Evidence map›Paper›PMID 36930064›Full record

ArticleMedicine2023

Classification and citation analysis of the 100 top-cited articles on nurse resilience using chord diagrams: A bibliometric analysis.

Hui-Ying Chiang, Huan-Fang Lee, Yu-Hsin Hung, Tsair-Wei Chien

Abstract read
In one paragraph

Article in Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

4 authors.

Hui-Ying ChiangNursing Department, Chi-Mei Medical Center, Taiwan.
Huan-Fang LeeDepartment of Nursing, College of Medicine, National Cheng Kung University, Taiwan.ORCID 0000-0001-5899-1124
Yu-Hsin HungDepartment of Nursing, College of Medicine, National Cheng Kung University, Taiwan.
Tsair-Wei ChienDepartment of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan.ORCID 0000-0003-1329-0679

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStudies of most-cited articles have been frequently conducted on various topics and in various medical fields. To date, no study has examined the characteristics of articles associated with theme classifications and research achievements of article entities related to nursing resilience. This study aims to graphically depict the characteristics of the 100 top-cited articles addressing nurse resilience (T100NurseR), diagram the relationship between articles and author collaborations according to themes extracted from article keywords, and examine whether article keywords are correlated with article citations.

methodsT100NurseR publications were retrieved from the Web of Science (WoS) core collection on October 13, 2022. Themes associated with articles were explored using coword analysis in WoS keywords plus. The document category, journal ranking based on impact factor, authorship, and L-index and Y-index were used to analyze the dominant entities. To report the themes of T100NurseR and their research achievements in comparison to article entities and verify the hypothesis that keyword mean citation can be used to predict article citations, 5 visualizations were applied, including network diagrams, chord diagrams, dot plots, Kano diagrams, and radar plots.

resultsCitations per article averaged 61.96 (range, 25-514). There were 5 themes identified in T100NurseR, including Parses theory, nurse resilience, conflict management, nursing identity, and emotional intelligence. For countries, institutes, departments, and authors in comparison of category, journal impact factor, authorship, and L-index scores, Australia (129.80), the University of Western Sydney (23.12), Nursing (87.17), and Kim Foster (23.76) are the dominant entities. The weighted number of citations according to Keywords Plus in WoS is significantly correlated with article citations (Pearson R = 0.94; P = .001).

conclusionWe present diagrams to guide evidence-based clinical decision-making in nurse resilience based on the characteristics of the T100NurseR articles. Article citations can be predicted using weighted keywords. Future bibliographical studies may apply the 5 visualizations to relevant studies, not being solely restricted to T100NurseR.

Indexed as

BibliometricsJournal Impact FactorAustraliaAuthorshipHumansNigeria

Identifiers

PMID36930064
PMCPMC10019250

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.