All Therapies Are Equal - Unless You’re a Bot: Evaluating the Effectiveness of Four Therapy Schools for AI Chatbot Therapists
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liu-andiliu-meng-eecs-2025-thesis.pdf
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Thesis PDF
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Author(s)
Liu, Andi
Advisor(s)
Gabrieli, John
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
This thesis tests two design questions for Large Language Model (LLM) Chatbot Therapists: Which therapeutic school suits an LLM best, and does an explicit Theory-of-Mind (ToM) reflection improve outcomes? We prompted GPT-4.1-mini to act as eight therapists — CBT, Narrative, Psychodynamic, and SFBT, each with and without a ToM step — and held 240 simulated sessions with scripted AI patients. SFBT achieved the greatest projected PHQ-9 improvement (around 4 points), significantly higher than CBT, Narrative, or Psychodynamic approaches. Immediate distress (SUDS) fell modestly and uniformly across schools. ToM reasoning did not alter either measure. The findings show that extra “thinking time” might not automatically translate into therapeutic gain, but also highlight a current strength of LLMs: executing brief, rule-based therapies.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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