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Open Access 01.12.2025 | Research

Workplace violence, psychopathological symptoms, and deviant workplace behavior among nursing interns in China: a network analysis

verfasst von: Simeng Dong, Xinshu Shen, Tong Zhao, Rui Zeng, Min Chen

Erschienen in: BMC Nursing | Ausgabe 1/2025

Abstract

Background

Workplace violence in healthcare has become a global concern, and nursing interns are not immune to it in clinical settings. It is critical to understand the impact of workplace violence on the psychological and work status of nursing interns.

Methods

Between April and May 2024, a total of 2213 nursing interns from 12 hospitals in China participated in the study. Data were collected with questionnaires on basic information, the Workplace Violence Scale, the Caregiver Occupational Deviant Behavior Scale, and the DSM-5 Level 1 Cross-Cutting Symptom Measure. The basic analysis was performed using SPSS 24.0 software, and the network structure analysis was constructed using R software to calculate the relationship between the nodes and the centrality index.

Results

In nursing interns, the items with the highest prevalence of workplace violence were verbal assault (32.038%) and threats (10.303%); in psychopathological symptoms, the items with the highest prevalence were anxiety (38.500%), anger (35.337%), and depression (33.439%). The strongest edge within the cluster is “Verbal sexual harassment-Physical sexual harassment,” and the strongest edge between clusters is “Verbal assault-Depression.” The node with the highest strength, expected influence, and betweenness indices is “Anxiety,” and the node with the highest closeness index is “Depression.”

Conclusions

The results demonstrate the effectiveness of the network perspective in elucidating the complex relationships and interconnections between different symptoms. We identified the strongest relationships between nodes, “Depression” and “Anxiety” as the most important symptom. These findings may provide more precise targets for developing interventions for nursing interns.
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Introduction

Workplace violence (WPV) in healthcare has become a global concern, especially in developing and industrialized countries [1]. Statistically, healthcare workers are 16 times more likely to be reported as experiencing WPV than other industries. Of these, clinical nurses, a significant group of frontline healthcare workers, are at the highest risk of experiencing WPV, 4 times more likely than other healthcare professionals [2, 3]. China has also seen a significant increase in the incidence and number of workplace violence incidents against healthcare workers over the past decade [4, 5]. A study showed that 26.8 and 44.9% of healthcare workers experience physical and non-physical violence every year [6]. Nursing interns are not immune to workplace violence in clinical settings. Experiences of violence during clinical placements can directly affect the learning and performance of nurse interns, causing them to be less efficient and productive, to stop participating in nursing programs, or even to leave the profession altogether [7]. Internships are an essential way for nursing students to gain clinical nursing experience and become qualified nurses [8]. Given the harm and severity of workplace violence, there is an urgent need to comprehensively assess the situation of WPV among nurse interns and its consequences to provide more effective evidence for the development of targeted interventions.
It is well known that workplace violence not only exposes individuals to safety risks but also carries a significant mental health burden. A large number of studies have revealed the tremendous impact of workplace violence on the physical and mental health of nursing interns, including individuals’ worry, depression, helplessness, despair, anger, sleep disruption, lowered self-esteem, reduced work motivation, and impaired interpersonal relationships [9]. As nursing interns are new to clinical work, their psychological regulation is unstable, and they are unable to recognize precursor phenomena or early warning signs of violence [10]. In addition to the direct physical harm that WPV can inflict on them, frequent experiences may lead to somatic and psychiatric symptoms in nursing interns [11]. Fear and anger were identified as the most prevalent psychological symptoms among nurses after experiencing violence, accompanied by negative emotions such as unfairness, worry, and guilt. Alarmingly, these symptoms, if not effectively alleviated and treated, will lead to more severe depression, cognitive difficulties, psychoactive substance abuse, and even suicidal behavior [1214].
Workplace deviance behavior (WDB) is an important issue in healthcare management. WDB refers to employees’ intentional violations of organizational norms, such as interpersonal conflict, passivity, absenteeism, and insults to coworkers [15, 16]. Research has shown that WPV is associated with WDB and that nurses who are subjected to violence may retaliate through WDB [17]. Affective Events Theory (AET) states that negative emotions can lead directly to undesirable behaviors such as tardiness, absenteeism, or arguing with coworkers [18]. These emotions may also change work behaviors by influencing attitudes [19]. Employees may feel stressed and frustrated after being exposed to violence and, in turn, adopt deviant behaviors such as intra-organizational aggression or retaliation to release stress [20].
More importantly, there is evidence that there may be some bidirectional associations between workplace violence, psychopathological symptoms, and workplace deviant behavior. On the one hand, exposure to workplace violence may increase the risk of workplace deviant behavior and promote the development of psychopathological symptoms [2123]. On the other hand, workplace deviant behavior may exacerbate psychopathological symptoms and expose individuals to renewed distress from workplace violence [24]. WPV triggers high arousal of negative emotions and aggressive responses, leading employees to engage in harmful behaviors toward colleagues or the organization [25, 26]. Conversely, deviant behaviors can lead to interpersonal anomalies and even long-term relationship disintegration. This relationship breakdown can cause adverse emotional, cognitive, and health outcomes, further triggering aggressive reactions in employees and creating a vicious cycle [27, 28].
However, despite the growing interest in the work environments of nursing interns and its impact on their well-being, there is still a lack of empirical evidence of broad patterns of associations between WPV, psychopathological symptoms, and WDB. In particular, limited attention has been paid to the dynamic interactions between them. This study aimed to examine the dynamic relationship between nursing interns’ experiences of workplace violence, workplace deviant behaviors, and psychopathological symptoms (e.g., depression, anxiety, anger, and sleep disturbance) through a network analysis approach, which is of greater practical value for the identification of intervention centers and the development of targeted interventions.

Methods

Participants

Generally, undergraduate nursing students in China must undertake a clinical internship during the fourth year of their undergraduate studies. The internship period usually lasts 10 months, and each intern is required to rotate through ten departments during the internship, one department per month [29]. Therefore, the inclusion criteria in our study were (1) Nursing students with three or more years of nursing program. (2) Clinical practicum of six months or more.

Instruments

Participants were asked about basic information. Survey instruments for basic individual information included age, gender, and household registration (from rural or urban) et al.
Workplace violence was measured using the Workplace Violence Scale (WVS), which was used to evaluate the frequency (type and frequency) of workplace violence experienced by survey respondents in the internship [30]. The scale consists of five entries: physical assault (PA), verbal assault (VA), threats (TH), verbal sexual harassment (VSH), and physical sexual harassment (PSH). Each entry was scored from 0, 1, 2–3, and ≥ 4 times in the order of 0–3 points. The total score ranges from 0 to 15, with higher total scores indicating a higher frequency of workplace violence. The Cronbach’s α for this scale was 0.728.
Deviant workplace behaviors was measured using the Chinese version of the Caregiver Occupational Deviant Behavior Scale based on Bennett and Robinson’s Workplace Deviant Behavior Scale [15, 31]. The scale contains 5 dimensions and 21 items: interpersonal behavioral deviations (IBD, 6 items), organizational behavioral deviations (OBD, 6 items), aggressive behavior toward organizational members (ABOM, 4 items), aggressive behavior toward service recipients (ABSR, 2 items), and labor discipline violations (LDV, 3 items). It is scored on a Likert 5 scale from 1 “never” to 5 “always”. The higher the score, the more serious the organizational deviant behavior. In this study, Cronbach’s α was 0.818.
Psychopathological symptoms was measured using the DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) [32]. The scale is a 13-symptom, 23-item self-report questionnaire that assesses psychopathological symptoms. The DSM-XC assesses the following clinical domains: depression (2 items), anger (1 item), mania (2 items), anxiety (3 items), somatic distress (Somatic)(2 items), suicidal ideation (Suicidal)(1 item), psychosis (2 items), sleep disturbance (Sleep)(1 item), memory (1 item), repetitive thoughts (Repetitive)(2 items), dissociation (1 item), substance use (Substance)(3 items), and personality functioning (Personality)(2 items). It is scored on a Likert 5 scale from 0 “not at all” to 4 “nearly every day”. The DSM-XC has good convergent validity with psychopathology measures (Bravo et al., 2018). In this study, the Cronbach’s alpha value was 0.963.

Data collection

Data were collected online between April to May 2024. We used data collection to create an online questionnaire using an online survey platform where participants could voluntarily fill out and submit the questionnaire online by accessing the questionnaire link via WeChat, QQ, or E-mail. On the first page of the electronic questionnaire, we described the purpose of the study, the procedures, and the privacy of the participants, who had the right to withdraw from the study at any time. Participant confidentiality was guaranteed throughout the survey. A total of 2,326 nurse interns were invited to participate in this survey; 113 questionnaires were excluded due to not meeting the criteria (questionnaires featuring highly consistent answers or obvious logical errors), and ultimately, 2,213 questionnaires were determined to be eligible and used for this analysis. Participants completed the Workplace Violence Scale (WVS), Caregiver Occupational Deviant Behavior Scale, and the DSM-XC online. All procedures followed relevant guidelines and regulations. Participants were not paid any fees.

Data analysis

Network analysis (NA) offers a novel approach to interpreting psychopathology, emphasizing the complexity and dynamics of the subject under study [33]. The approach places symptoms into a network of interconnected nodes and describes the relationships between symptoms. Based on the network’s centrality indicators (strength, excepted influence, closeness, and betweenness), core symptoms in this network structure are identified. Intervention in the core symptoms will not only provide greater relief from mental illness but will also favor the improvement of peripheral symptoms [33, 34]. This approach goes beyond traditional moderation and mediation studies and allows for exploring complex connections that are masked within and beyond different communities.
We first used SPSS software for the initial processing of the questionnaire, including demographic characteristics and the calculation of variables. We then performed network analysis of the variables using the bootnet and qgraph packages in R software [33, 34]. Firstly, we established the network structure and calculated the relationship between each node; then, we calculated the centrality index in this network and identified the key symptoms. Finally, we checked the stability of the centrality index using the Bootstrap method.

Results

Preliminary analysis

Firstly, we counted the demographic characteristics of the sample, in which the age of the sample ranged from 20 to 24 years with a mean value of 21.714 (± 1.031), the majority were female (93.945%), and 67.510% have rural household registration. The duration of the internship ranged from 6 to 12 months, with a mean internship duration of 8.873 (± 1.687) months.
In addition, we counted the prevalence of workplace violence and psychopathological symptoms, as shown in Table 1. Among them, in workplace violence, the item with the highest prevalence was VA (32.038%), followed by TH (10.303%), and the item with the lowest prevalence was PSH (7.682%). In psychopathological symptoms, the items with the highest prevalence were anxiety (38.500%), anger (35.337%), and depression (33.439%), and the lowest prevalence items were suicidal ideation (8.902%), substance use (7.411%), and psychosis (2.485%).
Table 1
Prevalence of workplace violence and psychopathological symptoms
Items
Mean
SD
Prevalence
 
PA
0.093
0.349
170(7.682%)
 
VA
0.444
0.717
709(32.038%)
Workplace Violence
TH
0.120
0.383
228(10.303%)
 
VSH
0.057
0.276
104(4.700%)
 
PSH
0.042
0.215
86(3.886%)
 
Depression
0.475
0.812
740(33.439%)
 
Anger
0.473
0.809
782(35.337%)
 
Mania
0.356
0.623
647(29.236%)
 
Anxiety
0.580
0.946
852(38.500%)
 
Somatic
0.240
0.582
393(17.759%)
 
Suicidal
0.122
0.422
197(8.902%)
Psychopathological Symptoms
Psychosis
0.034
0.222
55(2.485%)
Symptoms
Sleep
0.394
0.729
649(29.327%)
 
Memory
0.208
0.531
374(16.900%)
 
Repetitive
0.201
0.608
288(13.014%)
 
Dissociation
0.186
0.573
267(12.065%)
 
Personality
0.312
0.700
471(21.283%)
 
Substance
0.133
0.495
164(7.411%)

Network structure

Figure 1 shows the network of workplace violence, psychopathological symptoms, and deviant workplace behavior. The connecting lines between the nodes reflect their relationship; the thicker the line, the stronger the relationship between the nodes.
Regarding the basic characteristics of the final network, 147 of the 253 possible edges (58.103%) were non-zero, reflecting considerable inter-correlation between symptoms. Second, the top 5 strongest edges observed in the model were all within clusters (i.e., 2 edges for Workplace Violence, 2 edges for Psychopathological Symptoms, and 1 edge for deviant workplace behavior): VSH-PSH, PA-TI, Anger-Anxiety, IBD-OBD, and Depression-Anxiety (Fig. 1). Finally, the computation of the relationships between clusters shows that the five pairs of nodes with the strongest relationships are VA-Depression, VA-ABSR, Repetitive-ABOM, Anxiety-ABSR, and Personality-LDV.
Figure 2 shows the centrality indices of the nodes in the whole network structure. Commonly used centrality indices include strength, expected influence, closeness, and betweenness.
The Strength and expected influence are the sum of the weighted values of all connections associated with a node. Where Strength is a weighted sum of absolute values and expected influence contains positive and negative relationships. The greater the strength of a node, the more it is at the center of the network and the more critical it is to the network as a whole; Closeness is the sum of the distances from one node to all other nodes. This indicator emphasizes the proximity value of a node in the network; the greater the closeness, the closer the node is to all other nodes and the more centrally located it is. Betweenness refers to the degree to which a node is located in the shortest path between two connected nodes in the network. If a node acts as a “mediator,” the more times, the stronger the intermediary of this node; without this node, many two connected nodes will not be able to connect [33, 34].
As is shown in Fig. 2, the node with the highest strength, expected influence, and betweenness indices is “Anxiety,” and the node with the highest closeness index is “Depression.”

Stability analysis

We use a nonparametric bootstrap method to estimate the stability of edge weights between nodes. The result is shown in Fig. 3 (Left). The gray line is the Bootstrap sampling estimate, and the red line is the overall data estimate. The two lines overlap highly, meaning the edge weights obtained by Bootstrap samples approximate the edge weights estimated from the overall samples. So, the edge weights between nodes in our model are highly stable.
In addition, we use the Correlation stability coefficient (CS coefficient) to test the stability of the centrality index. The CS coefficient represents the maximum acceptable degree of sample reduction, and more than 0.5 is generally acceptable [33]. As Fig. 3 (Right) shown, the strength, expected influence, closeness, and betweenness index all showed excellent levels of stability, with every stability index being greater than 0.5.

Discussion

This study explored the network structure between workplace violence, psychopathology symptoms, and workplace deviant behaviors among Chinese nursing interns using network analysis. Findings suggest that workplace violence, workplace deviant behavior, and psychopathology represent interrelated domains with spatially continuous and interconnected nodes. While some studies have explored the relationships between these constructs using regression and structural equation modeling, network analysis allowed for analyzing the complex relationships inherent in these constructs. This study further demonstrates the effectiveness of the network perspective in elucidating the complex relationships between and interconnections of different symptoms. The findings may provide broader insights into preventing workplace deviant behaviors in caregivers and developing targeted interventions for psychopathological symptoms.
Regarding the strongest edges across clusters, the strongest correlations were demonstrated between VSH and the more severe PSH in the workplace violence cluster, Anger-Anxiety in the psychopathological symptoms cluster, and IBD-OBD in the workplace deviant behavior cluster. This finding appears to provide a fragmented picture of only a limited range of existing studies. This is despite the high prevalence (roughly between 37 and 72%) of sexual harassment (including verbal, physical, mental, and visual forms) and the harm it poses to nursing interns as a significant form of interpersonal violence reported in a large number of previous nursing studies [35, 36]. However, these studies did not consider associations between subsets of individual factors. The present study found that more severe types of PSH tended to be highly correlated with less severe VSH. Those repetitive and unwelcome intimacy issues or sexual remarks that occur at work may deteriorate into more severe physical harm or rape (PSH) [37]. Within the psychopathological symptoms cluster, Anger showed the strongest correlation with Anxiety. In general, Anger and Anxiety are the most prevalent psychological symptoms, and they are linked through a common physiological response to stress. Because irritability is characterized by a lowered anger threshold, it is a typical symptom of anxiety disorders [38, 39]. More severe expressions of anger (e.g., trait anger, internalized anger expressions), as well as prolonged experiences of anger, are associated with anxiety disorders independently of co-associations with other psychiatric disorders. Anger may be an essential emotion related to anxiety disorders [40]. Therefore, we can understand the strongest relationship between anger and anxiety. At the same time, symptoms such as depression, somatic, memory, mania, and sleep are more likely to accompany it. In addition, we found the strongest relationship between IBD-OBD within workplace deviant behavior. In previous studies, it is unclear whether employees tend toward organizational deviant behaviors, interpersonal deviant behaviors, or possibly both. However, in Chinese organizations with high power distance, committing deviant behaviors against the organization tends to be dangerous, and retaliation to superiors becomes difficult, making them more prone to deviant behaviors against colleagues around them [41]. When violence against nurses occurs in the workplace, one way in which predominantly female nurses show psychological resistance is by engaging in interpersonal transgressions [42], and transgressions may vary with severity, from minor transgressions (interpersonal) to more severe (organizational) transgressions [43].
Notably, the computation of nodal relationships revealed pairwise interactions between workplace violence, psychopathological symptoms, and workplace deviant behaviors that have been obscured in prior research. We identified some of the most highly correlated cross-cluster nodes as VA-Depression, VA-ABSR, Repetitive thoughts-ABOM, Anxiety-ABSR, and Personality functioning-LDV. This broad pattern of associations provides evidence of specificity between experiences of violence in the workplace and specific psychopathological symptoms and deviant behaviors. First, the strongest relationship was found between the VA and Depression nodes. This is consistent with previous findings that violence experienced by nurses often leads to depression [44, 45]. Regardless of the form of violence, it is a precursor to depression [46]. The most common form of workplace violence experienced by students during clinical training is verbal violence [47, 48]. Verbal violence is a form of emotional abuse designed to inflict intense humiliation, defamation, and fear on the exposed person, and in some ways, verbal violence can cause more harm than physical violence [49]. Because it is often difficult to recognize or define as a violent experience, verbal violence is often overlooked compared to physical violence. As practicing nursing interns are new to clinical work, their psychological regulation is unstable, and they are unable to recognize violence precursor phenomena or warning signs [3]. Most nursing interns show strong emotional reactions after experiencing verbal violence, which is a major factor in developing depression [46]. In addition, the relationship between VA and ABSR in the cluster of workplace deviant behaviors is also stronger. On the one hand, frequent exposure to VA is believed to reduce nursing interns' professional commitment and professional identity and create negative attitudes toward nursing, prompting them to reconsider whether or not to consider nursing as their intended career; on the other hand, VA-induced occupational stress and emotional exhaustion that leads to low level of quality of care for patients and nursing outcomes [50, 51].
Anxiety has the highest strength and expected influence on the whole network structure. This result suggests that Anxiety is the most central symptom in the entire network. Nursing administrators must pay close attention to Anxiety in practicum students and follow the development of the severity of mood-related symptoms. On the one hand, the internship stage is one of the most anxious periods for nursing students [52, 53]. Undergraduate nursing education in China requires students to complete a clinical internship lasting at least ten months [54]. The internship phase requires nursing students to face multiple pressures, such as academic research, employment, graduation, certification examinations, and the demands of clinical practice. At the same time, they worry about work-related errors due to inadequate preparation for internships [55]. On the other hand, nurses often describe WPV as a constant source of anxiety [56]. Anxiety serves as a normal physiological or psychological response to an external event, and this response can cause intense emotional states (tension, obsession, panic, and irritability) in individuals [57]. Most nurse practitioners tend to feel higher levels of anxiety after experiencing WPV, affecting nurses’ self-confidence in their work, which in turn can lead to an inability to respond effectively to workplace violence [58, 59].
In addition, closeness to centrality is an important indicator of the node’s characteristics, which affects other symptoms faster and is at the center of the whole network [34]. Based on the results of centrality analysis, the present study identified “Depression” as having the highest closeness to centrality, being at the center of the network, and being the most strongly associated with other symptoms. Depression is the most common mental health disorder today. The prevalence of depressive symptoms among nurses in China is 57.2%, and reducing the prevalence of depressive symptoms among nurses has become an urgent task for hospital administrators [46]. Therefore, the role of “Depression” in the symptom network should be emphasized to identify nursing interns who are in a depressed mood promptly. Professional training should focus more on how to effectively recognize depression in various stressful scenarios faced by nursing interns to block the pathway of other symptoms in the network preemptively.
Finally, the mediator centrality index (betweenness) suggests that anxiety symptoms are the central psychopathological node. This is consistent with the idea that anxiety plays an important role in the initiation of workplace violence as well as in the onset and course of workplace deviant behavior [60]. Anxiety is both a consequence of physical and non-physical violence and is the strongest predictor of workplace deviant behavior, especially aggressive behavior towards organizational members [61]. Based on the findings of this paper, effective interventions are necessary for nursing interns. Psychological interventions can positively influence an individual’s self-control and emotional regulation and negatively influence destructive deviance and promote work, task performance, and constructive behavior [6264]. For example, mindfulness-based cognitive therapy (MBCT), with the advantages of high compliance and significant efficacy, is widely used in the treatment of anxiety as well as depression [65]. It can hinder the potential adverse situational influences on an individual, positively affecting work, task, and safety performance and reducing destructive bias tendencies [66]. Nursing educators should enhance the psychological training of nurses by integrating positive thinking training into the teaching and learning process to encourage them to better cope with the complex challenges of their future work and life. Policymakers should establish a series of care and monitoring mechanisms to ensure that measures to promote the mental health of nurses are better implemented.

Conclusions

This study is the first to document the network structure of workplace violence, psychopathological symptoms, and workplace deviant behaviors in Chinese nursing interns. The results confirm some of the well-established findings in the field, with the top ten strongest borderline distributions observed in the model distributed across the scale structures, with the strongest preponderance between VSH-PSH. The present study identified “Depression” as being centrally located and most strongly associated with the other symptoms and “Anxiety” as being the most central symptom in the network and the most critical bridging symptom. These findings provide a more precise target for preventing and intervening in nursing interns -related symptoms.
Some limitations of this study deserve attention. First, because this was a cross-sectional study, it was not possible to determine causal relationships between the elements. Ongoing research should use longitudinal data over time to examine the relationship between workplace violence, psychopathic symptoms, and workplace deviant behavior. Second, participants may be at risk for recall bias, leading to inaccurate responses. Prospective cohort studies may reduce recall bias. Also, the incidence of workplace violence against nursing interns may be underestimated and underreported. Underreporting may be due to the acceptance of workplace violence as part of a nurse’s job, their fear of blame or retaliation, and fear of trouble for themselves if they report it. Third, the different identities of the perpetrators may have other impacts on the emotional and behavioral responses of nursing interns. Differences in outcomes between different perpetrators of violence (supervisors, colleagues, or patients) were not further analyzed in this study. Fourth, the study did not investigate variables, such as supervisors’ management styles of workplace violence and nurses’ strategies for coping with WPV, which may have implications for both workplace deviant behaviors and physical and mental health. Therefore, based on the above research limitations, we will consider them in further studies.

Acknowledgements

We would like to express our gratitude to all the participants who participated in the study.

Declarations

This study was approved by the Ethics Committee of Shengjing Hospital of China Medical University (Grant No. 2024PS1024K). All procedures followed relevant guidelines and regulations. Each participant signed an informed consent form before completing the questionnaire, and all data were anonymized to ensure the privacy and confidentiality of the participants.
Not applicable.

Competing interests

The authors declare no competing interests.

Declaration of competing interest

The authors of this study declare that they have no financial or commercial interests that could be perceived as a potential conflict of interest.
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Metadaten
Titel
Workplace violence, psychopathological symptoms, and deviant workplace behavior among nursing interns in China: a network analysis
verfasst von
Simeng Dong
Xinshu Shen
Tong Zhao
Rui Zeng
Min Chen
Publikationsdatum
01.12.2025
Verlag
BioMed Central
Erschienen in
BMC Nursing / Ausgabe 1/2025
Elektronische ISSN: 1472-6955
DOI
https://doi.org/10.1186/s12912-025-02771-0