Eating Disorders

Brain morphology in Anorexia Nervosa and its subtypes: A multi-cohort study of individual participant data.

BACKGROUND: In a recent coordinated meta-analysis of neuroimaging data, we reported gray matter (GM) alterations in acutely underweight patients with anorexia nervosa (AN). Here, we extend these findings by examining individual variation in brain structure within AN, individual-level differentiation between AN and healthy controls (HC), and differences between AN subtypes, with potential relevance...

Comment on "Interpretable Machine Learning Model for Predicting Refeeding Syndrome After Colorectal Cancer Surgery".

Cultural Relevance and Acceptability of Cognitive Behavioral Therapy Techniques Adapted by AI or a Human Psychologist: Experimental Study.

BACKGROUND: Evidence-based psychological interventions are usually not accessed by marginalized groups such as refugees. Culturally adapted psychologi...

Benchmarking Generative Artificial Intelligence Against Human Judgment in Eating Disorder Case Recognition and Treatment Recommendations.

OBJECTIVE: Generative AI is now used to access eating disorder (ED) information, yet the suitability of its outputs remains unclear. Using two vignett...

A Comparative Evaluation of Three Large Language Models for Parent-Centered Questions About Anorexia Nervosa.

BACKGROUND: Large language models (LLMs) are increasingly used to obtain health information, including guidance on child and adolescent mental health....

A Call for Leadership: Lessons Learnt from a Case of Artificial Intelligence (AI)-Augmented Cognitive Behavioural Therapy (CBT).

Anterior midcingulate cortex activity during pain catastrophizing predicts and sequentially tracks reduction in pain interference after cognitive behavioral therapy in fibromyalgia.

Fibromyalgia (FM) is a chronic pain disorder characterized by widespread pain, fatigue, and functional disability. Cognitive behavioral therapy (CBT) ...

Predicting depression treatment outcomes for cognitive behavioural therapy using machine learning: A systematic review and meta-analysis.

BACKGROUND: Cognitive behavioural therapy (CBT) is an empirically-supported treatment for depression, although some patients respond well and others d...

Artificial Intelligence for Predicting Treatment Response in Patients With Anxiety Disorders After Cognitive Behavioral Therapy: Systematic Review and Meta-Analysis.

BACKGROUND: Artificial intelligence (AI) models have been increasingly explored for predicting treatment response to cognitive behavioral therapy (CBT...

Leveraging machine learning to identify gendered stereotypes and body image concerns on diet and fitness online forums.

The pervasive expectations about ideal body types in Western society can lead to body image concerns, dissatisfaction, and in extreme cases, eating di...

An exploratory randomized controlled trial of an AI-enabled mental health intervention for generalized anxiety.

Generalized Anxiety Disorder (GAD) is prevalent and often co-occurs with depression, contributing to significant disability and healthcare burden. Alt...

Interpretable machine learning model for predicting refeeding syndrome after colorectal cancer surgery.

OBJECTIVE: Refeeding syndrome (RFS) is a common yet frequently overlooked complication during postoperative nutritional support in patients undergoing...

Novel bayesian nonparametric unsupervised learning approach to precision symptom management in cancer survivors: a re-analysis of a comparative effectiveness trial.

Cancer survivors often experience multiple cooccurring symptoms such as insomnia, pain, fatigue, and anxiety; yet conventional analyses in symptom sci...

Integrating Artificial Intelligence Into Exposure Therapy: A One Year Follow-Up Case Report of Emetophobia With Comorbid Panic Disorder.

Emetophobia is a specific phobia characterized by an intense fear of vomiting, often accompanied by panic attacks, hypervigilance to bodily sensations...

Increasing engagement with cognitive-behavioral therapy (CBT) using generative AI: a randomized controlled trial (RCT).

BACKGROUND: Shortages in mental healthcare lead to long periods of inadequate support for many patients. While digital interventions offer a scalable ...

Complex Interactions Between Stress, Nutrition, Gut Microbiota, and Infectious Diseases and Their Impact on Health in Global Conflicts: A Narrative Review.

Following the global recovery from the COVID-19 pandemic, wars and conflicts have escalated to levels unseen since the Cold War. It is well known that...

From innovation to implementation: Artificial intelligence in cognitive behaviour therapy training and supervision.

Artificial intelligence (AI) can transform mental health care globally by improving the efficiency, consistency, effectiveness and accessibility of tr...

Artificial intelligence (AI) in nutrition: A case-based comparison of generative AI models.

BACKGROUND: Clinical nutrition (CN) is becoming increasingly complex because of the rising prevalence of chronic illness, cancer, and malnutrition-rel...

Radiation Risk in 2D Mammography Screening: A Scoping Review of Modelling Strategies and Emerging AI Applications.

Breast cancer is the most commonly diagnosed cancer among women worldwide, and concerns regarding radiation exposure from mammography screening remain...

PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.

INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety ...