Pith. sign in

REVIEW 2 cited by

Can Large Language Models be Used to Provide Psychological Counselling? An Analysis of GPT-4-Generated Responses Using Role-play Dialogues

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2402.12738 v1 pith:NCZP4UED submitted 2024-02-20 cs.CL cs.AIcs.HC

classification cs.CLcs.AIcs.HC
keywords counselorsdialoguecounselingresponsesthoseanalysisdatagenerated
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. KokoroChat: A Japanese Psychological Counseling Dialogue Dataset Collected via Role-Playing by Trained Counselors

    cs.CL 2025-06 conditional novelty 7.0 of 10

    A large Japanese counseling dialogue dataset collected via role-play by trained counselors, with per-dialogue client feedback, improves LLM counseling response generation and evaluation.

  2. EmoStage: A Framework for Accurate Empathetic Response Generation via Perspective-Taking and Phase Recognition

    cs.CL 2025-06 conditional novelty 5.0 of 10

    EmoStage improves LLM counseling responses by prompting models to first take the client's perspective and recognize the counseling stage, with no training data.

Pith tools