Cargando…

Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety

Background: Nurses experience an alarming rate of violence in the workplace. While previous work has indicated that working conditions play an important role in workplace violence outcomes, these studies have not used comprehensive and systematically operationalized variables. Methods: Through cross...

Descripción completa

Detalles Bibliográficos
Autores principales: Havaei, Farinaz, Adhami, Nassim, Tang, Xuyan, Boamah, Sheila A., Kaulius, Megan, Gubskaya, Emili, O’Donnell, Kenton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10094471/
https://www.ncbi.nlm.nih.gov/pubmed/37046935
http://dx.doi.org/10.3390/healthcare11071008
_version_ 1785023849800138752
author Havaei, Farinaz
Adhami, Nassim
Tang, Xuyan
Boamah, Sheila A.
Kaulius, Megan
Gubskaya, Emili
O’Donnell, Kenton
author_facet Havaei, Farinaz
Adhami, Nassim
Tang, Xuyan
Boamah, Sheila A.
Kaulius, Megan
Gubskaya, Emili
O’Donnell, Kenton
author_sort Havaei, Farinaz
collection PubMed
description Background: Nurses experience an alarming rate of violence in the workplace. While previous work has indicated that working conditions play an important role in workplace violence outcomes, these studies have not used comprehensive and systematically operationalized variables. Methods: Through cross-sectional survey responses from 4066 British Columbian nurses, we identified which of the 13 psychosocial factors, as outlined in the National Standard of Psychological Workplace Health and Safety, are most predictive of workplace violence perpetrated against nurses by patients and their visitors (Type II violence) and organizational employees (Type III violence). Results: Eighty-seven percent of respondents indicated that they had experienced Type II violence, whereas 48% indicated they had experienced Type III violence over the last year. Lack of physical safety, workload management, and psychological protection were the top three psychosocial factors in the workplace predictive of Type II violence, whereas lack of civility and respect, organizational culture, and psychological support were the top three factors associated with Type III violence. Conclusions: The findings in this study shed light on the distinct psychosocial factors in the workplace in need of investment and intervention to address Type II and III violence.
format Online
Article
Text
id pubmed-10094471
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100944712023-04-13 Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety Havaei, Farinaz Adhami, Nassim Tang, Xuyan Boamah, Sheila A. Kaulius, Megan Gubskaya, Emili O’Donnell, Kenton Healthcare (Basel) Article Background: Nurses experience an alarming rate of violence in the workplace. While previous work has indicated that working conditions play an important role in workplace violence outcomes, these studies have not used comprehensive and systematically operationalized variables. Methods: Through cross-sectional survey responses from 4066 British Columbian nurses, we identified which of the 13 psychosocial factors, as outlined in the National Standard of Psychological Workplace Health and Safety, are most predictive of workplace violence perpetrated against nurses by patients and their visitors (Type II violence) and organizational employees (Type III violence). Results: Eighty-seven percent of respondents indicated that they had experienced Type II violence, whereas 48% indicated they had experienced Type III violence over the last year. Lack of physical safety, workload management, and psychological protection were the top three psychosocial factors in the workplace predictive of Type II violence, whereas lack of civility and respect, organizational culture, and psychological support were the top three factors associated with Type III violence. Conclusions: The findings in this study shed light on the distinct psychosocial factors in the workplace in need of investment and intervention to address Type II and III violence. MDPI 2023-04-01 /pmc/articles/PMC10094471/ /pubmed/37046935 http://dx.doi.org/10.3390/healthcare11071008 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Havaei, Farinaz
Adhami, Nassim
Tang, Xuyan
Boamah, Sheila A.
Kaulius, Megan
Gubskaya, Emili
O’Donnell, Kenton
Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety
title Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety
title_full Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety
title_fullStr Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety
title_full_unstemmed Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety
title_short Workplace Predictors of Violence against Nurses Using Machine Learning Techniques: A Cross-Sectional Study Utilizing the National Standard of Psychological Workplace Health and Safety
title_sort workplace predictors of violence against nurses using machine learning techniques: a cross-sectional study utilizing the national standard of psychological workplace health and safety
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10094471/
https://www.ncbi.nlm.nih.gov/pubmed/37046935
http://dx.doi.org/10.3390/healthcare11071008
work_keys_str_mv AT havaeifarinaz workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety
AT adhaminassim workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety
AT tangxuyan workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety
AT boamahsheilaa workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety
AT kauliusmegan workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety
AT gubskayaemili workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety
AT odonnellkenton workplacepredictorsofviolenceagainstnursesusingmachinelearningtechniquesacrosssectionalstudyutilizingthenationalstandardofpsychologicalworkplacehealthandsafety