Abstract

Aim

This study investigates the relationship between fear of workplace violence and life satisfaction among healthcare workers and evaluates the potential mediating role of psychological resilience in this relationship.

Materials and Methods

A cross-sectional design was employed with 173 healthcare workers at Balıkesir University Faculty of Medicine Hospital, recruited via convenience sampling between March 15, 2024, and April 15, 2025. Data were collected using the Fear of Workplace Violence, Psychological Resilience, and Life Satisfaction scales. Mediation analysis was conducted using PROCESS Macro v5.0 (Model 4) with 5,000 bootstrap samples and a 95% confidence interval. Gender, age, professional experience, education, marital status, and prior exposure to violence were included as control variables.

Results

Approximately 24.3% of participants reported previous exposure to violence. Correlational analyses indicated that fear of workplace violence was significantly and negatively associated with both psychological resilience (r=-0.382, p<0.001) and life satisfaction (r=-0.437, p<0.001), whereas psychological resilience was positively associated with life satisfaction (r=0.262, p< 0.01). In the mediation model, fear of violence significantly predicted lower psychological resilience B=-0.319) and had a strong direct adverse effect on life satisfaction (B=-0.517). The overall model explained 36.3% of the variance in life satisfaction (R²=0.363).

Conclusion

Fear of workplace violence is a significant predictor of reduced life satisfaction; this association remains robust after controlling for sociodemographic factors and prior victimization. Notably, psychological resilience did not mediate this relationship within this sample. These findings suggest that individual-level interventions alone are insufficient; organizational strategies must prioritize reducing the perceived risk and fear of violence to protect healthcare workers’ well-being.

Introduction

The field of healthcare services is one in which employees frequently encounter security threats and psychosocial stressors due to high workloads, shift work, and ongoing interactions with patients and their relatives. In this context, workplace violence is considered a significant occupational risk that affects employees’ sense of security, functioning, and psychological well-being, extending beyond the incident itself. In explaining the negative consequences of violence, not only the presence of exposure but also the cognitive and affective processes following exposure are decisive; it is emphasized that the fear of experiencing violence in the workplace may be a central mechanism in revealing the effects of violence experiences on health and work outcomes (1). It has been reported that fear is a multidimensional experience comprising components of worry and perceived risk, and that it is a distinct stressor in environments characterized by intense, often unpredictable interactions, such as healthcare, where it is associated with psychological well-being (2).

Indeed, in the study by Demirbaş et al. (3), 87.8% of healthcare workers reported exposure to verbal violence and 17.8% to physical violence. It was shown that the perception that the spread of violent content on social media could increase violence was widespread, and that the “code white” application was widely used. These findings support the notion that the fear of violence (FV) should be considered not only as an individual exposure but also as a risk perception sustained by the institutional security climate and visible prevention/response mechanisms. Similarly, Tekin and Selcen (4) five-year review covering 2018-2022 indicates that attacks on healthcare services totaled 3,980 incidents, with 2,697 injuries and 1,095 deaths reported. The study also emphasized that the impact of attacks extends beyond the moment of the incident, disrupting access to healthcare services and leading to secondary losses; therefore, it drew attention to the need for well-structured and functional reporting/recording systems (4).

Life satisfaction (LS), one of the core cognitive indicators of subjective well-being, refers to an individual’s assessment of their quality of life through a general and cognitive evaluation process (5, 6). LS is a relatively stable outcome shaped by the interaction of internal resources and external conditions (7-10). Within this framework, the fear of experiencing violence, which creates a persistent perception of threat, is expected to negatively affect LS. Psychological resilience (PR), as a dynamic and developable adaptive capacity, can play a mediating and/or buffering role in stress-health processes (11-15).

However, in the literature, studies focusing on fear of future workplace violence (FFVW) have mainly concentrated on clinical distress indicators such as depressive symptoms, anxiety, sleep problems, and burnout. There is limited testing of its reflection on a more general subjective well-being outcome, such as LS, and of the mediating role of resilience in this relationship, in a comprehensive manner (15-18). Therefore, this study aims to examine the relationship between fear of workplace violence and LS among healthcare workers, and to test whether PR mediates this relationship.

Conceptual Framework

Fear of Workplace Violence

Fear of workplace violence refers to the cognitive and emotional response triggered by an employee’s assessment of the likelihood of experiencing violence in the future, independent of any actual violent incident. This construct is considered one of the fundamental psychological processes explaining how exposure to violence translates into individual and organizational outcomes (1). Fear cannot be reduced to a mere momentary emotional state; it is defined as a multidimensional experience comprising worry about the future and perceived risk, which shape how employees interpret security threats in the work environment (2). Particularly in service contexts such as healthcare, where interaction intensity is high and unpredictability is pronounced, the “fear of FFVW” can function as a functional stressor, with significant effects on perceived safety and psychological well-being (18, 19).

The level of FFVW is related both to individual exposure patterns and to objective and perceived risk conditions in the working context. In addition to direct exposure to physical or verbal violence, indirect forms of exposure, such as witnessing violence or learning about incidents involving colleagues, can also trigger similar fear responses and be associated with functional impairment (20, 21). At the demographic and occupational level, findings indicate that female employees and younger staff report higher levels of fear; in the healthcare sector, both the risk of violence and fear are higher compared to industrial settings (16, 20, 22). Organizational conditions are also decisive: perceptions of organizational justice, adequacy of safety measures, and management support shape the intensity of fear. While perceived inadequacy of violence prevention policies may increase fear, perceived prevention and protective practices have been reported to reduce fear (23).

The analytical value of FFVW extends beyond a mere “consequence of exposure”; it also functions as a transmission mechanism mediating the effects of violence-related experiences on health and work outcomes. Early findings suggest that the fear and insecurity following exposure may impair mental health and performance more directly than the event itself (1). Current studies indicate that FFVW along with stress processes such as burnout in some models can partially or fully mediate the relationship between exposure to violence and depressive symptoms (15). Similarly, fear has been reported as one of the key explanatory pathways linking violence to reduced work ability (21). Furthermore, FFVW has been strongly associated with depressive symptoms, anxiety, and impaired sleep quality (17, 18) and has been linked to burnout processes over time through the depletion of psychological resources under perceived threat (16). At the organizational level, it has been linked to decreased job satisfaction and commitment, increased intention to leave, and absenteeism/productivity loss, particularly in high-risk service environments (20, 23). This body of evidence supports treating healthcare workers’ FV not merely as a post-event reaction but as a risk indicator with comprehensive effects on well-being and functioning.

Psychological Resilience

Although PR has been treated as a relatively stable personality trait over time, the current literature increasingly defines it as a dynamic, developable, and context-sensitive adaptation process (11, 12). According to process-based approaches, resilience encompasses the capacity to maintain, sustain, or regain functionality by demonstrating positive adaptation in the face of meaningful adversity (13, 14). Although the metaphor of “bouncing back” evokes recovery, contemporary frameworks view resilience not only as a return to the old equilibrium but also as the capacity to sustain purpose- and meaning-oriented functioning and to reconfigure adaptation in the face of prolonged adversity (24, 25). This approach aligns with the view that resilience is a multi-system phenomenon shaped by the interaction of psychological, social, and biological systems over time, rather than a singular outcome (11). It is also argued that biological processes, including epigenetic mechanisms, can shape resilience in interaction with supportive and adverse contextual conditions (26).

When examining how resilience is strengthened, individual and environmental resources are seen to jointly contribute. Individual resources, such as self-efficacy, positive affect, LS, and sleep quality, have been consistently associated with resilience, particularly in professions characterized by high demands and uncertainty (27). At the mechanistic level, emotion regulation, developing tolerance to stressors, and structuring experiences into a coherent narrative (narrative sense-making) are key components of adaptation processes (28). At the social level, relational resources such as family functioning and social support are prominent in the development of resilience; it has been reported that family functioning can enhance resilience through LS, especially in collectivist cultures (29).

Resilience is considered not only a trait that enhances well-being but also a process that explains the effects of stressors. It has been reported that the negative impact of high-threat stressors, such as workplace violence, on depressive symptoms varies according to resilience and can explain interindividual differences (15). Similarly, resilience has been suggested to mediate the relationship between poor sleep quality and mental well-being (30) and to serve as a conduit mechanism in the reflection of psychological distress, such as anxiety, on behavioral outcomes (31). In the context of healthcare workers, this framework positions resilience as a psychological capacity that enables the maintenance of well-being under perceived threat and chronic stress.

Life Satisfaction

LS is an individual’s general and cognitive assessment of their quality of life based on their own criteria and is one of the fundamental components of subjective well-being (5, 6). This construct differs from more momentary emotional experiences, such as happiness, in that it reflects a relatively stable, long-term judgment of the harmony between desired life conditions and the current situation (32, 33). Two main approaches are emphasized in explaining LS: the bottom-up perspective suggests the cumulative effect of satisfaction in areas such as work/family/health; the top-down perspective suggests that more stable tendencies, such as personality and general outlook, shape evaluations (7, 8). Findings indicate that the interaction of internal resources, such as self-esteem, PR, and optimism, and external factors, such as social support, economic conditions, and health, shapes LS (9, 10). The strong predictive power of self-esteem and the fact that this relationship can vary through intermediate processes such as body image or self-presentation tactics indicate that LS is fueled by the combined functioning of self-based cognitions and social-relational dynamics (10, 34).

From a developmental perspective, LS may exhibit varying trends across age periods. It is noted that it declines with age during adolescence (35), while in older age, despite physical health decline, it can be maintained or even increased thanks to coping mechanisms and gerotranscendence processes; this is discussed as the “aging paradox” (36, 37). PR has been reported to play a protective/restorative role in LS during stressful life events, illnesses, and crisis conditions such as pandemics (38, 39), and social capital indicators (family functioning, friend support, social networks) have been reported to support LS (29, 40). For healthcare workers, this body of research indicates that LS is an indicator of well-being that can become fragile under perceived threats; however, it can be sustained through protective psychological and social resources.

Research Hypotheses

Fear of workplace violence is defined as a multidimensional stress experience that reflects future threat perception, anxiety, and perceived risk, independent of exposure itself (1, 2). Findings suggest that FFVW is associated with psychological well-being among healthcare workers (18, 19) and classical evidence showing that fear acts as a pathway affecting mental health/functioning (1) suggest that this threat may also negatively affect the general cognitive assessment of quality of life. Since LS is an individual’s long-term and cognitive judgment of their living conditions (5, 6), it can be expected to be reported at lower levels in the context of persistent risk perception and insecurity.

H1: Fear of experiencing violence in the workplace negatively affects LS.

PR is approached as a process-based concept, defined as the capacity to maintain and regain functionality in the face of adversity/risk; it is described as a context-sensitive and developable adaptation system (11-14). The fact that FFVW is a significant stressor in healthcare services (16, 18) and that resilience in the context of violence is discussed as an explanatory mechanism for outcomes such as depressive symptoms, indicates that there will be a meaningful relationship between the level of fear and the capacity for resilience (15).

H2: There is a significant relationship between fear of workplace violence and PR.

LS is a multi-determinant indicator of subjective well-being shaped by the interaction of internal psychological resources and external conditions (7-10) . Findings indicate that resilience plays a protective/restorative role in maintaining well-being under stressful conditions (38, 39), and the nature of resilience is related to adaptation processes (13, 14) suggests that higher levels of resilience will be associated with higher LS.

H3: PR positively affects LS.

It has been associated with indicators of distress such as fear, depressive symptoms, anxiety, and impaired sleep quality (17, 18) and has been examined in conjunction with burnout processes through the depletion of psychological resources under perceived threat (16). Resilience, on the other hand, can function as a mediating and/or buffering mechanism in stress–health relationships; it can explain individual differences and the level of adverse effects in the context of workplace violence (15). Furthermore, findings indicate that resilience can mediate relationships between variables such as sleep quality and mental well-being (30, 31). This framework predicts that the effect of FV on LS involves an indirect pathway, partly mediated by PR.

H4: PR mediates the effect of fear of workplace violence on LS.

Materials and Methods

This cross-sectional study examines the relationship between fear of workplace violence and LS among healthcare workers and tests the mediating role of PR in this relationship. The research was conducted at Balıkesir University Faculty of Medicine Hospital and used convenience sampling due to time and access constraints. Data were collected between March 15, 2024, and April 15, 2025. A total of 173 healthcare workers were included in the study. Data were collected via online and face-to-face surveys. All scales used in the study were rated on a 5-point Likert scale (1=strongly disagree; 5=strongly agree).

Fear of workplace violence was assessed using the scale developed by Rogers and Kelloway (41); the Turkish validity and reliability study of the scale was conducted by Akbolat et al. (42). PR was measured using a 6-item scale developed by Smith et al. (43); the Turkish validity and reliability study was conducted by Doğan (44). LS was assessed using a 5-item scale developed by Diener et al. (5); the Turkish validity and reliability study was conducted by Dağlı and Baysal (45). Scale scores were calculated by averaging the items within each scale, and these average scores were used in the analyses.

To assess potential common method bias in self-report measures, Harman’s one-factor test was applied. In this context, a non-rotated principal component analysis was conducted, and the variance explained by the first factor was interpreted with reference to the commonly used 50% threshold in the literature.

Descriptive statistics (means, standard deviations, counts, and percentages) were calculated. The relationships between the variable “experiencing violence” and the socio-demographic variables were evaluated using the chi-square test, and the effect size was reported using Cramer’s V. The relationships between continuous variables were examined using Pearson’s correlation coefficient. Mediation analysis was performed using Hayes’ PROCESS macro (Model 4, v5.0). In this model, fear of workplace violence, PR, and LS were defined as the independent variable (X), the mediator variable (M), and the dependent variable (Y), respectively. The indirect effect was assessed using 5000 bootstrap samples and 95% bootstrap confidence intervals. The variables gender, age range, seniority, educational status, marital status, and exposure to violence were controlled for in the analyses. The level of statistical significance was set at p<0.05. The study received ethical approval from the Scientific Ethical Evaluation Board of Selçuk University’s Faculty of Economics and Administrative Sciences on (decision no: 03/26, date: 05.03.2024). Written informed consent was obtained from all participants before data collection. Participation was voluntary; participants were informed that they could withdraw from the study at any time without consequence.

Results

Since validity and reliability studies in Turkish had already been conducted for all scales employed in this study, no additional validity analyses were performed. Reliability (Cronbach’s alpha) coefficients and descriptive statistics for the scales are presented in Table 1. Accordingly, the Cronbach’s alpha coefficients are 0.879 for FV, 0.706 for PR and 0.894 for LS. The mean scale scores were 1.945±0.604 for FV, 3.646±0.482 for PS, and 4.183±0.634 for LS (Table 1).

The socio-demographic characteristics of the participants are presented in Table 2. Of the participants, 68.8% were male (n=119) and 31.2% were female (n=54). Of the participants, 57.8% (n=100) were married and 42.2% (n=73) were single. By seniority, 41.6% of participants were in the 0–5-year group (n=72) and 42.2% were in the 6–10-year group (n=73). Regarding the “experiencing violence” variable, 24.3% of participants answered yes (n=42), and 75.7% answered no (n=131) (Table 2).

The relationship between exposure to violence and socio-demographic variables was examined using chi-square analysis, and the results are presented in Table 3. The analyses indicate a significant association between experience of violence and educational status (χ²=9.757; df=3; p=0.021). Similarly, a significant relationship was found between the experience of violence and age group (χ²=8.114; df=3; p=0.044). The relationships between experiencing violence and gender (p=0.167), marital status (p=0.061), and years of employment (p=0.075) were not statistically significant. Effect sizes were reported using Cramér’s V, indicating small to moderate effects for age group (V=0.217) and educational status (V=0.237).

The findings of the correlation analysis conducted to determine the relationships between variables are presented in Table 4. Based on these findings, significant relationships were observed: a significant negative relationship between Fear of Experiencing Violence at Work and PR (r=-0.382; p<0.001); a significant negative relationship between Fear of Witnessing Violence (FWV) at work and LS (r=-0.437; p<0.001); and a significant positive relationship between PR and LS (r=0.262; p<0.001) (Table 4).

Regression-based results and path coefficients from the mediation analysis are shown in Table 5. Accordingly, FWV negatively predicts the mediating variable, PR [B=-0.319, standard error (SE)=0.059, t=-5.450; R²=0.278]. The direct effect of FV on LS is also negative (B=-0.517, SE=0.079, t=-6.520; R²=0.363). However, the predictive power of PD on LS is not statistically significant when SK and control variables are included in the model (B=0.052, SE=0.099, t=0.531). In the total effect model, the effect of SK on YD continues to be negative (B=-0.534, SE=0.073, t=-7.354; R²=0.362). In all models, gender, marital status, education, age group, seniority, and exposure to violence were included as covariates.

Discussion

This study demonstrated that fear of workplace violence among healthcare workers is negatively associated with LS; fear is inversely related to PR, while PR is positively associated with LS. This pattern indicates that fear of workplace violence serves as a stressor that undermines subjective well-being by fostering a perception of constant threat among healthcare workers (1, 2, 17, 18). However, because the study is cross-sectional, the findings should be interpreted at the “correlation” level, and claims about directionality and causality should be avoided.

The negative impact of FV on LS is consistent with the view, emphasized in the violence literature, that future uncertainty and threat assessments can determine psychological outcomes, independent of exposure (1). Intensive patient/patient relative contact in healthcare services, rapid decision-making, and conditions of uncertainty may make risk assessments more visible, negatively affecting individuals’ general cognitive judgments about their lives (5, 6). In this context, when the findings are evaluated alongside reports linking fear to depressive symptoms, anxiety, and sleep disturbance, they suggest that decreased LS may be part of a broader distress profile (17, 18). Therefore, assessments of fear levels should be approached not only through “exposure to violence” but also through “perceived risk and control” processes.

Mediation analyses did not support the expected mediating role of PR in the relationship between fear LS. Findings indicate that fear is related to resilience levels; however, the predictive power of resilience for LS is no longer significant when fear and control variables are considered. In other words, the effect of fear on LS largely persists; resilience does not mediate this relationship through a statistically significant indirect effect. This result suggests that, although resilience is generally a valuable resource for well-being, it may not be the primary channel through which fear affects broader outcomes such as LS. This finding should not be interpreted as “resilience is ineffective.” Rather, it should be interpreted as in this sample and this model, it has not been supported as an indirect mechanism in the fear-LS pathway.

Possible explanations for this result can be addressed under three headings. First, because LS is a holistic assessment that includes non-work domains, the effect of fear may be mediated by contextual processes such as organizational safety climate, perceived prevention capacity, management support, and perceived fairness rather than by resilience (23).

Second, the role of resilience may vary by outcome; resilience may play a more pronounced mediating/buffering role in psychological outcomes that are “closer” to LS (e.g., anxiety, sleep quality, burnout) (30, 31). Third, the presence of numerous covariates in the model may have reduced the specific contribution of resilience by explaining a portion of the variance in LS. This is consistent with the PD coefficient becoming insignificant in the multivariate model (including SK and covariates), despite the PD-LS relationship being significant at the correlation level; that is, the bivariate relationship may weaken at the multivariate level due to shared variance and possible measurement error or short scale length. Therefore, future research should model resilience alongside “organizational context” and “proximal psychological processes” to distinguish the mechanisms at play more clearly. Additionally, the possible “moderator” role of resilience (e.g., buffering the effect of fear on LS) should be tested; moderation may be a more plausible explanation than mediation.

When evaluating the relationships between exposure to violence and socio-demographic variables, analysis revealed significant associations with specific demographic characteristics. This finding provides a framework consistent with the literature, indicating that violence risk and exposure patterns may vary according to demographic/occupational characteristics (20, 21). The variation in LS across age groups, meanwhile, aligns with developmental findings indicating that LS can change across life stages (35, 37, 46). However, as these analyses are cross-sectional and categorical, the findings should be interpreted as a distribution or pattern rather than for determining risk.

From clinical and managerial perspectives, the results suggest that “post-event” approaches alone may not be sufficient to combat violence at the hospital level; processes aimed at reducing uncertainty and perceived risk, which fuel fear, need to be strengthened. The accessibility of violence reporting mechanisms, post-event psychosocial support, management feedback, and the visibility of safety practices may be critical in reducing fear levels (23). In this context, resilience-building programs may be supportive; however, since findings show that fear’s direct impact on LS remains strong, multi-component interventions that strengthen organizational prevention and the safety climate appear to be a higher priority (1, 16, 18). In practice, “individual resource enhancement” approaches should be positioned as complementary to, rather than as replacements for, “organizational risk reduction” strategies.

Study Limitations

These findings should be considered in light of certain limitations. Because the study has a cross-sectional design, the relationships between variables cannot be interpreted causally; longitudinal studies that assess temporal sequence would provide stronger evidence. Second, because the sample was selected from a single center using convenience sampling, the generalizability of the results to other hospitals and units is limited. Third, the data are self-reported; this may increase the risk of social desirability bias and standard method bias. Although the single-factor finding does not indicate a clear bias, validation with multiple measures would be helpful. Fourth, the “experiencing violence” variable could only be partially captured by the model, because the model did not include details such as the source, type, frequency, or timing of incidents. Finally, since organizational context variables that can shape the level of fear (e.g., perceived prevention capacity, safety climate, management support, perceived justice) were not measured, the possible role of these factors in the fear-well-being relationship could not be directly tested. Additionally, assessing PR using a brief scale may underrepresent context-sensitive components (e.g., team support, coping resources); more comprehensive measures may capture different manifestations of mediating or buffering effects.

Conclusion

This study shows that fear of workplace violence among healthcare workers is negatively related to LS. The findings reveal that PR decreases as fear levels increase and that LS increases as PR increases. However, mediation analyses indicate that PR is not a statistically significant indirect mechanism in the relationship between fear and LS; the effect of fear on LS is mainly direct. In this context, it seems appropriate to shift the priority of interventions toward processes that reduce the organizational risk perception that fuels fear (e.g., safety climate, perceived prevention capacity, management support).

These findings emphasize that post-event approaches alone may not be sufficient to combat violence and highlight the importance of institutional arrangements that reduce employees’ perceptions of future threats. Strengthening violence prevention policies, increasing the visibility of security practices, making reporting mechanisms accessible and reliable, and activating post-event psychosocial support can help maintain well-being indicators. In practice, institutional packages that integrate prevention, reporting, feedback, and psychosocial support can be considered a more rational goal than initiatives focused solely on individual resilience. Individual programs should be positioned as complementary to this effort.

Future research should use multicenter samples, longitudinal designs, and measures that assess the nature of violence exposure (type, frequency, source, and timing) in detail. Furthermore, testing models that include proximal psychological processes (e.g., anxiety, sleep disturbance, burnout) and organizational context variables (e.g., safety climate, management support, perceived fairness), which may mediate the effect of fear on well-being, will contribute to a clearer understanding of the mechanisms. In particular, the mediating or moderating role of safety climate/perceived prevention capacity and the “buffering” effect of PR (fear × resilience) should be tested in subsequent studies using interaction terms.