Research on rapid construction methods and evaluation of health education resources in public health emergencies based on knowledge development

Objectives This study aims to construct and validate an interdisciplinary framework based on Library and Information Science (LIS) to improve the timeliness and accuracy of health education resource development during public health emergencies, and to provide a practical technical approach and theoretical framework through a complete “analysis-generation-evaluation” cycle for resolving the conflict between “information overload” and “precise targeting” in crisis communication. Methods A total of 1,026 epidemic bulletins from various levels of government in China (2020–2024) were collected as the primary data source. In-depth knowledge development was achieved through core Library and Information Science (LIS) methods such as knowledge graph construction, thematic analysis, natural language processing (NLP), and association rule mining. Building upon these analytical results, an automated resource generation system was developed based on the Technology Acceptance Model (TAM). The system was subsequently evaluated using questionnaires administered to 305 users.