Robin Zatrib
Papers
1
Total Citations
3
H-Index
1
About
Robin Zatrib’s research sits at the intersection of social robotics, human-robot interaction, and health communication, exploring how robots can influence public behavior during crises. Their most cited work, a 2021 study testing the Elaboration Likelihood Model of Persuasion in video-based human-robot interactions, investigates how social robots can effectively encourage adherence to health regulations—such as mask-wearing and social distancing during a pandemic. This study, with 3 citations, demonstrates Zatrib’s early but impactful contribution to understanding robotic persuasion in public health contexts. By framing robots as assistive tools for public order offices, Zatrib highlights their potential to reduce infection risks while guiding human behavior. Though early in their career, Zatrib’s work bridges psychological theory and applied robotics, offering practical insights for deploying robots in real-world health scenarios. Their research is particularly relevant for students and researchers interested in persuasive technology, crisis communication, and the ethical deployment of social robots. As the field grows, Zatrib’s focus on evidence-based, theory-driven design positions them as a promising voice in shaping how robots can support public health initiatives.
Research Focus
Key Achievements
Top Papers
- 1