Evidence map›Paper›PMID 31250833›Full record

Observational studyJMIR mHealth and uHealth2019

Factors Influencing User Engagement of Health Information Disseminated by Chinese Provincial Centers for Disease Control and Prevention on WeChat: Observational Study.

Yan Zhang, Tingsong Xia, Lingfeng Huang, Mingjuan Yin, Mingwei Sun, Jingxiao Huang, Yu Ni, Jindong Ni

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 8% of its field
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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 39 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Yan Zhang *Guangdong Medical University, Dongguan, China.ORCID 0000-0002-4407-6686
Tingsong Xia *Baoan District Shajing Health Supervision Office, Shenzhen, China.ORCID 0000-0001-5215-9660
Lingfeng HuangGuangdong Medical University, Dongguan, China.ORCID 0000-0002-8893-1525
Mingjuan YinGuangdong Medical University, Dongguan, China.ORCID 0000-0002-6737-0714
Mingwei SunGuangdong Medical University, Dongguan, China.ORCID 0000-0002-2433-3016
Jingxiao HuangGuangdong Medical University, Dongguan, China.ORCID 0000-0002-5542-966X
Yu NiBeijing Jiaotong University, Beijing, China.ORCID 0000-0002-7707-2075
Jindong NiGuangdong Medical University, Dongguan, China.ORCID 0000-0001-5413-8353
Guangdong Medical College · CNBeijing Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media is currently becoming a new channel for information acquisition and exchange. In China, with the growing popularity of WeChat and WeChat official accounts (WOAs), health promotion agencies have an opportunity to use them for successful information distribution and diffusion online.

objectiveWe aimed to identify features of articles pushed by WOAs of Chinese provincial Centers for Disease Control and Prevention (CDC) that are associated with user engagement.

methodsWe searched and subscribed to 28 WOAs of provincial CDCs. Data for this study consisted of WeChat articles on these WOAs between January 1, 2017 and December 31, 2017. We developed a features frame containing title type, article content, article type, communication skills, number of marketing elements, and article length for each article and coded the data quantitatively using a coding scheme that assigned numeric values to article features. We examined the descriptive characteristics of articles for every WOA and generated descriptive statistics for six article features. The amount of reading and liking was converted into the level of reading and liking by the 75% position. Two-category univariate logistic regression and multivariable logistic regression were conducted to explore associations between the features of the articles and user engagement, operationalized as reading level and liking level.

resultsAll provincial CDC WOAs provided a total of 5976 articles in 2017. Shanghai CDC articles attracted the most user engagement, and Ningxia CDC articles attracted the least. For all articles, the median reading was 551.5 and the median liking was 10. Multivariable logistic regression analysis revealed that article content, article type, communication skills, number of marketing elements, and article length were associated with reading level and liking level. However, title type was only associated with liking level.

conclusionsHow social media can be used to best achieve health information dissemination and public health outcomes is a topic of much discussion and study in the public health community. Given the lack of related studies based on WeChat or official accounts, we conducted this study and found that article content, article type, communication skills, number of marketing elements, article length, and title type were associated with user engagement. Our study may provide public health and community leaders with insight into the diffusion of important health topics of concern.

Indexed as

ChinaGovernment ProgramsHumansInformation DisseminationPatient ParticipationText MessagingCDChealth educationuser engagementWeChatWeChat official accounts

Identifiers

PMID31250833
PMCPMC6620885
OpenAlexW2945051652

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.