# A Fully Generative Motivational Interviewing Counsellor Chatbot for Moving Smokers Towards the Decision to Quit

arXiv: https://arxiv.org/abs/2505.17362 · HTML: https://mlsanity.com/paper/2505.17362/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 87 references that are in the map.
- First posted on arXiv 23 May 2025.

## Builds on (most cited first, 9 of 9)

- [Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLP](https://mlsanity.com/paper/2109.06598/) (2021)
- [Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes](https://mlsanity.com/paper/1907.00326/) (2019)
- [Virtual Agents for Alcohol Use Counseling: Exploring LLM-Powered Motivational Interviewing](https://mlsanity.com/paper/2407.08095/) (2024)
- [Boosting Distress Support Dialogue Responses with Motivational Interviewing Strategy](https://mlsanity.com/paper/2305.10195/) (2023)
- [Multi-label Multi-task Deep Learning for Behavioral Coding](https://mlsanity.com/paper/1810.12349/) (2018)
- [Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning](https://mlsanity.com/paper/2403.15737/) (2024)
- [Dynamic Reward Adjustment in Multi-Reward Reinforcement Learning for Counselor Reflection Generation](https://mlsanity.com/paper/2403.13578/) (2024)
- [VERVE: Template-based ReflectiVE Rewriting for MotiVational IntErviewing](https://mlsanity.com/paper/2311.08299/) (2023)
- [Generation, Distillation and Evaluation of Motivational Interviewing-Style Reflections with a Foundational Language Model](https://mlsanity.com/paper/2402.01051/) (2024)

## Built on by (most cited first, 5 of 5)

- [CALM-IT: Enhancing Synthetic Motivational Interviewing Dialogue Quality with Conversational Dynamics](https://mlsanity.com/paper/2601.10085/) (2026)
- [Responsible Evaluation of AI for Mental Health](https://mlsanity.com/paper/2602.00065/) (2026)
- [Toward expert-level motivational interviewing for health behavior improvement with LLMs](https://mlsanity.com/paper/2512.15446/) (2025)
- [Benchmarking Motivational Interviewing Competence of Large Language Models](https://mlsanity.com/paper/2603.03846/) (2026)
- [Enhancing Mental Health Counseling Support in Bangladesh using Culturally-Grounded Knowledge](https://mlsanity.com/paper/2604.14576/) (2026)

## Abstract (arXiv)

The conversational capabilities of Large Language Models (LLMs) suggest that they may be able to perform as automated talk therapists. It is crucial to know if these systems would be effective and adhere to known standards. We present a counsellor chatbot that focuses on motivating tobacco smokers to quit smoking. It uses a state-of-the-art LLM and a widely applied therapeutic approach called Motivational Interviewing (MI), and was evolved in collaboration with clinician-scientists with expertise in MI. We also describe and validate an automated assessment of both the chatbot's adherence to MI and client responses. The chatbot was tested on 106 participants, and their confidence that they could succeed in quitting smoking was measured before the conversation and one week later. Participants' confidence increased by an average of 1.7 on a 0-10 scale. The automated assessment of the chatbot showed adherence to MI standards in 98% of utterances, higher than human counsellors. The chatbot scored well on a participant-reported metric of perceived empathy but lower than typical human counsellors. Furthermore, participants' language indicated a good level of motivation to change, a key goal in MI. These results suggest that the automation of talk therapy with a modern LLM has promise.