Can Large Language Models be Used to Provide Psychological Counselling? An Analysis of GPT-4-Generated Responses Using Role-play Dialogues
Not on the map. Why?
Abstract (arXiv)
Mental health care poses an increasingly serious challenge to modern societies. In this context, there has been a surge in research that utilizes information technologies to address mental health problems, including those aiming to develop counseling dialogue systems. However, there is a need for more evaluations of the performance of counseling dialogue systems that use large language models. For this study, we collected counseling dialogue data via role-playing scenarios involving expert counselors, and the utterances were annotated with the intentions of the counselors. To determine the feasibility of a dialogue system in real-world counseling scenarios, third-party counselors evaluated the appropriateness of responses from human counselors and those generated by GPT-4 in identical contexts in role-play dialogue data. Analysis of the evaluation results showed that the responses generated by GPT-4 were competitive with those of human counselors.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 5 of its 14 references that are in the map. First posted on arXiv 20 Feb 2024.
Builds on
5 of 14 references.
References · 5
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2021Towards Emotional Support Dialog Systemscited by 294
- 2021Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approachcited by 75
- 2022PAL: Persona-Augmented Emotional Support Conversation Generationcited by 39
- 2022Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnairescited by 26
Built on by
Citing papers per year: 2024: 3; 2025: 2; 2026: 1.
6 papers.
- 2025KokoroChat: A Japanese Psychological Counseling Dialogue Dataset Collected via Role-Playing by Trained Counselorscited by 13
- 2024Enhancing Psychotherapy Counseling: A Data Augmentation Pipeline Leveraging Large Language Models for Counseling Conversationscited by 3
- 2024Optimizing Psychological Counseling with Instruction-Tuned Large Language Modelscited by 2
- 2024UCFE: A User-Centric Financial Expertise Benchmark for Large Language Modelscited by 2
- 2025EmoStage: A Framework for Accurate Empathetic Response Generation via Perspective-Taking and Phase Recognitioncited by 0
- 2026Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counselingcited by 0
- 2026Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling27 Aug 2026
- 2025EmoStage: A Framework for Accurate Empathetic Response Generation via Perspective-Taking and Phase Recognition24 Jun 2025
- 2025KokoroChat: A Japanese Psychological Counseling Dialogue Dataset Collected via Role-Playing by Trained Counselors2 Jun 2025
- 2024UCFE: A User-Centric Financial Expertise Benchmark for Large Language Models17 Oct 2024
- 2024Optimizing Psychological Counseling with Instruction-Tuned Large Language Models19 Jun 2024
- 2024Enhancing Psychotherapy Counseling: A Data Augmentation Pipeline Leveraging Large Language Models for Counseling Conversations13 Jun 2024