Zhao, Yang et al. used UK Biobank data to examine the role of lifestyle factors in depression. They conducted multiple analyses and estimated underlying mechanisms related to brain structure, immunometabolism and genetics.

The authors conducted a systematic review and individual participant data meta-analysis of 14 studies to evaluate psychological interventions for depression relapse prevention.

Using a large sample from the UK Biobank, the authors investigate the effects of dietary patterns on multiple aspects of brain health and mental health.

The authors conducted a systematic review and individual participant data meta-analysis of 14 studies to evaluate psychological interventions for depression relapse prevention.

Generative artificial intelligence (AI), exemplified by large language models such as ChatGPT, shows promise in mental health practice, aiding research, training and therapy. However, bias, inaccuracy and trust issues necessitate careful integration with human expertise.

Using a large US cohort of adolescents, the authors examine exposomic and polygenic contributions to allostatic load and a mediating role of allostatic load on the path from exposomic and polygenic risks to psychopathology.

ADHD is the most common neurodevelopmental disorder in children, yet despite a large increase in awareness and in the number of diagnoses, much less is known about how this disorder affects adults. More research is needed to understand how ADHD may present differently as a function of age or how the experience of ADHD may change in people as they age.

In this Review, the authors discuss the neurobiological mechanisms of motor cortex-related analgesia, drawing insights from both experimental data and clinical data.

Authors present data supporting a neuropsychological pathway between emotion dysregulation and ADHD symptoms involving morphometry of the right pars orbitalis, transcriptomic, and white blood cell markers.

Applying machine learning to an objective framework for suicidality, the authors demonstrate that four suicidal thought and behavior variables can be predicted with high accuracy and may present a scalable system for suicide risk assessment.

Increasing inequality and social fragmentation may give rise to a collective state of despair that may not only diminish the desire to live but also dampen the drive to reproduce, resulting in shrinking fertility and population decline.

The COVID-19 pandemic has caused profound mental health problems among left-behind children (LBC). Here we discuss the challenges that LBC are facing in the post-COVID-19 era and the potential underlying mechanisms, and provide recommendations for future policy priorities.

In this Review, the authors cover the latest understanding of ensemble deep learning models as a means to complement Alzheimer’s disease diagnosis.