From turn-by-turn to larger chunks of talk: An exploratory study in psychotherapeutic micro-processes using conversation analysis
Independent of theoretical orientation therapies of all kind are talk-in-interaction. Influential overall conceptualizations (as e.g. intervention) belong to a certain model of medicalizing the psychotherapeutic endeavor. Talk-in-interaction is the base for applying Conversation Analysis (CA) in psychotherapeutic process research. CA is a powerful tool originating from social science taking data, hypotheses and theories from careful observing in a similar way as infant observers did. The common discovery is that conversation precedes language. Some features of infantile proto-conversation survive in adult life. CA has directed careful attention to processes like turn-taking, repair, conditional relevances, etc. in observing the rules of interaction. However, in studying psychotherapy process turn-by-turn analysis alone does not suffice. It can be completed by a new model of common ground activities and package-by-package analysis turning attention to new objects of observation in therapeutic conversation (allusions, metaphorical framing activities). We propose a methodology for both kinds of analyses based on transcribed examples from the CEMPP-Project. This exploratory designed project (Conversation analysis of empathy in Psychotherapy Process; supported by the Khler Foundation, Germany) compared psychoanalytic, psychodynamic and cognitive-behavioral treatments in five dyads each taking transcribed sessions from the beginning, the middle phase and the end; our database includes 45 transcribed sessions.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2017 Michael B. Buchholz, Horst KÃ¤chele, Horst KÃ¤chele
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.