Are you willing to forgive generative AI doctors? Trust repair after failures in online health consultation services

Abstract

While generative AI doctors are increasingly used in online health consultation services, research on trust repair following service failures remains limited. We examined how attribution style, social support, and anthropomorphism influence individuals' trust repair and behavioral intention. A total of 512 participants were recruited to take part in a between-subjects experiment with a 2 (internal vs. external attribution) × 2 (informational vs. emotional support) × 2 (anthropomorphism vs. non-anthropomorphism) design. The results revealed that participants exposed to internal attribution, emotional support, or anthropomorphism conditions reported higher levels of trust repair. Anthropomorphism influences the effectiveness of attribution style and social support in repairing trust in GAI doctors. Moreover, an interesting interaction was observed between attribution style and social support: when the GAI doctor used internal attribution, informational support was more effective; under external attribution, emotional support proved more effective. In addition, the effect of social support on behavioral intention was fully mediated by trust repair. These findings offer practical implications for optimizing the design of GAI doctors, enhancing communication and collaboration between GAI doctors and users, and ultimately strengthening the resilience of AI-based health consultation services.

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