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Patient mistreatment, emotional exhaustion and work-family conflict among nurses: a moderated mediation model of social sharing of negative work events and perceived organizational support

BMC Medical Education volume 24, Article number: 1041 (2024) Cite this article

Abstract

Background

Nursing literature suggested that patient mistreatment has significant impacts on nurses’ emotions and job burnout. Yet, further research is needed to understand the underlying mechanism and the spillover effect on nurses’ families. Leveraging the goal progress theory, this study aimed to examine the association between patient mistreatment, nurses’ emotional exhaustion, and work-family conflict, as well as the mediating role of social sharing of negative work events and the moderating role of perceived organizational support.

Methods

During the COVID-19 pandemic in China, a cross-sectional study was conducted with a sample of 1627 nurses from the Hematology Specialist Alliance of Chongqing from October to November 2022. Questionnaires were administered to measure patient mistreatment, perceived organizational support, social sharing of negative work events, emotional exhaustion, and work-family conflict. Hierarchical linear regression and conditional processes were used for statistical analyses.

Results

Patient mistreatment was positively associated with emotional exhaustion (β = 0.354, p < 0.001) and work-family conflict (β = 0.314, p < 0.001). Social sharing of negative work events played a partial mediating role in the relationship between patient mistreatment and emotional exhaustion (effect = 0.067, SE = 0.013), and work-family conflict (effect = 0.077, SE = 0.014). Moderated mediation analysis found that the mediation effect was stronger when the perceived organizational support was high.

Conclusion

Our findings reveal the amplifying effect of social sharing of negative work events on nurses’ emotional exhaustion and work-family conflict. Perceived organizational support strengthens the positive effect of patient mistreatment on the social sharing of negative work events, thus resulting in increased emotional exhaustion and work-family conflict. We also discuss practical implications, limitations, and directions for future research.

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Introduction

With the outbreak of COVID-19, workplace violence in medical organizations have intensified, putting tremendous pressure on healthcare workers [1, 2]. A survey of 522 Chinese nurses found that 55% of respondents had experienced workplace violence in the past 12 months, including verbal and physical aggression [3]. Workplace violence directly affected nurses’ job performance and organizational citizenship behavior [4, 5], reduced their quality of life [6], and increased their psychological distress and turnover intention [7, 8]. Among these, the behavior of patients and their families abusing nurses through insults, unreasonable demands, or physical attacks was described as patient mistreatment [9]. Previous research has confirmed that when nurses were mistreated by patients, they may experience persistent work meaninglessness, emotional exhaustion and depression [10,11,12], which further predicted their career withdrawal behavior and turnover intention [12].

Additionally, the negative impact of experiencing abuse from service users may spread from service providers to their families [13]. Research on customer mistreatment has shown that abusive stress events encountered by front-line service providers in the workplace can detrimentally affect their role performance in the family domain [14], consume additional resources, and lead to work-family conflict [15].

Some studies indicate that after experiencing negative events, individuals tend to share negative events with their families or friends to alleviate negative emotions [16, 17]. However, whether social sharing of negative work events can attenuate emotional exhaustion and reduce work-family conflict remains undetermined [18]. In this study, we examine the mediating effect of social sharing of negative work events between patient mistreatment and emotional exhaustion and work-family conflict.

One common solution for employees to address workplace violence was to seek organizational support [19, 20]. However, evidence from several studies suggested that organizational support didn’t mitigate the relationship between workplace violence and stress [21,22,23], suggesting that the benefit of organizational support is controversial. Thus, this study explores the moderating role of perceived organizational support (POS) in the effect of patient mistreatment on emotional exhaustion and work-family conflict via social sharing of negative work events.

It can be observed that existing literature on the functional mechanism of patient mistreatment and its spillover impact on nurses’ family domain remains rare and far from unanimous. Therefore, this study establishes and tests a theoretical model of the effects of patient mistreatment on nurses’ emotional exhaustion and work-family conflict and explores the underlying mechanism and boundary condition of this relationship. To be more specific, we aim to answer the following questions: Does patient mistreatment increase nurses’ emotional exhaustion and work-family conflict through social sharing of negative work events? Could perceived organizational support intensify the mediating effect of social sharing of negative work events?

Patient mistreatment, emotional exhaustion and work-family conflict

Similar to customer mistreatment, patient mistreatment occurs when nurses experience unfair interpersonal treatment from patients and their families, such as various forms of verbal attacks, including anger, cursing, shouting, and rudeness [24, 25]. Patient mistreatment adversely affects the quality of medical service and work performance of nurses, and imposes threats to their mental health. Previous studies have shown that employees exhibit negative emotions such as emotional dysregulation, declining morale, and post-traumatic stress disorder [7, 18, 26] when frequently or intensely exposed to interpersonal mistreatment. Negative job attitudes predict subsequent burnout, withdrawal, and service-destroying behaviors [27,28,29,30]. Drawing on the goal progress theory [31], we argue that patient mistreatment interrupts the service achievement process, and the failure of achieving service goals triggers a constantly cognitive rumination process that could result in continuous emotional exhaustion [32,33,34]. Research has also shown that individuals who experience customer abuse in the workplace may transfer their negative emotions to family members [14]. This causes the harmful effects of customer mistreatment to spread throughout the area of employees’ family life [35]. Hence, it can be expected that:

H1a.

Patient mistreatment is positively correlated with emotional exhaustion.

H1b.

Patient mistreatment is positively correlated with work-family conflict.

Patient mistreatment and social sharing of negative work events

Empirical evidence showed that individuals tend to share negative experiences with peers and friends in search of emotional support and to reduce burnout [18, 36], which may occur from a few hours to several months after the event. This kind of sharing of negative sentiments in a relatively trusted environment can be generalized as social sharing of negative work events [18]. The more frequently nurses experience mistreatment, the stronger their intentions of social sharing will grow. Accordingly, we propose the following hypothesis:

H2.

Patient mistreatment is positively correlated with social sharing of negative work events.

The mediating role of social sharing of negative work events

Social sharing involves confronting negative emotions and expressing them verbally in a safe environment [37]. However, social sharing of negative work events may be a maladaptive coping strategy that employees adopt when facing patient mistreatment, falling under the domain of social cognitive rumination [18, 38]. According to the goal progress theory, social sharing further promotes repetitive discussions or rehearsals of negative events [39]. It can engulf nurses in work rumination, affecting their subsequent work engagement [40]. Employees who are deeply immersed in negative work events for a long time may find it difficult to detach themselves from work and are unable to address the emotional needs generated by rumination [41]. Jeon (2021) also found that emotional rumination caused by work communication resulted in more emotional exhaustion [42]. Huang (2022) demonstrated that when peers engage in co-rumination due to negative events, it exacerbated working pressure, negative moods and psychological problems [43]. We believe that sharing negative events within a social context leads to a more negative view of patient mistreatment, thus aggravating emotional exhaustion after work [44] and causing further depletion of nurses’ cognitive and emotional resources [45].

Additionally, when employees focus on negative work events for extended periods, they invest a significant amount of time and energy into uncompleted work goals, thereby disrupting the time that could be allocated to family activities, often leading to disappointment and frustration for both employees and their families [46, 47]. It is documented that individuals subjected to severe customer mistreatment have fewer resources available to meet family needs, thereby increasing work-family conflict (WFC) [48]. The repetitive thinking triggered by negative work events makes it difficult for individuals to sufficiently engage in family roles, thus resulting in negative emotions spilling over from workplace into family life [14, 49,50,51,52]. Park and Kim (2019) also articulated that the harmful effects of customer mistreatment extended into the personal life domain [35]. Thus, we propose the following hypotheses:

H3a.

Social sharing of negative work events plays a mediating role between patient mistreatment and emotional exhaustion.

H3b.

Social sharing of negative work events plays a mediating role between patient mistreatment and work-family conflict.

The moderating role of perceived organizational support

Perceived organizational support refers to the overall perception of employees regarding the organization’s willingness to help them, value their contributions, and care about their overall well-being [53]. It is commonly believed to be helpful in dealing with the problems such as work frustration and burnout [54, 55]. POS meets the socio-emotional needs of respect, belonging, emotional support and recognition in the workplace [56], providing a safer and more trusted environment in which employees are more likely to share negative events with colleagues or peers [57]. We propose that:

H4. Perceived organizational support moderates the relationship between patient mistreatment and social sharing of negative work events, and this positive relationship is stronger when perceived organizational support is high (vs. low).

As elaborated in H3, patient mistreatment could be perceived by nurses as a failure of personal service goals, indicating that nurses have not successfully fulfilled their obligations and job requirements. This brings huge psychological and role pressure [58,59,60]. Perceived stress leads to negative emotional focus and cognitive rumination, which manifests as recursive thinking and sharing of negative work events, thus triggering job burnout [61]. Combining Hypotheses 1, 2, 3a, 3b and 4, we propose that the mediating effect of social sharing of negative work events will be moderated by perceived organizational support:

H5a. Perceived organizational support moderates the indirect influence of.

patient mistreatment on emotional exhaustion through social sharing of negative work events, and the indirect influence is stronger when the level of perceived organizational support is high (vs. low).

H5b. Perceived organizational support moderates the indirect influence of.

patient mistreatment on work-family conflict through social sharing of negative work events, and the indirect influence is stronger when the level of perceived organizational support is high (vs. low).

We summarize our conceptual model in Fig. 1.

Fig. 1
figure 1

Conceptual model

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Methods

Study design and setting

This study exploited a cross-sectional design to investigate the relationship between patient mistreatment, emotional exhaustion, and work-family conflict among Chinese nurses during the COVID-19 pandemic after the lockdown was imposed in mainland China. During the pandemic, our participants performed heavy work tasks and experienced psychological stress.

Participants and data collection

Collaborating with the Chongqing Hematology Specialist Alliance, we initiated a call for research on patient mistreatment and obtained a convenient sample. Clinical nurses were invited to participate in the survey through one-to-one contact. The inclusion criteria were as follows: (1) possession of a nursing practice license; (2) working as a clinical nurse; and (3) informed consent and voluntary participation. The exclusion criteria were as follows: (1) nurses with further education; (2) interns; (3) trainees; and (4) off-duty nurses (on leave, sick leave, or out for studying). To prevent COVID-19 risk, we used an online electronic questionnaire for ease of operation.

A small-scale pilot survey was conducted before the formal survey to ensure the rationality of questions and the accuracy of expressions. An anonymous cross-sectional online survey was conducted via the questionnaire website of Wenjuanxing (link: https://www.wjx.cn/) from October 9 to November 1, 2022. Finally, we obtained a sample of 1627 valid responses.

Measures

The measurement used was originally published in English; therefore, we adopted Brislin’s (1986) suggestion and translated the scale forward and backward to ensure Chinese equivalence and prevent semantic bias problems [62].

Patient mistreatment

We measured patient mistreatment using the 18 items developed by Wang et al. (2011) [63]. Some minor modifications were made to suit the hospital environment since the original scale was designed to assess customer mistreatment. Sample items included “Patients demanded special treatment” and “Patients took their bad temper out on you”. The respondents reported the frequency with which they had experienced mistreatment from their patients within the last three months. Each item was measured on a 5-point Likert scale (“0” = never and “4” = all of the time). The alpha coefficient was 0.95.

Social sharing of negative work events

We used the four items developed by Baranik et al. (2017) to capture the social sharing of negative work events [18]. Participants were asked how frequently they had talked about unpleasant things that had occurred at work in the past month with their lovers, family members, friends, and coworkers. Responses were recorded on a five-point scale (“0” = never and “4” = often). The Cronbach’s alpha coefficient was 0.86.

Emotional exhaustion

Emotional exhaustion was measured using the emotional exhaustion component of Maslach et al.‘s (2001) MBI scale [64], which consisted of nine items. Sample items included “I feel emotionally drained from my work.” Responses were made on a seven-point scale (“1” = never and “7” = every day). The alpha coefficient for this scale was 0.93.

Work-family conflict

Work-family conflict was measured using the five-item subscale of Netemeyer et al.’s (1996) [46]. A sample item is “The stress of my job makes it difficult for me to meet my family responsibilities.” Participants indicated their agreement with the items on a 7-point Likert scale (“1” = strongly disagree and “7” = strongly agree). The alpha coefficient for this scale was 0.94.

Perceived organizational support

We used the eight items developed by Shen and Benson (2016) to measure perceived organizational support [65]. Sample items included “My organization values my contributions to the organization” and “The organization really cares about my health and welfare.” Responses were recorded on a seven-point Likert scale (“0” = strongly disagree and “6” = strongly agree). The alpha coefficient for the entire scale was 0.90.

Control variables

Following previous studies [19, 20], we controlled for nurses’ gender, age, education, working years and position, all of which have been shown to possibly correlate with emotion exhaustion and work-family conflict. In addition, we controlled for marital status and children, two variables that may have an impact on work-family conflict [66, 67].

Statistical analysis

We used SPSS 25.0, Amos 23.0 and Mplus 8.5 for data analysis. Descriptive statistics were used to present the demographic characteristics of the sample. Pearson correlation analysis was used to explore the correlations among patient mistreatment, social sharing of negative work events, perceived organizational support, emotional exhaustion, and work-family conflict. Harman’s single factor analysis and the confirmatory factor analysis were used to investigate the common methods variance (CMV). In addition, we tested the hypotheses using hierarchical regression analysis, bootstrapping tests, and conditional process analysis (specifically, moderated mediation in this study).

Results

Characteristics of participants

The demographic characteristics of the participants are presented in Table 1. A total of 1627 nurses participated in the study, with a mean age of 31.3 years (SD = 6.0). Among them, 94.7% were female and 5.3% were male. The average number of working years was 9.3 (SD = 6.4). Most participants were married (62.6%) and had undergraduate degree (89.7%). 76.8% of participants were primary nurses. More than half of the participants had children (56.5%).

Table 1 Socio-demographic characteristics (N = 1627)
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Correlations among variables

Table 2 presents the means, standard deviations, and correlations of all the measured variables. First, the results indicated that patient mistreatment was positively correlated with social sharing of negative work events (r = 0.198, p < 0.01), emotional exhaustion (r = 0.361, p < 0.01) and work-family conflict (r = 0.316, p < 0.01), and negatively correlated with perceived organizational support (r=-0.319, p < 0.01). Furthermore, social sharing of negative work events, emotional exhaustion, and work-family conflict were all negatively correlated with perceived organizational support (r =-0.193, p < 0.01; r =-0.471, p < 0.01; r =-0.460, p < 0.01; respectively).

Table 2 Means, standard deviations (SD) and correlations
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We used the Harman single-factor test to assess the common method variance (CMV). Factor analysis shows that the first principal component explained 33.20% of total variance, suggesting that the same source bias is not severe in this study. Before testing our hypotheses, we conducted confirmatory factor analyses (CFA) to confirm the factor structure of our measurement model. As shown in Table 3, the proposed five-factor model fits the data better: χ2 = 2492.156, df = 831, Confirmatory Fit Index (CFI) = 0.971, Tucker-Lewis Index (TLI) = 0.970, and root-mean-square error of approximation (RMSEA) = 0.035. Thus, the distinctiveness of key constructs is supported [68].

Table 3 Confirmatory factor analyses
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Testing for the mediating effect

We used hierarchical regression and bootstrapping technique to test the mediation hypotheses. As shown in Table 4, patient mistreatment was positively associated with emotional exhaustion in Model 5 (β = 0.354, p < 0.001) and work-family conflict in Model 8 (β = 0.314, p < 0.001), thus supporting H1. The test for the mediating effect followed the recommended procedures by Baron and Kenny (1986) [69]. First, Model 2 indicated a positive correlation between patient mistreatment and social sharing of negative work events (β = 0.201, p < 0.001), supporting H2. Second, Model 6 and Model 9 indicated that social sharing of negative work events was positively associated with both emotional exhaustion (β = 0.199, p < 0.001) and work-family conflict (β = 0.206, p < 0.001). Finally, although patient mistreatment was still significantly associated with emotional exhaustion in Model 6 (β = 0.314, p < 0.001) and work-family conflict in Model 9 (β = 0.272, p < 0.001) after the introduction of mediation variables, the size of effects was slightly weakened, suggesting that there exists a partial mediation effect.

Table 4 Results of regression analyses
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We also calculated the indirect effects of patient mistreatment on two outcome variables via social sharing of negative work events and its 95% confidence interval, which was repeated 5000 times using bootstrapping technique. Bootstrapping is useful for testing indirect effects because it produces a repeated replacement sampling distribution of indirect effects rather than assuming a normal distribution (Preacher and Hayes, 2008) [70]. The results are presented in Table 5. Social sharing of negative work events significantly mediated the relationship between patient mistreatment and emotional exhaustion (estimate = 0.067, 95% CI = [0.043, 0.094]) and work-family conflict (estimate = 0.077, 95% CI = [0.050, 0.108]). Taken together, these results support H3a and H3b.

Table 5 Bootstrap test for mediating effect
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Testing for the moderated mediation effect

In our conceptual model, perceived organizational support was proposed to moderate the relationship between patient mistreatment, emotional exhaustion and work-family conflict via social sharing of negative work events. Following Aiken and West (1991), we mean-centered the variables used to form the interaction term [71]. As shown in the Model 3 of Table 4, the interaction between patient mistreatment and perceived organizational support was significantly correlated with social sharing of negative work events (β = 0.074, p < 0.01), supporting H4.

We used the Process plug-in to conduct a simple slope analysis [70, 72]; the results are shown in Table 6. The interaction patterns are shown in Fig. 2. The graph shows that when perceived organizational support was low (-1SD), patient mistreatment was positively correlated with social sharing of negative work events (simple slope = 0.156, p < 0.001), which was smaller than the coefficient when perceived organizational support was high (+ 1 SD) (simple slope = 0.338, p < 0.001).

Table 6 Simple slope analysis of moderating effect
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Fig. 2
figure 2

Moderating effect of POS on the relationship between patient mistreatment and social sharing of negative work events. Note PM = Patient Mistreatment; POS = Perceived Organizational Support; SS = Social Sharing of Negative Work Events

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Finally, we used Mplus 8.5 to examine the moderated mediating effects. The results in Table 7 show that the indirect effect of patient mistreatment on emotional exhaustion via social sharing of negative work events was positive and statistically significant when perceived organizational support was low (estimate = 0.029, 95% CI = [0.013, 0.047]) and high (estimate = 0.060, 95% CI = [0.035, 0.092]) There was a significant difference in indirect effects between high and low perceived organizational support (estimate = 0.037, 95% CI= [0.005, 0.074]), supporting H5a. Similarly, the indirect effect of patient mistreatment on work-family conflict via social sharing of negative work events was significant when perceived organizational support was low (estimate = 0.033,95% CI = [0.015, 0.055]) and high (estimate = 0.070, 95%CI = [0.039, 0.106]). The difference in indirect effects between high and low perceived organizational support was significant (estimate = 0.037, 95% CI= [0.005, 0.074]), supporting H5b.

Table 7 Conditional indirect effects
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In addition, we use the Johnson-Neyman method to depict continuous confidence intervals for indirect effects [73]. Figure 3 shows that the continuous intervals of indirect effect are greater than zero, and increasing with the perceived organization support. The higher the perceived organizational support, the stronger the effect of patient mistreatment on emotional exhaustion through social sharing of negative work events. Figure 4 shows similar pattern when work-family conflict is the outcome variable.

Fig. 3
figure 3

Conditional indirect effects of patient mistreatment on emotional exhaustion (via social sharing of negative work events) at different levels of perceived organizational support (POS)

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Fig. 4
figure 4

Conditional indirect effects of patient mistreatment on work-family conflict (via social sharing of negative work events) at different levels of perceived organizational support (POS)

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Discussion

Leveraging the goal progress theory, this study found that social sharing of negative work events mediated the relationship between patient mistreatment and work-family conflict and emotional exhaustion. The results of the moderated mediation analysis showed that the indirect effects of social sharing of negative events on the two outcomes caused by patient mistreatment were stronger among nurses with high (vs. low) perceived organizational support.

Our study contributes to the literature on the adverse consequences and negative emotions associated with patient mistreatment in several ways. Firstly, the research expands the scopes of literature on the outcomes of patient abuse by innovatively introducing the work-family conflict into the model. Previous research mainly focused on personal aspects directly related to work such as sleep quality, job satisfaction, and career withdrawal [27, 74, 75]. Our findings indicate that the boundary between work and family life is permeable, and negative emotions may flow from the work area into the family domain, causing certain conflicts.

Secondly, based on the goal progress theory [31], we explored the mediating role of social sharing of negative work events between patient mistreatment and negative outcomes, filling the research gap in this area. The social sharing of negative work events may be a maladaptive coping mechanism in stressful environments. It is a process of social cognitive rumination of service failure that challenges the self-concept of nurses and a typical manifestation of shared ruminative thinking that hinders the positive thinking at individual and/or team levels [34]. Our findings suggest that patient mistreatment, as a source of stress, produces a sufficiently long duration of negative emotions, which will be further amplified in the process of social sharing [40], eventually affecting the role conflict between work and family [43].

Thirdly, we incorporated perceived organizational support as a boundary condition and investigate its moderating role in the effects of patient mistreatment on emotional exhaustion and work-family conflict via social sharing of negative work events. The higher the perceived organizational support, the more likely employees were to experience severe rumination, resulting in further burnout. Perceived organizational support does not always produce positive outcomes [58] and in some circumstances it enhances the rumination of negative events, leading to greater occupational and psychological stress [61]. This finding enriches our understanding of the mechanism by which patient abuse affects nurses’ emotions and reactions in the context of the pandemic.

Limitations and future directions

This study has several limitations. First, our research was conducted in the context of the Confucian Chinese culture. Thus, Chinese nurses tend to show greater tolerance for patient mistreatment, since considering the overall interests of the organization is of great priority in a collective society. However, the same result may not hold for individualistic cultures. It is important to consider whether similar conclusions can be drawn in different cultural contexts.

Second, this cross-sectional study required nurses to recall patient mistreatment and negative emotions over previous months. Nurses’ subjective recall may have produced retrospective bias. Future research should use diary studies or experience-sampling techniques to record changes or fluctuations in patient mistreatment and nurses’ emotions over time.

Moreover, our findings supported the negative influences of the patient mistreatment. However, effective alleviations or remedies remained largely unexplored. It is highly recommended to study mindfulness interventions and other mechanisms to deal with patient mistreatment [74].

Practical implications

Previous research has indicated that patient mistreatment decreases frontline nurses’ job enthusiasm, thereby damaging job satisfaction and triggering withdrawal behaviors and dysfunction in the work-family domain [27, 44, 75]. This study shows that Chinese nurses suffer from emotional exhaustion and work-family conflict caused by patient mistreatment. Managers can employ certain techniques during recruitment to select individuals who are better equipped to handle patients’ incivility during frontline work [76, 77].

Moreover, managers can provide frontline staff with training and guidance, simulate scenarios of patient mistreatment, and improve their ability to address patient incivility [78]. At the meantime, managers should be careful with the polices regarding the social sharing within the organization. Too much exposure and immersion into the rumination of negative work events may deteriorate morale and cause personal and family problems. Additionally, medical professionals should be encouraged to have a positive mindset and demonstrate empathy and compassion towards patients while providing medical services to minimize unnecessary conflicts [22, 79,80,81].

Furthermore, hospital managers can establish eye-catching signs and indicators to guide patients to behave correctly and maintain a civilized manner throughout the treatment process. Society should collaborate with hospitals to create an appropriate medical environment for all patients by encouraging them and their families to take respectful and responsible actions, which will help nurses improve their work efficiency [82].

Conclusion

This study provides empirical evidence that patient mistreatment causes nurses’ emotional exhaustion and work-family conflict through the social sharing of negative work events. The findings of this study enrich the understanding of the mediating mechanism of patient mistreatment affecting nurses’ emotions and work-family conflict. We also reveal how perceived organizational support, as a moderating variable, enhances the positive relationship between patient mistreatment and the social sharing of negative work events and highlight that organizational support could result in greater psychological stress and family-related conflicts induced by patient mistreatment and mediated by social sharing of negative work events. Therefore, to effectively deal with patient mistreatment, hospital managers should provide training and other resources to nurses, help them regulate their negative emotions, and achieve a balance between work and family. Finally, patients should be educated to receive medical services in a civilized manner.

Data availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. We affirm that the methods used in the data analyses are suitably applied to our data within our study design and context, and the statistical findings have been implemented and interpreted correctly.

References

  1. Molero Jurado MDM, Gázquez Linares JJ, Pérez-Fuentes MDC. Martos Martínez Á. Aggression and burnout in nurses during COVID-19: a cross-sectional study. Nurs Health Sci. 2023;25(1):130–40.

    Article  Google Scholar 

  2. Nam S, Wong JYH, Wang T, An B, Fong DYT. Psychological distress as a mediator between workplace violence and turnover intention with caring for patients with COVID-19. Front Psychol. 2024;14:1321957.

    Article  Google Scholar 

  3. Huang S, Zhai J, Lu X, Liang Y, Li Q, Lilenga HS. Prevalence of workplace violence in Chinese obstetric nurses under the new situation and its correlation with violence prevention knowledge-attitude-practice and climate perception: a cross-sectional study. BMC Nurs. 2023;22(1):473.

    Article  Google Scholar 

  4. Duan X, Ni X, Shi L, Zhang L, Ye Y, Mu H, Li Z, Liu X, Fan L, Wang Y. The impact of workplace violence on job satisfaction, job burnout, and turnover intention: the mediating role of social support. Health Qual Life Outcomes. 2019;17:93.

    Article  Google Scholar 

  5. Ferri P, Stifani S, Accoto A, et al. Violence against nurses in the triage area: a mixed-methods study. J Emerg Nurs. 2020;46:384–97.

    Article  Google Scholar 

  6. Choi SH, Lee H. Workplace violence against nurses in Korea and its impact on professional quality of life and turnover intention. J Nurs Manag. 2017;25:508–18.

    Article  Google Scholar 

  7. Hong S, Nam S, Wong JYH, Kim H. Post-traumatic responses to workplace violence among nursing professionals: a collaborative and comparative study in South Korea and Hong Kong. BMC Nurs. 2023;22:354.

    Article  Google Scholar 

  8. Chowdhury SR, Kabir H, Das DC, Chowdhury MR, Chowdhury MR, Hossain A. Workplace violence against Bangladeshi registered nurses: a survey following a year of the COVID-19 pandemic. Int Nurs Rev. 2023;70:219–28.

    Article  Google Scholar 

  9. Bies RJ. Interactional (in)justice: The sacred and the profane. In Advances in Organizational Behavior (J. Greenberg & R. Cropanzano, eds.), 2001;89 – 11. Stanford University Press, Stanford, CA.

  10. Qi L, Wei X, Li Y, Liu B, Xu Z. The influence of mistreatment by patients on job satisfaction and turnover intention among Chinese nurses: A Three-Wave Survey. Int J Environ Res Public Health. 2020;17:1256.

    Article  Google Scholar 

  11. Jang SJ, Son YJ, Lee H. Prevalence, associated factors and adverse outcomes of workplace violence towards nurses in psychiatric settings: a systematic review. Int J Ment Health Nurs. 2022;31:450–68.

    Article  Google Scholar 

  12. Yan W, Bao N, Zheng S, Wang H, Yue D, Chen L. The impacts of patient mistreatment on healthcare workers’ role behaviors: a study in Chinese Fangcang shelter hospitals. BMC Nurs. 2023;22:444.

    Article  Google Scholar 

  13. Greenbaum RL, Quade MJ, Mawritz MB, Kim J, Crosby D. When the customer is unethical: the explanatory role of employee emotional exhaustion onto work-family conflict, relationship conflict with coworkers, and job neglect. J Appl Psychol. 2014;99:1188–203.

    Article  Google Scholar 

  14. Chi NW, Yang J, Lin CY. Service workers’ chain reactions to daily customer mistreatment: behavioral linkages, mechanisms, and boundary conditions. J Occup Health Psychol. 2018;23:58–70.

    Article  Google Scholar 

  15. Sarwar A, Imran MK, Hafeez H, Zaheer M, Fatima T. Does workplace ostracism negatively affect family life during a pandemic? Pers Rev. 2024;53(4):900-917.

  16. Egloff B. You are not alone - social sharing as a necessary addition to the embracing factor. Behav Brain Sci. 2017;40:e358.

    Article  Google Scholar 

  17. Spencer L. Social sharing of negative emotional events: whether or not sharing helps depends on the Listener’s response. The Pennsylvania State University; 2019.

  18. Baranik LE, Wang M, Gong Y, Shi. Customer mistreatment, employee health, and job performance: cognitive rumination and social sharing as mediating mechanisms. J Manage. 2017;43:1261–82.

    Google Scholar 

  19. Yeh T, Chang Y, Hsu YH, Huang L, Yang C. Causes of nursing staff burnout: exploring the effects of emotional exhaustion, work-family conflict, and supervisor support. Jpn J Nurs Sci. 2021;18(2):e12392.

  20. Cakal H, Keshavarzi S, Ruhani A, Dakhil-Abbasi G. Workplace violence and turnover intentions among nurses: the moderating roles of invulnerability and organisational support - A cross-sectional study. J Clin Nurs. 2021;00:1–11.

  21. Kim J. The moderating effect of social support on the relationship between violence experiences and violence responses of psychiatric nurses. J Korean Acad Psychiatr Ment Health Nurs. 2019;28(2):144.

    Article  Google Scholar 

  22. Yeh TF, Chang YC, Feng WH, Sclerosis M, Yang CC. Effect of workplace violence on turnover intention: the mediating roles of job control, psychological demands, and social support. Inquiry. 2020;57:46958020969313.

    Google Scholar 

  23. Shahrour G, Taha I, Ali AM, Alibrahim M. The moderating role of social support on workplace violence and stress among psychiatric nurses. Nurs Forum. 2022;57:1281–8.

    Article  Google Scholar 

  24. Grandey AA, Foo SC, Groth M, Goodwin RE. Free to be you and me: a climate of authenticity alleviates burnout from emotional labor. J Occup Health Psych. 2012;17:1–14.

    Article  Google Scholar 

  25. Koopmann J, Wang M, Liu Y, Song Y. Customer mistreatment: a review of conceptualizations and a multilevel theoretical model. Mistreatment Organ. 2015;13:33–79.

    Article  Google Scholar 

  26. Baranik LE, Zhu Y, Wang M, Zhuang W. When does witnessing patient mistreatment hurt nurses’ performance? Gauging the moderation roles of self-concern and other-orientation. J Manage Psychol. 2022;37:170–85.

    Article  Google Scholar 

  27. Cai D, Li F, Feng T, Liu B, Qi L, Men C. Mistreatment from patients and nurses’ career withdrawal intention: does political skill matter? Asia Pac J Hum Resou. 2022;60:342–61.

    Article  Google Scholar 

  28. Goussinsky R. The combined moderating effects of coworker support and occupational coping self-efficacy on the relationship between patients mistreatment and burnout. J Aggress Maltreat T. 2020;29:479–97.

    Article  Google Scholar 

  29. Garcia PRJM, Restubog SLD, Lu VN, et al. Attributions of blame for customer mistreatment: implications for employees’ service performance and customers’ negative word of mouth. J Vocat Behav. 2019;110:203–13.

    Article  Google Scholar 

  30. Kim S, Kitzmiller R, Baernholdt M, Lynn MR, Jones CB. Patient safety culture: the impact on workplace violence and health worker burnout. Workplace Health Saf. 2023;71:78–88.

    Article  Google Scholar 

  31. Martin LL, Tesser A. Toward a motivational and structural theory of ruminative thought. In: Uleman JS, Bargh JA, editors. Unintended thought. New York: Guilford Press; 1989. pp. 306–26.

    Google Scholar 

  32. Arnold KA, Walsh MM. Customer incivility and employee well-being: testing the moderating effects of meaning, perspective taking and transformational leadership. Work Stress. 2015;29:362–78.

    Article  Google Scholar 

  33. Jiang FB, Wang Z. Applications of cognitive appraisal theory of tress in managerial psychology research: scenes, methods, and myths. Adv Psychol Sci. 2022;30:2825–45.

    Article  Google Scholar 

  34. Haggard DL, Robert C, Rose AJ. Co-rumination in the workplace: adjustment trade-offs for men and women who engage in excessive discussions of workplace problems. J Bus Psychol. 2011;26:27–40.

    Article  Google Scholar 

  35. Park YA, Kim S. Customer mistreatment harms nightly sleep and next-morning recovery: job control and recovery self-efficacy as cross-level moderators. J Occup Health Psychol. 2019;24:256–69.

    Article  Google Scholar 

  36. McCance AS, Nye CD, Wang L, Jones KS, Chiu C. Alleviating the burden of emotional labor: the role of social sharing. J Manage. 2013;39(2):392–415.

    Google Scholar 

  37. Zhan Y, Wang M, Shi J. Lagged influences of customer mistreatment on employee mood: moderating roles of maladaptive emotion regulation strategies. In: Ashkanasy, N.M., Zerbe, W.J., Härtel, C.E.J, editors. Research On Emotion in Organizations. Emerald Group, Bingley, UK. 2013;9:203–224. Further Reading.

  38. Brown SP, Westbrook RA, Challagalla G. Good cope, bad cope: adaptive and maladaptive coping strategies following a critical negative work event. J Appl Psychol. 2005;90:792–8.

    Article  Google Scholar 

  39. Nolen-Hoeksema S. Emotion regulation and psychopathology: the role of gender. Annu Rev Clin Psycho. 2012;8:161–87.

    Article  Google Scholar 

  40. Wang HJ, Li PK, Bauer TN, Erdogan B. Patient mistreatment and new nurse adjustment: the role of rumination and work engagement. Hum Relat. 2023;0.

  41. Geisler M, Buratti S, Allwood CM. The complex interplay between emotion regulation and work rumination on exhaustion. Front Psychol. 2019;10.

  42. Jeon YJJ. The effects of after-working hours work contact through information and communication technology on emotional rumination, work-family conflict, and emotional exhaustion: a study of hotel and duty-free employees. J Tou Leis Res. 2021;33:407–23.

    Article  Google Scholar 

  43. Huang YY, Bullock A, Liu J, Wang ZX, Xu G, Sang B. Co-rumination with friends exacerbates association between peer victimization and adjustment in adolescence. J Appl Dev Psychol. 2022;80:101410.

    Article  Google Scholar 

  44. Shi X, Wang X. Daily spillover from home to work: the role of workplace mindfulness and daily customer mistreatment. Int J Contemp Hosp M. 2022;34:3008–28.

    Article  Google Scholar 

  45. Knipfer K, Kump B. Collective rumination: when ‘problem talk’ impairs organizational resilience. Appl Psychol-Int Rev. 2022;71:154–73.

    Article  Google Scholar 

  46. Netemeyer RG, Boles JS. Development and validation of work-family conflict and family-work conflict scales. J Appl Psychol. 1996;81:400–10.

    Article  Google Scholar 

  47. Huyghebaert-Zouaghi T, Morin AJS, Fernet C, Austin S, Gillet N. Longitudinal profiles of work-family interface: their individual and organizational predictors, personal and work outcomes, and implications for onsite and remote workers. J Vocat Behav. 2022;134:103695.

    Article  Google Scholar 

  48. He Y, Walker JM, Payne SC, Miner KN. Explaining the negative impact of workplace incivility on work and non-work outcomes: the roles of negative rumination and organizational support. Stress Health. 2021;37:297–309.

    Article  Google Scholar 

  49. Junker NM, Baumeister RF, Straub K, Greenhaus JH. When forgetting what happened at work matters: the role of affective rumination, problem-solving pondering, and self-control in work-family conflict and enrichment. J Appl Psychol. 2021;106:1750–66.

    Article  Google Scholar 

  50. Gillet N, Austin S, Huyghebaert-Zouaghi T, Fernet C, Morin AJS. Colleagues’ norms regarding work-related messages: their differential effects among remote and onsite workers. Pers Rev. 2022;53:173–92.

    Article  Google Scholar 

  51. Zhang R, W YQ, Ferreira-Meyers K. The work-family spillover effects of customer mistreatment for service employees: the moderating roles of psychological detachment and leader-member exchange. Front Psychol 2019;10.

  52. Karakurt N, Erden Y, Çelik AS. The relationship between nurses’ work stress levels and work-family conflict during the COVID-19 pandemic and the affecting factors: a study from Turkey. Arch Psychiat Nurs. 2023;42:61–7.

    Article  Google Scholar 

  53. Eisenberger R, Wen X, Zheng D, Yu J, Liu Z, Zhang J, Wang L, Kim TY, Krivacek S, Zagenczyk TJ, Joo MK, Mesdaghinia S, Lee DR, Kim TH. Does felt obligation or gratitude better explain the relationship between perceived organizational support and outcomes? Group Organ Manage. 2023;0.

  54. Yanbei R, Dongdong M, Yun L, et al. Does perceived organization support moderates the relationships between work frustration and burnout among intensive care unit nurses? A cross-sectional survey. BMC Nurs. 2023;22:22.

    Article  Google Scholar 

  55. Bobbio A, Manganelli AM. Antecedents of hospital nurses’ intention to leave the organization: a cross sectional survey. Int J Nurs Stud. 2015;52(7):1180–92.

    Article  Google Scholar 

  56. Baran B, Rhoades L, Miller L. Advancing perceived organizational support theory into the twenty-first century world of work. J Bus Psychol. 2012;27:123–47.

    Article  Google Scholar 

  57. Hngoi CL, Abdullah NA, Sulaiman WSW, Nor NIZ. Examining job involvement and perceived organizational support toward organizational commitment: job insecurity as mediator. Front Psychol. 2024;15.

  58. Pecino V, Mañas MA, Díaz-Fúnez PA, Aguilar-Parra JM, Padilla-Góngora D, López-Liria R. Organisational climate, role stress, and public employees’ job satisfaction. Int J Environ Res Public Health. 2019;16:1792.

    Article  Google Scholar 

  59. Keller EG, Hittle BM, Boch S, Davis K, Gillespie GL. Modeling wellbeing for U.S. correctional nurses: a cross sectional survey. Int J Nurs Stud. 2023;147:104589.

    Article  Google Scholar 

  60. Zhang J, Liu F, Smith AP. Exploring the relationship between work stress and work-related rumination. Psychol Rep. 2023;0(0).

  61. Weigelt O, Gierer P, Syrek CJ. My mind is working overtime-towards an integrative perspective of psychological detachment, work-related rumination, and work reflection. Int J Environ Res Public Health. 2019;16:2987.

    Article  Google Scholar 

  62. Brislin RW. The wording and translation of research instruments. In: Lonner WL, Berry JW, editors. Cross-cultural research and Methodology Series. Thousand Oaks, CA: Sage; 1986. pp. 137–64.

    Google Scholar 

  63. Wang M, Liao H, Zhan Y, Shi J. Daily customer mistreatment and employee sabotage against customers: examining emotion and resource perspectives. Acad Manage J. 2011;54:312–34.

    Article  Google Scholar 

  64. Maslach CA, Schaufeli WB, Leiter MP. Job burnout. Annu Rev Psychol. 2001;52:397–422.

    Article  Google Scholar 

  65. Shen J, Benson J. When CSR is a social norm: how socially responsible human resource management affects employee work behavior. J Manage. 2016;42:1723–46.

    Google Scholar 

  66. Nixon AE, Yang LQ, Zhang XC. Emotional labor in China: do perceived organizational support and gender moderate the process? Stress Health. 2011;27(4):289–305.

    Article  Google Scholar 

  67. Labrague LJ, Ballad CA, Fronda DC. Predictors and outcomes of work-family conflict among nurses. Int Nurs Rev. 2021;68(3):349–57.

    Article  Google Scholar 

  68. Feng TW, Huang YF, Avgerinos E. When marketing and manufacturing departments integrate: the influences of market newness and competitive intensity. Ind Market Manag. 2018;75:218–31.

    Article  Google Scholar 

  69. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51:1173–82.

    Article  Google Scholar 

  70. Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods. 2008;40:879–91.

    Article  Google Scholar 

  71. Aiken LS, West SG. Multiple regression: testing and interpreting interactions. Thousand Oaks, CA, US: Sage; 1991.

    Google Scholar 

  72. Edwards JR, Lambert LS. Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. Psychol Methods. 2007;12:1–22.

    Article  Google Scholar 

  73. Hayes AF. An index and test of linear moderated mediation. Multivar Behav Res. 2015;50:1–22.

    Article  Google Scholar 

  74. Yun M, Beehr T. When experiencing nice interactions at work: good sleep quality via well-being. Stress Health. 2024;40:e3390.

  75. Karaeminogullari A, Erdogan B, Bauer TN. Biting the hand that heals: mistreatment by patients and the well-being of healthcare workers. Pers Rev. 2018;47:572–91.

    Article  Google Scholar 

  76. Carlson D, Ferguson M, Hunter E, Whitten D. Abusive supervision and work-family conflict: the path through emotional labor and burnout. Leadersh Quart. 2012;23:849–59.

    Article  Google Scholar 

  77. Giusti EM, Pedroli E, D’Aniello GE, Badiale CS, Pietrabissa G, Manna C, Badiale MS, Riva G, Castelnuovo G, Molinari E. The psychological impact of the COVID-19 outbreak on health professionals: a cross-sectional study. Front Psychol. 2020;11:1684.

    Article  Google Scholar 

  78. Li S, Yan H, Qiao S, Chang X. Prevalence, influencing factors and adverse consequences of workplace violence against nurses in China: a cross-sectional study. J Nurs Manag. 2022;30:1801–10.

    Article  Google Scholar 

  79. Hannemann J, Abdalrahman A, Erim Y, Morawa E, Jerg-Bretzke L, Beschoner P, Geiser F, Hiebel N, Weidner K, Steudte-Schmiedgen S, Albus C. The impact of the COVID-19 pandemic on the mental health of medical staff considering the interplay of pandemic burden and psychosocial resources-A rapid systematic review. PLoS ONE. 2022;17:e0264290.

    Article  Google Scholar 

  80. Wieckowski AG. The emotional toll of frontline labor. Harv Bus Rev. 2023;2:48–50.

    Google Scholar 

  81. Mahoney DA, Gopisetty D, Osterberg L, Nudelman MJR, Smith-Coggins R. Patient mistreatment of health care professionals. BMC Med Educ. 2022;22:133.

    Article  Google Scholar 

  82. van Jaarsveld DD, Walker DD, Kim S. Encouraging good behavior from your customers. Harv Bus Rev. 2023;2:56–8.

    Google Scholar 

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Acknowledgements

We would like to thank all nurse participants and Zhang Yong, Li Hua, Ma Li, and Wee Chow Hou for their helpful comments as well as the seminar participants at Chongqing University, Peking University, and Nanyang Technological University.

Funding

This study was supported by the National Social Science Foundation of China (Grant number: 19BJY052, 22BGL141), National Natural Science Foundation of China (Grant number: 72110107002, 71974021), Natural Science Foundation of Chongqing (Grant number: cstc2021jcyj-msxmX0689), Fundamental Research Funds for the Central Universities (Grant number: 2022CDJSKJC14), and Chongqing Social Science Planning Project (Grant number: 2018PY76).

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Authors and Affiliations

  1. School of Economics and Business Administration, Chongqing University, Chongqing, China

    Wei Yan & Zeqing Cheng

  2. Medical Insurance Office, Hospital of Chongqing University, Chongqing, China

    Di Xiao

  3. School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, 430000, China

    Huan Wang

  4. Development and Planning Department, Chongqing Medical University, Chongqing, 400000, China

    Huan Wang

  5. Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, The Second Affiliated Hospital of Army Medical University, Chongqing, China

    Xin Du

  6. Human Resources Department, The Second Affiliate Hospital of Chongqing Medical University, No.74 Linjiang Road, Yuzhong District, Chongqing, China

    Li Li

  7. President Office, The Second Affiliated Hospital of Army Medical University, No. 83 Xinqiao Main Street, Shapingba District, Chongqing, China

    Caiping Song

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  1. Wei Yan
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Contributions

Wei Yan and Zeqing Cheng designed the study and prepared the first draft of this manuscript. Di Xiao and Xin Du participated in the data analysis. Huan Wang contributed to writing and revising the manuscript. Li Li and Caiping Song contributed to data collection and analysis. All the authors have read and approved the final version of the manuscript.

Corresponding authors

Correspondence to Li Li or Caiping Song.

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Ethical approval

Ethical approval was obtained from the Ethics Committee of the School of Economics and Business Administration of Chongqing University (IRB No. SEBA201906). Authors explained research objectives and procedures to all participants who were assured that their participation in this study was voluntary and anonymous. All procedures performed in this study were in accordance with the ethical standards of the National Research Council and Helsinki Declaration of 2013. Informed consent was obtained from all subjects and/or their legal guardian(s).

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The authors declare no competing interests.

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Yan, W., Cheng, Z., Xiao, D. et al. Patient mistreatment, emotional exhaustion and work-family conflict among nurses: a moderated mediation model of social sharing of negative work events and perceived organizational support. BMC Med Educ 24, 1041 (2024). https://doi.org/10.1186/s12909-024-06022-9

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BMC Medical Education

ISSN: 1472-6920

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