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Quality and readability of online information resources on insomnia
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《医学前沿（英文）》 2017年 第11卷 第3期 页码 423-431 doi: 10.1007/s11684-017-0524-9
The internet is a major source for health information. An increasing number of people, including patients with insomnia, search for remedies online; however, little is known about the quality of such information. This study aimed to evaluate the quality and readability of insomnia-related online information. Google was used as the search engine, and the top websites on insomnia that met the inclusion criteria were evaluated for quality and readability. The analyzed websites belonged to nonprofit, commercial, or academic organizations and institutions such as hospitals and universities. Insomnia-related websites typically included definitions (85%), causes and risk factors (100%), symptoms (95%), and treatment options (90%). Cognitive behavioral therapy for insomnia (CBT-I) was the most commonly recommended approach for insomnia treatment, and sleep drugs are frequently mentioned. The overall quality of the websites on insomnia is moderate, but all the content exceeded the recommended reading ease levels. Concerns that must be addressed to increase the quality and trustworthiness of online health information include sharing metadata, such as authorship, time of creation and last update, and conflicts of interest; providing evidence for reliability; and increasing the readability for a layman audience.
关键词： insomnia internet readability information quality health literacy cognitive behavioral therapy treatment
Multistage analysis method for detection of effective herb prescription from clinical data
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《医学前沿（英文）》 2018年 第12卷 第2期 页码 206-217 doi: 10.1007/s11684-017-0525-8
Determining effective traditional Chinese medicine (TCM) treatments for specific disease conditions or particular patient groups is a difficult issue that necessitates investigation because of the complicated personalized manifestations in real-world patients and the individualized combination therapies prescribed in clinical settings. In this study, a multistage analysis method that integrates propensity case matching, complex network analysis, and herb set enrichment analysis was proposed to identify effective herb prescriptions for particular diseases (e.g., insomnia). First, propensity case matching was applied to match clinical cases. Then, core network extraction and herb set enrichment were combined to detect core effective herb prescriptions. Effectiveness-based mutual information was used to detect strong herb–symptom relationships. This method was applied on a TCM clinical data set with 955 patients collected from well-designed observational studies. Results revealed that groups of herb prescriptions with higher effectiveness rates (76.9% vs. 42.8% for matched samples; 94.2% vs. 84.9% for all samples) compared with the original prescriptions were found. Particular patient groups with symptom manifestations were also identified to help investigate the indications of the effective herb prescriptions.
关键词： effective prescription detection herb set enrichment analysis core network extraction insomnia personalized treatment
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