Infodemic describes a special state during a public health emergency in which biased health information shows an explosive spread. This study systematically comprehends the definition, spreading mechanism, and coping strategies of infodemics. The study shows that the proliferation of false information relies on social media platforms and is driven by group psychological factors, social networks and algorithmic recommendation mechanisms, presenting complex dynamic characteristics. This article focuses on analyzing the commonly used tools in the field of communication science (including three types of models, ABM, SIR and MAP) and exploring their application value in simulating the diffusion path of disinformation. In terms of management strategies, the article proposes the strategies of constructing an intelligent information monitoring system, enhancing public health literacy, strengthening information filtering and quality control, and realizing the precise transformation of scientific knowledge. Despite the progress of the research, it still faces challenges such as fast dissemination speed and difficult supervision. In the future, interdisciplinary cooperation should be strengthened, a data-based information intervention system should be constructed, and the public's ability to immunize false information should be enhanced to protect public health safety.
It has been 36 years since the first version of essential medicine list (EML) was released by WHO in 1977,when 18 versions of WHO-EML and four versions of children essential medicine list have been released. In 1982, the first version of national essential medicine list (NEML) was released in China. Till 2012, there were eight versions of NEML in total. This paper introduces WHO-EML in aspects of origin, idea, definition, design, and innovation of selection methodology,principle, and workflow; compares the evolution, design, selection methodology between WHO-EML and Chinese NEML; and points out the challenges of evaluation and decision making of Chinese NEML.
The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) has been widely accepted in the assessment of diagnostic accuracy and quality. However, it is not suitable for assessing risk of bias in studies comparing diagnostic accuracy. The current common practice in systematic reviews is to derive comparative accuracy from non-comparative diagnostic accuracy studies, which is inherently biased. The QUADAS group developed the QUADAS-Compare (QUADAS-C) tool for assessing the risk of bias in comparative diagnostic accuracy studies. It was officially launched in October 2021. QUADAS-C retains the same 4-domain structure as QUADAS-2: patient selection, index test, reference standard, and flow and timing. It also includes an additional 14 signaling questions and 4 risk of bias questions. This allows researchers to identify high-quality research evidence and avoid bias in research design and conduct. This article interpreted the basic situation, evaluation items, evaluation standards, and usage methods and procedures associated with QUADAS-C to provide references for domestic users.
目的 通過關鍵詞共現分析和作者共現分析的方式，研究國內外循證醫學教育領域的研究熱點、學科分支和發展趨勢。 方法 通過檢索中國學術期刊數據庫（CNKI）和Medline數據庫，分別收集相關研究文獻，并提取關鍵詞詞頻、作者發文數、核心期刊和核心研究單位，對核心關鍵詞和核心發文作者建立共現矩陣，使用Ucinet繪制可視化網絡圖。 結果 成功得到核心關鍵詞和核心作者可視化網絡。中文可視化網絡包括“循證醫學”、“護理”、“教育”、“教學”4個方面，英文可視化網絡包括“evidence-based medicine”、“nursing”、“education”、“organization amp; administration”4個方面，國內外該學科發展趨勢相似。國內循證醫學教育以四川大學為核心，合作網絡較大。同時國內核心期刊與國外側重點不同。 結論 國內循證醫學教育研究領域總體發展趨勢良好，在醫學教育中起著極為重要的作用。Objective To built visualized networks of evidence-based medical education in and out of China by using co-occurrence analysis of key words and authors. Methods We searched the China National Knowledge Infrastructure (CNKI) database in Chinese and Medline database in English, collecting the related articles, and took out the core key words, core authors and core administrations. Then we built the matrix of key words and authors, and finally finished visualized network by Ucinet. Results We successfully obtained the visualization of this subject. Chinese network contained four parts: “evidence-based medicine”, “nursing”, “education” and “teaching”; while English network also contained four parts: “evidence-based medicine”, “nursing”, “education”, “organization” and “administration”. In China, Sichuan University located in the center of the network of authors, and also leading in the administrations. The network of authors in China showed a larger cooperation than overseas. And the core-periodicals had different emphases. Conclusion The evidence-based medical education develops well in China, and plays an important role in the medical education.
【摘要】 目的 通過關鍵詞共現分析和作者共現分析的方式，研究國內外循證心血管領域的研究熱點、學科分支和發展趨勢。 方法 通過檢索中國生物醫學數據庫和Medline數據庫，分別收集相關研究文獻，并提取關鍵詞詞頻、作者發文數和核心研究單位，對核心關鍵詞和核心發文作者建立共現矩陣，使用Ucinet繪制可視化網絡圖。 結果 成功得到核心關鍵詞和核心作者可視化網絡。中文可視化網絡包括循證醫學、治療和護理3個方面，英文可視化網絡包括evidence-based medicine、therapy和treatment outcome 3個方面。而在作者合作可視化網絡中，國內作者合作關系較為松散，合作團體較小，國外作者合作關系較為緊密，合作團體較大。國內核心研究機構分布于循證研究重點高校，國外則以發達國家為主。 結論 國內循證心血管研究領域總體發展趨勢較好，但較國外相比仍存在一些不足，需要進一步加強重點研究，調整研究規劃。【Abstract】 Objective To research on the hot issues, branch system and development trend of evidence-based cardiovascular medicine in and out of china by using co-word analysis of keywords and authors. Methods By Searching the CBM database in Chinese and Medline database in English, we collected the related articles and picked out the frequency of keywords, authors and core administrations, and built the matrix of keywords and authors. Finally we completed the visualized network by Ucinet. Results We successfully obtained the visualization of this subject. Chinese network contained three parts: evidence-based medicine, therapy and nursing, while English network also contained three parts: evidence-based medicine, therapy and treatment outcome. In the authors′ visualized network, Chinese authors had less cooperation and looser relationship compared with their counterparts overseas. The core administrations in china located in outstanding universities, and developed countries had the dominated roles in the world. Conclusions The development trend of evidence-based cardiovascular medicine in china is good, but still has some limitations compared with overseas studies. More emphasis should be put on strengthening core-area researching and research plan adjustment.
Hospital-based health technology assessment (HB-HTA) is an indispensable method and measure to improve the level of fine management and establish a value-based medical service system. This paper introduces the differences between HB-HTA and HTA, four organizational management models, assessment process, assessment steps and HB-HTA reporting standardization, which provides a reference for evaluating organizations.
ObjectiveTo analyze publications of the application of artificial intelligence related methods in medicine.MethodsPubMed and EMbase databases were electronically searched. Pathfinder Networks (PFNETs) algorithm, co-word network analysis and visualization technology were applied to analyze the time trend, journal distribution, and co-word structure of high-frequency medical keywords in key journals.ResultsThe amount of literature published on the application of artificial intelligence related methods in the medical field had been increasing annually. Nowadays, the number of studies published in the United States was the largest, and that in China, it was the sixth (first in developing countries). The number of the first author from the United States or China were among the top two, which were significantly more than any other regions. In 2012, IEEE Trans Neural Netw Learn Syst in the computer field became one of the major contributing journals. In recent years, the methods and applications proposed in the medical field were closely related to natural language processing, neural networks, and support vector machines.ConclusionsAt present, the United States is in a leading position in terms of artificial intelligence in medicine, and China has also abundant research strength. The number of medical literature published in interdisciplinary journals is increasing gradually, showing that the research and application of artificial intelligence related methods in medicine have become a research hotspot in recent years.
The QUADAS-2, QUIPS, and PROBAST tools are not specific for prognostic accuracy studies and the use of these tools to assess the risk of bias in prognostic accuracy studies is prone to bias. Therefore, QUAPAS, a risk of bias assessment tool for prognostic accuracy studies, has recently been developed. The tool combines QUADAS-2, QUIPS, and PROBAST, and consists of 5 domains, 18 signaling questions, 5 risk of bias questions, and 4 applicability questions. This paper will introduce the content and usage of QUAPAS to provide inspiration and references for domestic researchers.
Currently, the medical imaging methods based on artificial intelligence are developing rapidly, and the related literature reports are increasing year by year. However, there is no special reporting standard, and the reporting of the results is not standardized. In order to improve the report quality of this kind of research and help readers and evaluators evaluate the quality of this kind of research more scientifically, a checklist for artificial intelligence in medical imaging (CLAIM) was put forward abroad. This paper introduces the content of CLAIM and explains its items.
Objective To use visualization methods to illustrate and compare major subjects, domains, and developments in evidence-based medicine (EBM) in recent years. Methods We analyzed MeSH terms and keywords in EBM articles in the MEDLINE and CNKI databases, and developed subject charts, research field relationship charts, and strategy coordination charts using word co-occurrence, PFNET algorithms, and visualization methods. Results Rapid developments and growth are taking place in EBM in China and around the world. Studies on humans comprised 94.4% of the EBM studies that we identified, while animal studies accounted for 2.6% (three quarters of these animal studies were on primates). The six countries with the largest number of EBM articles and the eight host nations for the 108 journals with the most EBM publications were from high-income countries. In China, 31 provinces, municipalities, and autonomous regions have published EBM articles, although most of these publications come from the more highly-developed areas of the country. The investigation of word co-occurrence showed that EBM articles outside of China involve seven main fields: “Therapy”, “Methods”, “Standards”, “Research”, “Education”, ”Nursing” and “Organization and Administration”. Five of these fields (“Therapy”, “Nursing”, “Research”, “Education” and “Management”) were common to China but the top seven fields for this country included “Traditional Chinese Medicine (TCM)” and “Information resources”; and did not include “Methods” and “Standards”. Furthermore, studies on “Nursing” and “Research” were not as advanced in China as in other countries. Conclusion There are similarities between China and the rest of the world in several areas in the EBM literature but also some important differences. Throughout the world, the most resource-rich regions or organizations tend to have the most well-developed EBM. These regions and organizations are producing more evidence and conducting more methodology research than the less resourced regions and organizations. There is an urgent need for these regions and organizations to strengthen their use of evidence, to learn more about the philosophy that underpins EBM, and to improve accessibility to, and use of, evidence in choices about health care.
