A Fuzzy Fusion Model of Patients' Multi-source Perceived Trust Considering Time Factor in Online Health Community

Online health community has become a new way of seeking medical treatment. Due to the high perceived risk by patient and the importance of medical decision-making, it can easily lead to trust crises among patients. In the context of Online health community, patients establish perceived trust based on their personal past medical experiences and recommendations from others, which represents a typical trust fusion model. Among this, similarity determines the impact of past medical experiences and evaluations from others on patients' perceived trust, and memories of past experiences decay over time. Based on the aforementioned issues, this paper uses Case-Based Decision Theory as the fundamental framework of the model, combined with Intuitionistic Fuzzy Sets, Evidence Reasoning, and Anchoring Theory, integrates the Ebbinghaus forgetting curve into the calculation of patients' perceived trust, and constructs a multi-source perceived trust fusion model for patients. This model combines the decision-maker's experience and recommendations from others to effectively quantify patients' perceived trust in medical services and integrates multidisciplinary methods, providing new ideas for improving trust fusion methods and offering new measurement methods to help internet medical platforms predict patients’ perceived trust.