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Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice

The ability of knowledge, attitude, and practice of intensive care unit (ICU) nurses to perform medical device‐related pressure injuries (MDRPIs) can affect the incidence of MDRPI in ICU patients. Therefore, in order to improve ICU nurses' understanding and nursing ability of MDRPIs, we investi...

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Autores principales: Sun, Xiao‐Xuan, Chen, Rui‐Bin, Fang, Ping‐Ping, Yu, Ran, Wang, Xu‐Xing, Liu, Jia‐Qiu, Chen, Ying, Ling, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10410357/
https://www.ncbi.nlm.nih.gov/pubmed/36891887
http://dx.doi.org/10.1111/iwj.14129
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author Sun, Xiao‐Xuan
Chen, Rui‐Bin
Fang, Ping‐Ping
Yu, Ran
Wang, Xu‐Xing
Liu, Jia‐Qiu
Chen, Ying
Ling, Hua
author_facet Sun, Xiao‐Xuan
Chen, Rui‐Bin
Fang, Ping‐Ping
Yu, Ran
Wang, Xu‐Xing
Liu, Jia‐Qiu
Chen, Ying
Ling, Hua
author_sort Sun, Xiao‐Xuan
collection PubMed
description The ability of knowledge, attitude, and practice of intensive care unit (ICU) nurses to perform medical device‐related pressure injuries (MDRPIs) can affect the incidence of MDRPI in ICU patients. Therefore, in order to improve ICU nurses' understanding and nursing ability of MDRPIs, we investigated the non‐linear relationship (synergistic and superimposed relationships) between the factors influencing ICU nurses' ability of knowledge, attitude, and practice. A Clinical Nurses' Knowledge, Attitude, and Practice Questionnaire for the Prevention of MDRPI in Critically Ill Patients was administered to 322 ICU nurses from tertiary hospitals in China from January 1, 2022 to June 31, 2022. After the questionnaire was distributed, the data were collected and sorted out, and the corresponding statistical analysis and modelling software was used to analyse the data. IBM SPSS 25.0 software was used to conduct Single factor analysis and Logistic regression analysis on the data, so as to screen the statistically significant influencing factors. IBM SPSS Modeler18.0 software was used to construct a decision tree model of the factors influencing MDRPI knowledge, attitude, and practice of ICU nurses, and ROC curves were plotted to analyse the accuracy of the model. The results showed that the overall passing rate of ICU nurses' knowledge, attitude, and practice score was 72%. The statistically significant predictor variables ranked in importance were education background (0.35), training (0.31), years of working (0.24), and professional title (0.10). AUC = 0.718, model prediction performance is good. There is a synergistic and superimposed relationship between high education background, attended training, high years of working and high professional title. Nurses with the above factors have strong MDRPI knowledge, attitude, and practice ability. Therefore, nursing managers can develop a reasonable and effective scheduling system and MDRPI training program based on the study results. The ultimate goal is to improve the ability of ICU nurses to know and act on MDRPI and to reduce the incidence of MDRPI in ICU patients.
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spelling pubmed-104103572023-08-10 Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice Sun, Xiao‐Xuan Chen, Rui‐Bin Fang, Ping‐Ping Yu, Ran Wang, Xu‐Xing Liu, Jia‐Qiu Chen, Ying Ling, Hua Int Wound J Original Articles The ability of knowledge, attitude, and practice of intensive care unit (ICU) nurses to perform medical device‐related pressure injuries (MDRPIs) can affect the incidence of MDRPI in ICU patients. Therefore, in order to improve ICU nurses' understanding and nursing ability of MDRPIs, we investigated the non‐linear relationship (synergistic and superimposed relationships) between the factors influencing ICU nurses' ability of knowledge, attitude, and practice. A Clinical Nurses' Knowledge, Attitude, and Practice Questionnaire for the Prevention of MDRPI in Critically Ill Patients was administered to 322 ICU nurses from tertiary hospitals in China from January 1, 2022 to June 31, 2022. After the questionnaire was distributed, the data were collected and sorted out, and the corresponding statistical analysis and modelling software was used to analyse the data. IBM SPSS 25.0 software was used to conduct Single factor analysis and Logistic regression analysis on the data, so as to screen the statistically significant influencing factors. IBM SPSS Modeler18.0 software was used to construct a decision tree model of the factors influencing MDRPI knowledge, attitude, and practice of ICU nurses, and ROC curves were plotted to analyse the accuracy of the model. The results showed that the overall passing rate of ICU nurses' knowledge, attitude, and practice score was 72%. The statistically significant predictor variables ranked in importance were education background (0.35), training (0.31), years of working (0.24), and professional title (0.10). AUC = 0.718, model prediction performance is good. There is a synergistic and superimposed relationship between high education background, attended training, high years of working and high professional title. Nurses with the above factors have strong MDRPI knowledge, attitude, and practice ability. Therefore, nursing managers can develop a reasonable and effective scheduling system and MDRPI training program based on the study results. The ultimate goal is to improve the ability of ICU nurses to know and act on MDRPI and to reduce the incidence of MDRPI in ICU patients. Blackwell Publishing Ltd 2023-03-09 /pmc/articles/PMC10410357/ /pubmed/36891887 http://dx.doi.org/10.1111/iwj.14129 Text en © 2023 The Authors. International Wound Journal published by Medicalhelplines.com Inc and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Sun, Xiao‐Xuan
Chen, Rui‐Bin
Fang, Ping‐Ping
Yu, Ran
Wang, Xu‐Xing
Liu, Jia‐Qiu
Chen, Ying
Ling, Hua
Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
title Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
title_full Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
title_fullStr Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
title_full_unstemmed Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
title_short Model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
title_sort model construction of factors influencing intensive care unit nurses' medical device‐related pressure injury knowledge, attitude, and practice
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10410357/
https://www.ncbi.nlm.nih.gov/pubmed/36891887
http://dx.doi.org/10.1111/iwj.14129
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