Evidence map›Paper›PMID 36300045›Full record

ArticleFrontiers in psychology2022

The public information needs of COVID-19 vaccine: A study based on online Q&A communities and portals in China.

Lin Wang, Zuquan Xian, Tianyu Du

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2022. 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
0.8field-weighted citation impact, top 27% 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, 5 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

3 authors at 2 institutions in 1 country.

Lin WangChinese Academy of Science and Education Evaluation, Hangzhou Dianzi University, Hangzhou, China.
Zuquan XianSchool of Managment, Tianjin Normal University, Tianjin, China.
Tianyu DuSchool of Managment, Tianjin Normal University, Tianjin, China.
Tianjin Normal University · CNHangzhou Dianzi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study analyzes the topic and distribution features of public information needs for the COVID-19 vaccine from Chinese online Q&A communities and portals. It aims to identify the features and differences in public COVID-19 vaccine information needs at different periods. Design/Methodology: A total of 14,296 questions about the COVID-19 vaccine from four Chinese mainstream online communities and portals were studied following five procedures: data collection, data processing, K-means clustering, LDA topic model analysis, and needs identification. Findings: The study identified the topical features of public information needs for the COVID-19 vaccine during the first pandemic outbreak, pre-listing period, and post-listing period. It constructed a framework of public vaccine information needs. The information needs can be classified into 8 main categories and 16 subcategories. The eight main categories are vaccination (53.72%), evaluation and impact of other social events (17.90%), vaccine R&D and listing (9.49%), vaccine side effects and countermeasures (5.63%), vaccination necessity (4.98%), vaccine patent exemption (3.26%), vaccination effectiveness (2.94%), and essential knowledge of vaccine (2.08%), where percentage refers to the distribution of information needs data under various categories. Implications: Online communities and portals should provide dynamic and tailored information services according to changing public vaccine information needs. The public information needs regarding vaccination is prominent and should be addressed first. In the follow-up booster vaccination efforts, government health departments should prioritize susceptible groups, such as overseas students, airport workers, and healthcare workers. Originality/Value: We built a conceptual framework using data mining techniques and analyzed the COVID-19 vaccine information needs distribution at different time points and among different social groups, focusing on the theme of public information needs for the COVID-19 vaccine. It makes recommendations for government health departments and online platforms to improve the quality of COVID-19 vaccine information services for the public and provide a reference for the vaccination of COVID-19 booster shots.

Indexed as

COVID-19 vaccinedata miningonline Q&A communitiestopic modelvaccine information needs

Identifiers

PMID36300045
PMCPMC9589292
OpenAlexW4304161256

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.