Behavioural activation is effective for depression, but its effectiveness in treating adults with depression when delivered by lay workers remains unclear.

To examine the effectiveness of behavioural activation delivered by lay workers, compared with any control group, in reducing depressive symptoms in adults.

This systematic review searched six databases from inception to January 2025, for randomised controlled trials (RCTs) comparing behavioural activation and any control conditions for individuals with depression when delivered by lay workers. Additional searches were conducted in the international trial registries and reference lists (PROSPERO registration CRD42024625620). Risk of bias was assessed using the Cochrane Collaboration’s Risk-of-Bias 2 tool. Random effects meta-analysis was conducted using the Metafor package in R.

Of 9614 initial studies, six RCTs met the inclusion criteria and were included. A total of 1118 participants in the intervention groups and 1596 in the control groups. The findings demonstrated a small but statistically significant effect in reducing depressive symptoms in favour of the intervention group (standardised mean difference: −0.28, 95% CI −0.46 to −0.09; p = 0.0029). However, the risk of bias was high across all studies, with substantial heterogeneity (I2 = 76%).

Evidence from this review and meta-analysis suggests that behavioural activation, when delivered by trained lay workers, may offer an effective approach for reducing depressive symptoms in adults, particularly in settings with limited access to specialist mental healthcare professionals. However, high risk of bias and heterogeneity of the included studies means that these findings should be interpreted with caution.

The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Neuropsychiatric symptoms are common after traumatic brain injury (TBI) and often resolve within 3 months post-injury. However, the degree to which individual patients follow this course is unknown. We characterized trajectories of neuropsychiatric symptoms over 12 months post-TBI. We hypothesized that a substantial proportion of individuals would display trajectories distinct from the group-average course, with some exhibiting less favorable courses.

Participants were level 1 trauma center patients with TBI (n = 1943), orthopedic trauma controls (n = 257), and non-injured friend controls (n = 300). Trajectories of six symptom dimensions (Depression, Anxiety, Fear, Sleep, Physical, and Pain) were identified using growth mixture modeling from 2 weeks to 12 months post-injury.

Depression, Anxiety, Fear, and Physical symptoms displayed three trajectories: Stable-Low (86.2–88.6%), Worsening (5.6–10.9%), and Improving (2.6–6.4%). Among symptomatic trajectories (Worsening, Improving), lower-severity TBI was associated with higher prevalence of elevated symptoms at 2 weeks that steadily resolved over 12 months compared to all other groups, whereas higher-severity TBI was associated with higher prevalence of symptoms that gradually worsened from 3–12 months. Sleep and Pain displayed more variable recovery courses, and the most common trajectory entailed an average level of problems that remained stable over time (Stable-Average; 46.7–82.6%). Symptomatic Sleep and Pain trajectories (Stable-Average, Improving) were more common in traumatically injured groups.

Findings illustrate the nature and rates of distinct neuropsychiatric symptom trajectories and their relationship to traumatic injuries. Providers may use these results as a referent for gauging typical v. atypical recovery in the first 12 months post-injury.