情报科学 ›› 2025, Vol. 43 ›› Issue (2): 157-165.

• 业务研究 • 上一篇    下一篇

信息场域对社交媒体用户健康风险感知的影响机制研究 ——基于fsQCA组态路径分析

  

  • 出版日期:2025-02-05 发布日期:2025-12-12

  • Online:2025-02-05 Published:2025-12-12

摘要: 【目的/意义】本研究旨在探讨社交媒体用户对健康风险的感知机制,基于场域理论,分析认知场与知觉场 对用户感知健康风险的影响,为提升公众健康信息传播效果提供理论支持。【方法/过程】采用扎根理论提取关键影 响因素,构建理论框架,结合情景问卷调查数据,运用 fsQCA识别影响用户健康风险感知的因素组合路径。【结果/ 结论】信息场域中,影响社交媒体用户健康风险感知的因素包括认知场因素、知觉场因素和个体因素,但单一前因 条件均不构成社交媒体用户高/低健康风险感知的必要条件;存在三条差异路径可以导致高风险感知,分别是“认 知-知觉场双弱型”“弱认知-强知觉场型”与“认知-知觉场双强型”路径;有四条路径降低了社交媒体对健康风险 的感知程度,分别是“情感倾诉型”“健康自信型”“知识防御型”与“情感交流+健康自信型”。【创新/局限】受限于样 本地域性和截面数据,未来可进一步拓展样本的地域覆盖范围,并考虑多阶段的动态影响机制。

Abstract: 【Purpose/significance】This study aims to explore the perception mechanism of health risks among social media users. Based on field theory, it analyzes the impact of cognitive and perceptual fields on users´ perception of health risks, providing theoreti⁃ cal support for improving the effectiveness of public health information dissemination.【Method/process】Using grounded theory, key influencing factors were extracted to construct a theoretical framework. Combined with situational questionnaire survey data, fuzzy-set qualitative comparative analysis (fsQCA) was employed to identify the configurational paths that influence users´ perception of health risks.【Result/conclusion】In the information field, factors influencing social media users´ perception of health risks include cognitive field factors, perceptual field factors, and individual factors. However, no single antecedent condition can constitute a necessary condi⁃ tion for high or low health risk perception among social media users. Three distinct paths can lead to high-risk perception: "weak cognitive-perceptual field," "weak cognitive-strong perceptual field," and "strong cognitive-perceptual field." Four paths reduce the perception of health risks on social media, namely, "emotional confiding," "health confidence," "knowledge defense," and "emotional exchange + health confidence."【Innovation/limitation】Due to the geographical limitations of the sample and cross-sectional data, fu⁃ ture research can further expand the geographical coverage of the sample and consider multi-stage dynamic influence mechanisms.