Abstract
We explored use of Recurrence Quantification Analysis (RQA) of speech rhythm data from mental-health counseling sessions for prediction of quality of psychotherapy. Time-series of inter-syllable intervals (ISIs) were extracted from 239 counseling sessions conducted by 12 therapists who repeatedly interacted with 30 clients. We found a negative association between recurrence metrics and client-rated session quality and a negative link between percent of laminarity and therapist-rated session quality, after controlling for self-reported client depression and distress measures and duration of speech sound within a session. Placing value on reduced recurrence in patterns of ISIs, and especially reduced degree of a dyadic system remaining in the same speech-rhythm pattern may be indicative of a desire for variation in content and strategies of client-therapist interaction. These exploratory findings point to the possibility of RQA-based automated systems to capture the ‘footprint’ of the non-verbal dynamic that is indicative of successful mental-health counseling.
Original language | English |
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Pages (from-to) | 803-809 |
Number of pages | 7 |
Journal | Proceedings of the Annual Meeting of the Cognitive Science Society |
Volume | 44 |
Issue number | 44 |
Publication status | Published - 1 Jun 2022 |
Event | 44th Annual Meeting of the Cognitive Science Society: Cognitive diversity - Metro Toronto Convention Centre, Toronto, Canada Duration: 27 Jul 2022 → 30 Jul 2022 Conference number: 44th https://cognitivesciencesociety.org/cogsci-2022/ |
Keywords
- Recurrence Qualification Analysis
- Non-verbal speech parameters
- Speech rhythm
- Dialogue
- Psychotherapy