Taking a turn for the better: Conversation redirection throughout the course of mental-health therapy
Not on the map. Why?
Abstract (arXiv)
Mental-health therapy involves a complex conversation flow in which patients and therapists continuously negotiate what should be talked about next. For example, therapists might try to shift the conversation's direction to keep the therapeutic process on track and avoid stagnation, or patients might push the discussion towards issues they want to focus on. How do such patient and therapist redirections relate to the development and quality of their relationship? To answer this question, we introduce a probabilistic measure of the extent to which a certain utterance immediately redirects the flow of the conversation, accounting for both the intention and the actual realization of such a change. We apply this new measure to characterize the development of patient-therapist relationships over multiple sessions in a very large, widely-used online therapy platform. Our analysis reveals that (1) patient control of the conversation's direction generally increases relative to that of the therapist as their relationship progresses; and (2) patients who have less control in the first few sessions are significantly more likely to eventually express dissatisfaction with their therapist and terminate the relationship.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 10 of its 44 references that are in the map. First posted on arXiv 9 Oct 2024.
Builds on
10 of 44 references.
References · 10
- 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
- 2020ConvoKit: A Toolkit for the Analysis of Conversationscited by 71
- 2021Measuring Conversational Uptake: A Case Study on Student-Teacher Interactionscited by 44
- 2020Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentationcited by 41
- 2021TIAGE: A Benchmark for Topic-Shift Aware Dialog Modelingcited by 22
- 2020Balancing Objectives in Counseling Conversations: Advancing Forwards or Looking Backwardscited by 18
- 2023SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentationcited by 10
- 2019Conversation Model Fine-Tuning for Classifying Client Utterances in Counseling Dialoguescited by 8
- 2019Modeling Interpersonal Linguistic Coordination in Conversations using Word Mover's Distancecited by 7
- 2020Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forumscited by 4
Built on by
Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directionscited by 12
- 2025Hanging in the Balance: Pivotal Moments in Crisis Counseling Conversationscited by 4
- 2026CALM-IT: Generating Realistic Long-Form Motivational Interviewing Dialogues with Dual-Actor Conversational Dynamics Trackingcited by 3
- 2026Responsible Evaluation of AI for Mental Healthcited by 2
- 2026Discourse Diversity in Multi-Turn Empathic Dialoguecited by 1
- 2026Discourse Diversity in Multi-Turn Empathic Dialogue13 Apr 2026
- 2026Responsible Evaluation of AI for Mental Health20 Jan 2026
- 2026CALM-IT: Generating Realistic Long-Form Motivational Interviewing Dialogues with Dual-Actor Conversational Dynamics Tracking15 Jan 2026
- 2025Hanging in the Balance: Pivotal Moments in Crisis Counseling Conversations4 Jun 2025
- 2025A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions16 Feb 2025