Evidence map›Paper›PMID 36101592›Full record

ArticlePublic health in practice (Oxford, England)2021

Social network research hotspots and trends in public health: A bibliometric and visual analysis.

Bingjie Shen, Tianjia Guan, Jing Ma, Linghe Yang, Yuanli Liu

Abstract read
In one paragraph

Article in Public health in practice (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. The indispensableScandinavian journal of work, environment & health · 2024
    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

5 authors.

Bingjie ShenSchool of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, 46 Xizongbu Hutong, Beijing, 100005, China.
Tianjia GuanSchool of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, 46 Xizongbu Hutong, Beijing, 100005, China.
Jing MaActive Health and Translational Medicine Center, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, 32 Yihuan Road, Qingyang District, Chengdu, Sichuan Province, 610072, China.
Linghe YangSchool of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, 46 Xizongbu Hutong, Beijing, 100005, China.
Yuanli LiuSchool of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, 46 Xizongbu Hutong, Beijing, 100005, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To understand the research landscape and identify the research hotspots and trends of the application of social network theory and analysis to public health. Study design: A bibliometric study of publications regarding application of social network theory and analysis to public health. Methods: Choosing 1607 articles about the application of social network theory and analysis to public health from the core collection database of Web of Science published from 1991 to 2020 as the research sample. A bibliometric and visual analysis of publication quantity and content was performed to analyze time trends, spatial distribution, cooperation networks, influential references, and keyword co-occurrence, clusters, and emergence. Results: There is an increasing trend in the use of social network theory and analysis in the public health field, with the United States taking the lead. Research focuses include on transmission of diseases or behavior through social networks and the influence of social networks on population health at different ages. Current research frontiers primarily include the role of social networks in tracking of emerging infectious diseases like COVID-19, preventing and controlling chronic diseases, and carrying out healthy behavioral interventions. Conclusions: This study provides a comprehensive quantitative overview of the historic development of and latest topics in the application of social network theory and analysis method to public health. More attention should be paid to the important role of social networks in tracing the emergence of serious infectious diseases like COVID-19, as well as preventing and controlling chronic diseases and intervening in health behaviors, considering the increasing challenges and opportunities presented by online social networking.

Indexed as

Bibliometric analysisPublic healthResearch hotspotsSocial networkSocial network analysis

Identifiers

PMID36101592
PMCPMC9461482

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.