Evidence map›Paper›PMID 38645460›Full record

ArticleFrontiers in public health2024

Knowledge, attitude, and practice toward the prevention of occupational exposure in public health emergencies among nurses in Wuhan.

Yan Liu, Zhili Zhang, Ying Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2024. 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
3.7field-weighted citation impact, top 8% of its field
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, 5 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Yan LiuTongren Hospital of Wuhan University (Wuhan Third Hospital), Wuhan, China.
Zhili ZhangTongren Hospital of Wuhan University (Wuhan Third Hospital), Wuhan, China.
Ying LiuTongren Hospital of Wuhan University (Wuhan Third Hospital), Wuhan, China.
Tongren Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective: Nurses have an essential role in dealing with public health emergencies (PHE). This study explored the knowledge, attitude, and practice (KAP) towards preventing occupational exposure in PHE among nurses in Wuhan. Methods: This cross-sectional study was conducted in May 2023 to assess the KAP of nurses in Wuhan, China. Questionnaires were created and distributed to evaluate the KAP of nurses and explore the factors associated with KAP. Univariate and multivariate logistic regression analyses were used to assess the association between baseline demographic characteristics and KAP, and structural equation modeling (SEM) was used to explore complex relationships and causal pathways among relevant factors. Results: A total of 440 valid questionnaires were collected. The mean knowledge, attitude, and practice scores were 11.84 ± 2.37, 39.87 ± 3.10, and 44.05 ± 3.76, respectively. The univariate and multivariate logistic regression analyses revealed that age >50 years old ( Conclusion: Nurses exhibited moderate knowledge, relatively positive attitude, and practice, which needed to be improved regarding occupational exposure in PHE. The practice of the nurses could be promoted by paying more attention to the working experience, participation in training and scene rescue in PHE, and their knowledge and attitude.

Indexed as

Health Knowledge, Attitudes, PracticeOccupational ExposureAdultChinaCross-Sectional StudiesEmergenciesFemaleHumansMaleMiddle AgedNursesPublic HealthSurveys and Questionnairesattitudeknowledgenurseoccupational exposurepracticepublic health

Identifiers

PMID38645460
PMCPMC11026623
OpenAlexW4393985359

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.