Text mining of disease information needs of hemodialysis patients in online medical communities
10.3760/cma.j.cn115682-20241121-06407
- VernacularTitle:在线医疗社区中血液透析患者疾病信息需求的文本挖掘
- Author:
Dan ZHU
1
;
Dongqian LI
1
Author Information
1. 山西白求恩医院/山西医学科学院/同济山西医院/山西医科大学第三医院急诊科，太原 030032
- Publication Type:Journal Article
- Keywords:
Hemodialysis;
Online medical community;
Information needs;
Latent Dirichlet allocation model;
Theme mining
- From:
Chinese Journal of Modern Nursing
2025;31(26):3567-3572
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the disease information needs of hemodialysis patients in online medical communities based on text mining, to provide a basis for developing online medical nursing services that meet the needs of hemodialysis patients.Methods:The Bazhuyu Collector was used to collect information on the disease needs of hemodialysis patients in the online medical communities of "39 Health Network" "120 Ask" "Haodaifu Online", and "Family Doctor Online" from January 1, 2013, to December 31, 2022. The ROSTCM 6.0 software was used for word frequency and semantic network analysis, and a cloud chart was created based on the word frequency results. The latent dirichlet allocation model was used to perform text mining.Results:A total of 3 093 valid data were obtained, and three hemodialysis patient disease information need themes were extracted, namely, causes and treatment of hemodialysis, principles of hemodialysis and length of patient survival, and complications and costs of hemodialysis.Conclusions:The disease information needs of hemodialysis patients focus on three main aspects of the causes and treatment of hemodialysis, principles of hemodialysis and length of patient survival, and complications and costs of hemodialysis. Healthcare professionals can develop health education content based on the disease information needs of hemodialysis patients.
