Using machine learning methods to identify trajectories of change and predict responders and non-responders to short-term dynamic therapy.

Objectives: Predicting therapy responders can significantly improve clinical outcomes. This study aims to identify predictors of response to short-term dynamic therapy. Methods: Data from 95 patients who underwent 16-session therapy were analyzed using machine learning. Weekly progress was monitored...

Descripción completa

Detalles Bibliográficos

Publicado en:	Psychotherapy Research Vol. 35; no. 7; pp. 1070 - 1087
Autores principales:	Yonatan-Leus, Refael, Gwertzman, Gershom, Tishby, Orya
Formato:	Artículo
Publicado:	Taylor & Francis Ltd Sep2025
Materias:	Machine learning Random forest algorithms Psychodynamic psychotherapy Health outcome assessment Treatment effectiveness Emotion regulation Individualized medicine
Acceso en línea:	Ver este registro en EBSCOhost