Prof. Rubel does research that focuses on the developement and evaluation of empirically-based tools to enhace person-specific decisions in psychotherapy. His goal is to support therapists in their everyday clinical decision making with data. To this end, he utilizes machine-learning in large datasets of already treated patients to predict the probability of treatment sucess, failure, and duration under different treatment conditions. Moreover, he uses intensive longitudinal data to estimate idiographic models of the dynamic system of a patient to understand the person-specific symptom dynamics and fit individual interventions accordingly.

Researchgate
Julian A. Rubel
Twitter
@julian_rubel
Mail
Julian.Rubel@psychol.uni-giessen.de