Evidence map›Paper›PMID 32501808›Full record

ArticleJournal of medical Internet research2020

Nature and Diffusion of COVID-19-related Oral Health Information on Chinese Social Media: Analysis of Tweets on Weibo.

Zhuo-Ying Tao, Guang Chu, Colman McGrath, Fang Hua, Yiu Yan Leung, Wei-Fa Yang, Yu-Xiong Su

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Use of social media by parents as a resource for knowledge on children's oral health: a systematic review.Canadian journal of dental hygiene : CJDH = Journal canadien de l'hygiene dentaire : JCHD · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Zhuo-Ying TaoDivision of Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China (Hong Kong).ORCID 0000-0002-6486-4639
Guang ChuKey Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, Research Center of Stomatology, Xi'an Jiaotong University College of Stomatology, Xi'an, Shaanxi Province, China.ORCID 0000-0002-0013-2498
Colman McGrathApplied Oral Sciences & Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China (Hong Kong).ORCID 0000-0001-9379-0889
Fang HuaCenter for Evidence-Based Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, Hubei Province, China.ORCID 0000-0002-2438-5924
Yiu Yan LeungDivision of Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China (Hong Kong).ORCID 0000-0002-6670-6570
Wei-Fa YangDivision of Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China (Hong Kong).ORCID 0000-0001-6047-3705
Yu-Xiong SuDivision of Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China (Hong Kong).ORCID 0000-0001-7143-3370

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media has become increasingly important as a source of information for the public and is widely used for health-related information. The outbreak of the coronavirus disease (COVID-19) has exerted a negative impact on dental practices.

objectiveThe aim of this study is to analyze the nature and diffusion of COVID-19-related oral health information on the Chinese social media site Weibo.

methodsA total of 15,900 tweets related to oral health and dentistry information from Weibo during the COVID-19 outbreak in China (December 31, 2019, to March 16, 2020) were included in our study. Two researchers coded 1000 of the total tweets in advance, and two main thematic categories with eight subtypes were refined. The included tweets were analyzed over time and geographic region, and coded into eight thematic categories. Additionally, the time distributions of tweets containing information about dental services, needs of dental treatment, and home oral care during the COVID-19 epidemic were further analyzed.

resultsPeople reacted rapidly to the emerging severe acute respiratory syndrome coronavirus 2 threat to dental services, and a large amount of COVID-19-related oral health information was tweeted on Weibo. The time and geographic distribution of tweets shared similarities with epidemiological data of the COVID-19 outbreak in China. Tweets containing home oral care and dental services content were the most frequently exchanged information (n=4803/15,900, 30.20% and n=4478, 28.16%, respectively). Significant differences of public attention were found between various types of bloggers in dental services-related tweets (P<.001), and the tweets from the government and media engaged the most public attention. The distributions of tweets containing information about dental services, needs of dental treatment, and home oral care information dynamically changed with time.

conclusionsOur study overviewed and analyzed social media data on the dental services and oral health information during the COVID-19 epidemic, thus, providing insights for government organizations, media, and dental professionals to better facilitate oral health communication and efficiently shape public concern through social media when routine dental services are unavailable during an unprecedented event. The study of the nature and distribution of social media can serve as a useful adjunct tool to help make public health policies.

Indexed as

BetacoronavirusDentistryHealth CommunicationHealth EducationAsian PeopleAttentionChinaCoronavirus InfectionsCOVID-19Disease OutbreaksHumansOral HealthPandemicsPneumonia, ViralSARS-CoV-2Social MediaChinaCOVID-19dentistryhealth informationonline healthoral healthsocial mediatweetWeibo

Identifiers

PMID32501808
PMCPMC7296975

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.