@inproceedings{schmidmaier2025secondary,
	title        = {Using a Secondary Channel to Display the Internal Empathic Resonance of LLM-Driven Agents for Mental Health Support},
	author       = {Schmidmaier, Matthias and Rupp, Jonathan and Mayer, Sven},
	year         = 2025,
	month        = {October},
	booktitle    = {Proceedings of the 27th International Conference on Multimodal Interaction},
	location     = {Canberra, ACT, Australia},
	publisher    = {Association for Computing Machinery},
	address     = {New York, NY, USA},
	series       = {ICMI '25},
	pages        = {},
	doi          = {10.1145/3716553.3750759},
	isbn         = {979-8-4007-1499-3/2025/10},
	url          = {https://doi.org/10.1145/3716553.3750759},
	abstract     = {Conversational agents are becoming increasingly popular for digital mental health support. However, while empathy is essential for effective emotional support, the unimodal request-response interaction of such systems limits empathic communication. We address this limitation through a secondary channel that displays an agent's inner reflections, similar to how nonverbal feedback in human interaction conveys cognitive and emotional states. We implemented a chatbot that generates not only conversational responses but also describes internal reasoning and emotional resonance. A user study involving N=188 participants indicated a statistically significant increase in perceived empathy (+14.7%) when the agent's internal reflections were displayed. Our findings demonstrate a practical method to enhance empathic interaction with LLM-based chatbots in empathy-critical contexts. Additionally, this work opens possibilities for multimodal systems where LLM-generated reflections may serve as input for generating nonverbal feedback.},
	keywords     = {HCI, LLM, empathy, mental health, internal feedback}
}