It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.

To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.

Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.

IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).

Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

The Hierarchical Taxonomy of Psychopathology (HiTOP) and Research Domain Criteria (RDoC) frameworks emphasize transdiagnostic and mechanistic aspects of psychopathology. We used a multi-omics approach to examine how HiTOP’s psychopathology spectra (externalizing [EXT], internalizing [INT], and shared EXT + INT) map onto RDoC’s units of analysis.

We conducted analyses across five RDoC units of analysis: genes, molecules, cells, circuits, and physiology. Using genome-wide association studies from the companion Part I article, we identified genes and tissue-specific expression patterns. We used drug repurposing analyses that integrate gene annotations to identify potential therapeutic targets and single-cell RNA sequencing data to implicate brain cell types. We then used magnetic resonance imaging data to examine brain regions and circuits associated with psychopathology. Finally, we tested causal relationships between each spectrum and physical health conditions.

Using five gene identification methods, EXT was associated with 1,759 genes, INT with 454 genes, and EXT + INT with 1,138 genes. Drug repurposing analyses identified potential therapeutic targets, including those that affect dopamine and serotonin pathways. Expression of EXT genes was enriched in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT + INT liability was associated with reduced gray matter volume in the amygdala and subcallosal cortex. INT genetic liability showed stronger causal effects on physical health – including chronic pain and cardiovascular diseases – than EXT.

Our findings revealed shared and distinct pathways underlying psychopathology. Integrating genomic insights with the RDoC and HiTOP frameworks advanced our understanding of mechanisms that underlie EXT and INT psychopathology.

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in individuals genetically similar to European reference panels (EUR-like; n = 16,400 to 1,074,629). Traits included clinical (e.g. major depressive disorder, alcohol use disorder) and subclinical measures (e.g. risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

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.

In RISE, TV46000 once monthly (q1m) or once every 2 months (q2m) significantly extended time to impending schizophrenia relapse. The current study (SHINE, NCT03893825) evaluated the long-term safety, tolerability, and effect of TV46000.

Patients completing RISE without relapse (rollover) or newly recruited (de novo) were eligible. The de novo and placebo rollover cohorts were randomized 1:1 to q1m or q2m for ≤56 weeks; the TV46000 rollover cohort continued assigned regimen. Exploratory efficacy endpoints included time to impending relapse and patient centered outcomes (PCOs) including Schizophrenia Quality of Life Scale (SQLS).

334 patients were randomized and received TV46000 q1m (n=172) or q2m (n=162), for 202.3 patient-years [PY] of TV-46000 treatment. Treatment-emergent adverse events (AEs) reported for ≥5% of patients were: overall–injection site pain (event rate/100 PY, n [%]; 23.23, 16 [5%]); de novo (n=109)–injection site pain (56.10, 11 [10%]), injection site nodule (16.03, 6 [6%]), blood creatine phosphokinase increased (16.03, 8 [7%]), urinary tract infection (10.69, 7 [6%]); placebo rollover (n=53)–tremor (18.50, 5 [9%]); TV46000 rollover (n=172)–headache (7.97, n=8 [5%]). Serious AEs reported for ≥2 patients were worsening schizophrenia and hyperglycemia. Kaplan– Meier estimates for remaining relapse-free at week 56 were 0.98 (2% risk; q1m) and 0.88 (12%; q2m). SQLS improved for q1m (least-squares mean change [SE], − 2.16 [0.98]) and q2m (− 0.43 [0.98]); other PCOs (5Level EuroQoL 5Dimensions Questionnaire, Personal and Social Performance Scale, Drug Attitudes Inventory 10-item version) remained stable.

TV-46000 had a favorable long-term benefit–risk profile in patients with schizophrenia.

Teva Branded Pharmaceutical Products R&D Inc.

Study Registration Number: NCT03893825

Understanding characteristics of healthcare personnel (HCP) with SARS-CoV-2 infection supports the development and prioritization of interventions to protect this important workforce. We report detailed characteristics of HCP who tested positive for SARS-CoV-2 from April 20, 2020 through December 31, 2021.

CDC collaborated with Emerging Infections Program sites in 10 states to interview HCP with SARS-CoV-2 infection (case-HCP) about their demographics, underlying medical conditions, healthcare roles, exposures, personal protective equipment (PPE) use, and COVID-19 vaccination status. We grouped case-HCP by healthcare role. To describe residential social vulnerability, we merged geocoded HCP residential addresses with CDC/ATSDR Social Vulnerability Index (SVI) values at the census tract level. We defined highest and lowest SVI quartiles as high and low social vulnerability, respectively.

Our analysis included 7,531 case-HCP. Most case-HCP with roles as certified nursing assistant (CNA) (444, 61.3%), medical assistant (252, 65.3%), or home healthcare worker (HHW) (225, 59.5%) reported their race and ethnicity as either non-Hispanic Black or Hispanic. More than one third of HHWs (166, 45.2%), CNAs (283, 41.7%), and medical assistants (138, 37.9%) reported a residential address in the high social vulnerability category. The proportion of case-HCP who reported using recommended PPE at all times when caring for patients with COVID-19 was lowest among HHWs compared with other roles.

To mitigate SARS-CoV-2 infection risk in healthcare settings, infection prevention, and control interventions should be specific to HCP roles and educational backgrounds. Additional interventions are needed to address high social vulnerability among HHWs, CNAs, and medical assistants.

Major depressive disorder (MDD) contributes to suicide risk. Treating MDD effectively is considered a key suicide prevention intervention. Yet many patients with MDD do not respond to their initial medication and require a ‘next-step’. The relationship between next-step treatments and suicidal thoughts and behaviors is uncharted.

The VA Augmentation and Switching Treatments for Depression trial randomized 1522 participants to one of three next-step treatments: Switching to Bupropion, combining with Bupropion, and augmenting with Aripiprazole. In this secondary analysis, features associated with lifetime suicidal ideation (SI) and attempts (SA) at baseline and current SI during treatment were explored.

Compared to those with SI only, those with lifetime SI + SA were more likely to be female, divorced, or separated, unemployed; and to have experienced more childhood adversity. They had a more severe depressive episode and were more likely to respond to ‘next-step’ treatment. The prevalence of SI decreased from 46.5% (694/1492) at baseline to 21.1% (315/1492) at end-of-treatment. SI during treatment was associated with baseline SI; low positive mental health, more anxiety, greater severity and longer duration of current MDD episode; being male and White; and treatment with S-BUP or C-BUP as compared to A-ARI.

SI declines for most patients during next-step medication treatments. But about 1 in 5 experienced emergent or worsening SI during treatment, so vigilance for suicide risk through the entire 12-week acute treatment period is necessary. Treatment selection may affect the risk of SI.

While studies from the start of the COVID-19 pandemic have described initial negative effects on mental health and exacerbating mental health inequalities, longer-term studies are only now emerging.

In total, 34 465 individuals in the UK completed online questionnaires and were re-contacted over the first 12 months of the pandemic. We used growth mixture modelling to identify trajectories of depression, anxiety and anhedonia symptoms using the 12-month data. We identified sociodemographic predictors of trajectory class membership using multinomial regression models.

Most participants had consistently low symptoms of depression or anxiety over the year of assessments (60%, 69% respectively), and a minority had consistently high symptoms (10%, 15%). We also identified participants who appeared to show improvements in symptoms as the pandemic progressed, and others who showed the opposite pattern, marked symptom worsening, until the second national lockdown. Unexpectedly, most participants showed stable low positive affect, indicating anhedonia, throughout the 12-month period. From regression analyses, younger age, reporting a previous mental health diagnosis, non-binary, or self-defined gender, and an unemployed or a student status were significantly associated with membership of the stable high symptom groups for depression and anxiety.

While most participants showed little change in their depression and anxiety symptoms across the first year of the pandemic, we highlight the divergent responses of subgroups of participants, who fared both better and worse around national lockdowns. We confirm that previously identified predictors of negative outcomes in the first months of the pandemic also predict negative outcomes over a 12-month period.