Quality Analysis of Chinese Popular Scientific Articles Pertaining to Novel Coronavirus Pneumonia

Abstract Background: To evaluate the quality, reliability, comprehensiveness and accuracy of the popular science information related to the Corona Virus Disease 2019 (COVID-19) on the Chinese website.Methods: Searching for scientific articles with the keywords of "novel coronavirus pneumonia" in Baidu, Sogou and 360 search engine at 14:00 on May 22, 2020, and collecting information such as article source, length, upload time, etc. Using JAMA score and 5-point DISCERN scale, two specialists independently analyzed the reliability and quality of scientific articles. Combined with the "Novel Coronavirus Pneumonia Diagnosis and Treatment Program (Trial Version 6)", we made corresponding evaluation on the comprehensiveness and accuracy of articles. Results: A total of 45 scientific articles were included in the study. The average number of words is 2692.27±1267.61, and the average upload time is 11.8±10.80 days. Those popular scientific articles are mainly uploaded by government agencies and individuals. However, the JAMA score, DISCERN score, content comprehensiveness and accuracy of the articles were generally low. Among the 45 popular scientific articles, 27 articles were classified as accurate-content group and 18 articles were classified as misleading-content group. Scientific articles of accurate-content groups mainly came from government agencies, universities and hospitals. The publication date of articles in the accurate-content group is closer, the scores of JAMA, DISCERN and content comprehensiveness were higher (P<0.05). The results also showed that JAMA score, DISCERN score, content comprehensiveness and accuracy of popular science articles uploaded by government agencies, universities and hospitals were higher (P<0.05). The results indicated that there was a significant positive correlation between the scores of JAMA, DISCERN, comprehensiveness and accuracy (P<0.05). Conclusion: Although there are many scientific articles related to the novel coronavirus pneumonia on the Chinese website, the overall detection rate of high-quality scientific articles were low. We are Looking forward to more high-quality medical scientific articles published by government agencies, universities and hospitals. It is suggested that search engines adopt a more optimized sorting method to help more readers get high-quality information.