Evidence map›Paper›PMID 30274969›Full record

ArticleJMIR mHealth and uHealth2018

Social Media Users' Perception of Telemedicine and mHealth in China: Exploratory Study.

Ricky Leung, Huibin Guo, Xuan Pan

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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  7. Infodemiology and Infoveillance: Scoping Review.Journal of medical Internet research · 2020
    Article
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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

3 authors.

Ricky Leung *Department of Health Policy, Management and Behavior, School of Public Health, University at Albany, State University of New York, Rensselaer, NY, United States.ORCID http://orcid.org/0000-0002-2852-6771
Huibin Guo *School of Economics and Management, Hebei University of Economics and Business, Shijiazhuang, China.ORCID http://orcid.org/0000-0001-9115-1370
Xuan PanDepartment of Economics and Finance, School of Economics and Management, Tongji University, Shanghai, China.ORCID http://orcid.org/0000-0002-1671-5268

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of telemedicine and mHealth has increased rapidly in the People's Republic of China. While telemedicine and mHealth have great potential, wide adoption of this technology depends on how patients, health care providers, and other stakeholders in the Chinese health sector perceive and accept the technology.

objectiveTo explore this issue, we aimed to examine a social media platform with a dedicated focus on health information technology and informatics in China. Our goal is to utilize the findings to support further research.

methodsIn this exploratory study, we selected a social media platform-HC3i.cn-to examine the perception of telemedicine and mHealth in China. We performed keyword analysis and analyzed the prevalence and term frequency-inverse document frequency of keywords in the selected social media platform; furthermore, we performed qualitative analysis.

resultsWe organized the most prominent 16 keywords from 571 threads into 8 themes: (1) Question versus Answer; (2) Hospital versus Clinic; (3) Market versus Company; (4) Doctor versus Nurse; (5) Family versus Patient; (6) iPad versus Tablet; (7) System versus App; and (8) Security versus Caregiving. Social media participants perceived not only significant opportunities associated with telemedicine and mHealth but also barriers to overcome to realize these opportunities.

conclusionsWe identified interesting issues in this paper by studying a social media platform in China. Among other things, participants in the selected platform raised concerns about quality and costs associated with the provision of telemedicine and mHealth, despite the new technology's great potential to address different issues in the Chinese health sector. The methods applied in this paper have some limitations, and the findings may not be generalizable. We have discussed directions for further research.

Indexed as

Chinakeyword analysismHealthmobile phonesocial mediatelemedicinetext mining

Identifiers

PMID30274969
PMCPMC6231815

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.