

Adolescence is a critical developmental phase during which young people are vulnerable to the experiences of mental ill-health and social exclusion (consisting of various domains including education and employment, housing, finances and social supports and relationships). The aims of this study were to (i) obtain an understanding of the relationships between social exclusion, mental health and wellbeing of young people; and (ii) identify potentially modifiable targets, or population groups that require greater or targeted supports.

Data were obtained from the Mission Australia 2022 Youth Survey, Australia’s largest annual population-wide survey of young people aged 15–19 years (n = 18,800). Participants’ experiences of social exclusion in different domains were explored (e.g., prevalence, co-occurrence and controlling for differences in demographic characteristics). Multivariable linear regression models were used to map the relationships between social exclusion domains and mental health and wellbeing, controlling for confounding factors where necessary.

Sixty per cent of all young people experienced social exclusion in at least one domain, 25% in multiple. Young people who identified as gender diverse, Indigenous, living in a remote/rural or socio-economically disadvantaged area and with a culturally diverse background were more likely to report social exclusion. A strong association was seen between all domains of social exclusion and poor mental health (e.g., higher psychological distress and loneliness, reduced personal wellbeing, reduced sense of control over their life and a more negative outlook on the future). Notably, difficulties in socialising and obtaining social support were critical factors linked to increased psychological distress and reduced wellbeing.

Findings underscore the need to address multiple domains of social exclusion concurrently, and in collaboration with youth mental healthcare. Prevention efforts aimed at early identification and intervention should be prioritised to support young people vulnerable to social exclusion. Screening approaches are needed to identify individuals and groups of young people in need of support, and to facilitate care coordination across multiple providers.

The impact of social determinants of health (SDOH) on mental health is increasingly realized. A comprehensive study examining the associations of SDOH with mental health disorders has yet to be accomplished. This study evaluated the associations between five domains of SDOH and the SDOH summary score and mental health disorders in the United States.

We analyzed data from a diverse group of participants enrolled in the All of Us research programme, a research programme to gather data from one million people living in the United States, in a cross-sectional design. The primary exposure was SDOH based on Healthy People 2030: education access and quality, economic stability, healthcare access and quality, social and community context, and neighbourhood and built environment. A summary SDOH score was calculated by adding each adverse SDOH risk (any SDOH vs. no SDOH). Our primary outcomes were diagnoses of major depression (MD) (i.e., major depressive disorder, recurrent MD or MD in remission) and anxiety disorders (AD) (i.e., generalized AD and other anxiety-related disorders). Multiple logistic regression models were used to determine adjusted odd ratios (aORs) for MD and/or ADs after controlling for covariates.

A total of 63,162 participants with MD were identified (22,277 [35.3%] age 50–64 years old; 41,876 [66.3%] female). A total of 77,624 participants with AD were identified (25,268 [32.6%] age 50–64 years old; 52,224 [67.3%] female). Factors associated with greater odds of MD and AD included having less than a college degree, annual household income less than 200% of federal poverty level, housing concerns, lack of transportation, food insecurity, and unsafe neighbourhoods. Having no health insurance was associated with lower odds of both MD and AD (aOR, 0.48; 95% confidence interval [CI], 0.46–0.51 and aOR, 0.44; 95% CI, 0.42–0.47, respectively). SDOH summary score was strongly associated with the likelihood of having MD and AD (aOR, 1.97; 95% CI, 1.89–2.06 and aOR, 1.69; 95% CI, 1.63–1.75, respectively).

This study found associations between all five domains of SDOH and the higher odds of having MD and/or AD. The strong correlations between the SDOH summary score and mental health disorders indicate a possible use of the summary score as a measure of risk of developing mental health disorders.

Clinical high-risk for psychosis (CHR-P) states exhibit diverse clinical presentations, prompting a shift towards broader outcome assessments beyond psychosis manifestation. To elucidate more uniform clinical profiles and their trajectories, we investigated CHR-P profiles in a community sample.

Participants (N = 829; baseline age: 16–40 years) comprised individuals from a Swiss community sample who were followed up over roughly 3 years. latent class analysis was applied to CHR-P symptom data at baseline and follow-up, and classes were examined for demographic and clinical differences, as well as stability over time.

Similar three-class solutions were yielded for both time points. Class 1 was mainly characterized by subtle, subjectively experienced disturbances in mental processes, including thinking, speech and perception (basic symptoms [BSs]). Class 2 was characterized by subthreshold positive psychotic symptoms (i.e., mild delusions or hallucinations) indicative of an ultra-high risk for psychosis. Class 3, the largest group (comprising over 90% of participants), exhibited the lowest probability of experiencing any psychosis-related symptoms (CHR-P symptoms). Classes 1 and 2 included more participants with functional impairment and psychiatric morbidity. Class 3 participants had a low probability of having functional deficits or mental disorders at both time points, suggesting that Class 3 was the healthiest group and that their mental health and functioning remained stable throughout the study period. While 91% of Baseline Class 3 participants remained in their class over time, most Baseline Classes 1 (74%) and Class 2 (88%) participants moved to Follow-up Class 3.

Despite some temporal fluctuations, CHR-P symptoms within community samples cluster into distinct subgroups, reflecting varying levels of symptom severity and risk profiles. This clustering highlights the largely distinct nature of BSs and attenuated positive symptoms within the community. The association of Classes 1 and 2 with Axis-I disorders and functional deficits emphasizes the clinical significance of CHR-P symptoms. These findings highlight the need for personalized preventive measures targeting specific risk profiles in community-based populations.