Research Center for Network Public Opinion Governance of CPPU, Langfang, China.
Front Public Health. 2024 Aug 29;12:1392743. doi: 10.3389/fpubh.2024.1392743. eCollection 2024.
This study investigates the mutual influence between online medical search and online medical consultation. It focuses on understanding the health information needs that drive these health information-seeking behaviors by utilizing insights from behavioral big data.
We used actual behavioral data from Chinese internet users on Baidu platform's "Epidemic Index" from November 26, 2022, to January 25, 2023. Data modeling was conducted to ensure the reliability of the model. Drawing on the logistic model, we constructed a foundational model to quantify the evolutionary patterns of online medical search and online medical consultation. An impact function was defined to measure their mutual influence. Additionally, a pattern detection experiment was conducted to determine the structure of the impact function with maximum commonality through data fitting.
The analysis allowed us to build a mathematical model that quantifies the nonlinear correlation between online medical search and online medical consultation. Numerical analysis revealed a predation mechanism between online medical consultation and online medical search, highlighting the role of health information needs in this dynamic.
This study offers a novel practical approach to better meet the public's health information needs by understanding the interplay between online medical search and consultation. Additionally, the modeling method used here is broadly applicable, providing a framework for quantifying nonlinear correlations among different behaviors when appropriate data is available.
本研究旨在探讨在线医疗搜索与在线医疗咨询之间的相互影响。通过利用行为大数据的洞察,研究聚焦于理解驱动这些健康信息寻求行为的健康信息需求。
我们使用了来自 2022 年 11 月 26 日至 2023 年 1 月 25 日期间中国互联网用户在百度平台“疫情指数”上的实际行为数据。通过数据建模确保模型的可靠性。基于逻辑回归模型,我们构建了一个基础模型来量化在线医疗搜索和在线医疗咨询的演化模式。定义了一个影响函数来衡量它们之间的相互影响。此外,通过数据拟合进行模式检测实验,以确定具有最大共性的影响函数的结构。
该分析使我们能够构建一个数学模型,量化在线医疗搜索和在线医疗咨询之间的非线性相关性。数值分析揭示了在线医疗咨询和在线医疗搜索之间的捕食机制,强调了健康信息需求在这一动态中的作用。
本研究通过理解在线医疗搜索和咨询之间的相互作用,提供了一种新颖的实用方法,以更好地满足公众的健康信息需求。此外,这里使用的建模方法具有广泛的适用性,为在有适当数据可用时量化不同行为之间的非线性相关性提供了一个框架。