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Objective:To evaluate the quality, content and feasibility of health information on breast cancer treatment in Chinese websites, for reference in standardizing online health information.Methods:In January 2022, three Chinese search engines, namely Baidu, Sogou and Haosou, were used to search with " breast cancer" and " breast cancer treatment" as keywords. The first 50 links identified by each engine were accessed to screen breast cancer treatment health information websites. Subsequently, the DISCERN scoring tool was adopted to evaluate the quality of health information on the websites(16 items). The information content(10 items)assessment was conducted by referring to the " Guidelines and Specifications for Breast Cancer Diagnosis and Treatment of the Chinese Anti-Cancer Association(2019 Edition)". The feasibility of website health information was evaluated with Patient Education Materials Assessment Tool(PEMAT).Results:A total of 19 websites were included, and their service mode was mainly active information service(14 websites). The overall scoring for the quality of health information about breast cancer treatment was 2.0, with the highest score of " clarity of purpose" (3.4). According to the assessment results of information content, these websites were divided into 4 grades: excellent(3), good(11), fair(3), and poor(2). All the websites contained the information on clinical manifestations, etiology, examination and treatment of breast cancer. The overall feasibility of website health information was 44.5%, indicating incomplete feasibility.Conclusions:The Chinese website′s health information on breast cancer treatment is poor in quality and implementation. Hence, it′s urgent to further improve and standardize online health information, establishing a unified evaluation standard and actively exploring the new mode of " Internet+ Medical" service.
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OBJECTIVE: An automatic detection tool was created for examining health-related webpage quality we went further by examining its feasibility and performance. METHODS: We developed an automatic detection system to auto-assess the authorship quality indicator of an health-related information webpage for governmental websites in Taiwan. The system was integrated with the Chinese word segmentation system developed by the Academia Sinica in Taiwan and the SVM(light), which serve as an SVM (Support Vector Machine) Classifiers and a method of information extraction and identification. The system was coded in Visual Basic 6.0, using SQL 2000. RESULTS: We developed the first Chinese automatic webpage classification and information identifier to evaluate the quality of web information. The sensitivity and specificity of the classifier on the training set of webpages were both as high as 100% and only one health webpage in the test set was misclassified, due to the fact that it contained both health and non-health information content. The sensitivity of our authorship identifier is 75.3%, with a specificity of 87.9%. CONCLUSION: The technical feasibility of auto-assessment for the quality of health information on the web is acceptable. Although it is not sufficient to assure the total quality of web contents, it is good enough to be used to support the entire quality assurance program.