[HTML][HTML] Can we predict who will benefit from cognitive-behavioural therapy? A systematic review and meta-analysis of machine learning studies
Cognitive-behavioural therapy (CBT) is the first line of treatment for several mental health
disorders. However, not all patients show clinical improvements after receiving CBT …
disorders. However, not all patients show clinical improvements after receiving CBT …
A Generic Review of Integrating Artificial Intelligence in Cognitive Behavioral Therapy
M Jiang, Q Zhao, J Li, F Wang, T He, X Cheng… - arXiv preprint arXiv …, 2024 - arxiv.org
Cognitive Behavioral Therapy (CBT) is a well-established intervention for mitigating
psychological issues by modifying maladaptive cognitive and behavioral patterns. However …
psychological issues by modifying maladaptive cognitive and behavioral patterns. However …
Predicting therapy outcome in a digital mental health intervention for depression and anxiety: A machine learning approach
S Hornstein, V Forman-Hoffman, A Nazander… - Digital …, 2021 - journals.sagepub.com
Objective Predicting the outcomes of individual participants for treatment interventions
appears central to making mental healthcare more tailored and effective. However, little …
appears central to making mental healthcare more tailored and effective. However, little …
Effectiveness of individual cognitive-behavioral therapy and predictors of outcome in adult patients with obsessive-compulsive disorder
N Kathmann, T Jacobi, B Elsner, B Reuter - Psychotherapy and …, 2022 - karger.com
Introduction: Cognitive-behavioral therapy (CBT) for obsessive-compulsive disorder (OCD)
has proven its efficacy in randomized controlled trials (RCTs). Objective: To test …
has proven its efficacy in randomized controlled trials (RCTs). Objective: To test …
Early detection of paediatric and adolescent obsessive–compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms
Purpose Mental health issues of young minds are at the threshold of all development and
possibilities. Obsessive–compulsive disorder (OCD), separation anxiety disorder (SAD), and …
possibilities. Obsessive–compulsive disorder (OCD), separation anxiety disorder (SAD), and …
Clinical predictors of treatment response towards exposure therapy in virtuo in spider phobia: a machine learning and external cross-validation approach
While being highly effective on average, exposure-based treatments are not equally
effective in all patients. The a priori identification of patients with a poor prognosis may …
effective in all patients. The a priori identification of patients with a poor prognosis may …
[HTML][HTML] Psychotherapies and digital interventions for OCD in adults: What do we know, what do we need still to explore?
Background Despite significant advances in the understanding and treatment of obsessive
compulsive disorder (OCD), current treatment options are limited in terms of efficacy for …
compulsive disorder (OCD), current treatment options are limited in terms of efficacy for …
Does the network structure of obsessive-compulsive symptoms at treatment admission identify patients at risk for non-response?
JM Kuckertz, RJ McNally, BC Riemann… - Behaviour research and …, 2022 - Elsevier
Exposure and response prevention is the gold-standard treatment for obsessive compulsive
disorder (OCD), yet up to half of patients do not adequately respond. Thus, different …
disorder (OCD), yet up to half of patients do not adequately respond. Thus, different …
Using clinical patient characteristics to predict treatment outcome of cognitive behavior therapies for individuals with medically unexplained symptoms: a systematic …
L Sarter, J Heider, M Witthöft, W Rief… - General hospital …, 2022 - Elsevier
Objective For individuals with medically unexplained symptoms (MUS), cognitive behavioral
therapy (CBT) is the best-evaluated treatment. This systematic review and meta-analyses …
therapy (CBT) is the best-evaluated treatment. This systematic review and meta-analyses …
Predicting non-improvement of symptoms in daily mental healthcare practice using routinely collected patient-level data: a machine learning approach
K Franken, P Ten Klooster, E Bohlmeijer… - Frontiers in …, 2023 - frontiersin.org
Objectives Anxiety and mood disorders greatly affect the quality of life for individuals
worldwide. A substantial proportion of patients do not sufficiently improve during evidence …
worldwide. A substantial proportion of patients do not sufficiently improve during evidence …