Pan Xuan, Tang Zhuoyuan, Liu Ying, Ren Jingjing
The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Digit Health. 2024 Sep 26;10:20552076241282622. doi: 10.1177/20552076241282622. eCollection 2024 Jan-Dec.
The primary aim of this study is to analyze health information seeking behaviors of users related to child fever within online health communities. The findings will serve as a foundation for the development of targeted interventions and resources for addressing the specific information needs related to child fever. Ultimately, this will enhance parental capabilities in managing fever in children and for improving the quality of communication between healthcare professionals and parents dealing with feverish children.
This study employed data crawling to gather Q&A data on childhood fever from online health communities, specifically "haodf.com" between March 15, 2022, and March 15, 2023. A total of 47,781 texts were analyzed using a mixed research approach that combines qualitative text topic analysis with BERTopic algorithm.
The health information needs regarding children's fever can be categorized into 6 primary topics and 17 secondary topics. Among them, parents' demand for medication consultation and medical guidance (Topic A) was the highest at 45.40%, followed by information concerning the management of fever symptoms and body temperature in children (Topic B) at 30.35%. 13.24% of the data focused on examination recommendations and interpretation of results (Topic C).
This study proposes a mixed thematic analysis method combining qualitative text thematic analysis and the BERTopic topic model, which reveals parents' information-seeking behaviors about children with fever. It emphasizes the challenges faced by parents in assessing their children's condition and highlights the necessity of continuous health information support and evidence-based medical knowledge. This can promote the improvement of medical services, optimize doctor-patient communication, strengthen patient information support, and optimize the content of online health communities.
本研究的主要目的是分析在线健康社区中用户与儿童发热相关的健康信息搜索行为。研究结果将为制定针对性干预措施和资源提供基础,以满足与儿童发热相关的特定信息需求。最终,这将提高父母管理儿童发热的能力,并改善医疗保健专业人员与处理发热儿童的父母之间的沟通质量。
本研究采用数据爬取的方法,收集2022年3月15日至2023年3月15日期间在线健康社区(具体为“好大夫在线”)上有关儿童发热的问答数据。使用定性文本主题分析与BERTopic算法相结合的混合研究方法,对总共47781篇文本进行了分析。
儿童发热的健康信息需求可分为6个主要主题和17个次要主题。其中,家长对用药咨询和医疗指导的需求(主题A)最高,为45.40%,其次是关于儿童发热症状和体温管理方面的信息(主题B),占30.35%。13.24%的数据集中在检查建议和结果解读(主题C)上。
本研究提出了一种结合定性文本主题分析和BERTopic主题模型的混合主题分析方法,揭示了家长对发热儿童的信息搜索行为。它强调了家长在评估孩子病情时面临的挑战,并突出了持续健康信息支持和循证医学知识的必要性。这可以促进医疗服务的改善,优化医患沟通,加强患者信息支持,并优化在线健康社区的内容。