Comparing Human Roleplayers and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns

This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by Mistrals Mixtral 8x7b using 4-bit quantization. These interactions were analysed with a counselling communication pattern system at sentence level. We investigated two key questions: (1) to what extent LLM-generated responses replicate authentic conversational dynamics and (2) whether counsellors' communication behaviour differs when interacting with human versus LLM-simulated clients. The findings highlight both similarities and differences in the application of counselling patterns across scenarios, showing the potential of LLM-based role-playing exercises to enhance counselling competencies and to identify areas for further refinement in virtual client simulations.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-12
DOI
https://doi.org/10.5281/zenodo.15870259
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparing Human Roleplayers and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns

Zenodo (CERN European Organization for Nuclear Research)
Digital Mental Health Interventions
article

Comparing Human Roleplayers and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns

article en

Abstract

This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by Mistrals Mixtral 8x7b using 4-bit quantization. These interactions were analysed with a counselling communication pattern system at sentence level. We investigated two key questions: (1) to what extent LLM-generated responses replicate authentic conversational dynamics and (2) whether counsellors' communication behaviour differs when interacting with human versus LLM-simulated clients. The findings highlight both similarities and differences in the application of counselling patterns across scenarios, showing the potential of LLM-based role-playing exercises to enhance counselling competencies and to identify areas for further refinement in virtual client simulations.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 47%
Digital Mental Health Interventions
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