DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios

Suárez-García, Ricardo Xopan; Chavez-Castañeda, Quetzal; Orrico-Pérez, Rodrigo; Valencia-Marin, Sebastián; Castañeda-Ramírez, Ari Evelyn; Quiñones-Lara, Efrén; Ramos-Cortés, Claudio Adrián; Gaytán-Gómez, Areli Marlene; Cortés-Rodríguez, Jonathan; Jarquín-Ramírez, Jazel; Aguilar-Marchand, Nallely Guadalupe; Valdés-Hernández, Graciela; Campos-Martínez, Tomás Eduardo; Vilches-Flores, Alonso; Leon-Cabrera, Sonia; Méndez-Cruz, Adolfo René; Jay-Jímenez, Brenda Ofelia; Saldívar-Cerón, Héctor Iván

doi:10.3390/ejihpe15080152

Open AccessArticle

DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios

by

Ricardo Xopan Suárez-García

^1,2,

Quetzal Chavez-Castañeda

²

,

Rodrigo Orrico-Pérez

²,

Sebastián Valencia-Marin

^1,2,

Ari Evelyn Castañeda-Ramírez

^1,2,

Efrén Quiñones-Lara

^1,2,

Claudio Adrián Ramos-Cortés

^1,2,3,

Areli Marlene Gaytán-Gómez

^1,2,3,

Jonathan Cortés-Rodríguez

⁴,

Jazel Jarquín-Ramírez

^2,5,

Nallely Guadalupe Aguilar-Marchand

^2,5,

Graciela Valdés-Hernández

^2,6,

Tomás Eduardo Campos-Martínez

^2,6,

Alonso Vilches-Flores

^2,6

,

Sonia Leon-Cabrera

^2,6,7

,

Adolfo René Méndez-Cruz

^2,8

,

Brenda Ofelia Jay-Jímenez

^2,5,* and

Héctor Iván Saldívar-Cerón

^1,2,6,7,*

¹

Unidad de Remisión de Diabetes Mellitus (URDM), Facultad de Estudios Superiores-Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla 54090, Mexico

²

Carrera de Médico Cirujano, Facultad de Estudios Superiores-Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla 54090, Mexico

³

Laboratorio de Medicina de la Conservación, Escuela Superior de Medicina, Instituto Politécnico Nacional (IPN), Plan de San Luis y Díaz Mirón, Colonia Casco de Santo Tomás, Miguel Hidalgo, México City 11350, Mexico

⁴

Colegio de Ciencias y Humanidades, Plantel (I) Azcapotzalco (CCH), Av. Aquiles Serdan No. 2060, Ex-Hcienda del Rosario, Azcapotzalco, México City 02020, Mexico

⁵

Centro Internacional de Simulación y Entrenamiento en Soporte Vital Iztacala (CISESVI), Facultad de Estudios Superiores-Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla 54090, Mexico

⁶

Academia del Módulo de Sistema Endocrino, Carrera de Médico Cirujano, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México (UNAM), Tlalnepantla 54090, Mexico

⁷

Unidad de Biomedicina (UBIMED), Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla 54090, Mexico

⁸

Laboratorio de Inmunología (UMF), Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Los Barrios N° 1, Los Reyes Iztacala, Tlalnepantla 54090, Mexico

^*

Authors to whom correspondence should be addressed.

Eur. J. Investig. Health Psychol. Educ. 2025, 15(8), 152; https://doi.org/10.3390/ejihpe15080152

Submission received: 9 July 2025 / Revised: 30 July 2025 / Accepted: 5 August 2025 / Published: 7 August 2025

(This article belongs to the Special Issue Application of Artificial Intelligence in Health, Psychology and Education)

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Abstract

DIALOGUE (DIagnostic AI Learning through Objective Guided User Experience) is a generative artificial intelligence (GenAI)-based training program designed to enhance diagnostic communication skills in medical students. In this single-arm pre–post study, we evaluated whether DIALOGUE could improve students’ ability to disclose a type 2 diabetes mellitus (T2DM) diagnosis with clarity, structure, and empathy. Thirty clinical-phase students completed two pre-test virtual encounters with an AI-simulated patient (ChatGPT, GPT-4o), scored by blinded raters using an eight-domain rubric. Participants then engaged in ten asynchronous GenAI scenarios with automated natural-language feedback. Seven days later, they completed two post-test consultations with human standardized patients, again evaluated with the same rubric. Mean total performance increased by 36.7 points (95% CI: 31.4–42.1; p < 0.001), and the proportion of high-performing students rose from 0% to 70%. Gains were significant across all domains, most notably in opening the encounter, closure, and diabetes specific explanation. Multiple regression showed that lower baseline empathy (β = −0.41, p = 0.005) and higher digital self-efficacy (β = 0.35, p = 0.016) independently predicted greater improvement; gender had only a marginal effect. Cluster analysis revealed three learner profiles, with the highest-gain group characterized by low empathy and high digital self-efficacy. Inter-rater reliability was excellent (ICC ≈ 0.90). These findings provide empirical evidence that GenAI-mediated training can meaningfully enhance diagnostic communication and may serve as a scalable, individualized adjunct to conventional medical education.

Keywords: generative AI; medical education; diagnostic communication; ChatGPT; virtual patient; standardized patient; communication training; empathy in diagnosis; formative simulation

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MDPI and ACS Style

Suárez-García, R.X.; Chavez-Castañeda, Q.; Orrico-Pérez, R.; Valencia-Marin, S.; Castañeda-Ramírez, A.E.; Quiñones-Lara, E.; Ramos-Cortés, C.A.; Gaytán-Gómez, A.M.; Cortés-Rodríguez, J.; Jarquín-Ramírez, J.; et al. DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios. Eur. J. Investig. Health Psychol. Educ. 2025, 15, 152. https://doi.org/10.3390/ejihpe15080152

AMA Style

Suárez-García RX, Chavez-Castañeda Q, Orrico-Pérez R, Valencia-Marin S, Castañeda-Ramírez AE, Quiñones-Lara E, Ramos-Cortés CA, Gaytán-Gómez AM, Cortés-Rodríguez J, Jarquín-Ramírez J, et al. DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios. European Journal of Investigation in Health, Psychology and Education. 2025; 15(8):152. https://doi.org/10.3390/ejihpe15080152

Chicago/Turabian Style

Suárez-García, Ricardo Xopan, Quetzal Chavez-Castañeda, Rodrigo Orrico-Pérez, Sebastián Valencia-Marin, Ari Evelyn Castañeda-Ramírez, Efrén Quiñones-Lara, Claudio Adrián Ramos-Cortés, Areli Marlene Gaytán-Gómez, Jonathan Cortés-Rodríguez, Jazel Jarquín-Ramírez, and et al. 2025. "DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios" European Journal of Investigation in Health, Psychology and Education 15, no. 8: 152. https://doi.org/10.3390/ejihpe15080152

APA Style

Suárez-García, R. X., Chavez-Castañeda, Q., Orrico-Pérez, R., Valencia-Marin, S., Castañeda-Ramírez, A. E., Quiñones-Lara, E., Ramos-Cortés, C. A., Gaytán-Gómez, A. M., Cortés-Rodríguez, J., Jarquín-Ramírez, J., Aguilar-Marchand, N. G., Valdés-Hernández, G., Campos-Martínez, T. E., Vilches-Flores, A., Leon-Cabrera, S., Méndez-Cruz, A. R., Jay-Jímenez, B. O., & Saldívar-Cerón, H. I. (2025). DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios. European Journal of Investigation in Health, Psychology and Education, 15(8), 152. https://doi.org/10.3390/ejihpe15080152

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DIALOGUE: A Generative AI-Based Pre–Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios

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