AI-enabled service design in healthcare : consequences for well-being and trust
Ben HESS · Digital Library of the University of Innsbruck (University of Innsbruck) · 2026
Artificial intelligence is increasingly deployed in patient-facing healthcare services, raising fundamental questions about how patients form trust in AI-generated medical assessments and what consequences this trust has for their experience and downstream outcomes. This master's thesis examines how communication style and human oversight in AI-enabled telehealth providers influence patients' perceived trust, and how this trust subsequently affects well-being and willingness to pay. A 2×2 between-subjects experiment analyses the effects of communication style (affective vs. instrumental) and human oversight (present vs. absent) on perceived trust, with perceived risk and willingness to share as proposed moderators. The hypothesised interaction between communication style and human oversight did not significantly affect perceived trust. However, perceived trust strongly predicted both well-being and willingness to pay. Additional analyses reveal a dual-pathway structure: human oversight influenced both outcomes entirely through perceived trust, while affective communication exerted a direct effect on well-being independently of trust and had no effect on willingness to pay. Neither moderator reached significance. The findings clarify that structural credibility cues and affective communication cues operate through distinct psychological processes. Human oversight builds trust and thereby drives patients' economic valuation of the service, while affective communication shapes the emotional quality of the encounter without changing how reliable patients judge the provider to be. The results offer theoretical contributions to trust formation in AI-enabled services and practical guidance for designing telehealth tools that patients trust and are willing to pay for.