Evidence map›Paper›PMID 30093370›Full record

ArticleJournal of medical Internet research2018

Social Media Landscape of the Tertiary Referral Hospitals in China: Observational Descriptive Study.

Wei Zhang, Zhaohua Deng, Richard Evans, Fei Xiang, Qing Ye, Runxi Zeng

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

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

  1. Factors Associated with Outpatient Satisfaction in Tertiary Hospitals in China: A Systematic Review.International journal of environmental research and public health · 2020
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  18. Evaluating the Inequality of Medical Service Accessibility Using Smart Card Data.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Wei ZhangInstitute of Smart Health, School of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0003-0178-0750
Zhaohua DengInstitute of Smart Health, School of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0002-7744-7818
Richard EvansBusiness Information Management and Operations, University of Westminster, London, United Kingdom.ORCID 0000-0001-6367-0560
Fei XiangInstitute of Smart Health, School of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0002-9783-9253
Qing YeTongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0002-5432-7741
Runxi ZengSchool of Journalism and Communication, Chongqing University, Chongqing, China.ORCID 0000-0002-8353-9479

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media has penetrated all walks of life. Chinese health care institutions are increasingly utilizing social media to connect with their patients for better health service delivery. Current research has focused heavily on the use of social media in developed countries, with few studies exploring its usage in the context of developing countries, such as China. Tertiary hospitals in China are usually located in city centers, and they serve as medical hubs for multiple regions, with comprehensive and specialized medical care being provided. These hospitals are assumed to be the pioneers in creating official social media accounts to connect with their patients due to the fact that they appear to have more resources to support this innovative approach to communication and health care education.

objectiveThe objective of our study was to examine China's best tertiary hospitals, as recognized by The National Health Commission of the People's Republic of China (NHCPRC), and to map out the landscape of current social media usage by hospitals when engaging with patients.

methodsWe examined the best 705 tertiary hospitals in China by collecting and analyzing data regarding their usage of popular Chinese social media apps Sina Weibo and WeChat. The specific data included (1) hospital characteristics (ie, time since established, number of beds, hospital type, and regions or localities) and (2) status of social media usage regarding two of the most popular local social media platforms in China (ie, time of initiation, number of followers, and number of tweets or posts). We further used a logistic regression model to test the association between hospital characteristics and social media adoption.

resultsOf all, 76.2% (537/705) tertiary referral hospitals have created official accounts on either Sina Weibo or WeChat, with the latter being more popular among the two. In addition, our study suggests that larger and newer hospitals with greater resources are more likely to adopt social media, while hospital type and affiliation with universities are not significant predictors of social media adoption among hospitals.

conclusionsOur study demonstrated that hospitals are more inclined to use WeChat. The move by hospitals from Sina Weibo to WeChat indicates that patients are not satisfied by mere communication and that they now place more value on health service delivery. Meanwhile, utilizing social media requires comprehensive thinking from the hospital side. Once adopted, hospitals are encouraged to implement specific rules regarding social media usage. In the future, a long journey still lies ahead for hospitals in terms of operating their official social media accounts.

Indexed as

ChinaHumansSocial MediaTertiary Care Centersbest tertiary hospitalsChinaSina Weibosocial media usageWeChat

Identifiers

PMID30093370
PMCPMC6107732

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.