Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma

David Villarreal-Zegarra; C. Mahony Reategui-Rivera; Yscenia Paredes-Gonzales; Gianfranco Centeno-Terrazas; Joseph Finkelstein

doi:10.3233/SHTI250661

Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma

David Villarreal-Zegarra, C. Mahony Reategui-Rivera, Yscenia Paredes-Gonzales, Gianfranco Centeno-Terrazas, Joseph Finkelstein

Research output: Chapter in Book/Report › Conference contribution › peer-review

Abstract

This study evaluated GPT-based conversational agents in tasks related to healthcare provider stigma. The main finding was that GPT-4o models, using Role-Playing (RP) and Chain of Thought (CoT) techniques, outperformed other models in tasks such as defining healthcare provider stigma, identifying types of stigma, and explaining its consequences. The Personalized GPT model showed lower performance, particularly in areas related to treatment access, adherence, and stigma risk factors. These results suggest that advanced prompting techniques significantly enhance the agent’s ability to deliver complex and nuanced information about healthcare provider stigma. The study supports the potential of GPT-based agents as scalable educational tools for reducing stigma, especially in resource-limited settings.

Original language	American English
Title of host publication	Global Healthcare Transformation in the Era of Artificial Intelligence and Informatics
Editors	John Mantas, Arie Hasman, Parisis Gallos, Emmanouil Zoulias, Konstantinos Karitis
Publisher	IOS Press BV
Pages	4-8
Number of pages	5
ISBN (Electronic)	9781643686004
DOIs	https://doi.org/10.3233/SHTI250661
State	Indexed - 26 Jun 2025
Externally published	Yes
Event	23rd Annual International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2025 - Athens, Greece Duration: 4 Jul 2025 → 6 Jul 2025

Publication series

Name	Studies in Health Technology and Informatics
Volume	328
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	23rd Annual International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2025
Country/Territory	Greece
City	Athens
Period	4/07/25 → 6/07/25

Bibliographical note

Publisher Copyright:
© 2025 The Authors.

Keywords

ChatGPT
Generative Artificial Intelligence
Health Personnel
stigma

Access to Document

10.3233/SHTI250661

Cite this

Villarreal-Zegarra, D., Reategui-Rivera, C. M., Paredes-Gonzales, Y., Centeno-Terrazas, G., & Finkelstein, J. (2025). Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma. In J. Mantas, A. Hasman, P. Gallos, E. Zoulias, & K. Karitis (Eds.), Global Healthcare Transformation in the Era of Artificial Intelligence and Informatics (pp. 4-8). (Studies in Health Technology and Informatics; Vol. 328). IOS Press BV. https://doi.org/10.3233/SHTI250661

Villarreal-Zegarra, David ; Reategui-Rivera, C. Mahony ; Paredes-Gonzales, Yscenia et al. / Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma. Global Healthcare Transformation in the Era of Artificial Intelligence and Informatics. editor / John Mantas ; Arie Hasman ; Parisis Gallos ; Emmanouil Zoulias ; Konstantinos Karitis. IOS Press BV, 2025. pp. 4-8 (Studies in Health Technology and Informatics).

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title = "Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma",

abstract = "This study evaluated GPT-based conversational agents in tasks related to healthcare provider stigma. The main finding was that GPT-4o models, using Role-Playing (RP) and Chain of Thought (CoT) techniques, outperformed other models in tasks such as defining healthcare provider stigma, identifying types of stigma, and explaining its consequences. The Personalized GPT model showed lower performance, particularly in areas related to treatment access, adherence, and stigma risk factors. These results suggest that advanced prompting techniques significantly enhance the agent{\textquoteright}s ability to deliver complex and nuanced information about healthcare provider stigma. The study supports the potential of GPT-based agents as scalable educational tools for reducing stigma, especially in resource-limited settings.",

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month = jun,

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doi = "10.3233/SHTI250661",

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Villarreal-Zegarra, D, Reategui-Rivera, CM, Paredes-Gonzales, Y, Centeno-Terrazas, G & Finkelstein, J 2025, Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma. in J Mantas, A Hasman, P Gallos, E Zoulias & K Karitis (eds), Global Healthcare Transformation in the Era of Artificial Intelligence and Informatics. Studies in Health Technology and Informatics, vol. 328, IOS Press BV, pp. 4-8, 23rd Annual International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2025, Athens, Greece, 4/07/25. https://doi.org/10.3233/SHTI250661

Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma. / Villarreal-Zegarra, David; Reategui-Rivera, C. Mahony; Paredes-Gonzales, Yscenia et al.
Global Healthcare Transformation in the Era of Artificial Intelligence and Informatics. ed. / John Mantas; Arie Hasman; Parisis Gallos; Emmanouil Zoulias; Konstantinos Karitis. IOS Press BV, 2025. p. 4-8 (Studies in Health Technology and Informatics; Vol. 328).

Research output: Chapter in Book/Report › Conference contribution › peer-review

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AB - This study evaluated GPT-based conversational agents in tasks related to healthcare provider stigma. The main finding was that GPT-4o models, using Role-Playing (RP) and Chain of Thought (CoT) techniques, outperformed other models in tasks such as defining healthcare provider stigma, identifying types of stigma, and explaining its consequences. The Personalized GPT model showed lower performance, particularly in areas related to treatment access, adherence, and stigma risk factors. These results suggest that advanced prompting techniques significantly enhance the agent’s ability to deliver complex and nuanced information about healthcare provider stigma. The study supports the potential of GPT-based agents as scalable educational tools for reducing stigma, especially in resource-limited settings.

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Villarreal-Zegarra D, Reategui-Rivera CM, Paredes-Gonzales Y, Centeno-Terrazas G, Finkelstein J. Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma. In Mantas J, Hasman A, Gallos P, Zoulias E, Karitis K, editors, Global Healthcare Transformation in the Era of Artificial Intelligence and Informatics. IOS Press BV. 2025. p. 4-8. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI250661

Assessment of GPT-Based Conversational Agents Aimed to Reduce Healthcare Provider Stigma

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this