Work

Analyzing the Language of Therapist Empathy in Motivational Interview based Psychotherapy.

Year: 2012

Type: conference-paper

Abstract: Empathy is an important aspect of social communication, especially in medical and psychotherapy applications. Measures of empathy can offer insights into the quality of therapy. We use an N-gram language model based maximum likelihood strategy to classify empathic versus non-empathic utterances and report the precision and recall of classification for various parameters. High recall is obtained with unigram while bigram features achieved the highest F1-score. Based on the utterance level models, a group of lexical features are extracted at the therapy session level. The effectiveness of these features in modeling session level annotator perceptions of empathy is evaluated through correlation with expert-coded session level empathy scores. Our combined feature set achieved a correlation of 0.558 between predicted and expert-coded empathy scores. Results also suggest that the longer term empathy perception process may be more related to isolated empathic salient events.

Source: PubMed

Authors: Bo Xiao, Dogan Can, Panayiotis G Georgiou, David Atkins, Shrikanth S Narayanan

Institutions: University of Southern California, University of Washington

Language: English

Topic: Mental Health via Writing

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute on Alcohol Abuse and Alcoholism

Award: Implementation of Technology-Based Evaluation of Motivational Interviewing