Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy
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Computer Science > Computation and Language
Title:Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy
Abstract:Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy interaction. We introduce an ontology of ten therapeutic moves: compact, function-based categories grounded in the MULTI-60 inventory, validated through an annotation campaign with five licensed psychologists, and scaled with a judge-based approach that matches expert agreement. Applying it to real counseling transcripts and model-led sessions, we compare the move distributions between human clinicians and a panel of frontier models. Models over-use inquiry at up to three times the human rate, neglect psychoeducation, and are strongly context-anchored: they carry forward strategies initiated by a human clinician but rarely initiate them themselves. Exposing the ontology as a set of tools roughly halves the mean deviation from the human move distribution and improves turn-level alignment with human therapist by 7-9 percentage points, without any fine-tuning.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2608.21325 [cs.CL] |
| (or arXiv:2608.21325v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.21325
arXiv-issued DOI via DataCite (pending registration)
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