BACKGROUND: Internet addiction (IA) refers to excessive internet use that causes cognitive impairment or distress. Understanding the neurophysiological mechanisms underpinning IA is crucial for enabling an accurate diagnosis and informing treatment a...
OBJECTIVE: Mental health problems are the major cause of disability among adolescents. Personalized prevention may help to mitigate the development of mental health problems, but no tools are available to identify individuals at risk before they requ...
BACKGROUND: As the use of guided digitally-delivered cognitive-behavioral therapy (GdCBT) grows, pragmatic analytic tools are needed to evaluate coaches' implementation fidelity.
BACKGROUND: Self-injurious behaviors (SIB) are common in autistic people. SIB is mainly studied as a broad category, rather than by specific SIB types. We aimed to determine associations of distinct SIB types with common psychiatric, emotional, medic...
Artificial intelligence (AI) has been recently applied to different mental health illnesses and healthcare domains. This systematic review presents the application of AI in mental health in the domains of diagnosis, monitoring, and intervention. A da...
BACKGROUND: Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol...
BACKGROUND: Less than a third of patients with depression achieve successful remission with standard first-step antidepressant monotherapy. The process for determining appropriate second-step care is often based on clinical intuition and involves a p...
BACKGROUND: Internet-based interventions produce comparable effectiveness rates as face-to-face therapy in treating depression. Still, more than half of patients do not respond to treatment. Machine learning (ML) methods could help to overcome these ...
BACKGROUND: Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a gi...
BACKGROUND: We aimed to identify unmet treatment needs for improving social and occupational functioning in early schizophrenia using a data-driven causal discovery analysis.