217 papers
Understanding the human mind and treating mental health conditions requires a deep blend of biological insight and behavioral science. This category explores the cutting-edge research shaping how we diagnose and treat psychiatric disorders, from depression and anxiety to complex neurological conditions. Here, you will find the latest discoveries that bridge the gap between clinical observation and molecular mechanisms, offering fresh perspectives on patient care and therapeutic innovation.
Gist.Science brings these vital studies directly to you by monitoring medRxiv, the leading preprint server for health sciences. As soon as new manuscripts appear in this field, our team processes them to provide both accessible plain-language summaries and detailed technical overviews. This ensures that complex findings are understandable for everyone, from curious readers to busy professionals who need quick, accurate insights without wading through dense academic prose.
Below are the most recent psychiatry and clinical psychology preprints, curated and summarized to keep you informed on the evolving landscape of mental health research.
This paper presents a protocol and literature review for the "Impact Log," a novel, lived-experience-led tool and framework designed to systematically record, evaluate, and enhance the impact of co-production across all stages of the Brain and Genomics Hub's multidisciplinary research on severe mental illness.
This systematic review and meta-analysis of 68 studies involving over 82,000 participants reveals that posttraumatic stress disorder affects approximately 43% of conflict-affected adults in Sub-Saharan Africa, with significantly higher rates among refugees and strong associations with female sex, comorbid depression, and cumulative trauma exposure.
This study demonstrates that passive smartphone-based mobile sensing provides a valid, scalable, and robust alternative to actigraphy for monitoring sleep timing and duration in adolescents and young adults with bipolar disorder.
This study validates the Riga Cognitive Screening Task as an effective tool for identifying cognitive impairment in older adults by demonstrating significant multivariate covariance between its performance scores and cortical thickness in temporal and parietal brain regions.
This cross-sectional study of 297 adults with glaucoma at a tertiary hospital in Tanzania found that 11.1% experienced probable depressive symptoms, with strong and moderate social support identified as significant protective factors against depression.
This study demonstrates that in cognitively normal and mild cognitive impairment individuals, apathy associated with Mild Behavioural Impairment is significantly linked to reduced cortical thickness and grey matter volume in Alzheimer's disease-vulnerable regions, suggesting it reflects early AD-related neurodegeneration rather than traditional apathy-related structural changes.
This global cross-sectional survey of 1,732 medical researchers found that 38.8% are at risk of burnout, with higher levels of trait mindfulness serving as a significant independent protective factor against burnout risk after controlling for socio-demographic variables.
This study demonstrates that plasma lipidomic alterations, particularly in specific lipid classes like sphingolipids and phosphatidylcholines, robustly track multidimensional psychosis severity across schizophrenia and bipolar disorder, suggesting these lipid changes reflect transdiagnostic biological processes linked to illness burden that are not fully captured by categorical diagnoses or polygenic risk scores.
This longitudinal study of over 10,000 Belgian adults from 2020 to 2024 reveals that while most individuals maintained stable mild mental health symptoms, a significant minority experienced worsening anxiety and depression over time, driven by risk factors like financial insecurity and loneliness, while protective factors such as social support and life satisfaction played crucial but evolving roles in mitigating symptom severity.
In a large-scale, real-world quasi-experimental study, embedding AI-enabled continuous care features into routine psychotherapy was found to significantly improve early treatment engagement and accelerate the reduction of depressive and anxiety symptoms compared to psychotherapy alone.