mlsanityData to 7 Oct 2026

An Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives

arXiv 2310.17017 ↗First posted 25 Oct 2023cs.CL cs.AIcited by 16

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

Mental health conversational agents (a.k.a. chatbots) are widely studied for their potential to offer accessible support to those experiencing mental health challenges. Previous surveys on the topic primarily consider papers published in either computer science or medicine, leading to a divide in understanding and hindering the sharing of beneficial knowledge between both domains. To bridge this gap, we conduct a comprehensive literature review using the PRISMA framework, reviewing 534 papers published in both computer science and medicine. Our systematic review reveals 136 key papers on building mental health-related conversational agents with diverse characteristics of modeling and experimental design techniques. We find that computer science papers focus on LLM techniques and evaluating response quality using automated metrics with little attention to the application while medical papers use rule-based conversational agents and outcome metrics to measure the health outcomes of participants. Based on our findings on transparency, ethics, and cultural heterogeneity in this review, we provide a few recommendations to help bridge the disciplinary divide and enable the cross-disciplinary development of mental health conversational agents.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 12 of its 152 references that are in the map. First posted on arXiv 25 Oct 2023.

Builds on

12 of 152 references.

References · 12

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  3. 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
  4. 2023The Internal State of an LLM Knows When It's Lyingcited by 644
  5. 2017Rasa: Open Source Language Understanding and Dialogue Managementcited by 67
  6. 2019Towards Understanding Emotional Intelligence for Behavior Change Chatbotscited by 8
  7. 2021CASS: Towards Building a Social-Support Chatbot for Online Health Communitycited by 8
  8. 2021ERICA: An Empathetic Android Companion for Covid-19 Quarantinecited by 8
  9. 2021ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modelingcited by 7
  10. 2019Discourse Behavior of Older Adults Interacting With a Dialogue Agent Competent in Multiple Topicscited by 6
  11. 2020Alexa Depression and Anxiety Self-tests: A Preliminary Analysis of User Experience and Trustcited by 1
  12. 2021A Grounded Well-being Conversational Agent with Multiple Interaction Modes: Preliminary Resultscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 5.

16 papers.

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  1. 2025Evaluating LLM-based Agents for Multi-Turn Conversations: A Surveycited by 56
  2. 2024Can AI Relate: Testing Large Language Model Response for Mental Health Supportcited by 21
  3. 2025EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safetycited by 21
  4. 2025Challenges in Testing Large Language Model Based Software: A Faceted Taxonomycited by 8
  5. 2024COCOA: CBT-based Conversational Counseling Agent using Memory Specialized in Cognitive Distortions and Dynamic Promptcited by 7
  6. 2025KMI: A Dataset of Korean Motivational Interviewing Dialogues for Psychotherapycited by 5
  7. 2025Interpersonal Theory of Suicide as a Lens to Examine Suicidal Ideation in Online Spacescited by 5
  8. 2025From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysiscited by 4
  9. 2024Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulnesscited by 3
  10. 2026Eval4Sim: An Evaluation Framework for Persona Simulationcited by 2
  11. 2025Reviewing Clinical Knowledge in Medical Large Language Models: Training and Beyondcited by 1
  12. 2026The Slow Drift of Support: Boundary Failures in Multi-Turn Mental Health LLM Dialoguescited by 1
4 more
  1. 2025The Cost-Benefit of Interdisciplinarity in AI for Mental Healthcited by 0
  2. 2026Conversational Control with Ontologies for Large Language Models: A Lightweight Framework for Constrained Generationcited by 0
  3. 2026Enhancing Mental Health Counseling Support in Bangladesh using Culturally-Grounded Knowledgecited by 0
  4. 2026Trust Stack for Mental Health AI: A Survey of Calibration across Human, Interaction, and AI Layerscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Building Trust in Mental Health Chatbots: Safety Metrics and LLM-Based Evaluation Tools
  2. 2025Mentalic Net: Development of RAG-based Conversational AI and Evaluation Framework for Mental Health Support
  3. 2025MindEval: Benchmarking Language Models on Multi-turn Mental Health Support
  4. 2023Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Support
  5. 2024A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers
  6. 2024Prompt Engineering a Schizophrenia Chatbot: Utilizing a Multi-Agent Approach for Enhanced Compliance with Prompt Instructions
  7. 2025ESC-Judge: A Framework for Comparing Emotional Support Conversational Agents
  8. 2025Domain-Specific Constitutional AI: Enhancing Safety in LLM-Powered Mental Health Chatbots