AIMC Topic: Cognitive Behavioral Therapy
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Dynamic neural network modulation associated with rumination in major depressive disorder: a prospective observational comparative analysis of cognitive behavioral therapy and pharmacotherapy.
Translational psychiatry
Aug 6, 2025
Cognitive behavioral therapy (CBT) and pharmacotherapy are primary treatments for major depressive disorder (MDD). However, their differential effects on the neural networks associated with rumination, or repetitive negative thinking, remain poorly u...
PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.
BMJ open
Jul 10, 2025
INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experien...
Sleep disturbances and PTSD: identifying baseline predictors of insomnia response in an intensive treatment programme.
European journal of psychotraumatology
Jun 23, 2025
This study examined whether baseline demographic and clinical variables could predict clinically significant reductions in insomnia symptoms among veterans receiving a 2-week Cognitive Processing Therapy (CPT)-based intensive PTSD treatment programm...
Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety.
BMC psychiatry
May 30, 2025
BACKGROUND: Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for mild to moderate depression and anxiety disorders. However, up to 50% of patients do not achieve sufficient symptom relief. Identifying p...
Uncovering key factors in weight loss effectiveness through machine learning.
International journal of obesity (2005)
May 6, 2025
BACKGROUND/OBJECTIVES: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).
Exploring Therapists' Approaches to Treating Eating Disorders to Inform User-Centric App Design: Web-Based Interview Study.
JMIR formative research
May 6, 2025
BACKGROUND: The potential for digital interventions in self-management and treatment of mild to moderate eating disorders (EDs) has already been established. However, apps are infrequently recommended by ED therapists to their clients. Those that are...
Comparing three neural networks to predict depression treatment outcomes in psychological therapies.
Behaviour research and therapy
Apr 22, 2025
OBJECTIVE: Artificial neural networks have been used in various fields to solve classification and prediction tasks. However, it is unclear if these may be adequate methods to predict psychological treatment outcomes. This study aimed to evaluate the...
AI-driven analyzes of open-ended responses to assess outcomes of internet-based cognitive behavioral therapy (ICBT) in adolescents with anxiety and depression comorbidity.
Journal of affective disorders
Apr 3, 2025
OBJECTIVE: Although patients prefer describing their problems using words, mental health interventions are commonly evaluated using rating scales. Fortunately, recent advances in natural language processing (i.e., AI-methods) yield new opportunities ...
Capitalizing on natural language processing (NLP) to automate the evaluation of coach implementation fidelity in guided digital cognitive-behavioral therapy (GdCBT).
Psychological medicine
Apr 2, 2025
BACKGROUND: As the use of guided digitally-delivered cognitive-behavioral therapy (GdCBT) grows, pragmatic analytic tools are needed to evaluate coaches' implementation fidelity.
Predicting Therapy Outcomes in Patients With Stress-Related Disorders: Protocol for a Predictive Modeling Study.
JMIR research protocols
Mar 25, 2025
BACKGROUND: While cognitive behavioral therapy has shown efficacy in treating stress-related disorders, such as adjustment disorder and exhaustion disorder, knowledge about factors contributing to treatment response is limited. Improved identificatio...
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