*Article* **Antibacterial Treatment of Selected High-Touch Objects and Surfaces within Provision of Nursing Care in Terms of Prevention of Healthcare-Associated Infections**

**Martin Krause 1,2,\* and František Dolák 1**


**Abstract:** Prevention of healthcare-associated infections is an important part of providing nursing care. High-touch objects and surfaces that can be contaminated with various bacteria are matters of concern. The possibility of reducing contamination is the use of antibacterial and hydrophobic nanolayers. The aim of this study was to determine, by means of an experimental method, the microbial efficacy of applied antibacterial and hydrophobic nanolayers on high-touch objects and surfaces used in nursing practice in a regional hospital in the Czech Republic. The results show that the antibacterial efficacy of the applied nanolayer was not demonstrated. Furthermore, the results show that selected objects and surfaces can always be contaminated by bacterial agents in about 1/3 of cases. It is mainly contamination with nonpathogenic bacteria; however, the presence of pathogenic bacteria, such as *Staphylococcus aureus*, has also been detected. The results of this study pinpoint the importance of following the basic rules for the use of decontaminated objects and surfaces used to provide healthcare.

**Keywords:** antimicrobial nanolayer; bacterial contamination; prevention; healthcare-associated infections; nursing; high-touch objects and surfaces

#### **1. Introduction**

Healthcare-associated infections are still a current problem and, according to the Organization for Economic Co-operation and Development, they are among the most common adverse events in provision of healthcare services [1,2]. Healthcare-associated infections significantly affect patient mortality and morbidity, including increased financial costs of healthcare [3]. According to the European Parliament, an average of 1 in 20 patients acquire healthcare-associated infection every day in the European Union, i.e., 4.1 million patients and 37,000 patients die from healthcare-associated infections. At the same time, it is estimated that 20–30% of infections could be prevented [4]. In many cases, healthcareassociated infections can be effectively prevented using evidence that can reduce the incidence of these infections. One of the basic components of prevention is the observance of basic hygienic-epidemiological principles, including the decontamination of objects and surfaces intended for re-use [5].

Provision of healthcare is closely linked to the use of a variety of objects and surfaces, such as medical equipment and medical devices, including tools, instruments, gadgets and other objects [6]. Objects and surfaces of the hospital environment can be a potential reservoir for the transmission of bacteria and other microorganisms immediately after contaminated hands [7]. Transmission through contaminated hands or contact with contaminated surfaces may contribute up to 20–40% to the development of healthcare-associated infections [8–10]. According to available research, surfaces are a frequent source of transmission of pathogens associated with healthcare through direct contact with the patient or the

**Citation:** Krause, M.; Dolák, F. Antibacterial Treatment of Selected High-Touch Objects and Surfaces within Provision of Nursing Care in Terms of Prevention of Healthcare-Associated Infections. *Healthcare* **2021**, *9*, 675. https://doi.org/10.3390/ healthcare9060675

Academic Editors: Alberto Modenese and Fabriziomaria Gobba

Received: 14 April 2021 Accepted: 2 June 2021 Published: 4 June 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. 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/).

environment, or indirect contact through contaminated hands of healthcare professionals, including nurses. Noncritical objects and surfaces are based on the Spaulding classification, which categorizes reusable medical devices for decontamination [11,12]. The matter of concern is mainly noncritical objects and surfaces, which are associated with frequent hand contact [13,14]. In terms of contact frequency, objects and surfaces can be divided into hightouch (e.g., stethoscopes, telephones, medical records) and low-touch or minimal-touch (e.g., ceilings, mirrors, walls) [6,8,12,15,16]. Another important aspect of the transmission of agents is the ability of microorganisms to persist on dry and inanimate surfaces, where the main principle for reducing cross-transmission is the observance and implementation of regular decontamination of objects and surfaces [12,14,17]. High-touch objects and surfaces, which are used to provide healthcare services and specific nursing interventions, require increased attention since they are directly involved in the microorganism transmission chain. For this reason, they require cleaning and subsequent disinfection [18,19]. The Spaulding classification can be used to select the method of decontamination of individual objects and surfaces intended for repeated use [6,20]. In practice, the decontamination of high-touch objects and surfaces might be underestimated, as healthcare professionals may not be aware that these objects and surfaces could be involved in the transmission of pathogens from healthcare-associated infections [19].

Preventive measures also include finding and implementing other options, such as antimicrobial surfaces, which are used to cover or impregnate surfaces in various surfaces of healthcare provision [20]. The main goal of antimicrobial surfaces is to minimize the presence of microbial contamination or reduce the viability of organisms and reduce biofilm formation. Antimicrobial surfaces are gaining more attention for setting other infection prevention strategies [21,22]. The need for antimicrobial surfaces is important because bacterial contamination of the surface contributes to the transmission of healthcare-associated infections in situations where decontamination has not been performed effectively [23,24]. When antimicrobial surfaces are used on high-touch and reusable items, it has the potential to reduce the incidence of healthcare-associated infections [23]. Antimicrobial surfaces can be placed in two categories, antiadhesive surfaces (for example applying a layer of polyethylene glycol or diamond-like carbon) and antimicrobial coatings (organic antimicrobials, such as ionized silver or copper) [22]. Nanomaterials can also be used in surface treatments since there has been increasing evidence that nanomaterials offer new ways to design antimicrobial surfaces [21]. Nanoparticles of silver and other elements, which are gradually released into the environment, are important components for use in healthcare [25,26]. In particular, silver nanoparticles are one of the most important ones due to their bactericidal, fungicidal and virucidal activity [26]. At present, there are various surface treatments of objects and surfaces using a nanolayer containing various organic–inorganic particles ensuring antimicrobial efficiency. The nanolayer can be applied to objects and surfaces in various ways, e.g., by the sol-gel method [27]. Ongoing research on this surface is still important [22]. The aim of this study was to investigate the bacterial contamination of touch objects and surfaces in a nursing practice and to compare contaminations on objects covered by a nanolayer to control objects. Studies on the contaminations of objects and surfaces are important and it is necessary to develop relevant views of bacterial transmission in healthcare facilities and to highlight effective solutions to fight it.

#### **2. Materials and Methods**

#### *2.1. Study Design*

The research was carried out by the technique of experiment. Its aim was to determine the microbial effectiveness of the applied antibacterial and hydrophobic nanolayer on selected objects and surfaces in nursing practice. The research was carried out at clinical workplaces (standard surgical departments) of a regional hospital in the Czech Republic.

#### *2.2. Selection of Research Samples*

The research samples were selected high-touch objects and surfaces that nurses use to provide nursing care. Research samples were selected based on a previous study [28]. These were emesis basins, trays and boxes intended for storing medical supplies, including sterile material in a protective package. Two groups were chosen for the experiment: nano and control. The research samples (emesis basins, trays and boxes) were identical. The nano group included research samples to which an antibacterial and hydrophobic nanolayer was applied. The control group included research samples that were not treated with anything, i.e., without surface treatments. The research samples were selected based on the relevance and feasibility of nanomaterial application. There were six criteria for the selection of samples. Firstly, they had to be objects and surfaces that the nurses used to provide nursing care. Secondly, that objects and surfaces had to be intended for re-use. Thirdly, in order to be able to apply antibacterial and hydrophobic nanolayer. Fourthly, that objects and surfaces had not come into direct contact with the patient. Fifthly, objects and surfaces had to be high-touch. The last criterion was affordability. The control group included a total of 11 emesis basins, 12 trays and 3 boxes for medical supplies. The nano group included a total of 13 emesis basins, 12 trays and 3 boxes for medical supplies. The samples from the nano and control group were ready for use.

#### *2.3. Preparation and Application of the Nanolayer*

The nanolayer was applied to the entire surface of the research samples, not only to a part of it. A nanolayer (antibacterial sol), which was composed of a hybrid organicinorganic sol based on 3-(trimethoxysilyl) propyl methacrylate with silver, copper and zinc cations, under the designation AD30, was applied to the nano research samples. The antibacterial sol corresponded to the specification according to patent CZ303861 [29]. The nanomaterial was prepared and applied by the author of the patent. Further, dilution was performed to a suitable concentration for application using isopropyl alcohol. The actual application of the antibacterial sol to the surface of plastic materials was carried out by high-pressure spraying with compressed air guns. Heat treatment was then performed to complete the polymerization of the base matrix at a temperature of 80 ◦C for 3 h.

#### *2.4. Sampling Plan and Technique*

Research samples were placed at each workplace. Each research sample was marked with an original and random code so that the result was not affected (i.e., blinding the sample origin also to the person responsible for the microbial analysis). Swabs were taken and microbiological verification of the effectiveness of the applied nanolayer was performed in the accredited microbiological laboratory of the regional type hospital every 7 days for 12 weeks. Under standard procedures and according to the conditions of laboratory practice in the Czech Republic [30,31], swabs were taken from individual research samples (ready for use for the provision of nursing care) from the area of 10 × 10 cm using a template. Sterile cotton-tipped applicator sticks moistened with saline were used for the collection. Sampling was performed using aseptic techniques. In one day, swabs were taken from all research samples. Subsequently, the sampling kit was marked and transported in protective boxes to the microbiological laboratory.

#### *2.5. Bacterial Culture*

The swab was inoculated under sterile thioglycollate broth tubes (5 mL) under aseptic conditions. The sample was allowed to incubate for 7 days at 36 ◦C. Subsequently, direct inoculation was always performed on blood agar and Mac Conkey agar. It was then placed in a thermostat for 24 h at 36 ◦C. Then, a qualitative reading of the grown bacterial colonies was performed and evaluated by a microbiologist. In the case of positive findings, more specific identification was performed, i.e., microscopy (Gram staining), isolation of pure culture or biochemical diagnostics. Pathogenic bacteria were further identified by specifying whether they were multiresistant strains [30,31]. Specifically, *Corynebacterium species*, Coagulase negative *Staphylococcus*, *Streptococcus* species, *Micrococcus* species and Sporulating microorganisms were identified using microscopy. More detailed identification for research purposes was not performed. *Acinetobacter* species and *Pseudomonas aeruginosa* were identified using biochemical diagnostics (biochemical wedge agar), *Enterobacter cloacae* (ESBL negative) and *Serratia rubidaea* (ESBL negative) were identified using enterotest and disk diffusion test (AmpC and ESBL Detection Set D68C) on Mueller–Hinton agar. *Enterococcus* species was identified using biochemical diagnostics (MEAT agar). *Staphylococcus aureus* (MRSA negative and positive) was identified using biochemical diagnostics (STAPHYtest), CHROMagar and Oxacillin Screen Agar 2 and 6. The result was interpreted as without a finding, i.e., without bacterial contamination, or with a finding, i.e., with bacterial contamination. The finding with bacterial contamination was further divided into the presence of nonpathogenic and pathogenic bacteria. The interpretation of the finding was also carried out in accordance with the valid legislation of the Czech Republic. This Act No. 306/2012 Coll. [32] says that objects and surfaces have to be used to treat patients after their decontamination.

#### *2.6. Data Analysis*

Research data were analyzed and processed in statistical software (TIBCO Statistica, version 12, Palo Alto, CA, USA). The statistical analysis was carried out in two phases. First, the classification of the first degree was performed on the basis of descriptive statistics (absolute and relative frequency). In the second phase, statistical tests were performed to determine significant relationships between indicators. For statistical testing of hypotheses, the test of agreement of two alternative distributions and the chi-square test with a significance level of *p* = 0.05 were used.

#### *2.7. Ethical Considerations*

This study did not include any ethically controversial issues; the research was not conducted on humans. The research was carried out in compliance with the Regulation of the European Parliament and of the Council No. 2016/679 of 27 April 2016. The research was carried out in accordance with the 1975 Helsinki Declaration and its most recent revisions, and in accordance with national ethical standards and regulations. The hospital and the individual workplaces agreed with the implementation of the research.

#### **3. Results**

#### *3.1. Culture Results in Emesis Basins*

For the purposes of the research, 11 nano emesis basins and 13 control emesis basins were used. A total of 132 swabs from nano emesis basins and 156 swabs from control emesis basins were taken throughout the research. Based on 132 (100.0%) swabs from nano emesis basins, there was a finding without bacterial contamination in 94 (71.2%) swabs and a finding with bacterial contamination in 38 (28.8%) swabs. Based on 156 (100.0%) swabs from control emesis basins, there was a finding without bacterial contamination in 104 (66.7%) swabs and a finding with bacterial contamination in 52 (33.3%) swabs (Table 1). The culture finding was represented by nonpathogenic and pathogenic bacteria.


**Table 1.** Culture results in emesis basins.

#### *3.2. Culture Results in Trays*

For the purposes of the research, a total of 12 nano trays and 12 control trays were used, where 144 swabs from nano trays and 144 swabs from control trays were taken throughout the research. Based on 144 (100.0%) swabs from nano trays, there was a finding without bacterial contamination in 88 (61.1%) swabs and a finding with bacterial contamination in 56 (38.9%) swabs. Based on 144 (100.0%) swabs from control trays, there was a finding without bacterial contamination in 90 (62.5%) swabs and a finding with bacterial contamination in 54 (37.5%) swabs (Table 2). The culture finding in nano trays was represented only by nonpathogenic bacteria and in control trays it was represented by both nonpathogenic and pathogenic bacteria.


#### **Table 2.** Culture results in trays.

#### *3.3. Culture Results in Boxes for Storing Medical Supplies*

For the purposes of the research, a total of 3 nano boxes for medical supplies and 3 control boxes for medical supplies were used, where 36 swabs from nano boxes and 36 swabs from control boxes were taken throughout the research. Based on 36 (100.0%) swabs from nano boxes, there was a finding without bacterial contamination in 18 (50.0%) swabs and a finding with bacterial contamination in 18 (50.0%) swabs. Based on 36 (100.0%) swabs from control boxes, the findings were the same (Table 3). The culture finding was represented by nonpathogenic and pathogenic bacteria.


#### **Table 3.** Culture results in boxes for storing medical supplies.

#### *3.4. Evaluation of the Experiment*

The research investigated whether there was a statistically significant difference (*p* ≤ 0.05) between bacterial contamination of nano and control objects and surfaces (emesis basins, trays and boxes for medical supplies) within 12 weeks. Based on the analysis, it was found out that no statistically significant difference was demonstrated between bacterial contamination of emesis basins (*p* = 0.407), trays (*p* = 0.808) and boxes for medical supplies (*p* = 1.000) in nano and control groups.

Further, it was investigated whether or not the nano emesis basins, trays and boxes for medical supplies would show bacterial contamination. Based on interval estimates (α = 0.05), it can be stated that already during the beginning of the monitoring period the relative degree of contamination in emesis basins was at least 0.152 (i.e., emesis basins will be contaminated in 15.2% of 66 swabs), in trays at least 0.289 (i.e., trays will be contaminated in 28.9% of 72 swabs) and in boxes for medical supplies at least 0.164 (i.e., boxes for medical supplies will be contaminated in 16.4% of 18 swabs). Furthermore, it was found out that in all research nano samples, bacterial contamination will always be detected in at least 26.5%, i.e., more than 1/4 of objects and surfaces will always be contaminated with bacteria.

The experiment also determined whether the degree of bacterial contamination (i.e., findings with bacterial contamination) and the method of treatment of selected objects and surfaces (objects and surfaces with and without the application of antibacterial and hydrophobic nanolayers) are independent. Based on the evaluation of the prevalence between the degree of bacterial contamination and the method of treatment of research nano and control samples, it was found out that a statistically significant dependence could not be demonstrated (α = 0.05; X<sup>2</sup> = 0.210; *p* = 0.900).

Based on the above analyses, it was realized that no statistically significant difference (*p* ≤ 0.05) was found between the degree of bacterial contamination and the method of treatment or effectiveness of the nanolayer depending on the monitoring period. For this reason, a statistically significant incidence was investigated between the emesis basins, trays and boxes for medical supplies, regardless of whether they were treated with antibacterial

and hydrophobic nanolayers. From the analysis of the data, it was found out that a finding with bacterial contamination in the emesin basins was in 31.3% (*N* = 288), in the trays in 38.1% (*N* = 288), in the boxes for medical supplies in 50.0% (*N* = 72) and in all research samples in 36.4% (*N* = 648). Based on the achieved level of significance, it can be stated that a statistically significant difference (*p* ≤ 0.05) was found between the degree of bacterial contamination of the emesis basin and the box for medical supplies (*p* = 0.003). In other cases, i.e., the dependence between the emesis basin and the tray (*p* = 0.083) and also the tray and the box for medical supplies (*p* = 0.067), it was not possible to prove a statistically significant difference.

#### **4. Discussion**

The provision of nursing care requires the use of various objects and surfaces intended for single or repeated use for the implementation of nursing interventions. In terms of the possible transmission of healthcare-associated infections, the problematic areas are mainly objects and surfaces that are intended for repeated use and which come into frequent contact with the hands of nurses. These objects can be contaminated with various bacterial agents, as confirmed by this and other studies [8,33]. An important aspect of preventing transmission of healthcare-associated infections through these objects and surfaces is the observance of the basic principles of mechanical cleaning and disinfection [6,8,18]. In the event that disinfection is not performed or is performed imperfectly, the agents of healthcare-associated infections may persist on the surfaces and may be involved in the transmission of infectious pathogens [12–16]. In this context, it is important to seek out and exploit new opportunities to minimize the risk of transmission of healthcare-associated infections through high-touch objects and surfaces used to provide nursing care.

This research, which was carried out in a regional hospital in the Czech Republic, verified the effectiveness of antibacterial and hydrophobic nanolayer, which was applied to selected objects and surfaces. The research revealed that the research samples with the applied antibacterial and hydrophobic nanolayer do not show better antibacterial activity compared to the research samples without surface treatments. However, the study did not investigate the initial bacterial burden on samples. Several studies [7,34,35] have evaluated the direct bacterial concentration on surfaces that have been plated without an enrichment phase. This surface treatment was very effective. These studies observed that most of the touch surfaces were contaminated and that the bacterial burden was highly variable between samples. This may explain the limitations of this study. Based on the research results, it was found that 28.8% of nano emesis basins and 33.3% of control emesis basins were contaminated with bacteria. The situation was similar for trays, when 38.9% nano trays and 37.5% control trays were contaminated with bacteria.

The results show that the applied nanolayer achieves low efficiency. This may have been due to testing in clinical conditions with possible external influences, but in laboratory conditions the effect of antibacterial and hydrophobic nanolayer was significant, especially on Methicillin-resistant *Staphylococcus aureus* [29]. Another possible influence may have been the dependence on the resistance of the surface treatment and damage to the layer during use. A limitation of the study may be that the activity of the nanoparticles was tested in laboratory conditions, not in medical facilities. As well as this, temperature and humidity can be limiting factors. It is also appropriate to consider a change in the composition and method of synthesis of the applied nanolayer. Efficacy could also be affected by the use of disinfectants. This shows that it is necessary to further develop and optimize the nanomaterial applied to individual objects and surfaces in terms of the results of this study. In future studies, it will be important to focus on identifying the negative circumstances that affect the effectiveness of this antibacterial nanolayer. It is also necessary to increase its antimicrobial efficacy. The method of application of the nanolayer can also be an influencing factor. Another study also states that the actual production processes, such as the thickness of the coating and the surface geometry, are also important for the essence of surface treatments. It also states that it is necessary to design and manufacture new polymeric and nanocomposite materials for effective use in healthcare [36]. The study [37] states that, when used, ZnO-C nanocomposite coatings are very effective for the elimination of *Pseudomonas aeruginosa*.

On the contrary, other studies [22,23,34,35,38] show that antibacterial surfaces, including modifications, are an effective way to prevent healthcare-associated infections. New self-disinfecting surfaces with heavy metal surfaces (copper, silver, etc.) have antimicrobial properties and can retain antimicrobial activity for several weeks to months [38]. For example, a study using copper surfaces revealed that the microbial load on copper objects was 73% lower than without any surface treatments [7]. Another study showed that the frequency of the contamination as well as the specific bacterial population bioburden is reduced on copper alloy surfaces [35]. Additionally, in the Salgado study [39] it was found that reduction of bacterial contamination was observed on objects with copper surfaces against objects without copper surfaces in 44%. For example, another study showed a small reduction of bacterial contamination on surfaces with copper [40].

This study showed that bacterial contamination of noncritical objects and surfaces is relatively high. In the case of emesis basins, all emesis basins were contaminated in 31.3% of 288 swabs. Trays for the preparation of injection and infusion material were contaminated in 38.1% of 288 swabs and boxes used for storing medical supplies were contaminated in 50.0% of 72 swabs. Another important finding is the fact that all research samples were contaminated in 36.4% of 642 swabs. The results also showed that the emesis basins were contaminated with pathogenic microorganisms, such as *Pseudomonas aeruginosa* (0.8%), *Acinetobacter species* (0.8%) or *Staphylococcus aureus* (1.3%). Pathogenic microorganisms were also detected on control trays. In this case, the presence of *Acinetobacter species* (0.7%), *Enterobacter cloacae* (0.7%) or *Serratia rubidaea* (0.7%) was detected. The presence of pathogenic bacteria was similar in boxes for storing medical supplies, such as Methicillin-resistant *Staphylococcus aureus* (2.8%) and *Enterobacter cloacae* (2.8%). The most common nonpathogenic bacteria were Coagulase negative *Staphylococcus* and Sporulating microorganisms. At the same time, it was found that the objects and surfaces were mainly contaminated with skin flora bacteria. Similar results have been found in other studies [1,8,11–14,41,42]. However, another study [43] points to the dangers of Coagulase negative *Staphylococcus*, which are associated with a high degree of antibiotic resistance and are among the main causes of bacteremia. If an infection occurs, treatment options are limited. The Ndegwa study [24] also showed that less than 50% of hospital items and surfaces and other portable medical devices were decontaminated appropriately using chemical disinfectants. This may be due to the fact that healthcare professionals may not adhere to the recommended exposure time or the prescribed concentration of the used disinfectant, including the decontamination procedure [38,44]. In this context, some studies mention that surface contamination of objects and surfaces is mainly due to human failure in the form of the absence of thorough cleaning and disinfection of surfaces rather than the use of an unsuitable product or process [33]. Thus, contaminated objects and surfaces have an effect on the possible cross-transmission of healthcare-associated infections [33]. When implementing nursing interventions, it is important to follow the principles of hospital hygiene, including decontamination and aseptic techniques during the performed procedures [44]. At present, there is still a consensus on the need to improve the mechanical cleaning and disinfection of surfaces, which are among the day-to-day essential elements of the effectiveness of the infection prevention program [38]. This study also found that some nurses do not adequately decontaminate objects and surfaces.

An important aspect of the prevention of healthcare-associated infections is the search for and optimization of options with surface treatment. Furthermore, it is important to optimize and adhere to the set hygienic-epidemiological principles, especially with a focus on the implementation of effective decontamination of objects and surfaces after their use [33,44]. At the same time, it is important to regularly check and search for clinically relevant sites of decontamination by various methods, e.g., using visual inspection, fluorescence, adenosine triphosphate bioluminescence, microbiological swabs and oth-

ers [18,20,33]. There is also a need for continuous education and regular effective training of healthcare professionals in the prevention of infections associated with healthcare, including the implementation of simulation teaching methods. Studies have shown that educational interventions have a positive effect on performing decontamination of objects and surfaces [18,45,46]. Another clinically relevant issue is the knowledge of personnel, including nurses, who perform decontamination. The research has also shown that increasing knowledge of nurses is very important in some areas [47,48]. There are several aspects that affect the achievement of a high degree of efficiency in the decontamination of objects and surfaces, and traditional procedures and disinfection need to be increased and followed. At the same time, the cost-effectiveness of new technologies needs to be addressed [38]. At present, it is necessary to build on these results and compare the effectiveness of various prevention options with implementation in practice, while improving the quality and safety of healthcare services provided through education and the search for new options.

#### **5. Conclusions**

Prevention of healthcare-associated infections is an essential part of providing healthcare and nursing care. An important part of provision of healthcare is the use of decontaminated objects and surfaces to minimize the possible transmission of pathogens associated with healthcare to patients or medical staff. In some cases, decontamination of objects and surfaces is insufficient. For this reason, it is important to look for new possibilities for antimicrobial surfaces. Antibacterial and hydrophobic nanolayers may be one of the options. The effectiveness of the used antibacterial nanolayer is not confirmed in this research. Nano research samples show the presence of bacteria. However, there are study limits that could affect antibacterial efficacy. Based on the results of this research, it is important to optimize the applied nanolayer for its effectiveness. Some research states that some antibacterial copper surfaces may be effective in preventing healthcare-associated infections. Based on the results of the study, it is important to deal with the aspect of prevention of healthcare-associated infections and minimization of contamination of objects and surfaces using the current state of knowledge and implementation of new possibilities. It is important to note that approximately 1/3 of the items and surfaces used for nursing interventions may be contaminated with bacteria, including pathogenic bacteria. Based on the results of the study, it is necessary to strengthen the existing programs for the prevention of healthcare-associated infections and to use the available evidence to minimize the transmission of pathogens.

**Author Contributions:** Conceptualization, M.K., F.D.; methodology, M.K., F.D.; formal analysis, M.K., F.D.; investigation, M.K.; resources, M.K., F.D.; writing—original draft preparation, M.K.; writing—review and editing, M.K., F.D. Both authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the SGS of Technical University of Liberec, grant number 21222.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data are not publicly available.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Javier Fagundo-Rivera 1,2,3 , Regina Allande-Cussó 4 , Mónica Ortega-Moreno <sup>5</sup> , Juan Jesús García-Iglesias 6,\* , Adolfo Romero 7,\*, Carlos Ruiz-Frutos 6,8,† and Juan Gómez-Salgado 6,8,†**


**Abstract:** Shift work that involves circadian disruption has been highlighted as a likely carcinogenic factor for breast cancer in humans. Also, unhealthy lifestyle habits observed in night work nurses could be causally related to an increase in the incidence of estrogen-positive breast tumours in this population. Assessing baseline risk of breast cancer in nurses is essential. The objective of this study was to analyze the risk of breast cancer that nurses had in relation to their lifestyle and labour factors related to shift work. A cross-sectional descriptive study through a questionnaire about sociodemographic variables, self-perception of health, and working life was designed. The sample consisted of 966 nurses. The relationship between variables was tested. A binary logistic regression and a classification and regression tree were performed. The most significant labour variables in relation to the risk of breast cancer were the number of years worked (more than 16 years; *p* < 0.01; OR = 8.733, 95% CI = 2.811, 27.134) and the total years performing more than 3 nights per month (10 or more years; *p* < 0.05; OR = 2.294, 95% CI = 1.008, 5.220). Also, the nights worked throughout life (over 500; OR = 4.190, 95% CI = 2.118, 8.287) were significant in the analysis. Nurses who had or ever had breast cancer valued their self-perceived health more negatively (*p* < 0.001) and referred a lower quality of sleep (*p* < 0.001) than the non-cases nurses. The occupational factors derived from night work could have several impacts on nurses' health and their family-work balance. Promoting healthy lifestyles, informing about shift work risks, and adjusting shift work schedules are critical methods to decrease the possible effects of circadian disruption in nurses.

**Keywords:** breast cancer; night work; shift work; health personnel; occupational disease; working conditions; prevention; carcinogens

#### **1. Introduction**

Shift work, including night shift work, has been associated with circadian disruption in several epidemiological studies conducted on nurses [1–5] and in several targeted investigations [6–9] in which expression, methylation and polymorphisms of circadian genes that could be associated with breast cancer risk among shift nurses have been studied.

In fact, long-term rotating shifts (i.e., 12 h rotating shifts) and night work have been linked to the presence of tumours with oestrogen-positive (ER+) and progesterone (PR+)

**Citation:** Fagundo-Rivera, J.; Allande-Cussó, R.; Ortega-Moreno, M.; García-Iglesias, J.J.; Romero, A.; Ruiz-Frutos, C.; Gómez-Salgado, J. Implications of Lifestyle and Occupational Factors on the Risk of Breast Cancer in Shiftwork Nurses. *Healthcare* **2021**, *9*, 649. https:// doi.org/10.3390/healthcare9060649

Academic Editor: Alberto Modenese

Received: 10 May 2021 Accepted: 28 May 2021 Published: 30 May 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. 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/).

receptors [4,10–15], and to the luminal subtypes of tumour classification (mainly luminal A) in several studies using nursing populations [16,17]. In addition, high levels of oestradiol have been recorded in nurses performing night shifts compared to those performing day shifts [10,11,13], and several studies have found significant differences between nurses working on permanent night shifts and those who performed rotating shifts, concluding that long-term, high-intensity shifts for several consecutive years can significantly influence the risk of breast cancer. Under this evidence, shift work and night work were classified as likely carcinogenic factors (Group 2A) by the International Agency for Research on Cancer (IARC), especially incidents in those professions that, such as nursing, must adjust their work throughout 24 h a day [18–23], although in-depth studies confirming these findings are still required.

One of the most noted causes has been related to the loss of synchronisation between the circadian rhythm and the sleeping patterns of nurses during continuous and long-duration rotating shift work [18,19,24–26]. Also, eating at night or referring hunger during hours that are normally dedicated to nocturnal rest may lead to disturbances in the suprachiasmatic nucleus control of hunger and satiety cycles, intrinsically related to metabolic regulation mechanisms and energy activity in peripheral tissues [24]. In addition, certain levels of exposure to blue or artificial light at night are known to affect the circadian system, altering production times and melatonin levels, among other hormones [27,28].

Circadian and sleep disturbances (i.e., social jet lag [29] or shift work disorder [30]) can lead nurses to experience extreme tiredness [31,32], to have a less active life during free time [33], and to carry out poor dietary control [23], factors that together increase cardiovascular and diabetes risk [13,34–37], and pose an increased risk of breast cancer [18]. Thus, the duration of the work shift becomes a significant predictor of the quality of nurse care and job safety [38,39], since a longer duration of shifts has been linked to an increase in errors during attendance [40,41]. Therefore, occupational health specialists have the role of providing advice to managers and workers on the best strategies to reduce the negative effects of shift-induced circadian desynchronisation, by evaluating clinical symptoms and behaviours related to sleep-wake patterns, obesity, type 2 diabetes, or dyslipidaemia caused by the shift work disorder [24].

In view of the above, it is necessary to examine the risk profile of breast cancer that nurses working on rotating and night shifts have, as well as their perception of their own health and the factors that can harm or protect it. With this information, conclusions could be drawn that could facilitate health services' managers' decision-making when planning more appropriate work shifts to reduce risk factors of occupational breast cancer. In this way, the objective of this study was to analyse the risk of breast cancer and the selfperception of health by nurses in relation to lifestyle and occupational variables associated with shift work (including night shift).

#### **2. Materials and Methods**

#### *2.1. Design and Sample*

Cross-sectional, questionnaire-based descriptive study on the population of Registered Nurses in Spain, both men and women (currently 316,094 subjects) [42]. The sample selection was made by non-probabilistic snowball sampling, estimating the optimal size at 980 nurses with a 95% confidence level, 3.5% accuracy, and 20% adjustment for losses.

The inclusion criteria were (a) Being a nurse and being registered in the General Council of Nurses of Spain; (b) Working in private and/or public centres; (c) Wish to participate, having read and signed the informed consent. On the other hand, the exclusion criteria were (a) Not being Registered Nurses; (b) Being under 18; (c) Working outside Spain.

#### *2.2. Shift Work and Night Work Definition*

Cambridge Business English Dictionary defines shift work as: "a system in which different groups of workers work somewhere at different times of the day and night". Besides, the IARC defined night work as: "one that requires at least three hours of work between midnight and 5 a.m." [20,21,43]. The main characteristics of shift work are shown in Table S1 [11,20,21,23,44].

#### *2.3. Instrument*

To gather the appropriate information, an online questionnaire was used. The main risk variables related to breast cancer and night work which were used in this investigation were extracted and adapted ad hoc based on other questionnaires found in the scientific evidence [3,11,14,45,46]. The final questionnaire was formed by the 8 sections detailed below. The validation of the final instrument was carried out through two rounds of analysis by a panel of experts using a Delphi technique to determine whether the detected variables and the design of the questionnaire were relevant and appropriate in the context of the study. This group was made up of three nurses, two physicians, two psychologists, two members of a healthcare system management board and one methodologist. Subsequently, a piloting was carried out favourably in 10 people from different nursing areas to assess the suitability of the questions, possible grammatical errors or mistakes that were not previously detected.

#### *2.4. Variables*

The variables considered in this study were:


#### *2.5. Data Collection Procedure*

The study development took place from December 2019 to November 2020. Google Forms© (Google, Mountain View, CA, USA) was used to create the online questionnaire. Participants could not access the questionnaire until they had previously done the following: (a) Having read and understood an introductory letter to the study and its objectives; (b) Having confirmed voluntary and anonymous participation in the study; (c) Declaring working as a nurse in Spain and being currently registered. The data obtained from the questionnaires were entered in Excel (Microsoft©, Redmond, WA, USA), R Commander 4.0.0 [47], and SPSS version 26.0 (IBM©, Armonk, NY, USA) for the statistical analysis.

The online questionnaire link was provided via email to the nurses who were registered in the General Nursing Council of Spain and previously had accepted to receive

emails, news and information bulletins from this institution. The General Council of Official Nursing Colleges of Spain is the only regulatory body and competent authority of the nursing profession in Spain, therefore the registration in this government-authorized licensing body is obligatory to obtain a nursing license and be legally authorized to work, thus being considered a Registered Nurse (RN). Given this fact, a high number of nurses were consulted via email thanks to this collaboration, although we were not able to control this intervention due to the Data Protection policy of this institution. The social networks of official entities and professional groups of renowned prestige in the area of nursing in Spain (i.e., University of Huelva or Spanish Nurses Syndicate) also collaborated with the dissemination of the questionnaire.

#### *2.6. Statistical Analysis*

Absolute frequencies, percentages, and measures of position and dispersion, depending on the type of variable, described the variables of interest. Student's T-test for independent samples and the Chi-squared test were used to contrast differences and relationship (OR) between the variables and breast cancer risk. The Mann–Whitney U nonparametric test for independent samples was used to analyse heterogeneity in the self-perception of health category.

Binary logistic regression allowed building a model to study the presence of breast cancer and identify those risk variables that played a relevant role. The Hosmer-Lemeshow test was used, and Odds Ratios (OR) were estimated with their confidence intervals.

Finally, the CART (Classification and Regression Trees) data mining method [48,49] was used to design a binary algorithm to predict which variables of the self-perception of health category played a significant role in breast cancer. The CART methodology refers to a model where the target variable and the algorithm itself are used to predict values based on several categorical or continuous input variables. It is shown as a Decision Tree Classifier (Figure 1), where each round is known as Node. Each node will have a question or if-clause according to which the subjects of study will be routed to a specific internal or terminal/leaf-node that will tell the final prediction. Each node shows the predicted class, the predicted probability of cases within the node, and the percentage of cases of the node over the total sample. In summary, there are three types of nodes:


The questionnaire was answered by a total of 966 nursing professionals, of whom 502 (51.97%) were healthy, 99 (10.25%) had or ever had some form of cancer, and 365 (37.78%) had another type of disease. Of those who had or ever had cancer, for 56.57%, it was breast cancer (56 subjects). Common diseases found in both men and women were hypertension, diabetes, obesity, asthma, or seasonal allergy. In women, isolated cases of thyroid cancer,

For the bivariate analysis, healthy individuals (502) and breast cancer patients (56) were compared with the variables of interest. The median age of the sample was 41 years (*p* = 0.367) and 89.6% of the sample were women (*p* = 0.705). Subsequent bivariate analysis categorized by sex revealed only age (χ2 = 9.669; *p* 0.002; OR = 2.466; 95%CI= 1.376, 4.419) as significant in relation to breast cancer (see Table S2). According to the current workplace, a 19.2% of the sample worked on permanent shifts, mostly morning shifts, and a 74.5% worked on rotating shifts. Only a 3.8% worked on 24h-shifts. Approximately a 72.4% of the sample was working on night shifts at the time of the survey (Table 1).

 **Cases Percentage** 

Permanent Shift 107 19.2% *Only morning* 73 68.2% *Only afternoon/evening* 5 4.7% *Only night* 29 27.1%

*12-h shifts* 71 34.8% *Rotative M and N* 31 15.2% *Rotative M and AE* 62 30.4% *Rotative AE and N* 7 3.4% 24-h Shifts 21 3.8% Irregular 14 2.5% Total general 558 100%

Rotative 3 Shifts/24 h Cycles (M/AE/N) 212 37.9% Rotative 2 Shifts/24 h Cycles 204 36.6% *Only morning + eventual extra-duty (+17 h)* 33 16.2%

**Figure 1.** Decision Tree Classifier (for learning purpose). **Figure 1.** Decision Tree Classifier (for learning purpose).

**Table 1.** Description of the sample's work organization.

**3. Results** 

*Breast Cancer* 

cervical cancer, melanoma, leukaemia, and lymphoma were also found.

M: morning (7-h shift); AE: afternoon/evening (7-h shift); N: night (10-h shift).

#### *2.7. Ethical Considerations*

For this study, the Declaration of Helsinki (Fortaleza, 2013) was taken into consideration and explicit written permission was obtained from participants through their informed consent. Data obtained in this study were to be duly guarded by the research team, ensuring the confidential use and processing in accordance with the Organic Law on Protection of Personal Data and the Guarantee of Digital Rights. Approval was obtained from the Research Ethics Committee of the province of Huelva, belonging to the Regional Government of Andalusia, with code TD-CMTE-2020. Likewise, approval was obtained from the Research Ethics Committee of the General Council of Official Nursing Colleges of Spain with code PI 2109/02/CE.

#### **3. Results**

#### *3.1. Two-Dimensional Analysis for Healthy Participants and Those Who Have or Ever Had Breast Cancer*

The questionnaire was answered by a total of 966 nursing professionals, of whom 502 (51.97%) were healthy, 99 (10.25%) had or ever had some form of cancer, and 365 (37.78%) had another type of disease. Of those who had or ever had cancer, for 56.57%, it was breast cancer (56 subjects). Common diseases found in both men and women were hypertension, diabetes, obesity, asthma, or seasonal allergy. In women, isolated cases of thyroid cancer, cervical cancer, melanoma, leukaemia, and lymphoma were also found.

For the bivariate analysis, healthy individuals (502) and breast cancer patients (56) were compared with the variables of interest. The median age of the sample was 41 years (*p* = 0.367) and 89.6% of the sample were women (*p* = 0.705). Subsequent bivariate analysis categorized by sex revealed only age (χ <sup>2</sup> = 9.669; *p* 0.002; OR = 2.466; 95%CI= 1.376, 4.419) as significant in relation to breast cancer (see Table S2). According to the current workplace, a 19.2% of the sample worked on permanent shifts, mostly morning shifts, and a 74.5% worked on rotating shifts. Only a 3.8% worked on 24h-shifts. Approximately a 72.4% of the sample was working on night shifts at the time of the survey (Table 1).

**Table 1.** Description of the sample's work organization.


M: morning (7-h shift); AE: afternoon/evening (7-h shift); N: night (10-h shift).

No statistically significant differences were found for parity, either in the general (*p* = 0.684) and sex-categorized analysis (*p* = 0.648). On the other hand, significant associations with breast cancer were found in participants with a partner (*p* = 0.041) and those who cared for dependents at home outside the working hours (*p* < 0.001). Indeed, being single (OR = 0.541; 95% CI = 0.298, 0.982) and without family caring responsibilities (OR = 0.288; 95% CI = 0.146, 0.569) were related with breast cancer risk reduction (Table 2).


**Table 2.** Sociodemographic and lifestyle characteristics of the sample.


**Table 2.** *Cont.*

\*: Fisher. BMI: Body Mass Index. Under 18.5: Underweight; (18.5, 25) Normal; (25, 29.9) Overweight; equal or higher to 30: Obese.

Having ever had a mammogram and the number of performed mammograms also resulted significative for breast cancer risk (mean = 2.27; SD = 4.43; *p* < 0.001; OR = 1.353, 95% CI = 1.248, 1.466). Similarly, the presence of familial cancer was significant (*p* = 0.005), resulting in risk reduction when there was no family cancer history (OR = 0.398; 95% CI = 0.205, 0.773) (Table 2).

In terms of lifestyle habits, BMI showed significant differences (*p* = 0.045). The higher number of breast cancer cases had normal BMI. Similarly, statistically significant differences (*p* < 0.001) were detected depending on the intensity of physical activity at work. Most breast cancer cases classified their exertion at work as moderate. However, no significant differences were found for the physical activity during free time (*p* = 0.631). Statistically significant differences were found regarding the frequency of exposure to tobacco smoke at home (*p* = 0.001) and the compliance with the smoking ban in the workplace (*p* = 0.010), but not with having ever smoked (*p* = 0.953).

Lastly, the 79.2% of the nurses claimed not to take any sleep medication, although this variable was relevant in breast cancer cases (*p* < 0.001). In fact, not taking sleep medications resulted in risk reduction (OR = 0.138; 95% CI = 0.077, 0.247) (Table 2). The most common medication was oral melatonin (60 subjects, of which 11 had breast cancer). Among other remedies, infusions (valerian, melissa), hypnotics (doxylamine, zolpidem), anxiolytics (alprazolam, bromazepam), antidepressants (trazodone), and other benzodiazepines (lorazepam, lormetazepam, diazepam) were used. Oral contraceptives were only used by women in this study, not being significant for breast cancer (*p* = 0.441).

With respect to labour data (Table 3), being not currently working at night (*p* < 0.001; OR = 2.708, 95% CI = 1.548, 4.735) and being not currently shift working (*p* < 0.001; OR = 3.148, 95% CI = 1.765, 5.615) showed a statistical association with the risk of breast cancer. Considering the working history of the participating subjects, having exceeded 16 years of work was presented as one of the most significant variables in this study (*p* < 0.001; OR = 12.346, 95% CI = 4.854, 31.250). Nurses who had or ever had breast cancer had worked a mean of 26.1 years (SD = 8.1), while healthy nurses had worked a mean of 15.0 years (SD = 9.2). On the other hand, the percentage of cases with breast cancer was also higher in professionals with 500 or more nights worked (OR = 4.190, 95% CI = 2.118, 8.287) and when more than 3 nights per month had been worked for more than 10 years (OR = 4.132; 95% CI = 2.227, 7.634), finding a statistically significant difference in both situations (*p* < 0.001). The mean number of nights worked was 627.9 (SD = 639.4) in the case of healthy subjects and 1017.4 nights in those who had or ever had breast cancer (SD = 837.9). 2.3% of respondents never worked night shifts. Finally, the cumulative number of sick leaves, both in the last year (mean 0.35; SD = 0.542) and throughout the professional life (mean 2.20; SD = 2.118), have shown a statistically significant association with breast cancer (*p* < 0.001 in all cases) (Table 3).


**Table 3.** Labour variables and risk of breast cancer.

#### *3.2. Self-Perception of Health Descriptive Analysis*

Regarding the self-perception of health, the overall health was rated 7.94 (SD = 1.26) among the sample nurses, being lower in breast cancer cases (6.45) and higher in the healthy cases (8.11). The lowest value of this category was found in the quality of sleep and rest, with a mean of 6.28 (SD = 1.96) and decreasing to 5.29 in breast cancer cases. The highest value was identified when considering whether shifts affect the health of people, with a mean of 9.08 (SD = 1.37). In relation to stress at work, the mean value was 7.57 (SD = 1.86). The stress perception was higher among breast cancer cases (8.23) as compared to healthy cases (7.49). Finally, the satisfaction with the working conditions was valued with a mean of 7.28 (SD = 1.87). Among all the health self-perception variables, statistical differences were found in terms of overall health (*p* < 0.001), sleep and rest quality (*p* < 0.001), and stress at work (*p* = 0.002) (Table 4).

**Table 4.** Sample profile according to the health self-perception variables.


#### *3.3. Breast Cancer Prediction*

The following two regression methods were performed in this study to identify those variables that play a relevant role in breast cancer risk.

#### 3.3.1. Considering Labour Variables and Sleep Medication

Binary logistic regression analysis predicts breast cancer among nurses through the following variables: total years performing more than 3 nights per month, sleep medication, sick leaves, years worked, and actual exposition to night work. This model was validated with the Hosmer-Lemeshov test (*p* = 0.811), correctly classifying 91.3% of cases. In addition, all variables included in this model had significant values lower than 0.05 and OR values greater than the unit (Table 5).


**Table 5.** Logistic regression analysis for breast cancer.

OR: Odds ratio. \* *p* < 0.05; \*\* *p* < 0.01. <sup>1</sup> : (more than 16 years); <sup>2</sup> : (10 or more years).

#### 3.3.2. Self-Perception of Health Variable

With regard to the self-perception of health among nurses, the CART showed the 558 cases at a root node, of which 10.03% (0.10; 56 subjects) have breast cancer.

A second node differed according to the valuation of the overall health (higher or equal to 5.5; yes or no), resulting in a breast cancer percentage of 68% (0.68) in the 25 subjects (4% of the total cases) who valued their overall health below 5.5, and 7.3% of breast cancer cases in the subsequent 533 subjects (96% of the sample) whose scores were equal to or higher than 5.5.

For the 4% of cases with worse health perception (overall health below 5.5), an internal node differed according to the satisfaction with the current working conditions. The percentage of breast cancer cases reached 82.4% (0.82) when the level of job satisfaction was higher or equal than 5.5, and otherwise the percentage of cases was 38% (0.38).

Returning to those cases with overall health higher or equal to 5.5 (96%; 533 subjects), the following internal node differed again according to the valuation of the overall health (higher or equal to 7; yes or no). 502 nurses (90%) whose self-perception of health was ≥7 showed a 5.8% (0.06) of breast cancer cases. Otherwise, the 6% (33) of nurses whose self-perception of health was between 5.5 and 7 points comprised 29.4% (0.29) of cancer cases.

Finally, an internal node for sleep quality (<6; yes or no) is shown for the cases with overall health between 5.5 and 7. 62% (0.62) of breast cancer cases occurred in 1% (6) of nurses who perceived their sleep quality under 6. On the other hand, 19% of breast cancer cases occurred in the 5% (28) of nurses who perceived their sleep quality over 6 (Figure 2).

**Figure 2.** Classification and regression tree of breast cancer cases and self-perception of health. **Figure 2.** Classification and regression tree of breast cancer cases and self-perception of health.

#### **4. Discussion 4. Discussion**

2).

The main objective of this study was to analyse the relationship between shift work, especially night shift work, and the risk of developing breast cancer in nursing professionals in Spain, in order to obtain a descriptive image of the labour and lifestyle factors that can influence the risk of breast cancer in this group. The main objective of this study was to analyse the relationship between shift work, especially night shift work, and the risk of developing breast cancer in nursing professionals in Spain, in order to obtain a descriptive image of the labour and lifestyle factors that can influence the risk of breast cancer in this group.

nurses who perceived their sleep quality under 6. On the other hand, 19% of breast cancer cases occurred in the 5% (28) of nurses who perceived their sleep quality over 6 (Figure

The logistic regression model was successfully validated and showed significant values. Among the measurements of night work that appear to be associated with the risk of breast cancer, having worked a mean of three night shifts per month for 10 years or more (OR = 2.294; 95% CI = 1.008, 5.220) has been highlighted, although the number of total years worked was also significant (OR = 8.733; 95% CI = 2.811, 27.134), taking as a reference the performance of professional activity for more than 16 years and that 95% of the sample reported having worked in rotating shifts at some point of his or her career, although at the time of the survey it was 80.8%. Also noteworthy in this study is the increased risk of breast cancer when 500 nights or more have been worked throughout life (*p* < 0.001; OR = 4.190; 95% CI = 2.118, 8.287). In accordance with other studies [36,50], the data provided suggests that the risk profile of shift-related breast cancer highly varies depending on the number of nights worked, so exposure to permanent and rotating night shifts is considered of key relevance from an early age and throughout the working life. In this way, several studies confirmed the risk of breast cancer among nurses working on rotating night shifts at least 3 nights a month for 20 years or more, particularly those who started in their young adulthood (before the age of 30) [3,12,16]. In premenopausal women, those characteristics of night work that were indicative of high intensity of exposure (3 or more nights per week), long duration of night work over life (at least 10 years in a row), and long night shifts (10 or more hours) were associated with an increased risk of breast cancer The logistic regression model was successfully validated and showed significant values. Among the measurements of night work that appear to be associated with the risk of breast cancer, having worked a mean of three night shifts per month for 10 years or more (OR = 2.294; 95% CI = 1.008, 5.220) has been highlighted, although the number of total years worked was also significant (OR = 8.733; 95% CI = 2.811, 27.134), taking as a reference the performance of professional activity for more than 16 years and that 95% of the sample reported having worked in rotating shifts at some point of his or her career, although at the time of the survey it was 80.8%. Also noteworthy in this study is the increased risk of breast cancer when 500 nights or more have been worked throughout life (*p* < 0.001; OR = 4.190; 95% CI = 2.118, 8.287). In accordance with other studies [36,50], the data provided suggests that the risk profile of shift-related breast cancer highly varies depending on the number of nights worked, so exposure to permanent and rotating night shifts is considered of key relevance from an early age and throughout the working life. In this way, several studies confirmed the risk of breast cancer among nurses working on rotating night shifts at least 3 nights a month for 20 years or more, particularly those who started in their young adulthood (before the age of 30) [3,12,16]. In premenopausal women, those characteristics of night work that were indicative of high intensity of exposure (3 or more nights per week), long duration of night work over life (at least 10 years in a row), and long night shifts (10 or more hours) were associated with an increased risk of breast cancer at 5 years of their working life [3,15,51,52].

at 5 years of their working life [3,15,51,52]. On the other hand, the analysis of nurses' self-perception of health variables and the CART classification and regression tree have made it possible to highlight the importance of attending to the assessment of general health, sleep quality, stress level, and level of job satisfaction referred to by nurses themselves. The present study has confirmed that nurses who had or ever had breast cancer exhibited a higher level of work-related stress and On the other hand, the analysis of nurses' self-perception of health variables and the CART classification and regression tree have made it possible to highlight the importance of attending to the assessment of general health, sleep quality, stress level, and level of job satisfaction referred to by nurses themselves. The present study has confirmed that nurses who had or ever had breast cancer exhibited a higher level of work-related stress and worse self-perceived health than healthy nurses. Equally, it is important to consider the impact of stress at home, as it can lead to work-family related conflicts and health problems [5,34,53,54]. In fact, the perception of stress in the family environment could be considered relevant given the positive association between the care of dependents at home (*p* < 0.001; OR = 0.288; 95% CI = 0.146, 0.569), having a partner (*p* = 0.041;

OR = 0.541; 95% CI = 0.298, 0.982) and the risk of breast cancer found in this study. It is therefore worth noting that the work-family balance can affect the role of nurses [55] and the family stability [56,57], and this may lead to lack of time for leisure and self-care [5,58], tiredness [31], sleep problems [59] and many risk behaviours as alcohol consumption [53] if an important imbalance is given.

The risk profile analysis of nursing professionals in this study identified that professionals who had breast cancer valued worse the quality of their rest (5.29) than healthy professionals (6.39), with significant differences being detected between both groups (*p* < 0.001), although it is true that the quality of rest had a surprisingly low mean value between the two groups (6.28). Despite that, only 20% of respondents resorted to sleep medication, even though this variable showed a statistical significance for breast cancer in the model (OR = 5.841; 95% CI = 2.848, 11.978). Hypnotics intake has been associated with cancer due to the alterations on sleep patterns, such as insomnia, that occur during the disease at any stage and that persist in survivors [26,60]. In addition, slow rotating systems which include longer sequences of consecutive night shifts, can cause disturbances in sleep patterns [3,61], fatigue, and sleepiness even on rest days after shifts [62]. Other studies have shown that irregularity in the organization of the shifts affects the adaptive ability of shift work nurses [18,63,64]. 12-h shifts (day–night) imply less sleep disorders and a more balanced rest period than the 3 × 8 rotation (morning–afternoon–night) [18,65], thus allowing a better recovery. However, workload is more intense in 12-h shifts than in 3 × 8 shifts, due to the longer duration of the shift, resulting in greater physical and mental fatigue [18,64,65].

According to a recent study, when there are no symptoms of depression, anxiety, tiredness or stress, nurses are more resilient and more satisfied with their work [66]. In fact, job satisfaction is an interventional stress-reducing factor that can positively influence the perception of one's own health [67,68], the decrease in the frequency of physical and psychological symptoms [69], and the improvement of the quality and safety of patient care [70–72], as well as the re-induction of errors [40]. Instead, low job satisfaction is a contributing factor to nurses leaving their jobs and profession [73–75]. Data from this study have shown a mean satisfaction of 7.28, that does not differ significantly between the assessed groups. This would make it possible to emphasise that job satisfaction is not one of the most prominent problems regarding the sample of this study since, as can be seen in the CART, low job satisfaction was not a criterion for pointing out a large number of cases of breast cancer.

Finally, according to data on lifestyle habits, physical activity in the working context was statistically significant in relation to breast cancer, reporting the majority of cases when it was classified as "moderate". This may be contrary to other results that report a beneficial association of physically active jobs to reduce breast cancer risk [76]. Meanwhile, physical activity during free time was not significant in our study (*p* = 0.631). With reference to BMI, the 14.3% of the sample who had breast cancer were obese and the 30.4% had overweight. Obesity has been associated with consecutive night shifts (more than 8 shifts per month) and cumulative years of night work (more than 20 years) [36,77,78], as well as increased tobacco consumption [51]. In this line, recent research was consistent with the increased risk of breast cancer that occurs in active, heavy, and long duration smokers and passive smokers [51,79–81], particularly premenopausal women who smoked or were exposed to second-hand smoke between menarche and first full-term pregnancy, in the occupational and residential context [80]. This relationship could correspond to the results of the present study, which significantly linked breast cancer to tobacco exposure both in the workplace (*p* = 0.010) and at home (*p* = 0.001).

It is worth noting that the responses to the questionnaire on current work have identified that not undertaking shifts nor night work were risk factors for breast cancer, given that most of breast cancer cases did not work on shifts by the time of the survey. These results were in line with a literature review on returning to work following a breast cancer process in Spain [82], in which it was concluded that improvements in working

conditions allow workers to adapt their job to their new physical capacity. As described in another study [5], those individuals with breast cancer could have received a change or compensation on behalf of their workplace organisation when they were diagnosed or when re-joined after the sick leave, exempting them from rotating shifts and night work in order to create a less aggressive work environment for the worker.

#### *4.1. Implications for the Practice and Applicability*

With a view to future research, investigating nurses' breast cancer risk factors will still play an important role due to its importance in screening and prevention. Detailed information about nurses' working hours and night work-related circadian disruption may also be relevant to increase visibility regarding this occupational health issue. In this sense, it would be interesting to measure total nocturnal output of melatonin in shift workers to make a correlation with total and nocturnal melatonin levels. Cortisol levels also require attention due to its balance with melatonin levels and regulation during day light. It must be noted that future research should also study specific parameters of circadian disruption, such as the expression of peripheral clock genes and clock-controlled genes. Periodic assessment of parameters such as waist circumference, waist-to-hip ratio, BMI, glycemia, glycosylated haemoglobin, triglycerides, and total HDL and LDL cholesterol would be useful to evaluate the risk of night shift-related diseases, such as obesity, type 2 diabetes, dyslipidaemia and metabolic syndrome [83].

It is appropriate to adopt prevention and action guidelines that highlight associations between diet, weight, and physical activity to prevent the development of breast cancer and possible metabolic syndrome on shift workers, taking into account cases in premenopausal and postmenopausal women whenever possible [84–87]. It has recently been shown that the adoption of dietary recommendations by Spanish women who have had cancer was moderate. At the same time, adherence to physical activity and body weight management was higher among older women, women who had one or more children, and those who lived in rural areas. Increased compliance with smoking bans and greater limitation of alcohol consumption were also reported [86].

The results obtained in this study may have applicability in different spheres. In the university education system, it would be relevant to talk about the risk of shift-based breast cancer and cardiovascular risk in order to raise awareness among students of the repercussions of intensive night work during the first years of the career and the risks associated with circadian disruption in order to prevent them.

For the management and human resources systems of healthcare companies, this study would allow managers and supervisors to consider an equitable distribution of shifts and breaks, as well as a limitation of weekly night shifts performed by nurses and overtime (extra-duties).

Similarly, for night workers in general, and for nurses in particular, this study should encourage interventions to promote a healthy and balanced life in order to counteract the negative effects of work on rotating and night shifts. In this way, workers should be informed of the potential risks of performing nights intensively or for several years, and it would be appropriate to provide balanced diets, to install suitable spaces and lighting for work [88] and rest, and to allow sufficient time to eat, pause, and organise work efficiently.

As for nurses who have or have had breast cancer, this study makes it possible to wonder whether shift-related breast cancer could be considered an occupational disease. In such case, it would be desirable to demonstrate individual risk by counting nights and analysing biomarkers. If possible, people who have had breast cancer should be encouraged to return to work through a process of time adaptation and activities.

#### *4.2. Limitations*

With regard to the limitations of the study, it should be kept in mind that it was a cross-sectional study and these results, although in line with previous evidence, must be considered with prudence to avoid interpretation bias. In addition, breast cancer diagnosis was not clinically confirmed because data was collected using self-reported information. It is also important to consider the recall bias as another study limitation related to the retrospective study design. In this sense, some variables such as weight, height or total number of worked nights could have been influenced by recall bias. On the other hand, our analysis could be influenced by a small sample size, as it covered only 56 cases of breast cancer, which could potentially represent participation bias although the sample and number of responses has been estimated as sufficient to overcome low representativeness.

Many variables have not been considered in this study, such as menopausal status, age at menarche, age at first full-term parity, breastfeeding history, sleeping patterns or comorbidities. In this way, the authors encourage its detailed study in future investigations.

Another limitation that has been perceived refers to precision of the intensity grades of the physical activity at work and self-perception of health. In this study, the exertion scores have been stated as light, moderate, hard or very hard, similarly to those scores found in the Borg Rating of Perceived Exertion Scale [89]. However, greater detail of the description provided on the scales should have been considered, according to various authors who proposed a detailed explanation [90,91]. Health-related quality of life and self-perception of health are commonly incorporated as predicting survival factors in the design of research studies and clinical trials in oncology. This study has used a self-assessment scale with a range from 1 to 10, which has allowed the CART method to be performed later. However, it should be noted that there are several validated tools for health assessment and quality of life, so their use should be considered in future research [92–95]. In this same line, this study did not use standard tests to assess the quality of sleep and the state of the circadian system (chronotype). Some scales are purposed like the Pittsburgh Sleep Quality Index [96] or the Morningness-Eveningness stability scale improved (MESSi) [97].

#### **5. Conclusions**

This study has highlighted a statistically significant increase in the risk of breast cancer in nurses in association with total years of work experience (the risk increases by over 16 years worked) and the total number of years of more than 3 nights per month (the risk increases by over 10 years worked). In addition, other factors such as the total number of nights worked (the risk increases by more than 500 nights), taking medication to sleep, and having had sick leaves have been associated. Similarly, certain variables related to health self-assessment, such as poor overall health quality, stress levels, or low sleep quality, have been significant in pointing out an increased risk of breast cancer.

Given the incidence of breast cancer in nurses and the frequency of night shift working further research is needed to clinically measure the possible effects of shift work on breast cancer risk, circadian misalignments and other metabolic diseases that could affect nursing professionals. However, many interventions could be developed from the actual moment in order to prevent and inform about this carcinogenic factor.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/healthcare9060649/s1, Table S1: Shiftwork organization and characteristics; Table S2: Sex Analysis.

**Author Contributions:** Conceptualization, J.F.-R., R.A.-C., M.O.-M., J.J.G.-I., A.R., C.R.-F. and J.G.-S.; Data curation, J.F.-R., R.A.-C., M.O.-M., J.J.G.-I., A.R., C.R.-F. and J.G.-S.; Formal analysis, J.F.-R., R.A.-C., M.O.-M., J.J.G.-I., C.R.-F. and J.G.-S.; Funding acquisition, J.G.-S.; Investigation, J.F.-R., J.J.G.-I., A.R., C.R.-F. and J.G.-S.; Methodology, J.F.-R., R.A.-C., M.O.-M., C.R.-F. and J.G.-S.; Project administration, J.F.-R., C.R.-F. and J.G.-S.; Resources, J.F.-R., A.R., C.R.-F. and J.G.-S.; Software, J.F.-R., M.O.-M. and J.G.-S.; Supervision, J.F.-R., M.O.-M., C.R.-F. and J.G.-S.; Validation, J.F.-R., M.O.-M. and J.G.-S.; Visualization, J.F.-R., R.A.-C., M.O.-M., J.J.G.-I., A.R. and J.G.-S.; Writing—original draft, J.F.-R., R.A.-C., M.O.-M., J.J.G.-I., A.R. and J.G.-S.; Writing—review & editing, J.F.-R., R.A.-C., M.O.-M., J.J.G.-I., A.R., C.R.-F. and J.G.-S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was part of the project "Working exposure to breast cancer risk factors: night work in nursing" which was funded by the Andalusian Institute for the Prevention of Occupational Hazards (IAPRL) 17 June 2019.

**Institutional Review Board Statement:** For this study, the Declaration of Helsinki 2004 was taken into consideration and explicit written permission was obtained from participants through their informed consent for the confidential use and processing of their data in accordance with the Organic Law on Protection of Personal Data and the Guarantee of Digital Rights. Data are guaranteed to be duly guarded by the research team. Ethical approval was obtained from the Research Ethics Committee of the Spanish General Nursing Council, as well as from the Research Ethics Committee of the province of Huelva, belonging to the Regional Government of Andalusia (Spain) with code TD-CMTE-2020.

**Informed Consent Statement:** Informed written consent was obtained from all subjects involved in the study.

**Data Availability Statement:** All generated data is presented within this paper and its Supplementary Material. The research team and the University of Huelva are responsible of keeping the datasets of the study, which would be available for investigators under reasonable query.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


#### *Article* **The Effects of Emergency Room Violence toward Nurse**0 **s Intention to Leave—Resilience as a Mediator**

**Jui-Hsuan Li <sup>1</sup> , Ta-Wei Chen <sup>2</sup> , Hsiu-Fang Lee 1,3 and Whei-Mei Shih 1,4,\***


**Abstract:** (1) Background: Healthcare workplace violence has been a focused issue in the whole world. The rate of the occurrence is pretty high in every country. The emergency room is a high risk and high frequency place for violence to occur. Under the medical service demands from people, it is quite easy to bring about conflicts. This leads to serious physical and mental harm to nurses. When suffering from physical and mental injuries, resilience is a protective factor away from negative influence. It is rare to explore and study how the nurses' resilience ability, workplace violence and turnover intention are related. Thus, the aim of this study is to understand resilience as a mediator effect in emergency nurses toward the workplace violence. (2) Methods: A cross-sectional survey study was used to collect information from emergency room nurses of a medical center in northern Taiwan. There were 132 samples in total. Three research instruments were included as follows: Hospital Workplace Violence Prevention Questionnaire, Connor-Davidson Resilience Scale, and Turnover Intention Scale. Statistical analysis using *t*-test, ANOVA, Correlation, as well as Sobel test were used in this study. (3) Results: The results revealed that the average age was 29.5 ± 5.6. Almost 58% of nurses experienced workplace violence. Twelve percent of nurse had experienced physical violence and 53.8% had experienced mental violence. There was significant relationship between shift personnel and religious believers. To the people who suffered physical violence, there was a significant relationship between emergency room working years and the total working years. There was significant difference between those who had suffered mental violence and religious believers. Female nurses suffered mental violence to a much higher extent than male nurses. There was a significant relationship between nurses' working years, the total working years, resilience, and turnover intention. Resilience was not the mediator for workplace violence toward turnover intention in this study. (4) Conclusions: The outcome of this study suggested that on an individual level, nurses can enhance self-protection and communication skills to decrease workplace violence. For emergency environment settings, designing a good working environment, visitors' restriction, avoiding working alone, and enhancing supervising alarm system are recommended. As for hospital administrators, fitness for work and to set up a project team is necessary. These can be references in planning prevention on workplace violence and promoting quality of workplace and patient safety in the future.

**Keywords:** emergency room; workplace violence; resilience; intention to leave

#### **1. Introduction**

Workplace violence has been a much researched and serious issue in the whole world. Healthcare organizations have been high frequency sites and it is especially common in the emergency room [1–4]. Workplace violence toward nurses is twice higher than

**Citation:** Li, J.-H.; Chen, T.-W.; Lee, H.-F.; Shih, W.-M. The Effects of Emergency Room Violence toward Nurse0 s Intention to Leave—Resilience as a Mediator. *Healthcare* **2021**, *9*, 507. https:// doi.org/10.3390/healthcare9050507

Academic Editor: Alberto Modenese

Received: 21 March 2021 Accepted: 22 April 2021 Published: 28 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. 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/).

toward the doctors and the other medical staff. They suffered beating 2.26 times more than the others [5,6]. The International Labor Organization (ILO), World Health Organization (WHO), International Council of Nurses (ICN) and Public Services International (PSI), defined mutually, in 2002, the definition of workplace violence as, "Incidents where staff are abused, threatened or assaulted in circumstances related to their work, including commuting to and from work, involving an explicit or implicit challenge to their safety, well-being or health," including physical violence and psychological violence [5].

The survey according to the Occupational Health Safety Network (OHSN) in America in 2012–2015 showed that the rate of emergency room violence was 19.3% and the average annual growth rate was 23% [6]. The occurrence rates in the other countries were 56–75.8% [1,7–10]. The study indicated only 30% occurrence rate had been officially reported [8,11] and up to 80% remained unreported [12]. Besides, every country has different definition on workplace violence, which leads to different data. The causes of emergency room violence were analyzed from four dimensions: inner and external factors, environmental factors and organizational factors. For instance, violence was part of work; there was poor communication skills; the waiting time was too long; doctor–patient information was no equal; the supervisors did not value at all; it was too crowded and noisy; it lacked privacy and there was a shortage of manpower, etc. [1,8,9,13,14]. Eventually workplace violence would reduce nurses' passion for the job and it would result in health organizations losing experienced nurses [3].

Resilience is people's ability to recover after experiencing adversity [15–17]. At present, there is no universal definition, but there are some common characteristics, such as adaptation and adjustment, dynamic process and ordinary magic [18]. First, the person must be exposed to the severe adversity; secondly, he/she can still maintain a positive adaptation under adversity [19,20]. "Workplace adversity" relates to heavy workloads, inexperience, professional autonomy influenced by bullying and violence, organizational problems, and occupational safety issues. These problems may be considered as adversity to people [21]. Nurses with high resilience see adversity as a part of their life, but not a threat [22]. Resilience decreases the influence of mental health to the minimum for nurses who work in the critical care units. It helps them stay in the workplace but not to choose to leave [21,23].

Turnover may be understood as employees leaving the organization or profession voluntarily. Turnover intention means mental status before quitting the organization or profession. It indicates that the employees are not satisfied with their jobs, coming about the ideas to quit, looking for the opportunities to work, evaluating and comparing with other opportunities to work. This situation takes shape before the actual turnover action happens. According to a study of Finnish labors on job disamenities, job satisfaction, and intentions to quit, variables such as education, discrimination, no promotion, heavy mentally, neglect, uncertainty, and harm had significant effects on switch intentions [24]. Choi and Lee [25] specified that 95.5% of nurses had experienced different workplace violence in the past one year. Not only were they exposed to the physical threat, but they were also experiencing slight to severe job burnout. There is a direct relationship between nurses' experience of workplace violence and physical mental symptoms. The working pressure certainly impacts working satisfaction, increases turnover rate and the cost of the hospitals. In addition, it decreases their occupational life quality and healthcare quality and furthermore it becomes the factor of their turnover [26,27].

For more than 15 years of work in the emergency room, the researchers found out some of the nurses left the workplace after having experienced violence, and others were talking about leaving the current job. For those who stayed in the emergency room, they faced workplace violence either positively or ignored it. This phenomenon drew our attention to the relationship between workplace violence and intention to leave and why they still stay in the emergency room. The literature review indicated that healthcare professionals' turnover intentions were mostly job burnout, emotional exhaustion, work pressure, and work satisfaction. Although there were researchers who surveyed the relationship between healthcare professionals' resilience and turnover intention, only a few researchers explored

the related studies about healthcare professionals' workplace violence, resilience, and turnover intention. Therefore, the purpose of this study was to explore the effects of resilience as a mediator in emergency room violence toward nurses' intention to leave.

#### **2. Materials and Methods**

#### *2.1. Research Design and Samples*

A cross-sectional survey study was used to collect information on emergency room nurses of a medical center in northern Taiwan. There were a total of 171 registered nurses in the emergency room and all of them were recruited in this study. Fifteen subjects refused to participate in the survey and 24 questionnaires were not filled out completely, leaving 132 valid questionnaires. The response rate was 84.6%. Inclusion criteria included: nurses at the emergency room worked over three months and were willing to participate.

#### *2.2. Research Instruments*

#### 2.2.1. Workplace Violence Instruments

The scale "Workplace Violence Instruments" was conducted by Institute of Labor, Occupational Safety and Health, Ministry of Labor, Taiwan, in 2014. There were five parts in the questionnaire, including basic data, physical violence, psychological violence (verbal abuse, bullied/mobbed and threats), policies and measurements, and the opinions toward workplace violence (open-ended question: three most important strategies to decrease violence in working environment.).

#### 2.2.2. Connor-Davidson Resilience Scale

The original scale was developed by Connor and Davidson [28] and it was divided into five levels and 25 questions, and the sequence of the levels were: (1) personal competence, high standards, and tenacity; (2) trust in one's instincts, tolerance of negative affect, and strengthening effects of stress; (3) positive acceptance of change and secure relationship; (4) control; and (5) spiritual influences to evaluate the participants' ability to successfully respond to the pressure in the past one month. The present study used a 10-item CD-RISC Scale extracted by Campbell-Sills and Stein [29] from the original CD-RISC Scale. It is a Likert 5-point Scale and it respectively divides into Never (0), Occasionally (1), Sometimes (2), Often (3), and Always (4) from the lowest score 0 to the highest score 40. The higher the scores are, the higher the resilience is. The internal consistency of Cronbach's α is 0.95 in the present study.

#### 2.2.3. Intention to Leave Scale

The present study used the Professor Huang Kai-Yi's Chinese scale translated from Mobley's [25] Turnover Intention Scale. It was mainly to measure the intention of employees' leaving jobs. There were four questions including (1) the idea to leave, (2) the motivation to look for another job, (3) the degree of influence of the external job's opportunity, and (4) the willingness to leave the current job. The questionnaire adapted 7-point to be the scoring method, from the lowest score 4 to the highest 28. The higher the scores are, the higher the turnover intention is. The internal consistency of Cronbach's α is 0.72 in the present study.

#### *2.3. Statistical Method*

The Statistical Package Software of SPSS (IBM, Armonk, NY, USA) for Window 18.0 version was used for statistical analysis. Research data counted the obvious level and set *p* value < 0.05 as the standard to judge statistical meaning. Data analysis method included descriptive statistics, Independent Sample *t*-test, One Way Analysis of Variance, Chi-Square Test, Pearson Product-moment Correlation Coefficient, and Sobel Test Path Analysis.

#### **3. Results**

#### *3.1. The Current Situation between the Participants' Demographic Characteristics and Workplace Violence*

A total of 132 participants were recruited in this study. The average age was 29.5 ± 5.6; the average overtime per week was 0.2 h; the average working years in the emergency room was 6.8 ± 5.1; the average total working years was 7.5 ± 5.6; shift personnel was 81.8%; nurses with in-service training on violence prevention was 62.9%; religious believers was 34.1%. In the last year, 57.6% of nurses suffered workplace violence. Twelve percent of nurses experienced physical violence and 53.8% of nurses suffered mental violence. The average resilience scored was 26.48 ± 6.59 and the average turnover intention score was 15.43 ± 4.76 (see Table 1).

**Table 1.** Current Analysis of Participants' Demographic Data, Resilience, and Turnover Intention (*n* = 132).


Sixteen (12.1%) participants had suffered physical violence within one year. The main reasons were the patients' condition changed too fast; the patients' waiting time was too long; there was bad communication between nursing staff and patients. When the participants encountered the violence, they usually decided to stop the abusers to cease their behaviors and others would ask security guards for help. For mental violence, there were 71 (53.8%) participants who suffered verbal insult. The reasons were due to the

patients' waiting being too long, bad communication, and a crowded environment. Those who suffered bullying were 12 (9.1%). The bullying mainly came from their colleagues or supervisors and the bullying victims usually did not take any action about it. The personnel suffered threat was 20.5%. The probable causes were the patients' waiting being too long, bad communication, crowded environment, terrible traffic flow, and that the patients' condition changed too fast. When the participants faced mental violence, they usually decided to stop the abusers to cease their behaviors and the others would ask security guards for help. The reasons why they did not report mainly were they thought it was useless; it was not important; or they were afraid of negative results; or they did not know to whom they should report.

#### *3.2. The Comparison of Difference among the Participants' Workplace Violence, Resilience and Turnover Intention*

There was a significant difference among workplace violence nurses in shifts and religion. Nurses with shift rotation (X<sup>2</sup> = 4.840, *p* < 0.05 \*) and religion (X<sup>2</sup> = 5.121, *p* < 0.05 \*) had higher frequency of workplace violence. There was significant difference among those who experienced physical violence with working years in the emergency room and the total working years. Nurses with less working years in the emergency room (t = −2.05, *p* < 0.05 \*) and less total working years (t = −1.991, *p* < 0.05 \*) tended to have experienced physical violence. As far as for mental violence, there was significant difference in religion. Nurses who were religious suffered mental violence more (X<sup>2</sup> = 8.243, *p* < 0.01 \*\*) (see Table 2).

**Table 2.** The Comparison of Difference for the Participants Suffered Workplace Violence, Resilience, and Turnover Intention (*n* = 132).


\* *p* < 0.05, \*\* *p* < 0.01.

#### *3.3. The Related Comparison among the Participants' Workplace Violence, Resilience, and Turnover Intention*

There was a positive correlation between the working years in the emergency room and age (r = 0.934, *p* < 0.01 \*\*). The total working years and age had a positive correlation (r = 0.959, *p* < 0.01 \*\*). Satisfaction of dealing with physical violence had a negative correlation with age (r = −0.308, *p* < 0.01 \*\*), working years in the emergency room (r = −0.305, *p* < 0.01 \*\*) and total working years (r = −0.311, *p* < 0.01 \*\*) (see Table 3).

**Table 3.** Related Comparison on Participants' Demographic Data, Resilience, and Intention to leave (*n* = 76).


\* *p* < 0.05, \*\* *p* < 0.01.

#### *3.4. The Intermediary Effects of Resilience*

To test whether resilience was the mediator effect for the workplace violence and turnover intention, the Sobel test path was used according to Baron and Kenny's [30] method. Using resilience as the mediator variable, the results of path analysis for those who had suffered workplace violence and turnover intention were shown as below:

There was not any significant relationship between nurses who suffered workplace violence and turnover intention (c = 0.091, *p* > 0.05).

No significant relationship showed between nurses who suffered workplace violence and resilience (a = −0.100, *p* > 0.05).

There was not a significant relationship between workplace violence victims' resilience and turnover intention (b = −0.097, *p* > 0.05).

Resilience was not the mediator between nurses who suffered workplace violence and turnover intention (*p* > 0.05) (see Table 4).


**Table 4.** Regression Analysis Chart with resilience as the mediation variable test (*n* = 132).

#### **4. Discussion**

*4.1. Workplace Violence*

In the present study, 57.6% of participants had suffered workplace violence within one year, which was similar to previous research [1,7–10]. From patients' point of view, the main reasons were long waiting time, bad communication, crowded environment, and their personal feelings. To nurses, the reasons were that the conditions of the patients changed too fast, the staff0 s skill problems, and nurses' attitude toward patients. Di Martino [5] pointed out the related reasons in the medical workplace violence could divide into work design and workload, such as ambiguity, overload work, lack of control, death dealing; the interpersonal relationship at work, such as conflict with the other staff; relationship with the patients and their family members, such as, insufficient preparation, insufficient mood dealing, and the demands of the patients and their family members; work organization and work management, for example, lack of the staffs' support, employees' turnover, the management echelon, and the supervisors' difficulties, lack of resource and personnel shortage; the nursing techniques, such as treatment and nursing problems; personal, such as professional knowledge and skills [10,31–33]. It is recommended that nurse managers re-evaluate work assignment, re-enforce in-house education, and provide enough resources for emergency room nurses.

During the study, senior nurses always arranged with junior nurses, which increased workload for senior nurses. Meanwhile junior nurses suffered workplace violence during night shift and working alone. These reasons led to the results of this study that workplace violence was significantly correlated to shift rotation. There was a significant relationship between the workplace violence occurrence and shifts because the workload, time management, and the degree of busy would relatively enhance [22,32]. Tahghigit et al. [34] indicated that those who fitted the shifts well would be more highly pressure resistant. In this study, the religion was correlated with workplace violence. Nurses with religion tended to suffer workplace violence. It was probably based on Taiwanese0 s culture that most Taiwanese would search for the help of gods [35,36] in the first place when facing troubles. It is recommended that junior nurses should avoid working at night shift and alone as possible. Nursing managers should pay more attention to nurses who are religious so as to early detect whether they are the victims of workplace violence.

Resilience in this study was not a mediator for intention to leave, which was different from other studies that showed that resilience was the mediator [34,37]. This might be due to that the institutions continue to hold in-service training regarding identification of workplace violence and nurses can identify from the first place and see it as part of the work.

#### *4.2. Physical Violence*

There were 12.1% of nurses suffered physical violence in the past one year as compared to 19–28.6% [38,39] in Taiwan and 10–42.7% in other countries [11,31,40,41], which is low. One of the reasons was when suffering violence they usually tolerated and chose not to report [3,40]. Verbal insult usually was the sign of physical violence on abusers [42]. It is recommended the security guards stationed around the clock. When it came to verbal insult, the nurse can inform the security guard immediately and it may stop the physical conflicts before the abusers took his act of violence. In addition, there was usually low notification rate in physical violence [11] with high turnover rate for nurses [42], which might give support the reason why there was lower physical violence or the victims might have left in the study. Hence, there was correlation between physical violence and intention to leave, and yet no correlation between mental violence and intention to leave.

There was significant correlation between working years in the emergency room and physical violence, which was similar to the past studies [10,32,43,44]. Studies revealed that workplace violence is related to age, inexperience, past experience of violence, and lack of communication skills [31,32]. The senior nurses were good at simplifying the events and then dealing with them [45]. They were good at distinguishing situations and having better negotiation skills [31]. Experience can be taught through learning to distinguish the signs before violence, communication skills, and negotiation skills.

#### *4.3. Mental Violence*

This study revealed that 53.8% of nurses suffered mental violence. Among these, 53.8% was verbal insult, 9.1% was bullying, and 20.5% was threats, which were similar to the previous research [25,31,32,38–40,46,47]. Verbal violence was five times as much as physical violence [7]. Workplace violence was mainly mental violence [10,25,38] or non-physical violence [31]. Verbal violence was the highest [10,25,38]. Abusers with verbal

insults mainly came from the patients' family members or the patients themselves. Bullying came mostly from colleagues and supervisors, results which are similar to previous studies [25,36,41,48,49]. The main causes of violence were the delay of examination and treatment, or dissatisfaction with quality of care [31,32,45,50]. Violence between the colleagues might be due to the responsibility to protect patients [10]. Nurses were concerned about it being useless to report or were afraid of the negative consequence, which was similar to the past research [49]. Yet, the silent culture inside the organizations would impact the results of the report [43]. Moreover, some nurses complained of not knowing whom they should report to. Therefore, knowledge and systems of prevention of violence should be disseminated to all employees in the institution.

#### **5. Conclusions**

There were 57.6% participants who suffered workplace violence in the past one year, while 12.1% suffered physical violence and 53.8% suffered mental violence. Abusers mainly came from patients (32.6%) and patients' relatives and friends (35.6%). Violence occurred mainly because patients' conditions changed too fast, long waiting times, bad communication, crowded environment, and bad traffic flow. When facing violence, the victims would stop the abusers at the first moment and secondly, they would ask the security guards for help. There was a relationship between workplace violence and shifts, religious belief, working years in the emergency room, and total working years. Resilience was not the intermediary variable for workplace violence and turnover intention.

The present study offered suggestions that could be divided into three parts, including individuals, environment, and organization. For nurses, it is important to enhance self-protect, the ability to communicate and coordinate with the patients and their family members as well as to use positive communication skills. For the environment factor, emergency administrators should reinforce the safety control at the main entrance, mark precisely the area and the route, and avoid the environment to work alone, and increase surveillance cameras and alarm systems. As for the organization factor, hospital administrators should adjust the work, allot the work properly, set up task forces toward case management modes, offer conformably the case's mental health rebuilding system, present medical and legal assistance and improve police–civilian cooperation. The study concerned sensitive issues, so we adapted an anonymous questionnaire. Still, we could not exclude the participants not giving exact answers because they tried to fend off the sensitive issues. Therefore, an Internet questionnaire and APP application software are strongly advised in the future. In addition, the reason for low physical violence rate may be due to victims leaving jobs. It is recommended that the violence issue be included in nurses' exit interviews, for a better understanding in future studies.

There are still a high percentage of unreported workplace violence around the world [6,10,13]. Compared to other countries0 workplace violence rate, 56–75.8%, this research showed a lower rate of 57.6%. This study provides workplace violence prevention strategies as references for other healthcare organizations internationally.

#### **6. Limitation**

Resilience in this study was not a mediator for the intention to leave, which were nonexpected results. As for demographic data such as age, total working years, and emergency room working years, there was no correlation with intention to leave as well. This might be due to the institution continues to hold in-service training regarding identification of workplace violence, and nurses can identify it in the first place and see it as part of the work.

This study focused on the relationship between workplace violence and the intention to leave a job. Demographic data such as sex, age, education, marital status, working years, shift, training, and religion were included and yet some other non-occupational factors such as behaviors and emotional balance were not included. These variables will be considered in the future study.

**Author Contributions:** Conceptualization, T.-W.C. and W.-M.S.; methodology, J.-H.L.; software, T.-W.C.; validation, J.-H.L. and T.-W.C.; formal analysis, J.-H.L. and W.-M.S.; investigation, J.-H.L. and H.-F.L.; resources, H.-F.L.; data curation, J.-H.L. and W.-M.S.; writing—original draft preparation, J.-H.L.; writing—review and editing, W.-M.S.; visualization, H.-F.L.; supervision, W.-M.S.; project administration, W.-M.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (201800960B0).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

**Acknowledgments:** We would like to thank the nurses who participated in this study and nursing department0 s administrative support.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

