AI Medical Compendium Journal:
Journal of consulting and clinical psychology

Showing 1 to 5 of 5 articles

Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.

Journal of consulting and clinical psychology
OBJECTIVE: This study applied a machine-learning-based skill assessment system to investigate the association between supportive counseling skills (empathy, open questions, and reflections) and treatment outcomes. We hypothesized that higher empathy ...

Clinical science and practice in the age of large language models and generative artificial intelligence.

Journal of consulting and clinical psychology
In this article, Schueller and Morris discuss the recent advances made from large language models (LLMs) and generative artificial intelligence (AI). These advances include supporting humans to provide better interventions, understanding processes in...

Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.

Journal of consulting and clinical psychology
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...

Targeted prescription of cognitive-behavioral therapy versus person-centered counseling for depression using a machine learning approach.

Journal of consulting and clinical psychology
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 ...

Randomized controlled trial of an online machine learning-driven risk assessment and intervention platform for increasing the use of crisis services.

Journal of consulting and clinical psychology
OBJECTIVE: Mental illness is a leading cause of disease burden; however, many barriers prevent people from seeking mental health services. Technological innovations may improve our ability to reach underserved populations by overcoming many existing ...