The enduring impact of the COVID-19 pandemic on mental health and its implications for COVID-19 vaccine uptake necessitate comprehensive investigation. We aimed to characterize the persistence of moderate to severe anxiety and depression symptoms from July 2020 to July 2023, explore demographic associations with symptom persistence, and assess how these symptoms affected COVID-19 vaccination uptake between May 2021 and July 2023.

Participants from the national community-based CHASING COVID Cohort were enrolled between March and June 2020 and completed quarterly follow-ups until December 2023. Scores ≥10 on the Generalized Anxiety Disorder 7-item and the Patient Health Questionnaire 8-item at 14 follow-up assessments indicated moderate to severe anxiety and depression symptoms, respectively. Missing scores were imputed. Persistent anxiety and depression were defined as experiencing moderate to severe anxiety and depression symptoms ≥7 out of 14 follow-up assessments, respectively.

Among 4,851 participants, 15.9% experienced persistent anxiety symptoms and 19.3% persistent depression symptoms from July 2020 to July 2023. Demographic factors associated with symptom persistence included younger age, female or non-binary gender, Hispanic ethnicity, lower education level, household income <$100k, presence of children <18 in the household, greater healthcare barriers and comorbidities. Participants with ongoing moderate to severe anxiety and depression symptoms had 0.95 (95% CI: 0.94, 0.97) and 0.95 (95% CI: 0.93, 0.96) times rates of receiving additional COVID-19 vaccine doses between May 2021 and July 2023, respectively.

Customized support for individuals with mental disorders may mitigate barriers to vaccine uptake. Further investigation is warranted to validate these findings and inform targeted interventions.

It is widely recognized that the COVID-19 pandemic exerted an impact on the mental health of the general population, but epidemiological evidence is surprisingly sparse. We aimed to explore the association between serologically confirmed SARS-CoV-2 infection and psychological distress – assessed by symptoms of depression, anxiety and stress – in the general adult population in southern Switzerland, a region widely affected by the pandemic. We also investigated whether this association varied over time and between pandemic waves from late 2020 through 2021.

We used data from 305 adults who participated in the Corona Immunitas Ticino prospective seroprevalence study in southern Switzerland, including results of the serological tests of SARS-CoV-2 infection collected in June 2021, and explored associations with depression, anxiety and stress scores as measured by the 21-item Depression, Anxiety and Stress Scale at three time points between December 2020 and August 2021, accounting for socio-demographic and health characteristics.

In our sample, 84.3% of the participants (mean age of 51.30 years, SD = ±.93) were seronegative at baseline. Seropositive (i.e., infected) participants had a decreasing probability of being depressed and anxious through the COVID-19 pandemic waves compared to the seronegative (non-infected) participants. Further, seropositivity at baseline was also associated with more rapid decline in depressive, anxiety and stress symptomatology, and younger age and the presence of chronic diseases were independently associated with mild anxiety (OR = .97; P = 0.013; 95% CI = 0.95, 0.99; OR = 3.47; P = 0.001; 95% CI = 1.71, 7.04) and stress (OR = .96; P = 0.003; 95% CI = .94, .99; OR = 2.56; P = 0.010; 95% CI = 1.25, 5.22).

Our results suggest that the MH consequences of the pandemic may not be due to the SARS-CoV-2 infection per se, but to fears associated with the risk of infection, and to the pandemic uncertainties.

Achieving equitable healthcare access is a global challenge. Improving whole-population mental health and reducing the global burden of mental disorders is a key recommendation of the 2018 Lancet Global Mental Health Commission, which proposed monitoring national indicators, including the proportion of people with severe mental disorders who are service-users. This study aims to derive an equity indicator from national datasets integrating need, service utilisation and socioeconomic status, and demonstrate its utility in identifying gaps in mental health service use amongst those with the greatest need, thereby guiding equitable healthcare delivery.

We present a case study of a universal health insurance scheme (Medicare) in Australia. We developed the equity indicator using three national datasets. Geographic areas were linked to an area-based socioeconomic deprivation quintile (Census 2016). Per geographic area, we estimated the number with a mental healthcare need using scores ≥30 on the Kessler-10 (Australian National Health Surveys 2015 and 2018), and obtained the number of services used, defined as mental health-related contacts with general practitioners and mental health professionals (Medicare administrative data 2015–2019). We divided the number of services by the population with an estimated mental healthcare need and averaged these use-rates across each socioeconomic deprivation quintile. The equity indicator is the ratio of the use-rates in the least versus most deprived quintiles.

Those estimated to have the greatest need for mental healthcare in 2019 ranged between 8.2% in the most disadvantaged area quintile (Q1) and 2.4% in the least (Q5), corresponding to a proportional increase of 27.7% in Q1 and 19.5% in Q5 since 2015. Equity-indicator-adjusted service rates of 4.2 (3.8–4.6) and 23.9 (22.4–25.4) showed that individuals with the highest need for care residing in Q1 areas received a stark 6 times fewer services compared to their Q5 counterparts, producing an equity indicator of 6.

As the global prevalence of common mental disorders may be increasing, it is crucial to calculate robust indicators evaluating the equity of mental health service use. In this Australian case study, we developed an equity indicator enabling the direct comparison of geographic areas with different need profiles. The results revealed striking inequities that persisted despite publicly-funded universal healthcare, recent service reforms and being a high-income country. This study demonstrates the importance and feasibility of generating such an indicator to inform and empower communities, healthcare providers and policymakers to pursue equitable service provision.

Most information about the association between childhood maltreatment (CM) and subsequent psychiatric morbidity is based on retrospective self-reports. Findings from longitudinal studies using prospective reports to statutory agencies may be subject to attrition. We therefore compared the prevalence to age 30 of inpatient psychiatric diagnoses in those who experienced agency-reported CM with those of the rest of the cohort using administrative data to minimise loss to follow-up.

We used linked administrative data for two birth cohorts of all individuals born in Queensland, Australia in 1983 and 1984 (N = 83,050) and followed to age 30 years. This was the entire cohort aside from 312 people who died. Information on CM came from statewide child protection data and psychiatric diagnoses from all public and private hospital admissions in Queensland.

On adjusted analyses, the 4,703 participants (5.7%) who had been notified to the statewide child protection authority had three to eight times the odds of being admitted for any of the following psychiatric diagnoses by age 30 years old: schizophrenia-spectrum disorders, bipolar affective disorders, depression, anxiety and post-traumatic stress disorders (PTSD). There were similar findings for all the CM subtypes. Associations were especially strong for PTSD with between a seven – and nine-fold increase in the odds of admission.

This is one of the largest studies of the long-term effects of CM, covering an entire jurisdiction. All types of maltreatment are significantly related to a range of psychiatric disorders requiring hospitalisation. Early identification, intervention and providing appropriate support to individuals who have experienced CM may help mitigate the long-term consequences and reduce the risk of subsequent mental health problems.

Although it has been hypothesized that air pollution, particularly PM2.5 and PM10, causes depressed symptoms, their interactions with greenness have not yet been confirmed. This study examined the association between depression symptoms and air pollution, as well as the potential moderating effects of greenness.

A total of 7657 people from all around South Korea were examined using information from the Korean Longitudinal Study of Aging, for the years 2016, 2018 and 2020. Depressive symptoms were assessed using the CES-D 10 score (Center for Epidemiology Studies of Depression scale, Boston form), and annual air pollution levels (PM2.5, PM10) and greenness (NDVI, Landsat Normalized Difference Vegetation Index) at the district level (si-gun-gu) were considered for the association analysis. The investigation was primarily concerned with determining how the CES-D 10 score changed for each 10 ${\mu \text{g/}}{{\text{m}}^{\text{3}}}$ increase in PM2.5 and PM10 according to NDVI quantiles, respectively. The analysis used generalized estimating equation models that were adjusted with both minimal and complete variables. Subgroup analyses were conducted based on age groups (<65, ≥65 years old), sex and exercise status.

The impact of PM10 on depression in the fourth quantile of NDVI was substantially less in the fully adjusted linear mixed model (OR for depression with a 10 ${\mu\text{ g/}}{{\text{m}}^{\text{3}}}$ increment of PM10: 1.29, 95% CI: 1.06, 1.58) than in the first quantile (OR: 1.88, 95% CI: 1.58, 2.25). In a similar vein, the effect of PM2.5 on depression was considerably reduced in the fourth quantile of NDVI (OR for depression with a 10 ${\mu\text{ g/}}{{\text{m}}^{\text{3}}}$ increment of PM2.5: 1.78, 95% CI: 1.30, 2.44) compared to the first (OR: 3.75, 95% CI: 2.75, 5.10). Subgroup analysis results demonstrated beneficial effects of greenness in the relationship between particulate matter and depression.

This longitudinal panel study found that a higher quantile of NDVI was associated with a significantly reduced influence of air pollution (PM10, PM2.5) on depression among older individuals in South Korea.

Although natural hazards (e.g., tropical cyclones, earthquakes) disproportionately affect developing countries, most research on their mental health impact has been conducted in high-income countries. We aimed to summarize prevalences of mental disorders in Global South populations (classified according to the United Nations Human Development Index) affected by natural hazards.

To identify eligible studies for this meta-analysis, we searched MEDLINE, PsycINFO and Web of Science up to February 13, 2024, for observational studies with a cross-sectional or longitudinal design that reported on at least 100 adult survivors of natural hazards in a Global South population and assessed mental disorders with a validated instrument at least 1 month after onset of the hazard. Main outcomes were the short- and long-term prevalence estimates of mental disorders. The project was registered on the International Prospective Register of Systematic Reviews (CRD42023396622).

We included 77 reports of 75 cross-sectional studies (six included a non-exposed control group) comprising 82,400 individuals. We found high prevalence estimates for post-traumatic stress disorder (PTSD) in the general population (26.0% [95% CI 18.5–36.3]; I2 = 99.0%) and depression (21.7% [95% CI 10.5–39.6]; I2 = 99.2%) during the first year following the event, with similar prevalences observed thereafter (i.e., 26.0% and 23.4%, respectively). Results were similar for regions with vs. without recent armed conflict. In displaced samples, the estimated prevalence for PTSD was 46.5% (95% CI 39.0–54.2; k = 6; I2 = 93.3). We furthermore found higher symptom severity in exposed, versus unexposed, individuals. Data on other disorders were scarce, apart from short-term prevalence estimates of generalised anxiety disorder (15.9% [95% CI 4.7–42.0]; I2 = 99.4).

Global South populations exposed to natural hazards report a substantial burden of mental disease. These findings require further attention and action in terms of implementation of mental health policies and low-threshold interventions in the Global South in the aftermath of natural hazards. However, to accurately quantify the true extent of this public health challenge, we need more rigorous, well-designed epidemiological studies across diverse regions. This will enable informed decision making and resource allocation for those in need.

Epidemiological studies show that despite the episodic nature, the long-term trajectory of depression can be variable. This study evaluated the heterogeneity of 10-year trajectory of major depressive disorder (MDD) related service utilization and associated clinical characteristics among US Veterans with a first diagnosis after 9/11.

Using a cohort design, electronic health record data for 293,265 Operation Enduring Freedom and Iraqi Freedom (OEF/OIF) Veterans were extracted to identify those with MDD between 2001 and 2021 with a full preceding year of clinical data and 10 years following the diagnosis. Latent class growth analysis compared clinical characteristics associated with four depression trajectories. Across all Veterans Affairs (VA)hospitals, 25,307 Veterans met our inclusion criteria. Demographic and clinical information from medical records was extracted and used as predictors of depression 10-year trajectories.

Among the study cohort (N = 25,307), 27.7% were characterized by brief contact, 41.7% were later re-entry, 17.6% were persistent contact and 12.9% were prolonged initial contact for depression related services. Compared to Veterans with trajectories showing brief contact, those with protracted treatment (persistent or prolonged initial contact) were more likely to be diagnosed with comorbid posttraumatic stress disorder (PTSD) and with MDD that was moderate to severe or recurrent.

Depression is associated with a range of treatment trajectories. The persistent and prolonged initial contact trajectories may have distinct characteristics and uniquely high resource utilization and disability income. We can anticipate that patients with comorbid PTSD may need longer-term care which has implications for brief models of care.

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the risk of self-harming behaviours warrants further investigation. Here, we hypothesized that people with a history of hospitalization for self-harm may be particularly at risk of readmission in case of SARS-CoV-2 hospitalization.

We conducted a retrospective analysis based on the French national hospitalization database. We identified all patients hospitalized for deliberate self-harm (10th edition of the International Classification of Diseases codes X60–X84) between March 2020 and March 2021. To study the effect of SARS-CoV-2 hospitalization on the risk of readmission for self-harm at 1-year of the inclusion, we performed a multivariable Fine and Gray model considering hospital death as a competing event.

A total of 61,782 individuals were hospitalized for self-harm. During the 1-year follow-up, 9,403 (15.22%) were readmitted for self-harm. Between inclusion and self-harm readmission or the end of follow-up, 1,214 (1.96% of the study cohort) were hospitalized with SARS-CoV-2 (mean age 60 years, 52.9% women) while 60,568 were not (mean age 45 years, 57% women). Multivariate models revealed that the factors independently associated with self-harm readmission were: hospitalization with SARS-CoV-2 (adjusted hazard ratio (aHR) = 3.04 [2.73–3.37]), psychiatric disorders (aHR = 1.61 [1.53–1.69]), self-harm history (aHR = 2.00 [1.88–2.04]), intensive care and age above 80.

In hospitalized people with a personal history of self-harm, infection with SARS-CoV-2 increased the risk of readmission of self-harm, with an effect that seemed to add to the effect of a history of mental disorders, with an equally significant magnitude. Infection may be a significantly stressful condition that precipitates self-harming acts in vulnerable individuals. Clinicians should pay particular attention to the emergence of suicidal ideation in these patients in the aftermath of SARS-CoV-2 infection.

Psychotic-like experiences (PLEs), especially for persistent PLEs, are highly predictive of subsequent mental health problems. Hence, it is crucial to explore the psychopathological associations underlying the occurrence and persistence of PLEs. This study aimed to explore the above issues through a longitudinal dynamic network approach among PLEs and psychological and psychosocial factors.

A total of 3,358 college students completed two waves of online survey (from Oct 2021 to Oct 2022). Socio-demographic information was collected at baseline, and PLEs, depressive and anxiety symptoms, and adverse life events were assessed in both waves. Cross-lagged panel network analyses were used to establish networks among individuals with baseline PLEs as well as those without.

At baseline, 455(13.5%) students were screened positive for PLEs. Distinct dynamic network structures were revealed among participants with baseline PLEs and those without. While ‘psychomotor disturbance’ had the strongest connection with PLEs in participants with baseline PLEs, ‘suicide/self-harm’ was most associated with PLEs in those without. Among all three subtypes of PLEs, bizarre experiences and persecutory ideation were the most affected nodes by other constructs in participants with baseline PLEs and those without, respectively. Additionally, wide interconnections within the PLEs construct existed only among participants without baseline PLEs.

The study provides time-variant associations between PLEs and depressive symptoms, anxiety symptoms, and adverse life events using network structures. These findings help to reveal the crucial markers of the occurrence and persistence of PLEs, and shed high light on future intervention aimed to prevent and relieve PLEs.

The associations of prior homelessness with current health are unknown. Using nationally representative data collected in private households in England, this study aimed to examine Common Mental Disorders (CMDs), physical health, alcohol/substance dependence, and multimorbidities in people who formerly experienced homelessness compared to people who never experienced homelessness.

This cross-sectional study utilised data from the 2007 and 2014 Adult Psychiatric Morbidity Surveys. Former homelessness and current physical health problems were self-reported. Current CMDs, alcohol dependence and substance dependence were ascertained using structured validated scales. Survey-weighted logistic regression was used to compare multimorbidities (conditions in combination) for participants who formerly experienced homelessness with those who had never experienced homelessness, adjusting for sociodemographic characteristics, smoking status and adverse experiences. Population attributable fractions (PAFs) were calculated.

Of 13,859 people in the sample, 535 formerly experienced homelessness (3.6%, 95% CI 3.2–4.0). 44.8% of people who formerly experienced homelessness had CMDs (95% CI 40.2–49.5), compared to 15.0% (95% CI 14.3–15.7) for those who had never experienced homelessness. There were substantial associations between prior homelessness and physical multimorbidity (adjusted odds ratio [aOR] 1.98, 95% CI 1.53–2.57), CMD–physical multimorbidity (aOR 3.43, 95% CI 2.77–4.25), CMD–alcohol/substance multimorbidity (aOR 3.53, 95% CI 2.49–5.01) and trimorbidity (CMD–alcohol/substance–physical multimorbidity) (aOR 3.26, 95% CI 2.20–4.83), in models adjusting for sociodemographic characteristics and smoking. After further adjustment for adverse experiences, associations attenuated but persisted for physical multimorbidity (aOR 1.40, 95% CI 1.10–1.79) and CMD–physical multimorbidity (aOR 1.55, 95% CI 1.20–2.00). The largest PAFs were observed for CMD–alcohol/substance multimorbidity (17%) and trimorbidity (16%).

Even in people currently rehoused, marked inequities across multimorbidities remained evident, highlighting the need for longer-term integrated support for people who have previously experienced homelessness.

Depressive disorders are a major public health issue in Western societies, particularly among adolescents, young adults and women. The COVID-19 pandemic has exacerbated mental health challenges, increasing depression and anxiety symptoms, especially in younger people. This study focuses on the hard-hit Emilia-Romagna Region (ERR) in Italy, examining changes in antidepressant (AD) drug use post-COVID-19 to understand the pandemic’s effect on mental health.

A population-based interrupted time series design and a segmented regression analysis was carried out on ERR pharmaceutical data (FED, direct dispensation pharmaceuticals, AFT, territorial pharmaceutical assistance) out to estimate changes in AD use during the three pandemic years (2020, 2021 and 2022) compared to 2017–2019.Analyses were stratified by age, gender, citizenship, population density of the area of residence.

A notable increase in AD consumption compared to what was expected was observed among younger age groups, and especially in females. In the 12–19 age group, a gradual increase was recorded from January 2021 until it reached +48% in 2022 (+58% among women, +30% among men). An even more remarkable growth in AD usage among non-Italian residents in the same age group was recorded compared to expected. A relevant increase, although smaller, was detected among individuals in the 20–34 age group, with a peak of +9% in 2022. These differences persisted up until the end of the observation period.

The study suggests that the COVID-19 pandemic may have had a lasting negative impact on the mental health of younger individuals. The observed increase in AD use may foreshadow a potential long-term need for enhanced mental healthcare and services directed at this subpopulation.

At the basis of many important research questions is causality – does X causally impact Y? For behavioural and psychiatric traits, answering such questions can be particularly challenging, as they are highly complex and multifactorial. ‘Triangulation’ refers to prospectively choosing, conducting and integrating several methods to investigate a specific causal question. If different methods, with different sources of bias, all indicate a causal effect, the finding is much less likely to be spurious. While triangulation can be a powerful approach, its interpretation differs across (sub)fields and there are no formal guidelines. Here, we aim to provide clarity and guidance around the process of triangulation for behavioural and psychiatric epidemiology, so that results of existing triangulation studies can be better interpreted, and new triangulation studies better designed.

We first introduce the concept of triangulation and how it is applied in epidemiological investigations of behavioural and psychiatric traits. Next, we put forth a systematic step-by-step guide, that can be used to design a triangulation study (accompanied by a worked example). Finally, we provide important general recommendations for future studies.

While the literature contains varying interpretations, triangulation generally refers to an investigation that assesses the robustness of a potential causal finding by explicitly combining different approaches. This may include multiple types of statistical methods, the same method applied in multiple samples, or multiple different measurements of the variable(s) of interest. In behavioural and psychiatric epidemiology, triangulation commonly includes prospective cohort studies, natural experiments and/or genetically informative designs (including the increasingly popular method of Mendelian randomization). The guide that we propose aids the planning and interpreting of triangulation by prompting crucial considerations. Broadly, its steps are as follows: determine your causal question, draw a directed acyclic graph, identify available resources and samples, identify suitable methodological approaches, further specify the causal question for each method, explicate the effects of potential biases and, pre-specify expected results. We illustrated the guide’s use by considering the question: ‘Does maternal tobacco smoking during pregnancy cause offspring depression?’.

In the current era of big data, and with increasing (public) availability of large-scale datasets, triangulation will become increasingly relevant in identifying robust risk factors for adverse mental health outcomes. Our hope is that this review and guide will provide clarity and direction, as well as stimulate more researchers to apply triangulation to causal questions around behavioural and psychiatric traits.

Humanitarian migrants are at increased risk of post-traumatic stress disorder (PTSD) and elevated psychological distress. However, men and women often report varying degrees of stress and experience different challenges during migration. While studies have explored PTSD, psychological distress, gender, and resettlement stressors, they have not explored the interplay between these factors. This study aims to address that gap by investigating gender disparities in PTSD and psychological distress among humanitarian migrants in Australia, with a focus on the moderating role of socioeconomic factors.

This study used data from five waves of the Building a New Life in Australia (BNLA) survey, a longitudinal study of 2,399 humanitarian migrants who arrived in Australia in 2013. PTSD and psychological distress were measured using the PTSD-8 and Kessler-6 (K6) scales, respectively. We conducted generalised linear mixed-effect logistic regression analyses stratified by gender.

Female humanitarian migrants exhibited a significantly higher prevalence of PTSD and psychological distress than males over five years of resettlement in Australia. Women facing financial hardship, unemployment, or residing in short-term housing reported greater levels of PTSD and distress compared to men.

Women facing financial hardship, inadequate housing, and unemployment exhibit higher rates of PTSD and psychological distress, underscoring the significant impact of socioeconomic factors. Addressing these challenges at both individual and systemic levels is essential for promoting well-being and managing mental health among female humanitarian migrants.

Forcibly displaced people, such as refugees and asylum-seekers (RAS), are at higher risk of mental disorders, mainly post-traumatic stress disorder (PTSD), depression and anxiety. Little is known about the complex relationships between these mental disorders among culturally and linguistically diverse RAS. To investigate this, the present study applied a novel network analytical approach to examine and compare the central and bridge symptoms within and between PTSD, depression and anxiety among Afghan and Syrian RAS in Türkiye.

A large-scale online survey study with 785 Afghan and 798 Syrian RAS in Türkiye was conducted in 2021. Symptoms of PTSD (the short form of Post-Traumatic Stress Disorders Checklist [PCL-5]), depression and anxiety (Hopkins Symptoms Checklist-25) [HSCL-25]) were measured via self-administrated validated instruments. We conducted network analysis to identify symptoms that are most strongly connected with other symptoms (central symptoms) and those that connect the symptoms of different disorders (bridge symptoms) in R Studio using the qgraph package.

Overall, Afghans and Syrians differed in terms of network structure, but not in network strength. Results showed that feeling blue, feeling restless and spells of terror or panic were the most central symptoms maintaining the overall symptom structure of common mental disorders among Afghan participants. For Syrian participants, worrying too much, feeling blue and feeling tense were identified as the central symptoms. For both samples, anger and irritability and feeling low in energy acted as a bridge connecting the symptoms of PTSD, depression and anxiety.

The current findings provide insights into the interconnectedness within and between the symptoms of common mental disorders and highlight the key symptoms that can be potential targets for psychological interventions for RAS. Addressing these symptoms may aid in tailoring existing evidence-based interventions and enhance their effectiveness. This contributes to reducing the overall mental health burden and improving well-being in this population.

Exposure to multiple forms of victimisation in childhood (often referred to as poly-victimisation) has lifelong adverse effects, including an elevated risk of early-adulthood psychopathology. However, not all poly-victimised children develop mental health difficulties and identifying what protects them could inform preventive interventions. The present study investigated whether individual-, family- and/or community-level factors were associated with lower levels of general psychopathology at age 18, among children exposed to poly-victimisation. Additionally, it examined whether these factors were specific to poly-victimised children or also associated with fewer mental health difficulties in young adults regardless of whether they had been poly-victimised.

We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a population-representative cohort of 2,232 children born in 1994–1995 across England and Wales and followed to 18 years of age (with 93% retention, n = 2,066). Poly-victimisation (i.e., exposure to two or more of physical abuse, sexual abuse, emotional abuse and neglect, physical neglect, bullying by peers, and domestic violence) and nine putative protective factors (intelligence quotient, executive functioning, temperament, maternal and sibling warmth, atmosphere at home, maternal monitoring, neighbourhood social cohesion, and presence of a supportive adult) were measured prospectively between ages 5 and 12 years from interviews with mothers and children, surveys of neighbours, child-protection referrals, and researchers’ observations. Early-adulthood psychopathology was assessed in interviews with each twin at age 18 and used to construct a latent factor of general psychopathology.

Approximately a third (n = 720) of participants were prospectively defined as exposed to poly-victimisation (53% male). Poly-victimised children had greater levels of general psychopathology at age 18 than non-poly-victimised children (adjusted [adj.] β = 4.80; 95% confidence interval [95% CI] 3.13, 6.47). Presence of a supportive adult was the only factor robustly associated with lower levels of general psychopathology among poly-victimised children (adj.β = −0.61; 95% CI −0.99, −0.23). However, this association was also evident in the whole sample regardless of poly-victimisation exposure (adj.β = −0.52; 95% CI −0.81, −0.24) and no significant interaction was observed between the presence of a supportive adult and poly-victimisation in relation to age-18 general psychopathology.

Having at least one adult to turn to for support was found to be associated with less psychopathology in early adulthood among both poly-victimised and non-poly-victimised children. This suggests that strategies to promote better availability and utilisation of supportive adults should be implemented universally. However, it may be beneficial to target these interventions at poly-victimised children, given their higher burden of psychopathology in early adulthood.

The aim of this 4-year follow-up study was to examine the predictive effects of demographics, three types of sexual stigma, three types of self-identity confusion, anxiety, depression, family support and problematic Internet use before the coronavirus disease 2019 (COVID-19) pandemic on new-onset suicide risk and persistent suicide risk in young adult lesbian, gay and bisexual individuals who experienced the COVID-19 pandemic in Taiwan.

Baseline data were collected from 1,000 lesbian, gay and bisexual individuals in 2018 and 2019. Outcome data on suicide risk were collected again in 2023. The suicide module of the Mini International Neuropsychiatric Interview was used to assess suicide risk in terms of thoughts of death, desire to self-harm, thoughts of suicide, plans for suicide and suicide attempts in the preceding month at the initial and follow-up assessments. Baseline three types of sexual stigma, self-identity disturbance, depression, anxiety and problematic Internet use were used to examine their prediction of new-onset suicide risk and persistent suicide risk at follow-up.

In total, 673 individuals participated in the follow-up survey. Notably, 16.5% of the participants who had no suicide risk at baseline had new-onset suicide risk at follow-up; 46.4% of the participants who had suicide risk at baseline also had suicide risk at follow-up. Participants who were transgender (p = .003), who perceived greater levels of microaggression (p < .001), and who had greater levels of problematic Internet use at baseline (p = .024) were more likely to have new-onset suicide risk at follow-up. Participants who had greater levels of self-identity confusion were more likely to have persistent suicide risk at follow-up (p = .023).

Intervention strategies for reducing suicide risk in lesbian, gay and bisexual individuals should be developed with consideration of the predictors identified in this study.

There is considerable evidence that waiting list (WL) control groups overestimate the effect sizes of psychotherapies for depression. It is not clear, however, what are the exact causes for this overestimation. We decided to conduct a meta-analytic study to compare trials on psychotherapy for depression with a WL control group against trials with a care-as-usual (CAU) control group.

We used an existing meta-analytic database of randomized trials comparing psychological treatments of adult depression with control groups and selected trials using a WL or a CAU control group. We used subgroup and meta-regression analyses to examine differences in effect sizes between WL and CAU controlled trials.

We included 333 randomized controlled trials (472 comparisons; total number participants: 41,480), 141 with a WL and 195 with a CAU control group (3 included both). We found several significant differences between WL and CAU controlled trials (in type of therapy examined, treatment format, recency, target group, recruitment strategy, number of treatment arms and number of depression outcome measures). The overall effect size indicating the difference between treatment and control at post-test for all comparisons was g = 0.77 (95% confidence interval [CI]: 0.71; 0.84) with high heterogeneity (I2 = 84; 95% CI: 82; 85). A highly significant difference was observed between studies with a CAU control group (g = 0.63; 95% CI: 0.55; 0.71; I2 = 85; 95% CI: 83; 86) and studies with a WL (g = 0.95; 95% CI: 0.85; 1.04; I2 = 80; 95% CI: 78; 82; p for difference < 0.001). This difference remained significant in all sensitivity analyses, including a meta-regression analysis in which we adjusted for all differences in characteristics of studies with a WL versus CAU control group. We also found that pre-post effect sizes in WL control conditions (g = 0.37; 95% CI: 0.28; 0.46) were significantly smaller than change within CAU conditions (g = 0.64; 95% CI: 0.50; 0.78). We found few indications that pre-post effect sizes within therapy conditions differed between WL and CAU controlled trials.

WL control conditions considerably overestimate the effect sizes of psychological treatments, compared to trials using CAU control conditions. This overestimation is probably caused by a smaller improvement within the WL condition compared to the improvement in the CAU condition. WL control conditions should be avoided in randomized trials examining psychological treatments of adult depression.

The role of depression in subsequent infertility, miscarriage and stillbirth remains unclear. This study aimed to examine the association of a history of depression with these adverse outcomes using a longitudinal cohort study of women across their reproductive life span.

This study used data from participants in the Australian Longitudinal Study on Women’s Health who were born in 1973–1978. Participants (N = 8707) were followed up every 3 years from 2000 (aged 22–27) to 2018 (aged 40–45). Information on a diagnosis of depression was collected from each survey, and antidepressant medication use was identified through pharmaceutical prescription data. Histories of infertility, miscarriage, and stillbirth were self-reported at each survey. Time-lagged log-binomial models with generalized estimating equations were used to assess the association of a history of depression up to and including in a given survey with the risk of fertility issues in the next survey.

Women with a history of depression (excluding postnatal depression) were at higher risk of infertility [risk ratio (RR) = 1.34, 95% confidence interval (CI): 1.21–1.48], miscarriage (RR = 1.22, 95%CI: 1.10–1.34) and recurrent miscarriages (≥2; RR = 1.39, 95%CI: 1.17–1.64), compared to women without a history of depression. There were too few stillbirths to provide clear evidence of an association. Antidepressant medication use did not affect the observed associations. Estimated RRs of depression with infertility and miscarriage increased with age.

A history of depression was associated with higher risk of subsequent infertility, miscarriage and recurrent miscarriages.