The overall observed prevalence estimate was similar to estimates calculated using Bayesian hierarchical and random effects models, and ASD prevalence was lower among non-Hispanic White (White) children than among Asian or Pacific Islander (A/PI) children (27.7) than among Asian or Pacific Islander (A/PI) children (38.5).
Proposed models for the neural circuitry of normal anxiety as well as the anxiety disorders are discussed.
A randomized controlled trial testing an expert–fine-tuned Gen-AI–powered chatbot, Therabot, for mental health treatment of adults with clinically significant symptoms of major depressive disorder, generalized anxiety disorder, or at clinically high risk for feeding and eating disorders.
The behavioral data in healthy controls with and without genetic risk for depression, and in patient populations during the symptomatic phase of depression and when being remitted, suggest a trait abnormality of serotonin function in depression and that antidepressants may compensate for the underlying deficit.
A computational model called Centaur, developed by fine-tuning a language model on a huge dataset called Psych-101, can predict and simulate human nature in experiments expressible in natural language, even in previously unseen situations.
This position paper argues that the promise of LLM social simulations can be achieved by addressing five tractable challenges, and identifies promising directions, including context-rich prompting and fine-tuning with social science datasets.
Homer-regulated PSD remodeling may represent a mechanism of synaptic plasticity and a putative target for both pharmacotherapy and pharmacogenomics of behavioral disorders.
This Review describes how natural language processing (NLP) can be used to analyse text data in behavioural science, and provides actionable recommendations for using NLP to ensure rigour and reproducibility.
GBD 2021 showed that the burden of mental disorders has increased over the past three decades, with notable regional disparities, and high SDI regions and females should be paid more attention.
This work explores how increasingly capable AI agents may generate the perception of deeper relationships with users, especially as AI becomes more personalised and agentic.
A systematic review of the literature on augmentation strategies for major depression found no evidence of clinical efficacy as measured by response in augmentation with buspirone, testosterone, methylphenidate, yohimbine, inositol, and atomoxetine and future research will need to investigate optimal duration of augmentation therapy.
The role of neuroinflammation in depression is explored, focusing on glial cell activation, cytokine signaling, blood–brain barrier dysfunction, and disruptions in neurotransmitter systems, to highlight how inflammatory mediators influence brain regions implicated in mood regulation.
Results in schizophrenia are consistent with previous findings in depression where having a higher percent of patients randomized to placebo increased drug-placebo differences.
It is argued that social scientists can address many of these limitations of Generative AI by creating open-source infrastructure for research on human behavior, not only to ensure broad access to high-quality research tools, but also because the progress of AI will require deeper understanding of the social forces that guide human behavior.
Testing two families of large language models (LLMs) (GPT and LLaMA2) on a battery of measurements spanning different theory of mind abilities, Strachan et al. find that the performance of LLMs can mirror that of humans on most of these tasks.
A roadmap for the ambitious yet responsible application of clinical LLMs in psychotherapy is provided and a vision is outlined for how LLMs might enable a new generation of studies of evidence-based interventions at scale, and how these studies may challenge assumptions about psychotherapy.
Estimates from the 2022 NSCH provide information on pediatric ADHD during the last full year of the COVID-19 pandemic and can be used by policymakers, government agencies, health care systems, public health practitioners, and other partners to plan for needs of children with ADHD.
The Banbury Forum reviewed the evidence for DMHTs, identified the challenges to successful and sustainable implementation, investigated the factors that contributed to more successful implementation internationally, and developed the following recommendations: guided DMHTs should be offered to all patients experiencing common mental disorders, DMHT products and services should be reimbursable to support integration into the U.S. health care system.
The necessity for longitudinal studies to explore the long-term effects of AI on educational outcomes and mental health is suggested and the importance of incorporating student perspectives for a thorough understanding of AI’s role in education is underscored.
This study presents, for the first time in GBD, a quantification of the mean age at the time of suicide death, alongside comprehensive estimates of the burden of suicide throughout the world.
A higher socio‐demographic index moderated lower recovery and higher chronicity in AN across countries, and children/adolescents had more favorable outcomes across and within EDs than adults.
How ChatGPT fosters dependency through key features such as personalised responses, emotional validation, and continuous engagement is explored, highlighting the need for further research into the psychological and social impacts of prolonged interaction with AI tools like ChatGPT.
Inspired by Jürgen Habermas’s theory of communicative action, the “Habermas Machine” was designed to iteratively generate group statements that were based on the personal opinions and critiques from individual users, with the goal of maximizing group approval ratings.
Participants with resolved persistent symptoms after Covid-19 had objectively measured cognitive function similar to that in participants with shorter-duration symptoms, although short-duration Covid-19 was still associated with small cognitive deficits after recovery.
The paper first defines AI and its scope in the area of mental health, then it looks at various facets of AI like machine learning, supervised machine learning and unsupervised machine learning and other facets of AI.
An online survey was conducted to assess psychiatrists' familiarity with the metabolic syndrome and its components in patients with bipolar disorder, and characterize their perspectives and practices regarding its impact on patient management.
An exhaustive umbrella review was conducted to systematically assess the prevalence and determinants of pain, depression, and anxiety among cancer survivors worldwide by analyzing systematic reviews and meta-analyses and found that depression and anxiety prevalence among cancer survivors was 33.16% and 30.55%, respectively, with significantly higher rates during COVID-19 at 43.25% and 52.93%.
Several key domains that may be relevant to the characterization of the individual patient with a FED aimed at personalization of management are reviewed, including symptom profile, clinical subtypes, severity, clinical staging, physical complications and consequences, antecedent and concomitant psychiatric conditions and neurobiological markers.
Key recommendations include a focus on metabolic health from treatment initiation, timely assessment and management of non-response, symptom domain-specific interventions, mitigation of side-effects, and the prompt use of clozapine in cases of treatment resistance.
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