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Navigating Health Information: Understanding Conflicting Adoption Mechanisms and Cognitive-Behavioral Paradoxes from the Patient’s Lens

  • Yan Jin,
  • Di Zhao,
  • Zhuo Sun,
  • Chongwu Bi,
  • Ruixian Yang

摘要

The advancement of information technology has significantly expanded the avenues and approaches through which individuals can access health-related information. However, this proliferation of information sources has also introduced challenges. Specifically, the abundance of diverse sources often generates conflicting health information, making it increasingly challenging for individuals to make informed decisions and navigate their health-related choices. While previous research has primarily focused on factors influencing adoption behavior, willingness to adopt, and the outcomes of adoption, there has been a relative neglect of the underlying processes, formation mechanisms, and the mechanics governing adoption behavior itself. To address this gap, this study takes a patient-centered approach to construct a model of Conflicting health information adoption. It seeks to comprehensively explore the adoption process and behavioral phenomena among patients, while also employing the concept of “trans-theory” to conduct a thorough analysis. The study’s findings illuminate a common pattern when patients encounter conflicting health information: a misalignment between their cognitive understanding and their subsequent behavior across various facets of adoption behavior. This inconsistency arises from a complex interplay of factors, including the influence of information, individual abilities, psychological factors, and environmental conditions, all shaping the process of adopting Conflicting health information. This research, grounded in a patient-centric perspective, aims to shed light on the intricate dynamics of conflicting health information adoption. By bridging the gap between cognition and behavior, it seeks to contribute to a more informed and effective approach to health information management in a world marked by information abundance and complexity.