Evidence map›Paper›PMID 37294093›Full record

ArticleNursing open2023

Nurses' preparedness to respond to COVID-19 and associated factors after the outbreak in China.

Jing Han, Yuping Liu, Feng Gu, Jinmei Li, Dan Wang, Yao Zhang, Ruijin Tang, Li Zhang

Abstract read
In one paragraph

Article in Nursing open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

8 authors.

Jing HanSchool of Nursing, Xuzhou Medical University, Xuzhou, China.ORCID 0000-0002-4618-0444
Yuping LiuDepartment of Nursing Administration, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Feng GuDepartment of Nursing Administration, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Jinmei LiDepartment of Nursing Administration, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Dan WangDepartment of Oncology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Yao ZhangSchool of Nursing, Xuzhou Medical University, Xuzhou, China.
Ruijin TangSchool of Nursing, Xuzhou Medical University, Xuzhou, China.ORCID 0000-0002-3620-0958
Li ZhangSchool of Nursing, Xuzhou Medical University, Xuzhou, China.

Funding

Foundation of Major Projects of Philosophy and Social Science Research in Jiangsu Province 2020SJZDA126Postdoctoral Research Foundation of Jiangsu Province 2021K624CResearch Foundation of Xuzhou Medical University D2019037
6 · The paper itself

Abstract

aimNurses are key staff in the response to the COVID-19 epidemic. The aim of present study was to assess Chinese clinical nurses' preparedness levels for COVID-19 after the outbreak, as well as the associated demographic factors.

designThe design was a cross-sectional survey.

methodsWe distributed an online questionnaire to nurses from five eastern coastal area hospitals. The questionnaire collected demographic information, and included the nurses' preparedness to respond to COVID-19 questionnaire (NPR COVID-19).

resultsThe total mean NPR COVID-19 score was 200.99 (standard deviation = 33.60), and the psychological approaches subscale had the lowest mean score. Education and training were positively associated with the NPR COVID-19 score. Nurses' characteristics, such as seniority, job category and educational level, were entered into the NPR COVID-19 regression model, and seniority (≤5 years) showed the strongest negative association with NPR COVID-19 scores (standard coefficient = -0.20).

conclusionsChinese nurse's preparedness to respond to COVID-19 was adequate. Nurses with less than 5 years of work experience, nursing researchers and diploma-educated nurses reported feeling a low preparedness to respond to COVID-19. These nurses should receive specific training.

Indexed as

COVID-19NursesChinaCross-Sectional StudiesDisease OutbreaksHumansSurveys and QuestionnairesCOVID-19education and trainingnursespreparedness

Identifiers

PMID37294093
PMCPMC10416027

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.