Evidence map›Paper›PMID 37378298›Full record

ArticleFrontiers in medicine2023

WeChat official accounts' posts on medication use of 251 community healthcare centers in Shanghai, China: content analysis and quality assessment.

Xujian Liang, Ming Yan, Haixin Li, Zhiling Deng, Yiting Lu, Panpan Lu, Songtao Cai, Wanchao Li, Lizheng Fang, Zhijie Xu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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

10 authors at 8 institutions in 1 country.

Xujian LiangDepartment of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Ming YanDepartment of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Haixin LiDepartment of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Zhiling DengThe Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Yiting LuDepartment of General Practice, Tongji University School of Medicine, Shanghai, China.
Panpan LuDepartment of General Practice, Taizhou Municipal Hospital, Taizhou, China.
Songtao CaiDepartment of General Practice, Longgang District People's Hospital of Shenzhen, Shenzhen, China.
Wanchao LiLinCheng Health Center of Changxing County, Huzhou, China.
Lizheng FangDepartment of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zhijie XuDepartment of General Practice, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Sir Run Run Shaw Hospital · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CNLonggang Central Hospital · CNSecond Affiliated Hospital of Zhejiang University · CNSun Yat-sen University · CNTaizhou Municipal Hospital · CNTongji University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The dissemination of online health information (OHI) on medication use via WeChat Official Accounts (WOAs) is an effective way to help primary care practitioners (PCPs) address drug-related problems (DRPs) in the community. Although an increasing number of primary care institutions in China have published WOA posts on medication use, their content and quality have not yet been assessed. Objective: This study aimed to explore the general features and content of WOA posts on medication use published by community healthcare centers (CHCs) in Shanghai, China and to assess their quality of content. It also aimed to explore the factors associated with the number of post views. Methods: From June 1 to October 31, 2022, two coauthors independently screened WOA posts on medication use published throughout 2021 by the CHCs in Shanghai. Content analysis was performed to analyze their general features (format, length, and source, etc.) and content (types of medicines and diseases). The QUEST tool was used to assess the quality of the posts. We compared the differences among posts published by CHCs in central urban areas and suburban areas, and used multiple linear regression to explore the factors associated with the number of post views. Results: A total of 236 WOAs of interest published 37,147 posts in 2021, and 275 (0.74%) of them were included in the study. The median number of post views was 152. Thirty percent of the posts were reviewed by the CHCs' staff before publication and only 6% provided information on PCPs' consultations. The most commonly mentioned medicines and diseases in the posts were Chinese patent medicines (37.1%) and respiratory diseases (29.5%). The posts frequently provided information on indications (77%) and usage (56%) but rarely on follow-up (13%) and storage (11%). Of the posts, 94.9% had a total QUEST score < 17 (full score = 28). The median number of post views and total post quality scores did not significantly differ among the CHCs in central urban and suburban areas. In the multiple linear regression model, the number of post views was associated with scores of complementarity (B = 56.47, 95% CI 3.05, 109.89) and conflict of interest (B = -46.40, 95% CI -56.21, -36.60). Conclusion: The quantity and quality of WOA posts on medication use published by CHCs in China need improvement. The quality of posts may partially impact the dissemination effect, but intrinsic causal associations merit further exploration.

Indexed as

community healthcare centersmedication useonline health informationsocial mediaWeChat official accounts

Identifiers

PMID37378298
PMCPMC10291264
OpenAlexW4380372506

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.