Evidence map›Paper›PMID 38681974›Full record

ArticlePsychology research and behavior management2024

Burnout among Nurses: A Bibliometric Analysis of the Global Publications.

Zihan Yang, Miaomiao Zhang, Yan Guo, Rui Wang, Fei Xie

Abstract read
In one paragraph

Article in Psychology research and behavior management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Knowledge mapping of burnout among nursing professionals: A bibliometric study.International journal of nursing studies advances · 2025
    Article
  6. Article
  7. Article
  8. 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.

Zihan Yang *First Department of Foot and Ankle Surgery, Tianjin Hospital, Tianjin University, Tianjin, People's Republic of China.
Miaomiao Zhang *Emergency Department, Tianjin Haihe Hospital, Tianjin, People's Republic of China.
Yan GuoAdministration Department, Tianjin Hospital, Tianjin University, Tianjin, People's Republic of China.
Rui WangSchool of Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China.
Fei XieNursing Department, Tianjin Hospital, Tianjin University, Tianjin, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the current situation, trending subjects, and future directions in the field of burnout among nurses, and to serve as a resource for researchers conducting related research. Methods: The bibliometric analysis was carried out using R package "bibliometrix", bibliometric online analysis platform (https://bibliometric.com/) and VOSviewer (1.6.18). Results: The leading countries that had a significant impact on this field were the USA and China. University of Pennsylvania was the most influential institution. Journal of Nursing Management was the top productive journal. Critical care, oncology care, acute care, and infectious disease care were more likely to lead to symptoms of burnout among nurses. "Mental health", "job satisfaction", "stress", and "COVID-19" were the current hot topics in this field. Conclusion: Our study not only provides a thorough outline to assist researchers in understanding the leading countries, institutions, journals, and potential collaborators, but it also examines the current and upcoming trends in this field and inspires researchers to select research directions.

Indexed as

burnoutCOVID-19hotspotsmental healthnursetrends

Identifiers

PMID38681974
PMCPMC11055547

What OpenQuestion holds

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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.