Hesy: an AI-driven training tool for vaccine communication in medical education, Italy, 2026
Abstract
Background: Vaccine hesitancy is a critical public health threat that requires healthcare professionals to possess advanced interpersonal and advocacy skills. Traditional medical curricula often lack scalable, interactive settings to practise complex communication strategies. HESY was developed as an innovative digital training tool to bridge this gap, using generative AI to simulate clinical encounters in a risk-free environment.
Objectives: The programme aims to equip healthcare professionals with the Motivational Interviewing (MI) framework and the 5Cs model to manage hesitant patient archetypes. The primary goals are to evaluate AI’s capacity to replicate realistic patient hesitancy and assess the impact of these simulations on user confidence when managing medical misinformation. The platform provides 24/7 access to 5 distinct patient scenarios, simulations are structured in 5 sequential interactions, providing a safe environment to master evidence-based discourse.
Results: A pilot evaluation was conducted using a 13-item, 5-point Likert scale questionnaire, between February and April 2026 with 51 medical students (66% women, mean age 24) enrolled at the University of Udine. Participants reported high perceived realism of the AI-driven profiles (mean 3.9/5) and stated that the tool effectively allowed them to practise MI techniques (mean 4.2/5). The simulation significantly increased student confidence in managing vaccine hesitancy (mean 3.7/5) and medical misinformation (mean 3.8/5). Furthermore, it improved their understanding of the emotional roots behind hesitancy, such as fear or mistrust (mean 3.9/5).
Conclusions: HESY represents an innovative public health pilot tool that facilitates the transition from theoretical knowledge to practical interpersonal effectiveness. A primary lesson learnt is that AI-driven role-play with integrated feedback is a scalable and effective tool for preparing a workforce capable of navigating diverse patient hesitancy.
Key messages: • AI-driven simulations offer a scalable, evidence-based platform to master vaccine communication using Motivational Interviewing and the 5Cs model.
• Integrating diverse patient archetypes and automated feedback into digital training significantly enhances confidence in addressing vaccine hesitancy and medical misinformation.
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BibTeX
@article{tesei2026hesy,
title = {{Hesy: an AI-driven training tool for vaccine communication in medical education, Italy, 2026}},
author = {L Tesei and M Zerbinati and G Ghinelli and E Lampis and L Brunelli and S Brusaferro},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.884},
url = {https://doi.org/10.1093/eurpub/ckag169.884},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Hesy: an AI-driven training tool for vaccine communication in medical education, Italy, 2026
AU - L Tesei
AU - M Zerbinati
AU - G Ghinelli
AU - E Lampis
AU - L Brunelli
AU - S Brusaferro
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.884
UR - https://doi.org/10.1093/eurpub/ckag169.884
AB - Background: Vaccine hesitancy is a critical public health threat that requires healthcare professionals to possess advanced interpersonal and advocacy skills. Traditional medical curricula often lack scalable, interactive settings to practise complex communication strategies. HESY was developed as an innovative digital training tool to bridge this gap, using generative AI to simulate clinical encounters in a risk-free environment. Objectives: The programme aims to equip healthcare professionals with the Motivational Interviewing (MI) framework and the 5Cs model to manage hesitant patient archetypes. The primary goals are to evaluate AI’s capacity to replicate realistic patient hesitancy and assess the impact of these simulations on user confidence when managing medical misinformation. The platform provides 24/7 access to 5 distinct patient scenarios, simulations are structured in 5 sequential interactions, providing a safe environment to master evidence-based discourse. Results: A pilot evaluation was conducted using a 13-item, 5-point Likert scale questionnaire, between February and April 2026 with 51 medical students (66% women, mean age 24) enrolled at the University of Udine. Participants reported high perceived realism of the AI-driven profiles (mean 3.9/5) and stated that the tool effectively allowed them to practise MI techniques (mean 4.2/5). The simulation significantly increased student confidence in managing vaccine hesitancy (mean 3.7/5) and medical misinformation (mean 3.8/5). Furthermore, it improved their understanding of the emotional roots behind hesitancy, such as fear or mistrust (mean 3.9/5). Conclusions: HESY represents an innovative public health pilot tool that facilitates the transition from theoretical knowledge to practical interpersonal effectiveness. A primary lesson learnt is that AI-driven role-play with integrated feedback is a scalable and effective tool for preparing a workforce capable of navigating diverse patient hesitancy. Key messages: • AI-driven simulations offer a scalable, evidence-based platform to master vaccine communication using Motivational Interviewing and the 5Cs model. • Integrating diverse patient archetypes and automated feedback into digital training significantly enhances confidence in addressing vaccine hesitancy and medical misinformation.
SN - 1101-1262
SN - 1464-360X
ER -