Evidence map›Paper›PMID 39432632›Full record

ArticleMedicine2024

Bibliometric analysis of research hotspots and global trends in patient safety education for nursing students.

Ying Wang, Yi-Wen Chen, Xin-Ping Hu, Hua Mei

Abstract read
In one paragraph

Article in Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Ying WangShanghai University of Traditional Chinese Medicine, 201203, Shanghai, China.ORCID 0009-0009-0864-8673
Yi-Wen ChenShanghai University of Traditional Chinese Medicine, 201203, Shanghai, China.
Xin-Ping HuShanghai University of Traditional Chinese Medicine, 201203, Shanghai, China.
Hua MeiShanghai University of Traditional Chinese Medicine, 201203, Shanghai, China.

Funding

2023 Shanghai Education Science Research Program C2023145
6 · The paper itself

Abstract

Patient safety education for nursing students has recently garnered interest. However, there is a paucity of data on the key areas and global trends over time. This study aims to analyze research patterns in the field of patient safety education for nursing students, identifying key contributors and global trends. A descriptive bibliometric approach was employed to analyze 782 articles related to patient safety education using data from the Web of Science Core Collection and CiteSpace 6.2. R4. Co-occurrence and co-citation analyses were conducted to identify prominent authors, institutions, countries, and common keywords. The analysis revealed contributions from 335 authors and 302 institutions across 78 countries. Levett-Jones T emerged as the most prolific author with 12 articles. The United States and the University System of Ohio were identified as the most productive countries and institutions, with 276 and 26 articles, respectively. Frequently occurring keywords included patient safety, education, medical education, simulation training, and standardized patients. This study provides valuable insights into the global research landscape of patient safety education in nursing, highlighting key contributors and trends. These findings can assist nursing students, educators, and researchers in identifying potential collaborators and informing future research to advance patient safety education in nursing.

Indexed as

BibliometricsPatient SafetyStudents, NursingEducation, NursingHumans

Identifiers

PMID39432632
PMCPMC11495743

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.