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Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey
Engagement in research misconduct by nurses may results in professional misconduct in the clinical setting, thereby jeopardizing the quality of patient care. We still know little about the research misconduct situation among nurses. Previous attempts also hardly reflected participants’ actual knowle...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9344333/ https://www.ncbi.nlm.nih.gov/pubmed/35928343 http://dx.doi.org/10.1016/j.dib.2022.108471 |
_version_ | 1784761198416232448 |
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author | Han, Shuyu Li, Ke Wang, Zhiwen |
author_facet | Han, Shuyu Li, Ke Wang, Zhiwen |
author_sort | Han, Shuyu |
collection | PubMed |
description | Engagement in research misconduct by nurses may results in professional misconduct in the clinical setting, thereby jeopardizing the quality of patient care. We still know little about the research misconduct situation among nurses. Previous attempts also hardly reflected participants’ actual knowledge level of research misconduct. This data article presents a novel dataset of a cross-sectional study investigating the research misconduct knowledge level and associated factors among nurses in China. Between March 2018 and March 2021, a national survey was conducted at 200 tertiary hospitals in 25 provinces. A multistage sampling (province, hospital, and participants) was applied and 4,112 nurses were recruited in this study. Participants completed questionnaires online through smartphones scanning a Quick Response (QR) code. The survey consisted of demographic characteristics, research activities, scientific misconduct knowledge, perceived reasons for research misconduct and perceived consequences for research misconduct. Data from 3,640 nurses were reserved in the dataset after data cleaning. This dataset may provide comprehensive information on research misconduct knowledge and associated factors, and important evidence for designing research integrity continuing training for nurses. |
format | Online Article Text |
id | pubmed-9344333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-93443332022-08-03 Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey Han, Shuyu Li, Ke Wang, Zhiwen Data Brief Data Article Engagement in research misconduct by nurses may results in professional misconduct in the clinical setting, thereby jeopardizing the quality of patient care. We still know little about the research misconduct situation among nurses. Previous attempts also hardly reflected participants’ actual knowledge level of research misconduct. This data article presents a novel dataset of a cross-sectional study investigating the research misconduct knowledge level and associated factors among nurses in China. Between March 2018 and March 2021, a national survey was conducted at 200 tertiary hospitals in 25 provinces. A multistage sampling (province, hospital, and participants) was applied and 4,112 nurses were recruited in this study. Participants completed questionnaires online through smartphones scanning a Quick Response (QR) code. The survey consisted of demographic characteristics, research activities, scientific misconduct knowledge, perceived reasons for research misconduct and perceived consequences for research misconduct. Data from 3,640 nurses were reserved in the dataset after data cleaning. This dataset may provide comprehensive information on research misconduct knowledge and associated factors, and important evidence for designing research integrity continuing training for nurses. Elsevier 2022-07-16 /pmc/articles/PMC9344333/ /pubmed/35928343 http://dx.doi.org/10.1016/j.dib.2022.108471 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Han, Shuyu Li, Ke Wang, Zhiwen Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey |
title | Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey |
title_full | Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey |
title_fullStr | Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey |
title_full_unstemmed | Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey |
title_short | Dataset of research misconduct knowledge and associated factors among nurses in China: A national cross-sectional survey |
title_sort | dataset of research misconduct knowledge and associated factors among nurses in china: a national cross-sectional survey |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9344333/ https://www.ncbi.nlm.nih.gov/pubmed/35928343 http://dx.doi.org/10.1016/j.dib.2022.108471 |
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