Measuring empathy: a statistical physics grounded approach

Empathy plays a major role in changing a pathological mind’s configuration, and the establishment of an empathic link between therapist and patient is a crucial component of a good therapeutic alliance and outcome. Yet, the definition of empathy and its facets is still under debate, limiting the development of objective quantitative measures. Most authors, though, agree that a fundamental immediate resonance, based on mimicry, contagion, and interpersonal regulation, is among the grounding processes of empathy. Following the growing literature on interpersonal physiology, we investigated the hypothesis that this basic empathic process should present appreciable physiological underpinnings. We applied a Principal Component Analysis (PCA) on simultaneous electrodermal activity, and heart rate variability signals from a patient–therapist dyad involved in a 16-sessions psychodynamic therapy. Confirming our expectations, PCA revealed a first ‘shared’ component correlated to both participants’ signals, and two ‘individual’ components separately correlating to the patient’s and therapist’s signals. A session-by-session regression analysis showed that the shared component predicted therapy outcome (R2 = .28). We further investigated the shared component dynamic via a symbolic Markovian discrete model, and cluster analysis, observing a behaviour that mirrors previously reported properties of a single heart rate dynamic. In conclusion, the PCA extraction of the shared physiological activity is an unsupervised data-driven procedure showing promising properties. Further validation of this novel procedure may lead to a full-fledged objective measure, characterized by simple analysis and interpretation, and a very high temporal resolution, which may offer an objective assessment of fundamental empathy facets, implying exciting practical implications in the study of the clinical process