ORIGINAL RESEARCH article
Front. Public Health
Sec. Public Mental Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1649342
This article is part of the Research TopicAdvances in Artificial Intelligence Applications that Support Psychosocial HealthView all 6 articles
The Impact of Generative AI's Information Delivery Methods on Emotional Exhaustion Among Bullying Roles in the Medical Workplace
Provisionally accepted
- 1North Sichuan Medical College, Nanchong, China
- 2Sichuan Provincial primary health service development research center, Sichuan, China
- 3Jiangxi Normal University, Nanchang, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Workplace bullying is closely related to poor work states. Previous studies have primarily explored the binary relationship between perpetrators and victims, with limited research examining the emotional exhaustion of bullying roles from the perspectives of victims and bystanders. Therefore, this study recruited 597 participants and conducted a scenario-based experiment to investigate whether generative AI can alleviate the poor work states of bullying roles in the medical workplace, thereby demonstrating the interaction between generative AI's information delivery methods and bullying roles in relation to emotional exhaustion. The results showed that bullying roles in the medical workplace significantly influence emotional exhaustion, with victims experiencing significantly higher levels than bystanders.Moreover, generative AI's information delivery methods can effectively moderate the work states of victims. Thus, this study advances the field of human-computer interaction by shifting its focus from functional adaptation to emotional ecology. It also provides empirical evidence from medical scenarios for the uncanny valley theory. Furthermore, this research lays a theoretical foundation for the design of emotional interaction functions in medical AI systems.
Keywords: Generative AI, Information delivery methods, workplace bullying, bullying roles, Emotional exhaustion, bystander, Victim
Received: 23 Jun 2025; Accepted: 30 Jul 2025.
Copyright: © 2025 Deng, Yang, Liang, Hu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Dajun Yang, Sichuan Provincial primary health service development research center, Sichuan, China
Pengcheng Zhang, North Sichuan Medical College, Nanchong, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.