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Analysis of large-scale representative data from the Chinese National Transgender Survey finds that exposure to gender identity conversion practice is a risk factor for mental health problems, worsens mental health disorder severity and increases suicidality.
Using machine learning, Zhang et al. identify EEG signature to predict psychotherapy outcomes in PTSD, paving the way towards the development of scalable biomarkers.
Tully et al. detected increased variability in brain total grey matter volume in individuals with disruptive behaviour disorder and antisocial personality disorder.
Seitz-Holland et al. examined the relationship between systemic cellular senescence markers and clinical variables in late-life depression. The authors find that signs of enhanced cellular senescence are associated with poor cardiometabolic health, older age, male sex and worse cognition.
Using data-driven disease-progression modelling, Jiang, Wang, Zhou et al. characterized and replicated two distinct ‘trajectories’ of brain atrophy in patients with schizophrenia.
Cash et al. examined whether coordinates derived from neuroimaging studies might delineate a dysfunctional brain network in unipolar depression rather than isolated neuroanatomical foci. The authors found highly robust distributed brain networks that closely recapitulate clinically meaningful models of depression circuitry.
Lee et al. combined data from mobile phone users, green spaces distribution and the United Kingdom Household Longitudinal Survey from 2020 to 2021 to evaluate how access to green spaces affected people’s mental health during COVID-19 pandemic lockdowns.
Lee et al. identify a positive relationship between life stress and current psychological symptoms in individuals with low, but not high, cortisol response and positive affectivity.
In this prospective cohort study of Syrian refugee children living in Lebanon, authors identified that daily exposure to stressors was the factor most strongly associated with children’s mental health problems.
Using magnetic resonance imaging and connectome-based predictive modelling, Gao et al. find that brain connectivity data can predict suicide risk in patients with late-life depression.
Traynor, Ruocco et al. find that the conjoint magnetic seizure therapy and dialectical behaviour therapy lead to a rapid, significant and clinically meaningful reduction in suicidal ideation in individuals with comorbid borderline personality disorder and treatment-resistant depression.
Man, Gao and colleagues find that methylphenidate treatment in children with attention deficit hyperactivity disorder is associated with reduced risk of physical abuse.
In this network and pairwise meta-analysis of 498 brain imaging studies, McCutcheon et al. demonstrate patterns of distinct and overlapping brain volume changes across psychiatric disorders.
Osimo et al. developed two models to predict the risk of treatment-resistant schizophrenia in patients with a first-episode psychosis using blood-based biomarkers and sociodemographic data routinely collected at psychosis onset in psychosis early intervention services in the United Kingdom. They used clozapine treatment as a proxy for treatment-resistant schizophrenia using data from 785 patients for model development and 1,110 patients for external validation.