Center for Reproductive Medicine, Cheeloo College of Medicine, Shandong University, Jinan, China.
Research Unit of Gametogenesis and Health of ART-Offspring, Chinese Academy of Medical Sciences, Jinan, China.
Front Public Health. 2023 Sep 18;11:1192405. doi: 10.3389/fpubh.2023.1192405. eCollection 2023.
The advent of bigdata era fundamentally transformed the nature of medical information seeking and the traditional binary medical relationship. Weaving stress coping theory and information processing theory, we developed an integrative perspective on information seeking behavior and explored the antecedent and consequence of such behavior.
Data were collected from 573 women suffering from infertility who was seeking assisted reproductive technology treatment in China. We used AMOS 22.0 and the PROCESS macro in SPSS 25.0 software to test our model.
Our findings demonstrated that patients' satisfaction with information received from the physicians negatively predicted their behavior involvement in information seeking, such behavior positively related to their perceived information overload, and the latter negatively related to patient-physician relationship quality. Further findings showed that medical information seeking behavior and perceived information overload would serially mediate the impacts of satisfaction with information received from physicians on patient-physician relationship quality.
This study extends knowledge of information seeking behavior by proposing an integrative model and expands the application of stress coping theory and information processing theory. Additionally, it provides valuable implications for patients, physicians and public health information service providers.
大数据时代的到来从根本上改变了医学信息检索的性质和传统的二元医患关系。我们将压力应对理论和信息处理理论编织在一起，对信息寻求行为进行了综合分析，并探讨了这种行为的前因和后果。
数据来自中国 573 名正在接受辅助生殖技术治疗的不孕妇女。我们使用 AMOS 22.0 和 SPSS 25.0 软件中的 PROCESS 宏来测试我们的模型。
我们的研究结果表明，患者对医生提供的信息的满意度会负向预测他们的信息寻求行为参与度，这种行为会正向影响他们的信息过载感，而后者又会负向影响医患关系质量。进一步的研究结果表明，医疗信息寻求行为和感知信息过载会依次中介医生提供的信息满意度对医患关系质量的影响。
本研究通过提出一个综合模型，扩展了信息寻求行为的知识，拓展了压力应对理论和信息处理理论的应用。此外，它为患者、医生和公共卫生信息服务提供者提供了有价值的启示。
