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Intrapersonal and interpersonal vocal affect dynamics during psychotherapy
Adar Paz1, Eshkol Rafaeli1, Eran Bar-Kalifa2
1Psychology Department.
Journal of Consulting and Clinical Psychology
|April 8, 2021
Summary
This study shows how vocal arousal dynamics in therapy, like dampening, predict better treatment outcomes. Automatic vocal analysis reveals key intrapersonal and interpersonal affect patterns linked to therapy success.
Area of Science:
- Psychology and Psychotherapy Research
- Affective Science
- Computational Linguistics
Background:
- Understanding affect dynamics is crucial for effective psychotherapy.
- Traditional methods for assessing affect dynamics are often subjective and time-consuming.
- Automatic analysis of vocal cues offers a promising avenue for objective emotion assessment.
Purpose of the Study:
- To implement an automatic method for assessing vocal arousal.
- To explore intrapersonal and interpersonal affect dynamics using dynamic system models within psychotherapy.
- To determine the association between these affect dynamics and psychotherapy treatment outcomes.
Main Methods:
- Extracted 21,133 mean vocal arousal observations from 279 therapy sessions (30 clients, 24 therapists).
- Utilized dynamic system models to analyze intrapersonal (self-regulation) and interpersonal (dyadic interaction) affect dynamics.
- Clients self-reported well-being using the Outcome Rating Scale before and after each session.
Main Results:
- Both clients and therapists exhibited intrapersonal dampening (vocal arousal returning to baseline).
- Clients and therapists showed interpersonal dampening (arousal levels influenced by the other party).
- Interpersonal dampening decreased, while intrapersonal dampening increased over treatment; higher interpersonal dampening correlated with better outcomes.
Conclusions:
- Automatic vocal measures effectively capture nuanced intrapersonal and interpersonal affect dynamics in psychotherapy.
- These vocal affect dynamics are significantly associated with treatment gains and therapeutic success.
- The findings highlight the utility of computational methods for understanding therapeutic processes and outcomes.
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