Evidence map›Paper›PMID 37841020›Full record

ArticleFrontiers in medicine2023

Evaluation and improvement of workplace vertical violence of nursing interns based on the Importance-Performance Analysis method.

Weifang Xu, Lili Feng, Haohao Huang, Siqi Liu, Mao Ye, Fuqin Tang, Yen-Ching Chuang, Fuman Cai

Abstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Poor Work Ability Is Associated with Workplace Violence in Nurses: A Two-Wave Panel Data Analysis.International journal of environmental research and public health · 2024
    Article
  4. Observational
  5. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Weifang XuCollege of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Lili FengCollege of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Haohao HuangCollege of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Siqi LiuDepartment of Intensive Care Unit, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Mao YeDepartment of Intensive Care Unit, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Fuqin TangDepartment of Nursing, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Yen-Ching ChuangInstitute of Public Health and Emergency Management, Taizhou University, Taizhou, Zhejiang, China.
Fuman CaiCollege of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To analyze the key factors related to workplace vertical violence among nursing interns in China and to propose strategies to improve the nursing practice environment. Methods: A cross-sectional study was conducted using the Importance-Performance Analysis (IPA) method to analyze the key factors and significance of workplace vertical violence for nursing interns. The data were obtained by administering a workplace vertical violence survey, designed specifically for this study, to 120 nursing interns at a tertiary general hospital in Zhejiang Province, China. Results: The results demonstrated that the variables "I was ordered to do something beyond my ability and lacked guidance ( Conclusion: Managers must prioritize the use of relevant resources during internships to minimize false reinforcement and unfair criticism. Efforts should focus on improving information sharing, emphasizing the role of nursing interns in clinical work, providing better guidance when arranging for nursing interns to do work that exceeds their capacity, reducing workplace vertical violence, and improving nursing intern practice environments.

Indexed as

Importance-Performance Analysis (IPA)multiple criteria decision-making (MCDM)nursing internspriority improvementworkplace vertical violence

Identifiers

PMID37841020
PMCPMC10569029

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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.