ArticleFrontiers in public health2025
The impact of generative AI'S information delivery methods on emotional exhaustion among bullying roles in the medical workplace.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Research on factors affecting trust formation of generative AI agents in human-AI interaction contexts.Frontiers in psychology · 2026Article
- Joint latent profiles of workplace violence and burnout among healthcare workers and their associated factors: a cross-sectional study.Frontiers in psychiatry · 2026Article
- Associations of perceived teacher-student relationship and friendship quality with adolescents' interest in physical education: a latent profile analysis.Frontiers in sports and active living · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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