Psychiatry

Heterogeneity of depression and suicidal ideation among college students in Eastern China: a latent profile analysis and machine learning approach.

To investigate the heterogeneity of depression and suicidal ideation among Chinese college students and to examine the roles of family and individual psychological factors in differentiating risk profile. A total of 4,368 college students completed measures of depression, suicidal ideation, parental rejection, parent-child relationship, psychological resilience, and self-control. Latent profile an...

Abnormal dynamics of brain networks in bipolar disorder: a dynamic degree centrality and imaging-transcriptomic investigation.

Boon or a bane: Different usage of LLM correlates with mental health.

BACKGROUND: While large language models (LLMs) are increasingly integrated into daily life, the relationship between purpose-specific usage and mental...

Matrix-dependent analytical strategies for the detection of drug-infused foods: A comprehensive review.

Drug-infused foods are increasingly encountered in forensic investigations, including drug-facilitated crimes (DFC), chemical submission cases, and th...

Exploring schizophrenia-associated image-derived digital phenotypes in dual-energy X-ray densitometer scans of non-dominant distal forearm: An explainable machine-learning framework.

Schizophrenia remains diagnosed primarily through clinical assessment, which motivates the researchers to search for quantifiable digital phenotypes. ...

Neuroimaging-Based Subgroups in Schizophrenia: A Critical Appraisal of Clustering Studies.

Efforts to define biologically grounded subtypes of schizophrenia have increasingly leveraged neuroimaging data and clustering algorithms. Such approa...

Integrating EEG microstate dynamics in a stacked ensemble for neurodiagnostic ASD assessment.

Autism Spectrum Disorder (ASD) remains diagnostically challenging due to its neurobiological heterogeneity and the current reliance on subjective beha...

Factors influencing disinformation avoidance behavior among generative artificial intelligence users: A cognition-affect-conation framework.

This study aimed to uncover the mechanisms driving disinformation avoidance behavior among generative artificial intelligence users to reduce negative...

Building a Science-Driven Business: How National Institutes of Health Funding Enabled an Evidence-Based Approach to Maternal Mental Health Innovation.

The digital mental health (DMH) industry has grown drastically over the last decade; yet, many DMH products have failed to demonstrate meaningful clin...

Comprehensive integrative analysis of Exosome-associated genes in major depressive disorder: Diagnostic biomarker discovery, immune modulation, and therapeutic implications.

OBJECTIVE: This study systematically analyzed the expression profiles of exosome-associated genes in Major Depressive Disorder (MDD), constructed diag...

Monitoring airline pilot mental health: a 3PM framework utilising digital phenotyping and AI.

The aeromedical certification of commercial airline pilots relies on periodic, self-disclosure-dependent assessments. However, this reactive model lac...

Cerebellar gray matter volume difference in first-episode bipolar and unipolar depression.

BACKGROUND: Early differential diagnosis of bipolar disorder (BD) and unipolar depression (UD) remains a major clinical challenge, especially during t...

A multimodal fNIRS-based machine learning model for symptom assessment and treatment response prediction in schizophrenia.

OBJECTIVE: Predicting early symptom severity and treatment response in schizophrenia is crucial for selecting optimal therapeutic strategies. This stu...

A comparative evaluation of EEG-based deep learning models for schizophrenia detection with cross-dataset validation and explainable AI.

OBJECTIVES: Schizophrenia is a neuropsychiatric disorder that affects emotional, behavioral, and brain functions that can be tracked using electroence...

Effectiveness of a Fully Automated Mobile Therapeutic Versus a General Chatbot in Reducing Depression and Anxiety and Improving Well-Being: Feasibility Randomized Controlled Trial.

BACKGROUND: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternativ...

Multimodal brain imaging-based classification of functional constipation subtypes using machine learning.

Functional constipation (FC) is a common gastrointestinal condition often accompanied by anxiety and depression status (FCAD). Gastrointestinal sympto...

Beyond psychosocial support: A family-system-centric approach to AI-driven geriatric monitoring in Indonesia.

Development of Mind-Body Interventions for the Emergency Department.

Emergency department (ED) visits are a common experience that most individuals will have across their lifetime. ED-based evaluation for acute complain...

Are Lemons Fast for People With Autism? Semantic and Perceptual Crossmodal Correspondences in Autism Beyond the Kiki-Bouba Effect.

Attenuated sound-shape matching in the classic Kiki-Bouba effect in autism has already been replicated in several studies, but it remains unclear whet...

Workers/crews' mental workload dynamics in closed cabins: A task-difficulty-adaptive random forest model for instrument monitoring tasks using multimodal biosignals.

BackgroundAccurate assessment of operator mental workload (MWL) is critical for ensuring safety in closed-cabin environments, yet traditional contact-...