title: Workplace Violence against Health Care Workers in North Chinese Hospitals: A Cross-Sectional Survey.
abstract: This research aimed to determine the prevalence of workplace violence (WPV) against healthcare workers, explore the frequency distribution of violence in different occupational groups, and determine which healthcare occupation suffers from WPV most frequently. Furthermore, the current study aimed to compare risk factors affecting different types of WPV in Chinese hospitals. A cross-sectional design was utilized. A total of 1899 healthcare workers from Heilongjiang, a province in Northeastern China, completed the questionnaire. Of the respondents, 83.3% reported exposure to workplace violence, and 68.9% reported non-physical violence. Gender, education, shift work, anxiety level, and occupation were significantly correlated with physical violence (p< 0.05 for all correlations). Additionally, age, professional title, and occupation were correlated with non-physical violence, which critically affected doctors. Thus, gender, age, profession, anxiety, and shift work were predictive of workplace violence toward healthcare workers. Doctors appeared to experience non-physical workplace violence with particularly higher frequency when compared to nurses and other workers in hospitals. For healthcare workers, interventions aimed at WPV reduction should be enacted according to the types of violence, profession, and other factors underlying the various types of WPV in hospitals.
authors.affiliation: Department of Health, Policy and Hospital Management, School of Public Health, Harbin Medical University, Harbin 150081, China. sun745450570@163.com.
authors.forename: Peihang
authors.initials: P
authors.lastname: Sun
authors.affiliation: School of Humanities and Social Sciences, Harbin Medical University, Harbin 150081, China. xuezhang1212@sina.com.
authors.forename: Xue
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Human Resources Department, Shanghai Mental Health Center, Shanghai 200000, China. yihuasunS@163.com.
authors.forename: Yihua
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Department of Finance and Public Management, Harbin University of Commerce, Harbin 150081, China. hongkunmaM@163.com.
authors.forename: Hongkun
authors.initials: H
authors.lastname: Ma
authors.affiliation: Department of Health, Policy and Hospital Management, School of Public Health, Harbin Medical University, Harbin 150081, China. minglijiao@126.com.|Institute of Quantitative and Technical Economics, Chinese Academy of Social Science, Beijing 100000, China. minglijiao@126.com.
authors.forename: Mingli
authors.initials: M
authors.lastname: Jiao
authors.affiliation: Department of Health, Policy and Hospital Management, School of Public Health, Harbin Medical University, Harbin 150081, China. xingkai19921202@163.com.
authors.forename: Kai
authors.initials: K
authors.lastname: Xing
authors.affiliation: Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin 150081, China. zhengkang1983@126.com.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Kang
authors.affiliation: Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin 150081, China. hyhyjw@126.com.
authors.forename: Ning
authors.initials: N
authors.lastname: Ning
authors.affiliation: Graduate Department of Cancer Hospital Affiliated to Harbin Medical University, Harbin 150000, China. yapengfu@163.com.
authors.forename: Yapeng
authors.initials: Y
authors.lastname: Fu
authors.affiliation: Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin 150081, China. qunhongwu@126.com.
authors.forename: Qunhong
authors.initials: Q
authors.lastname: Wu
authors.affiliation: School of Humanities and Social Sciences, Harbin Medical University, Harbin 150081, China. meiyin1212@sina.com.
authors.forename: Mei
authors.initials: M
authors.lastname: Yin
mesh_terms: D000328:Adult; D000367:Age Factors; D002681:China / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D009790:Occupations / Q000706:statistics & numerical data; D010564:Personnel, Hospital / Q000706:statistics & numerical data*; D000066550:Physical Abuse / Q000706:statistics & numerical data; D015995:Prevalence; D012307:Risk Factors; D012737:Sex Factors; D014754:Violence / Q000706:statistics & numerical data; D064450:Workplace Violence / Q000706:statistics & numerical data*
keywords: different types of violence; risk factors; workplace violence