Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes (P19-1)
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| Challenge: | a new study examines the role of dialogue observers in psychotherapy . the model is based on motivational interviewing, which is effective for treating addictions . |
| Approach: | They propose to model MI behavioral codes for therapists by an observer . they propose to use the observer to forecast therapist and client MI behavioral code . |
| Outcome: | The proposed model outperforms baseline models for both tasks and reveals tradeoffs in performance. |
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| Challenge: | Motivational interviewing (MI) is a client-centered counseling technique that encourages individuals to change behaviors through emphatic conversations. |
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| Challenge: | Recent surge of text-based online counseling applications enables us to collect and analyze interactions between counselors and clients. |
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| Challenge: | Recent studies have focused on the role of client emotions and therapist interventions in predicting treatment outcomes from psychotherapy dialogues. |
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| Challenge: | Motivational Interviewing (MI) is gaining attention as a theoretical basis for mental health chatbots. |
| Approach: | They propose a framework that simulates MI sessions enriched with the expertise of professional therapists by using large language models to generate utterances through prompt engineering. |
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| Challenge: | Motivational interviewing (MI) is a directive, client-centered counseling approach for eliciting clients' motivation for behavioral change. |
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Xinwei Yang, Junyi Fan, Yuqing Liu, Jiaxuan Wang, Jiashuai Zhang, Hongru Liang, Wenqiang Lei, Yao Song
| Challenge: | Recent efforts have turned to large language models (LLMs) as therapeutic agents for psychological therapy tasks, yet robustness across diverse patients remains underexplored. |
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Boosting Distress Support Dialogue Responses with Motivational Interviewing Strategy (2023.findings-acl)
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| Challenge: | Lack of psychotherapeutic data makes it difficult to train chatbots . lack of mental health workers and stigma further demotivates people from seeking help. |
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How Well Can Large Language Models Reflect? A Human Evaluation of LLM-generated Reflections for Motivational Interviewing Dialogues (2025.coling-main)
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Erkan Basar, Xin Sun, Iris Hendrickx, Jan de Wit, Tibor Bosse, Gert-Jan De Bruijn, Jos A. Bosch, Emiel Krahmer
| Challenge: | Motivational Interviewing (MI) is a counseling technique that promotes behavioral change through reflective responses to mirror or refine client statements. |
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M3TCM: Multi-modal Multi-task Context Model for Utterance Classification in Motivational Interviews (2024.lrec-main)
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| Challenge: | Motivational interviews have two distinct roles, namely client and therapist . previous approaches did not fully incorporate all of these characteristics into utterance classification . |
| Approach: | They propose a multi-modal, multi-task context model for utterance classification that integrates text and speech as well as conversation context. |
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Schema-Guided Response Generation using Multi-Frame Dialogue State for Motivational Interviewing Systems (2026.findings-acl)
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| Challenge: | Motivational interviewing (MI) is a goal-directed dialogue aimed at motivating clients to change their behavior. |
| Approach: | They propose a method for updating multi-frame dialogue states and a strategy decision mechanism that dynamically determines the response focus in a manner grounded in MI principles. |
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