Local dynamic mode of Cognitive Behavioral Therapy
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Abstract (arXiv)
In order to increase mental health equity among the most vulnerable and marginalized communities, it is important to increase access to high-quality therapists. One facet of addressing these needs, is to provide timely feedback to clinicians as they interact with their clients, in a way that is also contextualized to specific clients and interactions they have had. Dynamical systems provide a framework through which to analyze interactions. The present work applies these methods to the domain of automated psychotherapist evaluation for Cognitive Behavioral Therapy (CBT). Our methods extract local dynamic modes from short windows of conversation and learns to correlate the observed dynamics to CBT competence. The results demonstrate the value of this paradigm and outlines the way in which these methods can be used to study and improve therapeutic strategies.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 27 references that are in the map. First posted on arXiv 28 Apr 2022.
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References · 7
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2014Dynamic mode decomposition with controlcited by 128
- 2017Online dynamic mode decomposition for time-varying systemscited by 22
- 2021Automated Quality Assessment of Cognitive Behavioral Therapy Sessions Through Highly Contextualized Language Representationscited by 13
- 2018Multi-label Multi-task Deep Learning for Behavioral Codingcited by 12
- 2021Automated Evaluation Of Psychotherapy Skills Using Speech And Language Technologiescited by 9
- 2020Feature Fusion Strategies for End-to-End Evaluation of Cognitive Behavior Therapy Sessionscited by 6
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