@inproceedings{tayal-etal-2025-towards,
title = "Towards conversational assistants for health applications: using {C}hat{GPT} to generate conversations about heart failure",
author = "Tayal, Anuja and
Salunke, Devika and
Di Eugenio, Barbara and
Allen-Meares, Paula and
Abril, Eulalia Puig and
Garcia-Bedoya, Olga and
Dickens, Carolyn and
Boyd, Andrew",
editor = "B{\'e}chet, Fr{\'e}d{\'e}ric and
Lef{\`e}vre, Fabrice and
Asher, Nicholas and
Kim, Seokhwan and
Merlin, Teva",
booktitle = "Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue",
month = aug,
year = "2025",
address = "Avignon, France",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.sigdial-1.43/",
pages = "527--537",
abstract = "We explore the potential of ChatGPT to generate conversations focused on self-care strategies for African-American patients with heart failure, a domain with limited specialized datasets. To simulate patient-health educator dialogues, we employed four prompting strategies: aspects, African American Vernacular English, Social Determinants of Health (SDOH), and SDOH-informed reasoning. Conversations were generated across key self-care aspects{---} food, exercise, and fluid intake{---}with varying turn lengths and incorporated patient-specific SDOH attributes such as age, gender, neighborhood, and socioeconomic status. Our findings show that effective prompt design is essential. While incorporating SDOH and reasoning improves dialogue quality, ChatGPT still lacks the empathy and engagement needed for meaningful healthcare communication."
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<abstract>We explore the potential of ChatGPT to generate conversations focused on self-care strategies for African-American patients with heart failure, a domain with limited specialized datasets. To simulate patient-health educator dialogues, we employed four prompting strategies: aspects, African American Vernacular English, Social Determinants of Health (SDOH), and SDOH-informed reasoning. Conversations were generated across key self-care aspects— food, exercise, and fluid intake—with varying turn lengths and incorporated patient-specific SDOH attributes such as age, gender, neighborhood, and socioeconomic status. Our findings show that effective prompt design is essential. While incorporating SDOH and reasoning improves dialogue quality, ChatGPT still lacks the empathy and engagement needed for meaningful healthcare communication.</abstract>
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%0 Conference Proceedings
%T Towards conversational assistants for health applications: using ChatGPT to generate conversations about heart failure
%A Tayal, Anuja
%A Salunke, Devika
%A Di Eugenio, Barbara
%A Allen-Meares, Paula
%A Abril, Eulalia Puig
%A Garcia-Bedoya, Olga
%A Dickens, Carolyn
%A Boyd, Andrew
%Y Béchet, Frédéric
%Y Lefèvre, Fabrice
%Y Asher, Nicholas
%Y Kim, Seokhwan
%Y Merlin, Teva
%S Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2025
%8 August
%I Association for Computational Linguistics
%C Avignon, France
%F tayal-etal-2025-towards
%X We explore the potential of ChatGPT to generate conversations focused on self-care strategies for African-American patients with heart failure, a domain with limited specialized datasets. To simulate patient-health educator dialogues, we employed four prompting strategies: aspects, African American Vernacular English, Social Determinants of Health (SDOH), and SDOH-informed reasoning. Conversations were generated across key self-care aspects— food, exercise, and fluid intake—with varying turn lengths and incorporated patient-specific SDOH attributes such as age, gender, neighborhood, and socioeconomic status. Our findings show that effective prompt design is essential. While incorporating SDOH and reasoning improves dialogue quality, ChatGPT still lacks the empathy and engagement needed for meaningful healthcare communication.
%U https://aclanthology.org/2025.sigdial-1.43/
%P 527-537
Markdown (Informal)
[Towards conversational assistants for health applications: using ChatGPT to generate conversations about heart failure](https://aclanthology.org/2025.sigdial-1.43/) (Tayal et al., SIGDIAL 2025)
ACL
- Anuja Tayal, Devika Salunke, Barbara Di Eugenio, Paula Allen-Meares, Eulalia Puig Abril, Olga Garcia-Bedoya, Carolyn Dickens, and Andrew Boyd. 2025. Towards conversational assistants for health applications: using ChatGPT to generate conversations about heart failure. In Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 527–537, Avignon, France. Association for Computational Linguistics.