Psychiatry

Artificial Intelligence for Enhancing Emotion Expression in Augmentative and Alternative Communication Systems: A Preliminary Study Including Children Both With and Without Autism.

PURPOSE: Artificial intelligence is increasingly being explored in augmentative and alternative communication (AAC) to support personalized and responsive communication. Integrating emotion recognition into AAC systems may help users convey emotion content in real time, enhancing social interaction and communication quality. METHOD: This preliminary study utilized DeepFace, a facial emotion recogn...

360° Video-Based Virtual Reality for Preparing Medical Students for Body Donor Dissection: Randomized Controlled Trial.

BACKGROUND: Body donor dissection is fundamental to medical education but often induces anxiety and emotional distress in students, potentially impacting learning outcomes and well-being. Traditional preparation methods emphasize technical and procedural elements while inadequately addressing students' emotional challenges. Recent advances in educational technology, particularly 360° video-based v...

Prediction of treatment response and adverse events in pediatric ADHD treated with acupuncture combined with conventional treatment.

INTRODUCTION: To develop and externally validate machine learning (ML) models for predicting treatment response and adverse events in children with at...

Using Ultra-Abridged Individual Difference Scales for Personalization in Digital Mental Health to Improve Uptake, Engagement, and Experiences: Three-Tiered Decision Framework for Scale Shortening.

Given the diversity of human characteristics and experiences, personalization in nudges, messages, choice presentations, interventions, and overall pr...

A large-scale annotated Urdu corpus and deep learning benchmark for mental health classification.

Millions of people worldwide are affected by mental health disorders, particularly anxiety and depression, which pose a growing health concern globall...

Utilization of Heritage Manifestations in a Reminiscence Programme (App) Directed at Older Adults with and Without Neurocognitive Disorder, Employing AI: A Pilot Study in Portugal and Spain.

Cultural and intangible heritage has been part of human daily life since time immemorial, fulfils a function within the community and acts as an eleme...

Exploration of comorbidity mechanisms between chronic pain and depression: Machine learning prediction models and SHAP interpretability analysis based on the CHARLS cohort.

INTRODUCTION: With rapid population aging in China, depression among middle-aged and older adults has become a major public health concern. Chronic pa...

State anxiety may mediate the association between striato-cortical circuitry and anxiety symptom severity in generalized anxiety disorder: A resting-state fMRI study and support vector machine analysis.

BACKGROUND: Patients with generalized anxiety disorder (GAD) show structural and functional striatal abnormalities. While state and trait anxiety are ...

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples.

Human social interactions rely on the ability to reflect on one's own and others' internal states and traits-a process known as mentalizing. Impaired ...

Regional variability in the associations between social and health-related risk factors and memory across Europe.

Interventions targeting social and health-related risk factors are thought to reduce the risk of cognitive decline and dementia in older age. Despite ...

Home-based eye tracking for early autism screening: a scoping review of approaches, evidence, and implementation challenges.

BACKGROUND: Early identification of autism spectrum disorder (ASD) is essential for improving developmental outcomes but remains challenging due to di...

Career anxiety in the age of artificial intelligence: Survey data of university students in Bangladesh.

Career anxiety has become a significant issue in today's world, particularly in developing countries where job opportunities are scarce compared to th...

Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study.

PURPOSE: To develop and validate a machine learning (ML)‑based model for predicting malnutrition risk in patients undergoing maintenance peritoneal di...

Developing and Testing a Brief Mindfulness Just-in-Time Adaptive Intervention to Reduce Stress Among Caregivers of People With Dementia: Quasi-Experimental Study.

BACKGROUND: Dementia caregiving entails chronic, fluctuating stress with downstream risks to caregivers' mental health and quality of care. Mindfulnes...

Exploratory eye movement characteristics to aid screening of schizophrenia and bipolar disorder: A cross-sectional outpatient study.

Current psychiatric diagnoses lack objective criteria, and this study aims to evaluate EEM as a potential tool for improving diagnostic objectivity ac...

Prediction of an fMRI-based schizophrenia biomarker from EEG using dynamic functional connectivity: a simultaneous EEG-fMRI study.

OBJECTIVE: Recent advances in functional magnetic resonance imaging (fMRI) have identified brain functions associated with psychiatric disorders using...

Determining the relative importance of risk and protective factors for adjustment disorder symptoms during the COVID-19 pandemic by mixed-effects random forests.

BACKGROUND: The COVID-19 pandemic exposed individuals to numerous psychosocial and health-related stressors associated with adjustment disorder (AjD) ...

Resting-state EEG microstates as biomarkers for major depressive disorder.

OBJECTIVES: To investigate the temporal dynamics of resting-state electroencephalography (EEG) microstates in patients with Major Depressive Disorder ...

Integrating epidemiologic modeling and explainable machine learning to predict and identify factors associated with self-reported depression among adults in Tennessee, United States.

BACKGROUND: Depression is a major public health concern, with Tennessee ranking among the U.S. states with the highest prevalence. Despite its burden,...

Large Language Models and Metabolic Bariatric Surgery: A Pilot Concordance Study Between ChatGPT and Multidisciplinary Team Recommendations.

INTRODUCTION: Operation selection in metabolic surgery is a complex decision making process led by a multidisciplinary team that integrates multiple a...