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Goals, Tasks, and Bonds: Toward the Computational Assessment of Therapist Versus Client Perception of Working Alliance
Vail, Alexandria K. Girard, Jeffrey Bylsma, Lauren Cohn, Jeffrey Fournier, Jay Swartz, Holly Morency, Louis-Philippe
Vail, Alexandria K.
Girard, Jeffrey
Bylsma, Lauren
Cohn, Jeffrey
Fournier, Jay
Swartz, Holly
Morency, Louis-Philippe
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Abstract
Early client dropout is one of the most significant challenges facing psychotherapy: recent studies suggest that at least one in five clients will leave treatment prematurely. Clients may terminate therapy for various reasons, but one of the most common causes is the lack of a strong working alliance. The concept of working alliance captures the collaborative relationship between a client and their therapist when working toward the progress and recovery of the client seeking treatment. Unfortunately, clients are often unwilling to directly express dissatisfaction in care until they have already decided to terminate therapy. On the other side, therapists may miss subtle signs of client discontent during treatment before it is too late. In this work, we demonstrate that nonverbal behavior analysis may aid in bridging this gap. The present study focuses primarily on the head gestures of both the client and therapist, contextualized within conversational turn-taking actions between the pair during psychotherapy sessions. We identify multiple behavior patterns suggestive of an individual’s perspective on the working alliance; interestingly, these patterns also differ between the client and the therapist. These patterns inform the development of predictive models for self-reported ratings of working alliance, which demonstrate significant predictive power for both client and therapist ratings. Future applications of such models may stimulate preemptive intervention to strengthen a weak working alliance, whether explicitly attempting to repair the existing alliance or establishing a more suitable client-therapist pairing, to ensure that clients encounter fewer barriers to receiving the treatment they need.
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Date
2021-01-12
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IEEE
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Keywords
Face recognition, Sociology, Medical treatment, Collaboration, Gesture recognition, Predictive models, Maintenance engineering
Citation
Vail, A. K., Girard, J., Bylsma, L., Cohn, J., Fournier, J., Swartz, H., & Morency, L. P. (2021). Goals, Tasks, and Bonds: Toward the Computational Assessment of Therapist Versus Client Perception of Working Alliance. Proceedings of the ... International Conference on Automatic Face and Gesture Recognition. IEEE International Conference on Automatic Face & Gesture Recognition, 2021, 10.1109/fg52635.2021.9667021. https://doi.org/10.1109/fg52635.2021.9667021