Introduction

Recent changes in the healthcare environment, such as an aging population, the rising prevalence of chronic diseases, increasing patient expectations, and a growing emphasis on evaluating medical institutions, have led to a greater demand for high-quality medical services. Nurses, who constitute the largest proportion of healthcare providers, are expected to deliver specialized and high-quality care along with a higher level of consideration and kindness in response to these changes [1]. Compared to other hospital staff, nurses experience heavier workloads and faster work demands [2]. Because of the nature of their work, which involves frequent interactions with patients, families, and various healthcare professionals, nurses are often exposed to emotional distress and burnout caused by job-related stress [1].

Burnout refers to the physical, emotional, and psychological exhaustion that occurs when healthcare workers are repeatedly exposed to emotional pressure and excessive job stress that exceed their ability to cope [3]. Among nurses, burnout leads to negative self-concept, reduced professional commitment, and cynicism toward patients, which adversely affects nurses’ health and fosters negative attitudes toward the nursing profession [1]. Severe burnout may result in physical symptoms such as headaches, muscle pain, digestive issues, and respiratory problems. Burnout can also spread within healthcare teams, affecting fellow nurses, other healthcare professionals, and patients, ultimately impacting the entire organization [4]. When caused by excessive workload, burnout may increase turnover intentions [3], making nurse burnout a critical issue that must not be overlooked. Therefore, identifying and managing factors that contribute to burnout is essential.

Role conflict refers to the tension that arises when an individual’s actions do not meet the expectations of others and it has been identified as a contributing factor to nurse burnout [5]. This type of conflict commonly occurs when nurses, as professionals, are unable to make decisions in complex situations involving multiple responsibilities [6]. Nurses often experience role conflicts due to unclear job duties, nonprofessional tasks, and excessive workloads [7]. When role conflict intensifies, burnout increases [8], limiting nurses’ ability to provide high-quality care, potentially leading to a decline in professional value, and further exacerbating burnout [6].

Emotional labor refers to the effort required to regulate facial expressions and body language to convey emotions and meet organizational expectations. Previous studies have shown that 98% of hospital nurses engage in emotional labor [9]. With rising income levels and increased awareness of patient rights, medical consumers have high expectations of service quality, prompting nurses to suppress or alter their emotions [9]. While emotional labor can enhance patient understanding [9], expressions that are externally imposed rather than voluntarily given may lead to emotional dissonance. Dissonance is associated with elevated levels of depression and stress, potentially resulting in burnout [10].

Resilience refers to the ability to adapt successfully by flexibly and proactively coping with situational demands and stressful environments [11]. This capacity has been identified as a protective factor in reducing burnout among nurses [11,12]. Nurses can enhance their resilience by actively utilizing internal and external resources, overcoming adversity, and advancing their professional development [12]. Previous studies have shown that higher levels of resilience are associated with lower burnout among nurses [11].

Previous Korean studies have identified emotional intelligence [6] and job stress [11,13] as factors affecting burnout. While emotional labor [9,13] and resilience [11–13] have also been investigated in relation to burnout, few studies have examined role conflict as a contributing variable. Although role conflict, emotional labor, and resilience have been studied individually, few studies have assessed the relationship between these three variables and the degree of burnout. Therefore, the purpose of this study was to provide foundational data to support the development of intervention programs for the management and prevention of burnout. These programs would aim to enhance the physical and psychological well-being of nurses and contribute to the advancement of nursing organizations.

To achieve this, this study assessed role conflict, emotional labor, resilience, and the degree of burnout in nurses and examined differences in these variables based on demographic characteristics. In addition, the study explored the correlations among role conflict, emotional labor, resilience, and burnout, and identified factors influencing nurse burnout.

Materials and Methods

1. Design

This descriptive correlational study aimed to assess the levels of role conflict, emotional labor, resilience, and burnout in nurses; examine the relationships among these variables; and identify the factors influencing burnout (Fig. 1).

2. Participants

The participants in this study were nurses employed at Korea University Hospital in Seoul who fully understood the purpose of the study and voluntarily agreed to participate. The required sample size was calculated using G*power 3.1.9.7, based on a significance level of 0.05, an effect size of 0.15, a power of 0.80, and 13 predictor variables (demographic characteristics, role conflict, emotional labor, and resilience). To account for a 10% dropout rate, 145 questionnaires were distributed and all were returned (100%). Of these, 11 (7.5%) were deemed invalid and 134 (92.4%) were included in the final analysis.

The inclusion criteria were nurses with at least 6 months of clinical experience who understood the purpose of the study and who voluntarily agreed to participate. The exclusion criteria were nurses with less than 6 months of clinical experience and those who were not in direct contact with patients, such as those involved in nursing administration or nursing education.

3. Data collection and procedures

The data collection for this study was conducted over a 14-day period, from July 8 to July 21, 2023. To recruit participants, the researcher visited the nursing department of the hospital, explained the purpose and procedures of the study to the nursing director, and obtained departmental cooperation. Following approval for participant recruitment, recruitment notices were posted to promote the study and encourage voluntary participation among eligible nurses. Before the survey began, the researchers provided a thorough explanation of the purpose and procedures of the study as well as the principles of anonymity, confidentiality, and voluntary participation. After obtaining written consent, questionnaires were distributed to the participants. Upon completion, the questionnaires were immediately sealed in collection envelopes to ensure confidentiality and collected in person by the researchers.

4. Tools

A structured, self-administered questionnaire was used to analyze the factors related to nurse burnout. The questionnaire comprised 113 items: 10 on demographic characteristics, 37 on role conflict, 16 on emotional labor, 30 on resilience, and 20 on burnout. All tools used in this study were approved by the developers and translators via email prior to data collection.

1) Demographic characteristics

Demographic characteristics were assessed using ten questionnaire items on age, gender, marital status, religion, highest level of education, department of work, working conditions, total clinical experience, average overtime hours, and job satisfaction.

2) Role conflict

The measurement tool for nurses’ role conflict developed by Lee and Lee [6] was used in this study. The tool consists of 37 items divided into four subscales: role ambiguity (15 items), lack of ability (11 items), environmental barriers (6 items), and lack of cooperation (5 items). Each item is rated on a 5-point Likert scale ranging from 1 (“Not at all”) to 5 (“Very much”), with a total score ranging from 37 to 185 points. Higher scores indicate a greater degree of role conflict. The reliability of the tool was assessed as Cronbach’s α=.94 in a previous study [6] and Cronbach’s α=.95 in the present study.

3) Emotional labor

This study used the emotional labor measurement tool developed by Kang et al. [14]. This tool consists of 16 items grouped into three factors: professional emotion regulation efforts (7 items), client-centered emotional suppression (5 items), and emotional values by norms (4 items). Each item is rated on a 5-point Likert scale, with a total score ranging from 16 to 80. Higher scores indicate a greater degree of emotional labor. The reliability was assessed as Cronbach’s α=.80 in Kang et al.’s study [14] and Cronbach’s α=.71 in this study.

4) Resilience

The nurse resilience measurement tool developed by Park and Park [15] was used in this study. The tool consists of 30 items grouped into five factors: temperamental patterns (5 items), relational patterns (4 items), situational patterns (10 items), philosophical patterns (6 items), and professional patterns (5 items). Each item is rated on a 5-point Likert scale, with a total score ranging from 30 to 150 points. Higher scores indicate greater resilience. The reliability of the tool was assessed as Cronbach’s α=.94 at the time of development and Cronbach’s α=.95 in this study.

5) Burnout

The burnout measurement tool employed by Moon and Kim [16] was used in this study. The tool consists of 20 items grouped into three factors: physical exhaustion (6 items), emotional exhaustion (7 items), and mental exhaustion (7 items). Each item is rated on a 5-point Likert scale ranging from 1 (“Never feel”) to 5 (“Always feel”), with a total score ranging from 20 to 100. Higher scores indicate a greater degree of burnout. The reliability of the tool was assessed as Cronbach’s α=.92 in Moon and Kim’s study [16] and Cronbach’s α=.90 in this study.

5. Statistical analysis

IBM SPSS Statistics version 25.0 was used for the data analysis. Descriptive statistics, including means, standard deviations, frequencies, and percentages, were used to summarize the participants’ general characteristics and levels of role conflict, emotional labor, resilience, and burnout.

Independent t-tests and one-way ANOVA were conducted to examine group differences in role conflict, emotional labor, resilience, and burnout based on participants’ demographic and job-related characteristics. Scheffé’s post-hoc tests were applied for pairwise comparisons where appropriate.

Pearson’s correlation coefficients were calculated to assess the relationships between role conflict, emotional labor, resilience, and burnout.

Stepwise multiple linear regression analysis was performed to identify significant predictors of burnout. Tolerance and the variance inflation factor (VIF) were used to test for multicollinearity, and the Durbin-Watson statistic was used to assess autocorrelation. Statistical significance was set at p≤.05 for all inferential analyses.

6. Ethical considerations

This study was conducted after obtaining approval from the Institutional Review Board (IRB) of Korea University Hospital, a tertiary general hospital, to ensure the ethical protection of all participants involved in the study (IRB approval number: K2024-0679-002). Additionally, prior to data collection, official permission was obtained from the original developers and authorized translators for all measurement tools employed in the study to ensure appropriate and ethical use of these instruments.

To protect the confidentiality and anonymity of participants, all collected data were coded using identification numbers, and no personally identifiable information was included in the analysis. The data were used exclusively within the scope outlined in the consent form and the participant information sheet. Personal information was rigorously protected in accordance with the relevant data protection laws and institutional guidelines governing the handling of human subject data.

Physical documents containing the participants’ personal data were securely stored in a locked location to prevent unauthorized access. Similarly, electronic data were encrypted and stored on password-protected devices, with access restricted solely to the principal investigator. Personal information collected solely for providing participation incentives was stored separately from the survey data and immediately destroyed upon completion of the reward distribution.

All research-related documentation will be securely retained for three years from the official conclusion of the study and submission of the final report. After this retention period, the documents will be permanently destroyed to prevent any potential recovery or reconstruction.

Participants were informed both verbally and in writing that they had the right to voluntarily withdraw from the study at any point without facing any form of disadvantage, discrimination, or penalty. A small token of appreciation was provided to each participant upon completion of the survey, in recognition of their valuable time and contribution to the study.

Results

1. Demographic characteristics of the participants and differences in burnout based on general characteristics

The demographic characteristics of the participants and the associated differences in burnout are presented in Table 1. Statistically significant differences were observed in age (t=3.76, p=.026), department of work (t=4.48, p=.013), and job satisfaction (t=52.38, p=＜.001). Scheffe’s post-hoc test results showed that nurses in their 30s had higher levels of burnout than those in their 40s or older, and those working in internal medicine/surgical wards or special wards had higher burnout than those working in other departments (outpatient, clinical specialty, and mental health wards). Additionally, burnout levels were highest among nurses who were dissatisfied with their jobs, followed by those who were satisfied, and were lowest among those who were indifferent. This finding indicates that greater job satisfaction is associated with lower burnout. Significant differences were observed in burnout levels for multiple factors.

2. Role conflict, emotional labor, resilience, and burnout levels in nurses

Descriptive statistics for role conflict, emotional labor, resilience, and burnout levels among the nurses are presented in Table 2. Role conflict showed an overall average score of 3.68±0.56. The average scores for the subscales were 3.75±0.60 for role ambiguity, 3.41±0.70 for lack of ability, 4.04±0.67 for environmental barriers, and 3.61±0.71 for lack of cooperation. Emotional labor showed an overall average score of 2.80±0.38. Subscale scores showed an average of 2.10±0.52 for professional emotion regulation efforts, 3.35±0.88 for client-centered emotional suppression, and 3.32±0.63 for emotional value by norms. Resilience showed an overall average score of 3.83±0.48. Subscale scores showed an average of 3.66±0.59 for temperamental patterns, 4.03±0.46 for relational patterns, 3.94±0.49 for situational patterns, 3.72±0.71 for philosophical patterns, and 3.77±0.58 for professional patterns. Finally, burnout showed an overall average score of 3.11±0.61. Subscale scores showed an average of 3.91±0.66 for physical exhaustion, 2.55±0.80 for emotional exhaustion, and 2.99±0.67 for mental exhaustion.

3. Correlation between role conflict, emotional labor, resilience, and burnout

The relationships between role conflict, emotional labor, resilience, and burnout in nurses were examined using Pearson’s correlation analysis (Table 3). Burnout showed the strongest negative correlation with resilience (r=−.406, p ＜.001), while showing positive correlations with emotional labor (r=.286, p＜.001) and role conflict (r=.202, p=.019). These results indicate that lower resilience and higher emotional labor and role conflict are associated with higher burnout. Emotional labor was negatively correlated with resilience (r=−.399, p＜.001), suggesting that higher emotional labor is linked to lower resilience. No statistically significant correlations were found between role conflict and emotional labor (r=.037, p=.671) or between role conflict and resilience (r=.149, p=.086).

4. Factors influencing burnout in nurses

To identify the factors influencing burnout in nurses, stepwise multiple regression analysis was conducted using role conflict, emotional labor, resilience, and general characteristics that showed significant differences, including age, department, and job satisfaction as variables. Categorical variables were treated as dummy variables. The detailed results are presented in Table 4.

To assess multicollinearity among the variables, tolerance and VIF values were reviewed. The tolerance values ranged from 0.75 to 0.95, all above 0.1, and the VIF values ranged from 1.05 to 1.34, all below a threshold of 10, indicating no multicollinearity. Additionally, autocorrelation of errors was tested using the Durbin-Watson statistic, which was 1.83, close to the benchmark value of 2, indicating that the assumption of independence was satisfied. The F-statistic was 29.77 (p＜.001), confirming that the regression model was appropriate.

Ultimately, the significant predictors of burnout in nurses were job satisfaction (dissatisfaction) (β=.37, p＜.001), job satisfaction (satisfaction) (β=−.33, p＜.001), resilience (β=−.22, p=.001), role conflict (β=.18, p=.003), emotional labor (β=.17, p=.009), and department (other) (β=−.14, p=.021). This model explained approximately 58.4% of burnout among the nurses (adjusted R²=.565).

Discussion

1. Differences in role conflict, emotional labor, resilience, burnout levels, and general characteristics

The average burnout level among the study participants was 3.11, which was lower than that reported in Moon and Kim’s study [16] on nurses in general hospitals. These differences may reflect variations in burnout levels associated with individual characteristics, hospital size and type, patient conditions, staffing levels, region, and other environmental factors.

In this study, burnout levels differed significantly based on demographic characteristics such as age, department of work, and job satisfaction. Nurses in their 30s reported the highest level of burnout, with a significant difference compared with those in their 40s or older. This finding is consistent with Cho’s study [17], which showed significantly higher burnout levels among nurses in their 20s and 30s than among those in their 40s. In this study, nurses working in internal medicine and surgical or special wards showed significantly higher burnout than those in other departments, such as outpatient, clinical, and mental health wards. Although burnout levels were higher in internal medicine and surgical wards than in special wards, the differences were not statistically significant. These findings are partially consistent with those of Kim and Noh’s study [18], which showed that nurses working in wards, emergency rooms, and intensive care units (ICUs) experienced higher burnout levels than those in outpatient settings. Additionally, the present study found that nurses with higher job satisfaction had lower levels of burnout. Based on these results, enhancing job satisfaction may be an important strategy to reduce burnout among nurses.

2. Correlation between role conflict, emotional labor, resilience, and burnout

In the present study, a negative correlation was found between emotional labor and resilience, indicating that higher emotional labor is associated with lower resilience among nurses. This finding is supported by Kim’s study [13] of hospice nurses, which found a significant negative correlation between emotional labor and resilience.

Burnout showed the strongest significant negative correlation with resilience, and significant positive correlations with emotional labor and role conflict. In other words, lower resilience, higher emotional labor, and role conflict were associated with higher burnout levels. These findings align with those of previous studies showing that higher resilience is related to lower burnout [11,13] and that higher emotional labor is associated with higher burnout [6,13]. Therefore, to reduce burnout in nurses, it is essential to implement regular education, develop intervention programs, and evaluate their effectiveness in reducing role conflict and emotional labor, while increasing resilience.

Resilience showed the strongest correlation with burnout. Similarly, Ryu and Kim’s study [19] found that nurses who participated in an emotional coaching program showed a significant increase in resilience compared to those who did not. To reduce burnout in nurses, it is important to enhance resilience through programs that foster positive relationships by promoting empathy, active listening, and acceptance as well as stress management strategies focused on positive emotions and emotional regulation.

3. Factors affecting nurse burnout

A stepwise multiple regression analysis was conducted to identify the factors influencing burnout in nurses. The results showed that the predictors explained 58.4% of the variance in burnout, in the following order: job satisfaction (dissatisfaction), job satisfaction (satisfaction), resilience, role conflict, emotional labor, and department of work (other).

Regarding demographic characteristics, when job satisfaction was used as the reference variable, burnout increased as job satisfaction decreased. Similarly, when nurses in internal medicine and surgical wards were set as the reference group, those working in other departments (outpatient, clinical specialist, and mental health wards) showed lower burnout levels. These findings align with Baek et al.’s study [10], which found that lower job satisfaction was associated with higher burnout. While it may be difficult to confirm that the department of work is a factor influencing burnout in nurses, these findings are partially consistent with those of Kim and Noh’s study [18], which showed the highest burnout levels in emergency rooms, followed by wards and outpatient departments. Therefore, further research is needed to identify the factors that influence job satisfaction and better understand how departmental characteristics affect burnout in nurses.

Role conflict, emotional labor, and resilience were identified as factors influencing burnout in nurses. Resilience had the strongest impact on burnout, excluding general demographic characteristics. These findings are consistent with those of Kim and You’ study [20], who examined insurance review nurses. Resilience enables nurses to mitigate the effects of stressful situations and cope with crises [11]. Since resilience can be enhanced through training and education [12], it is essential to develop educational programs aimed at strengthening resilience and reducing burnout among nurses.

Additionally, role conflict was identified as a contributing factor to burnout among nurses. These findings are consistent with those of Kim and You’s study [20] on insurance review nurses and Lee’s study [6] on ICU nurses, both of which showed that higher role conflict was associated with higher burnout. Based on these results, reducing role conflict is essential for reducing burnout among nurses. Additionally, legally establishing nurse-to-patient ratios, expanding facilities to support efficient workflows, and clarifying the scope of nursing roles are critical factors.

Emotional labor was also identified as a contributing factor to burnout in nurses, supporting previous findings [13] that showed a positive correlation between emotional labor and burnout. Repeated emotional labor may lead to emotional disharmony among nurses, ultimately contributing to burnout [13]. Therefore, it is important to assess the extent of emotional labor among nurses periodically.

Given prolonged medical strikes in many instances and the unpredictable nature of infectious disease outbreaks, burnout in nurses working in hospitals is inevitable, making its management a priority. This study confirmed that job satisfaction, resilience, role conflict, emotional labor, and the department of work influenced burnout in nurses, providing foundational data to support these findings. Based on the results of this study, it is essential to develop strategies to reduce burnout by regularly assessing job satisfaction and resilience, reducing role conflict and emotional labor, through using appropriate measurement tools tailored to each department, and implementing appropriate education and intervention programs.

Notes

Acknowledgements

This article is a condensed form of the first author’s master’s (doctoral) thesis from Korea University.

Conflicts of interest

The authors declared no conflict of interest.

Funding

None.

Fig. 1.

Theoretical framework of the study.

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