Exploring intrapersonal and interpersonal processes
We are interested in several factors related to the client (e.g., interpersonal patterns, emotional experience, affect), the therapist (e.g., focus of intervention, personal characteristics) and the therapeutic relationship (e.g., interpersonal patterns of the therapeutic bond, working alliance, ruptures). We have designed studies that systematically explore fundamental aspects of Psychodynamic theory (e.g. transference, countertransference, rigidity/flexibility in self/object representations, progression in treatment from dissociation to dialectics)
Capturing the dyadic nature of treatment
We have applied methods developed in dyadic research, such as the Truth & Bias model (T&B; West & Kenny, 2011) and the Actor Partner Interdependence Model (APIM; Kenny & Cook, 1999) to capture the dyadic nature of the therapy relationship and enable analysis of session by session data and the examination of temporal patterns of change in psychotherapy.
Tracing processes via advanced machine learning techniques
One of the main barriers to psychotherapy process-outcome studies is the limited amount of data available to analyze the process, due to the substantial effort required for human judges to evaluate and code recorded or transcribed sessions. We have been interested in applying computerized coding systems that exploit machine learning and text/audio analysis techniques to enhance the study of process data without losing its depth.