Department of Psychology
Dana Atzil-Slonim received her PhD from the Hebrew University and joined Bar-Ilan University at 2015. She is currently the head of the clinical track at BIU's Psychology Department. Dana has a lengthy practical experience as a clinician and supervisor in clinical psychology. Her main research goal is to shed more light on the process and mechanisms of change that underlie gains in psychotherapy. This has important implications for improving the effectiveness of treatments to those suffering from emotional pain as well as for developing training and supervision strategies that foster successful psychotherapy interventions. The research conducted in her lab aims to advance the ideal of greater integration between research and practice in the field of clinical psychology in which information flows reciprocally between researchers and clinicians. To do so, she and a team of researchers from the Psychology Department at Bar-Ilan University implement a model in which all clinical activities within the research clinic are available for scientific inquiry. This includes a clinical research protocol enabling session-by-session monitoring, within-session recording, and therapist feedback for more than 150 treatments each year.
The importance of tailoring therapeutic interventions to the specific needs and characteristics of the individual patient has long been recognized by clinicians. However, traditional approaches to clinical diagnostics and psychotherapy have not been contributing to such personalization. Contrary to traditional nomothetic methods, idiographic assessment and modeling of intraindividual dynamic processes, as well as the use of machine learning techniques to analyze massive amount of multi-modal data, hold tremendous promise for tailoring psychodiagnosis and psychotherapy to the individual patient who suffers from mental health disorder. In a current collaboration between psychology experts and leading computer scientists, Dana and her colleagues are conducting a multidisciplinary project that integrate moment-by-moment linguistic, vocal, facial, kinesthetic, and physiological data, with the aim of developing person-specific assessments of treatment response and predictions of relapse or recovery in clients who suffer from mental health disorders and especially from depression. This approach is expected to yield unique insights regarding the processes that underlie psychopathology and therapy gains.