PURPOSE: Adolescent major depressive disorder (MDD) is a highly prevalent, incapacitating and costly illness. Many depressed teens do not improve with cognitive behavioral therapy (CBT), a first-line treatment for adolescent MDD, and face devastating...
The availability of large-scale datasets and sophisticated machine learning tools enables developing models that predict treatment outcomes for individual patients. However, few studies used routinely available sociodemographic and clinical data for ...
Journal of consulting and clinical psychology
31841022
OBJECTIVE: Research on predictors of treatment outcome in depression has largely derived from randomized clinical trials involving strict standardization of treatments, stringent patient exclusion criteria, and careful selection and supervision of st...
Journal of consulting and clinical psychology
31841021
OBJECTIVE: Depression is a highly common mental disorder and a major cause of disability worldwide. Several psychological interventions are available, but there is a lack of evidence to decide which treatment works best for whom. This study aimed to ...
IMPORTANCE: Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for meas...
BACKGROUND AND AIMS: Clinical staff are typically poor at predicting alcohol dependence treatment outcomes. Machine learning (ML) offers the potential to model complex clinical data more effectively. This study tested the predictive accuracy of ML al...
BACKGROUND: Previous attempts to identify predictors of treatment outcomes in body dysmorphic disorder (BDD) have yielded inconsistent findings. One way to increase precision and clinical utility could be to use machine learning methods, which can in...
IMPORTANCE: The mechanisms by which engagement with internet-delivered psychological interventions are associated with depression and anxiety symptoms are unclear.
Psychotherapy research : journal of the Society for Psychotherapy Research
32619163
Understanding patient responses to psychotherapy is important in developing effective interventions. However, coding patient language is a resource-intensive exercise and difficult to perform at scale. Our aim was to develop a deep learning model to...
Identifying predictors of suicide attempts is critical in intervention and prevention efforts, yet finding predictors has proven difficult due to the low base rate and underpowered statistical approaches. The objective of the current study was to use...