Evidence map›Paper›PMID 34222091›Full record

ReviewJournal of diabetes and metabolic disorders2021

Visualization of knowledge flow in interpersonal scientific collaboration network endocrinology and metabolism research institute.

Leila Shahmoradi, Aboozar Ramezani, Rasha Atlasi, Nazli Namazi, Bagher Larijani

Abstract readReview
In one paragraph

Review in Journal of diabetes and metabolic disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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

Leila ShahmoradiHalal Research Center of IRI, FDA, Tehran, Iran.ORCID https://orcid.org/0000-0002-2269-9022
Aboozar RamezaniDepartment of Medical Library and Information Sciences, Virtual School, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0002-3888-1363
Rasha AtlasiEvidence Based Practice Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0002-9118-5324
Nazli NamaziDiabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0002-3119-2805
Bagher LarijaniEndocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0001-5386-7597

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeResearch collaborations can help to increase scientific productivity. The purpose of the present study was to draw up the knowledge flow network of the Endocrinology and Metabolism Research Institute (EMRI) affiliated to Tehran University of Medical Sciences.

methodsThe present study is a descriptive cross-sectional study on the publications of the EMRI. Web of Science Core collection databases were searched for the EMRI publications between 2002 to November 2019. Besides, publications were classified and visualized based on authorships (institutes and country of affiliation), and keywords (co-occurrence and trend). Scientometric methods including VOSviewer and HistCite were used for descriptive statistics and data analysis.

resultsTotal citations to the records were 47,528 and papers were published in 916 journals. The annual growth rate of publications and the citation was 14.2% and 18.9%, respectively. A total of 9466 authors from 136 countries collaborated in the publications. The co-authorship patterns showed that the average co-authorship and collaboration coefficient was 3.3 and 0.19.

conclusionKnowledge flow between EMRI researchers with international collaborations, engagement with leading countries, and interdisciplinary collaborations have an increasing trend. To develop a full picture of co-authorship, using social network analysis indicators are suggested for future studies.

Indexed as

BibliometricsData visualizationEMRIKnowledge discovery

Identifiers

PMID34222091
PMCPMC8212232

What OpenQuestion holds

Textmetadata
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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.