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Systematic evaluation of COVID-19 related Internet health rumors during the breaking out period of COVID-19 in China.
Pu, Ge; Jin, Liu; Xiao, Han; Shu-Ting, Wei; Xi-Zhe, He; Ying, Tang; Xin, Xu; Sheng-Yuan, Wang; Ying, Bian; Yibo, Wu.
  • Pu G; Institute of Chinese Medical Sciences & State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China.
  • Jin L; The Third Clinical Department, China Medical University,Shenyang 110013,Liaoning Province,China.
  • Xiao H; School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou 510006, Guangdong Province, China.
  • Shu-Ting W; Cheeloo College of Medicine,ShanDong University,Jinan 250012,Shandong Province,China.
  • Xi-Zhe H; Jiangxi University of Traditional Chinese Medicine,Nanchang 330004,Jiangxi Province,China.
  • Ying T; Changzhi Medical College,Changzhi 046000,Shanxi Province,China.
  • Xin X; School of Life Science, Peking University, Beijing 100871,China.
  • Sheng-Yuan W; Liaoning Technical University College of the Media and Arts, Fuxin 123000,China.
  • Ying B; Institute of Chinese Medical Sciences & State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China.
  • Yibo W; School of Public Health, Peking University, Beijing 100191,China.
Health Promot Perspect ; 11(3): 288-298, 2021.
Article in English | MEDLINE | ID: covidwho-1374787
ABSTRACT

Background:

To adapt the scientific evaluation tool for the confusion evaluation of health rumors and to test this tool to the confusion evaluation of coronavirus disease 2019 (COVID-19)-related health rumors on Chinese online platforms during the outbreak period of COVID-19in China.

Methods:

The design of our study was systematic evaluation of COVID-19-related health rumors. Retrieved from 7 rumor-repellent platforms, rumors about COVID-19 were collected during the publication from December 1, 2019, to February 6, 2020, and their origins were traced. Researchers evaluated rumors using the confusion evaluation tool in 6 dimensions(creators, evidence selection, evidence evaluation, evidence application, backing and publication platform, conflict of interest). Items were scored using a seven-point Likert scale. The scores were converted into percentages, and the median of rumors from different sources was compared with rank-sum test.

Results:

Our research included 127 rumors. Scores were converted to percentages, median and interquartile range are used to describe the data. The median score creators 25.00%(interquartile range, IQR, 16.67-37.50%), evidence selection 27.78% (IQR, 13.89-44.44%),evidence evaluation 33.33% (IQR, 25.00-45.83%), evidence application 36.11% (IQR, 22.22-47.22%), backing and publication platform 8.33% (IQR, 4.17-20.83%), conflict of interest75.00% (IQR, 50.00-83.33%). Almost 40% rumors came from WeChat and the rumors with the lowest scores were concentrated on the WeChat platform. The rumors about prevention methods have relatively lower scores.

Conclusion:

Most rumors included were not highly confusing for evaluators of this project.WeChat is the "worst-hit area" of COVID-19 related health rumors. More than half rumors focus on the description of prevention methods, which reflects the panic, anxiety and blind conformity of the public under public health emergencies.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Systematic review/Meta Analysis Language: English Journal: Health Promot Perspect Year: 2021 Document Type: Article Affiliation country: Hpp.2021.37

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Systematic review/Meta Analysis Language: English Journal: Health Promot Perspect Year: 2021 Document Type: Article Affiliation country: Hpp.2021.37