Relationship between Compassion fatigue, Medical Narrative Ability, and Retention intention among Nurses: A Cross-Sectional Multi- center Study

Relationship between Compassion fatigue, Medical Narrative Ability, and Retention intention among Nurses: A Cross-Sectional Multi- center Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationship between Compassion fatigue, Medical Narrative Ability, and Retention intention among Nurses: A Cross-Sectional Multi- center Study Yanjia Li, Jue Wu, Limei Zhang, Xiaoying Zeng, Zhenyu Huang, Ping Yuan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5870594/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background In recent years, due to the increase in care demands caused by population aging and the rise in nurse-patient conflicts, the retention intention of nurses has become an urgent global issue, as high turnover rates pose significant challenges to healthcare systems around the world. Therefore, this study will explore nurses’ retention intention and the associated factors. Methods This multi-center cross-sectional study recruited 1,831 nurses from eight hospitals across China between January and February 2024 through convenience sampling. Data collection was conducted using online surveys. The questionnaire was divided into four sections: the sociodemographic questionnaire, the Chinese Questionnaire for Nurse Intention to Remain Employed (C-QNIRE), the Medical Narrative Ability Scale (MNAS), and the Chinese version of Compassion Fatigue Short Scale (C-CF-Short Scale). We utilized descriptive statistics, normality test, one-way ANOVA, t-tests, Pearson correlation analysis, and multiple linear regression analysis. Results The results of this study showed that the total score of nurses’ retention intention was 22.79 ± 3.71. The Multiple stepwise linear regression results showed that compassion fatigue ( β = -0.334, P < 0.001), medical narrative ability( β = 0.250, p < 0.001), age (46-60years) ( β = 0.143, p < 0.001), age (41-45years) ( β = 0.121, p < 0.001), age (36-40years) ( β = 0.107, p < 0.001), age (31-35years) ( β = 0.093, p 50h) ( β = -0.096, p < 0.05),working week(46-50h) ( β = -0.071, p < 0.05),working week(40-45h) ( β = -0.070, p 8) ( β = -0.062, p < 0.05) were the main associated factors of nurses’ retention intention, explaining 27.0% of the total variation. Conclusion This study indicated that nurses demonstrate a moderate retention intention. Nursing administrators and educators should address this issue by proactively introducing strategies to reduce compassion fatigue and improve narrative medicine ability among nursing staff. Such initiatives can positively impact nurses’ retention intention, thereby reducing the turnover of skilled nursing personnel. This is essential for effective management of nursing human resources and enhancing the overall quality of nursing care. Nurse Compassion fatigue Medical narrative ability Retention intention Introduction As global healthcare systems continue to advance, nurses remain indispensable in delivering medical care. However, recent years have witnessed a concerning increase in nurse turnover rates worldwide, particularly in high-stress environments, where the retention intention declined[ 1 ]. A decrease in retention intention implies greater job mobility and a higher likelihood of nurses leaving their positions. This trend not only jeopardizes the quality and stability of nursing services but also increases recruitment and training costs for hospitals, potentially disrupting the smooth operation of the entire healthcare system[ 2 ]. In China, this phenomenon is particularly striking. With the increasing aging of the population, the impact of COVID-19 on the global economy, and the implementation of Diagnosis Related Groups (DRG)-based medical insurance payment reform in China, nurses’ retention intention has further decreased[ 3 ]. Additionally, layoffs and even bankruptcies at some medical institutions have exacerbated the trend. Therefore, it is crucial to conduct a thorough analysis of the current state of nurses’ retention intention and its associated factors within nursing management research. Such studies can improve nursing management practices and provide a solid basis for healthcare institutions to formulate effective human resource strategies. The retention intention of nurses reflects their desire and probability to continue working in those positions[ 4 ]. The factors that influence this retention intention are diverse and intricate. Studies show that nurses with strong retention intention tend to remain in the nursing field for longer durations, demonstrate higher job involvement, and positively contribute to the quality of nursing care[ 5 ]. On the other hand, nurses with weaker retention intention are more prone to leaving their jobs, which can negatively impact healthcare organizations and patient outcomes[ 6 ]. A thorough review of existing literature indicates that the primary drivers of nurses’ retention intention include aspects such as the work environment, compensation, opportunities for career advancement, and personal psychological and emotional well-being[ 7 ]. In addition, some studies have pointed out that new nurses may experience greater stress due to their lack of experience, while senior nurses may accumulate fatigue due to long-term exposure[ 8 ]. Age, length of service, and professional title are often related to experience, responsibility, and career development stage, which affect stress perception, coping resources, and intention to leave[ 2 ]. Therefore, we speculate that these sociodemographic variables may also have some relationship with nurses’ retention intention. Hao et al. [ 9 ] emphasize that rising work pressures have exacerbated psychological challenges among nurses, yet these issues frequently do not receive adequate attention. Additionally, various studies propose that nurses’ professional capabilities, encompassing clinical expertise, communication skills, and empathetic qualities, can significantly affect their retention intention[ 10 , 11 ]. Prolonged high-pressure work environments and emotional investment expose nurses to varying levels of emotional exhaustion, making compassion fatigue a critical concern for occupational mental health. Compassion fatigue is marked by the depletion of emotional, mental, and physical resources due to continuous exposure to the distress and trauma experienced by others[ 12 ]. Studies show that this condition not only negatively impacts the mental well-being of nurses but can also diminish work efficiency, job satisfaction, and the overall quality of nursing care[ 13 ]. According to Charles Figley’s Compassion Fatigue Theory, the main drivers often include the demanding work environment, patient suffering, and the emotional needs of patients[ 14 ]. In intensive nursing roles, while offering emotional support to patients, nurses must also cope with their own emotional strain and occupational stress. This dual burden is frequently the primary factor leading to compassion fatigue, which subsequently affects job satisfaction[ 15 ]. Additionally, research by Lee et al.[ 16 ] highlights a significant link between job burnout and retention intention among nurses, and also indicating a positive correlation between compassion fatigue and job burnout, potentially accelerating turnover rates [ 17 , 18 ]. Therefore, it is reasonable to infer that compassion fatigue may also be related to the nurses’ retention intention. In recent years, the medical narrative ability of nurses has increasingly attracted academic interest as a critical element in their interaction and communication with patients. Medical narrative ability involves healthcare providers’ ability to understand and interpret patients’ accounts of their illnesses, convey the underlying meanings of these narratives accurately, empathize with patients, and advocate for their best interests[ 10 ]. Drawing from Hochschild’s Emotional Labor Theory, which posits that service professions demand employees to control and modulate their emotional expressions to fulfill job requirements[ 19 ]. Medical narrative ability can be seen as a type of emotional labor. It requires nurses to manage and express emotions effectively, listen attentively to patients’ experiences, and cultivate trust and empathy during care[ 20 ]. However, nurses often encounter heightened demands for emotional labor, especially when this labor lacks adequate support, potentially leading to greater job burnout and decreased retention intention. Research also suggests that effective medical narratives can strengthen the emotional bond between nurses and patients, enhance patient treatment experiences, and increase patient satisfaction[ 21 ]. On the other hand, insufficient medical narrative skills may result in suboptimal communication and increased professional stress for nurses[ 22 ]. While some studies have investigated the impact of medical narrative ability on nurses’ occupational health, fewer have explored its connection with retention intention. Considering the prevalent issues of job burnout and stress among nurses, often associated with lower retention rates[ 16 ]. Medical narrative ability provides a valuable form of emotional support. It enables nurses to better handle emotional challenges at work. We propose that improving medical narrative ability could help alleviate these challenges, and improve nurses’ retention intention. Nurses’ retention intention is shaped by an intricate combination of various factors. Although some studies have explored the relevant factors of nurses’ retention intention, the impact on the specific situation, regional differences and cultural background of Chinese nurses needs to be further studied. At the same time, in combination with the Job Demands-Resources Model (JD-R Model), we regard compassion fatigue as the negative outcome of occupational stressors (emotional demands)[ 23 ]. It is the ultimate product of the exhaustion process when job demands are too high and resources are insufficient. High compassion fatigue itself also constitutes a serious internal stressor, further damaging health and job performance. As a result, job satisfaction, organizational commitment, and mental health levels will all decline, and the intention to quit will naturally increase. We consider medical narrative ability as an important personal resource (ability), which includes the ability to understand, communicate, and respond to patients’ stories (cognitive, emotional, and behavioral dimensions), which may buffer the impact of stress or directly promote the retention intention. And the retention intention is a positive work outcome. Furthermore, there is currently a lack of literature on the relationship between compassion fatigue, medical narrative ability and nurses’ retention intention. Therefore, this study aims to investigate the current situation of retention intention among Chinese nurses through a multi-center cross-sectional survey, explore the correlation between retention intention, compassion fatigue, and medical narrative ability, and propose strategies to improve nurse’s retention intention from a new perspective. This approach seeks to provide theoretical support and practical guidance for enhancing the stability of the nursing team, optimizing the allocation of nursing resources, and improving the quality of nursing services. Methods Design and participants This study employed convenience sampling to conduct an online questionnaire survey among 1,831 nurses from 8 hospitals across the country from January to February 2024. The inclusion criteria were as follows: (i) age ≥18 years old; (ii) obtain the professional qualification registration of nurses; (iii) voluntary participation in this study;(iv) the working time is more than six months. The exclusion criteria are as follows: (i) nurses who were not on duty during the survey period; (ii) participants who withdrew voluntarily during the study period. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were followed. Measures This study used four measures to collect data: the sociodemographic questionnaire (gender, age, education level, marital status, professional title, department, working experience, income, how many night shifts a month, have you experienced a major traumatic event in the past year, working week), the Chinese Questionnaire for Nurse Intention to Remain Employed (C-QNIRE), the Medical Narrative Ability Scale (MNAS), and the Chinese version of Compassion Fatigue Short Scale (C-CF- Short Scale). Nurses’ retention intention was measured using the C-QNIRE, which was translated by [24]. The C-QNIRE is a one-dimensional scale consisting of 6 items. Each item is scored on a 1 to 5 Likert scale, with items 2, 3, and 6 reverse-scored. The C-QNIRE ranges from 6 to 30 points. The higher the score, the higher the retention intention. In this study, the Cronbach’s alpha coefficient of the C-QNIRE was 0.749. The content validity correlation coefficients of the items in C-QNIRE range from 0.590 to 0.810. Nurses’ medical narrative ability was measured using the MNAS, which was developed by [25]. The MNAS consisted of 27 items categorized into three domains: pay attention and listen, understanding and response, reflection and representation. The items are rated on a 7-point Likert Scale ranging from 1 (“completely inconsistent”) to 7 (“completely consistent”). In order to better present the results, The total score of the scale ranges from 27 to 189 points, and the higher the score, the stronger the medical narrative ability of the individual. In this study, the Cronbach’s alpha coefficient for the MNAS was 0.967 and the content validity was 0.890. The Compassion Fatigue Scale (CFS) was developed by Adams et al.,[26] in 2006. the Chinese version of Compassion Fatigue Short Scale (C-CF-Short Scale) was revised by Lou[27]. The scale consists of two dimensions, secondary traumatic stress (5 items) and burnout (8 items), with a total of 13 items. It uses a Likert 10-point scale from 1(“never”) to 10(“very often”). The total score of this scale ranges from 13 to 130 points, and the higher the score, the higher the level of individual empathy fatigue. Cronbach’s alpha coefficient of the C-CF- Short Scale was 0.955 in this study. The content validity correlation coefficients of the items in C-CF- Short Scale range from 0.830 to 0.870. Data collection and recruitment We distributed an online questionnaire to 1,840 eligible and voluntarily active nurses in eight hospitals nationwide. The online questionnaire was created using a survey tool called “So Jump” and delivered through the social software WeChat to the research heads of each hospital. Subsequently, researchers at each hospital selected suitable participants based on predetermined criteria and provided them with information about the purpose of the questionnaire as well as instructions for completion within a designated time frame. To prevent duplicate responses, only one submission per WeChat account was allowed for completing the questions ensuring comprehensive participation. In total, we disseminated 1,840 questionnaires resulting in receiving 1,831 valid responses with an effective recovery rate of 99.5%. Ethics approval and consent to participate Ethical approval for this study was obtained from the Ethics Committee of Sichuan Taikang Hospital (No. SCTK-IRB-2024-030). This research was conducted in strict accordance with the Helsinki Declaration. All the data collected were anonymized and strictly kept confidential. Informed consent was obtained from all participants. Statistical analyses Data analysis was conducted using IBM SPSS 27.0. The normality of distributions for nurses’ retention intention, medical narrative ability, and compassion fatigue was evaluated using Kolmogorov-Smirnov (KS) test. Descriptive statistics were applied to provide an overview of the participants' demographic characteristics and the scores of the main study variables. To assess differences in retention intention according to participant characteristics, one-way ANOVA and independent samples t-tests were employed. Pearson correlation analysis was used to explore the relationships among key variables. Additionally, multiple stepwise linear regression analysis was carried out to determine significant related factors of retention intention. Statistical significance was set at p < 0.05 for two-tailed tests. Results Description of the participants Before data analysis, we standardized the main variables. In addition, the Harman single-factor test method was used to test the common method bias of the original data. The results showed that there were 8 factors with eigenvalues greater than 1, and the explanation rate of the first factor was 38.22%, which was lower than the critical value of 40%, indicating that there was no common method bias. A total of 1,831 valid questionnaires were collected in this study. Respondents were predominantly female (n = 1,783, 97.4%), and the majority of participants (n = 1,308, 71.4%) had at least a bachelor’s degree or above. In addition, only a small percentage of participants (n = 483, 26.4%) were single, divorce or others. About half of the nurses earned less than 5,000 RMB per month (n = 805, 44%). The remaining general demographic information is shown in Table 1. Single factor analysis of retention intention Kolmogorov-Smirnov (KS) test showed that the data for compassion fatigue, medical narrative ability, and retention intention were approximately normally distributed( p >0.05). Therefore, mean and standard deviations were used to describe the states of these variables. The differences in the nurses’ retention intention with the gender, age, professional title, working experience, income, how many night shifts a month, have you experienced a major traumatic event in the past year, and working week ( p < 0.05) (Table1). Table 1 Personal characteristics and single factor analysis of retention intention Variables N (%) M ± SD （ score ） t /F p Gender 2.923 0.004 Female 1783 (97.4) 22.83±3.68 male 48 (2.6) 21.25±4.38 Age(years) 17.888 <0.001 18-25 210 (11.5) 21.70±3.60 26-30 601 (32.8 22.33±3.79 31-35 500 (27.3) 22.71±3.56 36-40 259 (14.1) 23.21±3.59 41-45 124 (6.8) 24.18±3.32 46-60 137 (7.5) 24.72±3.48 Marital status 19.000 0.088 Married 1348 (73.6) 23.06±3.70 Single 410 (22.4) 21.81±3.60 Divorce or others 73 (4.0) 23.37±3.45 Education level -0.465 0.642 College 523 (28.6) 22.73±3.71 University or above 1308 (71.4) 22.82±3.71 Professional title 14.05 <0.001 nurse 267 (14.6) 22.21±3.63 senior nurse 738 (40.3) 22.41±3.67 nurse-in-charge 701 (38.3) 23.15±3.72 associate chief nurse or above 125 (6.8) 24.28±3.48 Department 1.808 0.094 Internal medicine 688 (37.6) 22.54±3.80 Surgical 432 (23.6) 22.75±3.71 Pediatric 86 (4.7) 23.34±3.12 Obstetrics and gynecology 115 (6.3) 23.33±3.19 Outpatient 83 (4.5) 23.43±3.79 Emergency 87 (4.8) 22.55±3.72 Others 340 (18.6) 22.93±3.76 Working experience (years) 19.510 <0.001 <3 212 (11.6) 21.77±3.66 3-5 319 (17.4) 22.38±3.67 6-10 426 (23.3) 22.23±3.75 11-15 521 (28.5) 23.04±3.62 ＞15 353 (19.3) 24.08±3.47 Income (RMB / month) 10.083 <0.001 ＜3000 106（5.8） 21.32±4.01 3000-5000 699 (38.2) 22.64±3.66 5001-10000 978 (53.4) 22.98±3.69 ＞10000 48 (2.6) 24.44±2.87 How many night shifts a month 17.287 <0.001 0 406 (22.2) 23.66±3.63 1-4 569（31.1） 23.02±3.58 5-8 455（24.8） 22.51±3.66 ＞8 401（21.9） 21.90±3.79 Have you experienced a major traumatic event in the past year 2.728 0.006 No 1703（93.0） 22.85±3.70 Yes 128（7.0） 21.93±3.78 Working week （ hours ） 14.568 <0.001 50 196（10.7） 21.46±3.75 Descriptive Statistics of compassion fatigue, medical narrative ability, and retention intention In this study, the total mean score of nurses’ compassion fatigue, medical narrative ability, and retention intention were 48.03±27.27, 154.48±22.93, 22.79±3.71 (Table 2). T able2 Descriptive analyses of compassion fatigue, medical narrative ability, and retention intention Variables Min Max M ± SD （ score ） C ompassion fatigue Secondary traumatic stress 5 50 16.60±10.94 Burnout 8 80 31.43±17.94 Total score 13 130 48.03±27.27 M edical narrative ability Pay attention and listen 19 63 50.06±7.41 Understanding and response 12 84 69.48±11.34 Reflection and representation 6 42 34.94±5.66 Total score 38 189 154.48±22.93 Retention intention Total score 6 30 22.79±3.71 Correlation between nurses’ compassion fatigue, medical narrative ability, and retention intention The results of the Pearson correlation indicated that compassion fatigue was negatively correlated with medical narrative ability ( r = -0.238, p <0.01) and retention intention ( r = -0.411, p < 0.01). The medical narrative ability was positively correlated with retention intention ( r = 0.344, p < 0.01) (Table 3). Table 3 Correlation coefficients of the main study variables Variables Compassion fatigue Medical narrative ability Retention intention Compassion fatigue 1 Medical narrative ability -0.238** 1 Retention intention -0.411** 0.344** 1 ** p < 0.01 Multiple stepwise linear regression analysis of nurse’ retention intention In this study, nurses’ retention intention score was used as the dependent variable, and the statistically significant variables in univariate analysis and correlation analysis were taken as independent variables; we conducted multivariate stepwise linear regression analysis. The independent variable assignment methods were either original value input or dummy variable assignment (age, professional title, professional title, department, working experience, income, number of night shifts per month, working week). The results showed that compassion fatigue, medical narrative ability, age, working week, and how many night shifts a month entered the regression equation ( P < 0.05) (Table 4). Table 4 The multivariate stepwise linear regression analysis of nurse’ retention intention Variables B Beta β t P 95% CI VIF Constant 18.680 0.653 - 28.592 <0.001 17.399-~ 19.960 - Compassion fatigue -0.045 0.003 -0.334 -16.066 <0.001 -0.051 ~ -0.040 1.081 M edical narrative ability 0.040 0.003 0.250 12.115 <0.001 0.034 ~ 0.047 1.068 Age(46-60 years ) 2.008 0.372 0.143 5.392 <0.001 1.278 ~ 2.738 1.752 Age(41-45 years ) 1.788 0.370 0.121 4.836 <0.001 1.064 ~ 2.513 1.576 Age(36-40 years ) 1.135 0.297 0.107 3.818 50h) -1.148 0.332 -0.096 -3.458 0.001 -1.798 ~ -0.497 1.921 Working week(46-50h) -0.633 0.281 -0.071 -2.256 0.024 -1.183 ~ -0.083 2.464 Working week(40-45h) -0.522 0.249 -0.070 -2.100 0.036 -1.010 ~ -0.035 2.773 How many night shifts a month( ＞ 8) -0.554 0.251 -0.062 -2.210 0.027 -1.046 ~ -0.063 1.964 Note. R 2 = 0.275, Adjusted R 2 = 0.270, F = 53.124, P < 0.001 Discussion The results of this study indicated that nurses’ retention intention was at a moderate level, consistent with the findings of Liu et al. [4]. Following the significant economic impact of the global coronavirus pandemic, China has also experienced a general reduction in nurses’ compensation[28]. Moreover, some hospitals in China have cut expenses, increasing the risk of layoffs and bankruptcy, which has inadvertently heightened work pressure on nurses and influenced their retention intention[8]. With the intensification of global aging, the demand for medical care among the elderly in China has risen. Long-term high-intensity work, emotionally demanding labor, and relatively low salaries are likely key factors contributing to nurses’ reduced retention intention[29]. The decline in nurses’ retention intention not only exacerbates nurse turnover but also threatens the quality of nursing services and the stability of the healthcare system. Therefore, it is recommended that nursing managers enhance retention intention by improving salary and welfare benefits, offering career development and promotion opportunities, and ensuring rational allocation of human resources[30]. Our research findings indicate that the higher the compassion fatigue of nurses is, the lower their retention intention will be. This finding underscores the substantial impact of compassion fatigue, a specific manifestation of occupational fatigue, on nursing professionals. Research indicates that nurses experience high levels of emotional labor, particularly in high-pressure departments such as emergency and ICU units, leading to elevated levels of compassion fatigue[31]. Intense and close emotional interactions with critically ill or terminally ill patients can intensify emotional consumption, resulting in emotional exhaustion, job burnout, anxiety, depression, and other mental health issues, thereby diminishing career satisfaction and retention intention[32]. Therefore, hospital and nursing managers should be aware of the long-term effects of compassion fatigue and invite relevant psychotherapists to implement interventions such as cognitive behavioral therapy (CBT) and mindfulness-based stress reduction (MBSR) [33, 34]. Additionally, providing adequate organizational support, reasonable scheduling, and workload adjustments can help alleviate compassion fatigue and enhance nurses’ retention intention. Our research findings indicate that the higher the medical narrative ability of nurses is, the stronger their retention intention in their positions will be. Specifically, as nurses’ medical narrative ability increases, so does their retention intention. This ability not only enhances emotional interaction with patients but also strengthens nurses’ identification with their professional roles[35]. Effective communication through storytelling allows nurses to build stronger trust relationships with patients, better understand patient emotions and needs, and thereby increase their sense of identity and engagement in nursing work[20]. This finding aligns with existing research that identifies medical narrative ability as a critical factor in enhancing nurses’ emotional support and professional value[20]. By improving this skill, nurses can achieve greater job satisfaction, harmonize nurse-patient relationships, and reduce work-related stress, ultimately boosting their retention intention. Therefore, it is recommended that hospitals and nursing managers regularly implement narrative medicine training programs while providing comprehensive emotional and psychological support to help nurses enhance their communication skills, empathize with patients, manage emotional demands, and improve overall job satisfaction and retention intention[36, 37]. This study reveals that compared with nurses aged 18-25, those aged 31-60 show a stronger retention intention, while younger nurses have a lower retention intention. Research indicates that older nurses, having experienced multiple career stages, typically possess extensive work experience and a strong sense of professional identity, enabling them to maintain high retention intention despite work pressures[38]. In contrast, younger nurses in the early stages of their careers are more prone to job burnout within a relatively short period due to uncertainties in career development paths, excessive occupational pressure, unclear career prospects, and dissatisfaction with salary and benefits[39]. Additionally, young nurses often face instability in personal and family life, leading to higher career mobility and greater susceptibility to changes in the external environment and career opportunities, which further reduces their retention intention[40]. Therefore, it is recommended that hospital managers provide older nurses with more challenging positions, management opportunities, or academic research spaces to sustain their work motivation and loyalty[41]. For younger nurses, offering comprehensive vocational training, promotion opportunities, and career planning can effectively enhance their retention intention[42, 43]. Our research reveals that compared with nurses working 40 hours or less per week, those working more than 40 hours per week have a lower retention intention. This finding highlights the adverse impact of frequent overtime on the mental health and retention intention of nurses, providing an important basis for improving working conditions in the nursing industry and increasing the retention intention[44]. In China, the shortage of nursing human resources has led to widespread overtime work among nurses. Research indicates that nurses working longer hours experience higher levels of occupational fatigue and emotional strain, which diminishes their enthusiasm for nursing and reduces their willingness to remain in the profession[45]. The excessive workload, particularly for frontline clinical nurses, not only compromises their quality of life and personal relationships but also poses significant health risks, ultimately affecting career development and retention intention[46]. Therefore, ensuring a reasonable distribution of working hours to promote work-life balance is essential for enhancing nurses’ retention intention[47]. This study reveals that nurses who work more than eight night shifts per month have a lower retention intention compared to those who do not work night shifts. Prolonged nocturnal work disrupts circadian rhythms, leading to diminished sleep quality and compromised immune function, among other health issues[48]. Additionally, night shifts are typically characterized by heavy workloads and high psychological stress. Night shift nurses often bear greater responsibilities independently, which can negatively impact their family life and social interactions. This heightened emotional burden not only exacerbates psychological pressure but also diminishes job satisfaction and enthusiasm, thereby affecting retention intention[49]. Therefore, it is recommended that nursing managers optimize the scheduling of night shifts to prevent clustering of consecutive night shifts and ensure adequate rest periods between shifts[50, 51]. Furthermore, enhancing working conditions for night shift nurses, such as providing comfortable rest areas and appropriate financial incentives, can effectively alleviate the associated stress and fatigue[50, 51]. Limitations This research explored the connections among compassion fatigue, medical narrative ability, and nurses’ retention intention. Utilizing a multi-center cross-sectional survey approach, this study bolstered the reliability and applicability of its outcomes, thereby offering a theoretical basis for formulating specific intervention strategies aimed at enhancing nurses’ retention intention. Despite its significant contributions, the study is not without limitations. Firstly, the limitations of the sampling method. This study adopted a convenience sampling method, which may lead to sample selection bias and thereby affect the representativeness and generalizability of the research results. Therefore, future studies should consider more representative sampling strategies (such as stratified sampling) to enhance the sample's reflection of the target population. Secondly, the limitations of the measurement tools. This study mainly relied on self-report questionnaires for data collection, which may be influenced by subjective factors such as social desirability bias and recall bias, potentially reducing the accuracy of variable measurement. Thus, it is recommended that future studies combine intervention studies or qualitative research methods to enhance the objectivity and depth of the data. Thirdly, the limitations of sample representativeness. The sample used in this study was only drawn from Chinese hospitals, and the research conclusions may be influenced by specific cultural backgrounds. To verify the universality of the research conclusions and explore the moderating role of cultural factors, conducting cross-cultural comparative studies in the future is of great significance. Finally, the limitations of not including key confounding factors. This study did not consider some known organizational and psychosocial factors that have significant impacts on nurses’ retention intention, such as leadership support, workload perception, and job satisfaction. The absence of these variables may weaken the explanatory power of the research model for the variation in retention intention and affect the completeness and external validity of the research conclusions. Therefore, it is suggested that future studies further include and explore the relationships between these variables and the retention intention. In addition, in the future, methods such as probability sampling, multilevel modeling, validated tools, and prospective data collection can be adopted to better highlight the value of the research. Conclusion This research indicated that nurses demonstrated a moderate retention intention. The study found that compassion fatigue had an inverse relationship with retention intention, whereas medical narrative ability showed a positive correlation. The findings of this study hold both theoretical innovation value and practical significance. On one hand, it integrates medical humanities and occupational psychology, providing a new framework for understanding nurses’ professional experiences and their retention intention. On the other hand, it directly addresses the core issue of global nursing workforce shortages and high turnover rates, offering clear, evidence-based intervention directions and improvement strategies for healthcare institutions, educational institutions, and policymakers. These strategies aim to enhance nurses' well-being, strengthen their professional resilience, and ultimately stabilize the nursing workforce and ensure high-quality medical services. Declarations Acknowledgments We thank all the participants in this study. Author contributions Y L, L Z, X Z, Z H, P Y, J W, J L and Y H conducted the research design and collected data. Y L, J W, and L Z analysed the data and wrote the manuscript. Y L, J W, L Z, J Land Y H revised the manuscript. All authors approved the final version for submission. Funding This research was supported by the Sichuan Medical and Health Care Promotion Institute Scientific Research Project (No. KY2023QN0218; No.KY2024SJ0232), the research project of Sichuan Gerontology Society (No.24SCLN0124), the research project of Sichuan Applied Psychology Research Center (No. CSXL-24308), and the Primary Health Development Research Center of Sichuan Province Program (No.SWFZ23-Y-21), the 2023 Scientific Research Project of Mianyang City Health Commission (NO.202318)，and the Yaan Applied Technology Research and Development Project in 202(NO.32). Data availability statement The data on which the results of this study are based can be obtained from the corresponding author. Ethics approval and consent to participate Ethical approval for this study was obtained from the Ethics Committee of Sichuan Taikang Hospital (No. SCTK-IRB-2024-030). This research was conducted in strict accordance with the Helsinki Declaration. All the data collected were anonymized and strictly kept confidential. Informed consent was obtained from all participants. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Clinical trial number Not applicable. References Min D, et al. Factors associated with retention intention of Registered Nurses in Korean nursing homes. Int Nurs Rev. 2022;69(4):459. Cho EY, Wee H. Factors Affecting Nurse Retention Intention: With a Focus on Shift Nurses in South Korea. Healthc (Basel). 2023;11:8. Lee Y, Hwang WJ. The impact of nurse’s sense of calling, organizational commitment, job stress, and nursing work environment on patient safety management activities in comprehensive nursing care service units during the covid-19 pandemic. BMC Nurs. 2024;23(1):311. Liu J, et al. Relationship between Spiritual Care Competence, Perceived Professional Benefit, and Retention Intention among Intern Nursing Students: A Correlational Study. 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Relationship Between Perceived Organizational Support, Work Well-Being, and Medical Narrative Ability Among Nurses: A Cross‐Sectional Multicenter Study. J Nurs Adm Manag.2024;2024(1). Wit RF, et al. International comparison of professional competency frameworks for nurses: a document analysis. BMC Nurs. 2023;22(1):343. Liu D, et al. The effect of perceived organizational support and ego-resilience on the relationship between occupational stressors and compassion fatigue in COVID-19 frontline nurses: a cross-sectional study in Sichuan, China. BMC Nurs. 2024;23(1):817. Mansouri P, et al. The relationship between professional quality of life and sleep quality among nurses working in intensive care units: a cross-sectional study. BMC Nurs. 2025;24(1):34. Zhang J, et al. Clinical nurses’ compassion fatigue psychological experience process: a constructivist grounded theory study. BMC Nurs. 2023;22(1):487. Taşdemir H 0, et al. Unveiling the burden of compassion fatigue in nurses. Nurs Ethics. 2024;31(2–3):371. Lee SH, Joo MH. The Moderating Effects of Self-Care on the Relationships between Perceived Stress, Job Burnout and Retention Intention in Clinical Nurses. Healthcare (Basel).2023;11(13). Bu T, et al. Nurse burnout: deep connections and solutions revealed by network analysis. BMC Nurs. 2024;23(1):531. Zhang YY, et al. Extent of compassion satisfaction, compassion fatigue and burnout in nursing: A meta-analysis. J Nurs Manag. 2018;26(7):810. Hogan B, Drentea P. Secondary emotional labor: How female nurses respond to the contradictions of caring. Health (London). 2023;27(6):924. Yu Y et al. Medical narrative ability and humanistic care ability of Chinese clinical nurses: The mediating role of empathy ability. J Eval Clin Pract,2024;14046. Lv J, et al. The mediating effect of nurses’ narrative ability on humanistic caring ability and humanistic caring behavior. Asian J Surg. 2024;47(6):2778. Wang L, Zhou Q, Hu A. An Analysis of the Current Situation and Influence Factors of Narrative Competence Among Nurses in VIP Ward. Altern Ther Health Med. 2024;30(11):369. Tang H, An S, Zhang L, Xiao Y, Li X. The Antecedents and Outcomes of Public Service Motivation: A Meta-Analysis Using the Job Demands-Resources Model. Behav SCI-Basel.2024; 14(10). Tao H, Wang L. Revision of the Chinese version of nurse retention intention questionnaire. J Second Military Med Univ. 2010;31(08):925. Ma W, et al. Establishment and validity test of medical narrative ability scale for medical staff. Chin J Nurs. 2020;55(04):578. Adams RE, Boscarino JA, Figley CR. Compassion fatigue and psychological distress among social workers: a validation study. Am J Orthopsychiatry. 2006;76(1):103. Sun B, et al. Validation of the Compassion Fatigue Short Scale among Chinese medical workers and firefighters: a cross-sectional study. BMJ Open. 2016;6(6):e011279. Yang YH, Wei LC. Addressing nurse burnout and retention during COVID-19: Reflections on Dincer and Altay’s study. J Eval Clin Pract.2024. He X, et al. Factors influencing the development of nursing professionalism: a descriptive qualitative study. BMC Nurs. 2024;23(1):283. Pressley C, Garside J. Safeguarding the retention of nurses: A systematic review on determinants of nurse's intentions to stay. Nurs Open. 2023;10(5):2842. Chen X, et al. Latent profiles of nurses' moral resilience and compassion fatigue. Nurs Ethics. 2024;31(4):635. Santos L, et al. Compassion Fatigue: A Comprehensive Discussion on its Development and Repercussions Among Oncology Nurses. Semin Oncol Nurs. 2024;40(4):151655. Rosa WE et al. Adaptation of meaning-centered psychotherapy for healthcare providers to buffer work-induced distress and improve wellbeing. Transl Behav Med.2024. Advance online publication. Sarıbudak TP, üstün B. Compassion Fatigue Resiliency Program Effects on Oncology-Hematology Nurses' Professional Quality of Life, Stress Levels, and Patients' Care Satisfaction: Nurse, Nurse Manager, and Patient Perspectives, a Mixed-Methods Study. Semin Oncol Nurs. 2024;40(1):151546. Xue M, et al. Narrative medicine as a teaching strategy for nursing students to developing professionalism, empathy and humanistic caring ability: a randomized controlled trial. BMC Med Educ. 2023;23(1):38. Li Y, et al. Development and psychometric testing of the narrative nursing teaching effectiveness scale: A methodological study. Nurse Educ Today. 2024;133:106060. Yuan J, et al. Narrative medicine in clinical internship teaching practice. Med Educ Online. 2023;28(1):2258000. Shin BJ, Park EY. The life history narrative of clinical nurses with more than 30 years of experience. BMC Nurs. 2022;21(1):93. Joseph B, et al. Factors influencing the transition and retention of mental health nurses during the initial years of practice: Scoping review. J Nurs Manag. 2022;30(8):4274. Chen X, et al. Status and related factors of professional growth among young nursing talents: a cross-sectional study in China. BMC Nurs. 2024;23(1):116. Chiao LH, et al. Exploring factors influencing the retention of nurses in a religious hospital in Taiwan: a cross-sectional quantitative study. BMC Nurs. 2021;20(1):42. Baharum H, et al. Success factors in adaptation of newly graduated nurses: a scoping review. BMC Nurs. 2023;22(1):125. Yamamoto K, et al. Sustaining the nursing workforce - exploring enabling and motivating factors for the retention of returning nurses: a qualitative descriptive design. BMC Nurs. 2024;23(1):248. Camveren H, Arslan YH, Kocaman G. Why do young nurses leave their organization? A qualitative descriptive study. Int Nurs Rev. 2020;67(4):519. Doleman G, De Leo A, Bloxsome D. The impact of pandemics on healthcare providers’ workloads: A scoping review. J Adv Nurs. 2023;79(12):4434. Imes CC, et al. Shift work organization on nurse injuries: A scoping review. Int J Nurs Stud. 2023;138:104395. Emmanuel T, et al. The important factors nurses consider when choosing shift patterns: A cross-sectional study. J Clin Nurs. 2024;33(3):998. Zhang H, et al. Relationship between night shift and sleep problems, risk of metabolic abnormalities of nurses: a 2 years follow-up retrospective analysis in the National Nurse Health Study (NNHS). Int Arch Occup Environ Health. 2023;96(10):1361. Jørgensen JT, et al. Shift work and incidence of psychiatric disorders: The Danish Nurse Cohort study. J Psychiatr Res. 2021;139:132. Shan G, et al. Correction: Authoritarian leadership and nurse presenteeism: the role of workload and leader identification. BMC Nurs. 2023;22(1):3. Additional Declarations No competing interests reported. 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However, recent years have witnessed a concerning increase in nurse turnover rates worldwide, particularly in high-stress environments, where the retention intention declined[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A decrease in retention intention implies greater job mobility and a higher likelihood of nurses leaving their positions. This trend not only jeopardizes the quality and stability of nursing services but also increases recruitment and training costs for hospitals, potentially disrupting the smooth operation of the entire healthcare system[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In China, this phenomenon is particularly striking. With the increasing aging of the population, the impact of COVID-19 on the global economy, and the implementation of Diagnosis Related Groups (DRG)-based medical insurance payment reform in China, nurses\u0026rsquo; retention intention has further decreased[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, layoffs and even bankruptcies at some medical institutions have exacerbated the trend. Therefore, it is crucial to conduct a thorough analysis of the current state of nurses\u0026rsquo; retention intention and its associated factors within nursing management research. Such studies can improve nursing management practices and provide a solid basis for healthcare institutions to formulate effective human resource strategies.\u003c/p\u003e\u003cp\u003eThe retention intention of nurses reflects their desire and probability to continue working in those positions[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The factors that influence this retention intention are diverse and intricate. Studies show that nurses with strong retention intention tend to remain in the nursing field for longer durations, demonstrate higher job involvement, and positively contribute to the quality of nursing care[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. On the other hand, nurses with weaker retention intention are more prone to leaving their jobs, which can negatively impact healthcare organizations and patient outcomes[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A thorough review of existing literature indicates that the primary drivers of nurses\u0026rsquo; retention intention include aspects such as the work environment, compensation, opportunities for career advancement, and personal psychological and emotional well-being[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition, some studies have pointed out that new nurses may experience greater stress due to their lack of experience, while senior nurses may accumulate fatigue due to long-term exposure[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Age, length of service, and professional title are often related to experience, responsibility, and career development stage, which affect stress perception, coping resources, and intention to leave[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, we speculate that these sociodemographic variables may also have some relationship with nurses\u0026rsquo; retention intention. Hao et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] emphasize that rising work pressures have exacerbated psychological challenges among nurses, yet these issues frequently do not receive adequate attention. Additionally, various studies propose that nurses\u0026rsquo; professional capabilities, encompassing clinical expertise, communication skills, and empathetic qualities, can significantly affect their retention intention[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eProlonged high-pressure work environments and emotional investment expose nurses to varying levels of emotional exhaustion, making compassion fatigue a critical concern for occupational mental health. Compassion fatigue is marked by the depletion of emotional, mental, and physical resources due to continuous exposure to the distress and trauma experienced by others[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Studies show that this condition not only negatively impacts the mental well-being of nurses but can also diminish work efficiency, job satisfaction, and the overall quality of nursing care[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. According to Charles Figley\u0026rsquo;s Compassion Fatigue Theory, the main drivers often include the demanding work environment, patient suffering, and the emotional needs of patients[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In intensive nursing roles, while offering emotional support to patients, nurses must also cope with their own emotional strain and occupational stress. This dual burden is frequently the primary factor leading to compassion fatigue, which subsequently affects job satisfaction[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, research by Lee et al.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] highlights a significant link between job burnout and retention intention among nurses, and also indicating a positive correlation between compassion fatigue and job burnout, potentially accelerating turnover rates [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, it is reasonable to infer that compassion fatigue may also be related to the nurses\u0026rsquo; retention intention.\u003c/p\u003e\u003cp\u003eIn recent years, the medical narrative ability of nurses has increasingly attracted academic interest as a critical element in their interaction and communication with patients. Medical narrative ability involves healthcare providers\u0026rsquo; ability to understand and interpret patients\u0026rsquo; accounts of their illnesses, convey the underlying meanings of these narratives accurately, empathize with patients, and advocate for their best interests[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Drawing from Hochschild\u0026rsquo;s Emotional Labor Theory, which posits that service professions demand employees to control and modulate their emotional expressions to fulfill job requirements[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Medical narrative ability can be seen as a type of emotional labor. It requires nurses to manage and express emotions effectively, listen attentively to patients\u0026rsquo; experiences, and cultivate trust and empathy during care[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, nurses often encounter heightened demands for emotional labor, especially when this labor lacks adequate support, potentially leading to greater job burnout and decreased retention intention. Research also suggests that effective medical narratives can strengthen the emotional bond between nurses and patients, enhance patient treatment experiences, and increase patient satisfaction[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. On the other hand, insufficient medical narrative skills may result in suboptimal communication and increased professional stress for nurses[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While some studies have investigated the impact of medical narrative ability on nurses\u0026rsquo; occupational health, fewer have explored its connection with retention intention. Considering the prevalent issues of job burnout and stress among nurses, often associated with lower retention rates[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Medical narrative ability provides a valuable form of emotional support. It enables nurses to better handle emotional challenges at work. We propose that improving medical narrative ability could help alleviate these challenges, and improve nurses\u0026rsquo; retention intention.\u003c/p\u003e\u003cp\u003eNurses\u0026rsquo; retention intention is shaped by an intricate combination of various factors. Although some studies have explored the relevant factors of nurses\u0026rsquo; retention intention, the impact on the specific situation, regional differences and cultural background of Chinese nurses needs to be further studied. At the same time, in combination with the Job Demands-Resources Model (JD-R Model), we regard compassion fatigue as the negative outcome of occupational stressors (emotional demands)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It is the ultimate product of the exhaustion process when job demands are too high and resources are insufficient. High compassion fatigue itself also constitutes a serious internal stressor, further damaging health and job performance. As a result, job satisfaction, organizational commitment, and mental health levels will all decline, and the intention to quit will naturally increase. We consider medical narrative ability as an important personal resource (ability), which includes the ability to understand, communicate, and respond to patients\u0026rsquo; stories (cognitive, emotional, and behavioral dimensions), which may buffer the impact of stress or directly promote the retention intention. And the retention intention is a positive work outcome. Furthermore, there is currently a lack of literature on the relationship between compassion fatigue, medical narrative ability and nurses\u0026rsquo; retention intention. Therefore, this study aims to investigate the current situation of retention intention among Chinese nurses through a multi-center cross-sectional survey, explore the correlation between retention intention, compassion fatigue, and medical narrative ability, and propose strategies to improve nurse\u0026rsquo;s retention intention from a new perspective. This approach seeks to provide theoretical support and practical guidance for enhancing the stability of the nursing team, optimizing the allocation of nursing resources, and improving the quality of nursing services.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eDesign and participants\u003c/h3\u003e\n\u003cp\u003eThis study employed convenience sampling to conduct an online questionnaire survey among 1,831 nurses from 8 hospitals across the country from January to February 2024. The inclusion criteria were as follows: (i) age\u0026nbsp;≥18 years old; (ii) obtain the professional qualification registration of nurses; (iii) voluntary participation in this study;(iv) the working time is more than six months. The exclusion criteria are as follows: (i) nurses who were not on duty during the survey period; (ii) participants who withdrew voluntarily during the study period. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were followed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used four measures to collect data: the sociodemographic questionnaire (gender, age, education level,\u0026nbsp;marital status,\u0026nbsp;professional title,\u0026nbsp;department,\u0026nbsp;working experience,\u0026nbsp;income,\u0026nbsp;how many night shifts a month,\u0026nbsp;have you experienced a major traumatic event in the past year,\u0026nbsp;working week),\u0026nbsp;the Chinese Questionnaire for Nurse Intention to Remain Employed (C-QNIRE),\u0026nbsp;the Medical Narrative Ability Scale\u0026nbsp;(MNAS),\u0026nbsp;and\u0026nbsp;the Chinese version of\u0026nbsp;Compassion\u0026nbsp;Fatigue\u0026nbsp;Short\u0026nbsp;Scale\u0026nbsp;(C-CF- Short Scale).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNurses’ retention intention was measured using the C-QNIRE, which was translated by [24]. The C-QNIRE is a one-dimensional scale consisting of 6 items. Each item is scored on a 1 to 5 Likert scale, with items 2, 3, and 6 reverse-scored. The C-QNIRE ranges from 6 to 30 points. The higher the score, the higher the retention intention. In this study, the Cronbach’s alpha coefficient of the C-QNIRE was 0.749. The content validity correlation coefficients of the items in C-QNIRE range from 0.590 to 0.810.\u003c/p\u003e\n\u003cp\u003eNurses’ medical narrative ability was measured using the MNAS, which was developed by [25]. The MNAS consisted of 27 items categorized into three domains: pay attention and listen, understanding and response, reflection and representation. The items are rated on a 7-point Likert Scale ranging from 1 (“completely inconsistent”) to 7 (“completely consistent”). In order to better present the results, The total score of the scale ranges from 27 to 189 points, and the higher the score, the stronger the medical narrative ability of the individual. In this study, the Cronbach’s alpha coefficient for the MNAS was 0.967 and the content validity was 0.890.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Compassion Fatigue Scale (CFS) was developed by Adams et al.,[26] in 2006. the Chinese version of Compassion Fatigue Short Scale (C-CF-Short Scale) was revised by Lou[27]. The scale consists of two dimensions, secondary traumatic stress (5 items) and burnout (8 items), with a total of 13 items. It uses a Likert 10-point scale from 1(“never”) to 10(“very often”). The total score of this scale ranges from 13 to 130 points, and the higher the score, the higher the level of individual empathy fatigue. Cronbach’s alpha coefficient of the C-CF- Short Scale was 0.955 in this study. The content validity correlation coefficients of the items in C-CF- Short Scale range from 0.830 to 0.870.\u003c/p\u003e\n\u003ch3\u003eData collection and recruitment\u003c/h3\u003e\n\u003cp\u003eWe distributed an online questionnaire to 1,840 eligible and voluntarily active nurses in eight hospitals nationwide. The online questionnaire was created using a survey tool called “So Jump” and delivered through the social software WeChat to the research heads of each hospital. Subsequently, researchers at each hospital selected suitable participants based on predetermined criteria and provided them with information about the purpose of the questionnaire as well as instructions for completion within a designated time frame. To prevent duplicate responses, only one submission per WeChat account was allowed for completing the questions ensuring comprehensive participation. In total, we disseminated 1,840 questionnaires resulting in receiving 1,831 valid responses with an effective recovery rate of 99.5%.\u003c/p\u003e\n\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Ethics Committee of Sichuan Taikang Hospital (No. SCTK-IRB-2024-030). This research was conducted in strict accordance with the Helsinki Declaration. All the data collected were anonymized and strictly kept confidential. Informed consent was obtained from all participants.\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eData analysis was conducted using IBM SPSS 27.0. The normality of distributions for nurses’ retention intention, medical narrative ability, and compassion fatigue was evaluated using Kolmogorov-Smirnov (KS) test. Descriptive statistics were applied to provide an overview of the participants' demographic characteristics and the scores of the main study variables. To assess differences in retention intention according to participant characteristics, one-way ANOVA and independent samples t-tests were employed. Pearson correlation analysis was used to explore the relationships among key variables. Additionally, multiple stepwise linear regression analysis was carried out to determine significant related factors of retention intention. Statistical significance was set at \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 for two-tailed tests.\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003eDescription of the participants\u003c/h3\u003e\n\u003cp\u003eBefore data analysis, we standardized the main variables. In addition, the Harman single-factor test method was used to test the common method bias of the original data. The results showed that there were 8 factors with eigenvalues greater than 1, and the explanation rate of the first factor was 38.22%, which was lower than the critical value of 40%, indicating that there was no common method bias. A total of 1,831 valid questionnaires were collected in this study. Respondents were predominantly female (n = 1,783, 97.4%), and the majority of participants (n = 1,308, 71.4%) had at least a bachelor\u0026rsquo;s degree or above. In addition, only a small percentage of participants (n = 483, 26.4%) were single, divorce or others. About half of the nurses earned less than 5,000 RMB per month (n = 805, 44%). The remaining general demographic information is shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle factor analysis of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eretention intention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKolmogorov-Smirnov (KS) test showed that the data for compassion fatigue, medical narrative ability, and retention intention were approximately normally distributed(\u003cem\u003ep\u003c/em\u003e\u0026gt;0.05). Therefore, mean and standard deviations were used to describe the states of these variables. The differences in the nurses\u0026rsquo; retention intention with the gender, age, professional title, working experience, income, how many night shifts a month, have you experienced a major traumatic event in the past year, and\u0026nbsp;working week (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) (Table1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Personal characteristics and single factor analysis of retention intention\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM \u0026plusmn; SD\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003escore\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e/F\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e2.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e1783 (97.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.83\u0026plusmn;3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e48 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.25\u0026plusmn;4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e17.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e18-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e210 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.70\u0026plusmn;3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e26-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e601 (32.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.33\u0026plusmn;3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e31-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e500 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.71\u0026plusmn;3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e36-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e259 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.21\u0026plusmn;3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e41-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e124 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e24.18\u0026plusmn;3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e46-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e137 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e24.72\u0026plusmn;3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e19.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e1348 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.06\u0026plusmn;3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e410 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.81\u0026plusmn;3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eDivorce or others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e73 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.37\u0026plusmn;3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e-0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e0.642\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e523 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.73\u0026plusmn;3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eUniversity or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e1308 (71.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.82\u0026plusmn;3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional title\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\n \u003cp\u003e14.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003enurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e267 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.21\u0026plusmn;3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003esenior nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e738 (40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.41\u0026plusmn;3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003enurse-in-charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e701 (38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.15\u0026plusmn;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eassociate chief nurse or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e125 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e24.28\u0026plusmn;3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepartment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e1.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eInternal medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e688 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.54\u0026plusmn;3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eSurgical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e432 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.75\u0026plusmn;3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003ePediatric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e86 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.34\u0026plusmn;3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eObstetrics and gynecology\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e115 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.33\u0026plusmn;3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eOutpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e83 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.43\u0026plusmn;3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eEmergency\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e87 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.55\u0026plusmn;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eOthers\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e340 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.93\u0026plusmn;3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking experience (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e19.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e212 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.77\u0026plusmn;3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e3-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e319 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.38\u0026plusmn;3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e6-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e426 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.23\u0026plusmn;3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e11-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e521 (28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.04\u0026plusmn;3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e＞15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e353 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e24.08\u0026plusmn;3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome (RMB / month)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e10.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e＜3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e106（5.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.32\u0026plusmn;4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e3000-5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e699 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.64\u0026plusmn;3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e5001-10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e978 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.98\u0026plusmn;3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e＞10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e48 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e24.44\u0026plusmn;2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHow many night shifts a month\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e17.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e406 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.66\u0026plusmn;3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e569（31.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.02\u0026plusmn;3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e5-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e455（24.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.51\u0026plusmn;3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e＞8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e401（21.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.90\u0026plusmn;3.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave you experienced a major traumatic event in the past year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e2.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e1703（93.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.85\u0026plusmn;3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e128（7.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.93\u0026plusmn;3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking week\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003ehours\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.5289%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9752%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\n \u003cp\u003e14.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u0026lt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e195（10.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.59\u0026plusmn;3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e40-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e1038（56.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e23.03\u0026plusmn;3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e46-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e402（22.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e22.43\u0026plusmn;3.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7438%;\"\u003e\n \u003cp\u003e\u0026gt;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.5289%;\"\u003e\n \u003cp\u003e196（10.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9752%;\"\u003e\n \u003cp\u003e21.46\u0026plusmn;3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.876%;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive Statistics of compassion fatigue, medical narrative ability, and retention intention\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the total mean score of nurses\u0026rsquo; compassion fatigue, medical narrative ability, and retention intention were 48.03\u0026plusmn;27.27, 154.48\u0026plusmn;22.93,\u0026nbsp;22.79\u0026plusmn;3.71\u0026nbsp;(Table\u0026nbsp;2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003cstrong\u003eable2\u003c/strong\u003e Descriptive analyses of\u0026nbsp;compassion fatigue, medical narrative ability, and retention intention\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"653\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM \u0026plusmn; SD\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003escore\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eompassion fatigue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eSecondary traumatic stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e16.60\u0026plusmn;10.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eBurnout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e31.43\u0026plusmn;17.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eTotal score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e48.03\u0026plusmn;27.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003eedical narrative ability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60.7034%;\"\u003e\n \u003cp\u003ePay attention and listen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e50.06\u0026plusmn;7.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eUnderstanding and response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e69.48\u0026plusmn;11.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eReflection and representation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e34.94\u0026plusmn;5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eTotal score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e154.48\u0026plusmn;22.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRetention intention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60.7034%;\"\u003e\n \u003cp\u003eTotal score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.2446%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.3028%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.7492%;\"\u003e\n \u003cp\u003e22.79\u0026plusmn;3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation between nurses\u0026rsquo; compassion fatigue, medical narrative ability, and\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eretention intention\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the Pearson correlation indicated that compassion fatigue was negatively correlated with medical narrative ability (\u003cem\u003er\u003c/em\u003e = -0.238, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01) and retention intention (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= -0.411, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01). The medical narrative ability was positively correlated with retention intention (\u003cem\u003er\u0026nbsp;\u003c/em\u003e= 0.344, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eCorrelation coefficients of the main study variables\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34.4209%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.1436%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompassion fatigue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.9233%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical narrative ability \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.5122%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRetention intention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.4209%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompassion fatigue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.1436%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9233%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5122%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.4209%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical narrative ability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.1436%;\"\u003e\n \u003cp\u003e-0.238**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9233%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5122%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.4209%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRetention intention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.1436%;\"\u003e\n \u003cp\u003e-0.411**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9233%;\"\u003e\n \u003cp\u003e0.344**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.5122%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e**\u003cem\u003ep \u0026lt; 0.01\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple stepwise linear regression analysis of nurse\u0026rsquo; retention intention\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, nurses\u0026rsquo; retention intention score was used as the dependent variable, and the statistically significant variables in univariate analysis and correlation analysis were taken as independent variables; we conducted multivariate stepwise linear regression analysis. The independent variable assignment methods were either original value input or dummy variable assignment (age, professional title, professional title, department, working experience, income, number of night shifts per month, working week). The results showed that compassion fatigue, medical narrative ability, age, working week, and how many night shifts a month entered the regression equation (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eThe multivariate stepwise linear regression analysis of nurse\u0026rsquo; retention intention\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"637\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBeta\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.675%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVIF\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e18.680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e28.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e17.399-~ 19.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompassion fatigue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e-0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e-0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e-16.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e-0.051 ~ -0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003eedical narrative ability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e12.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e0.034 ~ 0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(46-60\u003c/strong\u003e\u003cstrong\u003eyears\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e2.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e5.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e1.278 ~ 2.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(41-45\u003c/strong\u003e\u003cstrong\u003eyears\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e1.788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e4.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e1.064 ~ 2.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(36-40\u003c/strong\u003e\u003cstrong\u003eyears\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e1.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e3.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e0.552 ~ 1.718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.960\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(31-35y\u003c/strong\u003e\u003cstrong\u003eears\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e2.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e0.263 ~ 1.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e2.479\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking week(\u0026gt;50h)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e-1.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e-0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e-3.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e-1.798 ~ -0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.921\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking week(46-50h)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e-0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e-0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e-2.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e-1.183 ~ -0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e2.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorking week(40-45h)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e-0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e-0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e-2.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e-1.010 ~ -0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e2.773\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26.8446%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHow many night shifts a month(\u003c/strong\u003e\u003cstrong\u003e＞\u003c/strong\u003e\u003cstrong\u003e8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.89011%;\"\u003e\n \u003cp\u003e-0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e-0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.675%;\"\u003e\n \u003cp\u003e-2.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.10518%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.5824%;\"\u003e\n \u003cp\u003e-1.046 ~ -0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote.\u0026nbsp;\u003cem\u003eR\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e\u003c/em\u003e= 0.275, Adjusted\u003cem\u003e\u0026nbsp;R\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e\u003c/em\u003e= 0.270, \u003cem\u003eF\u0026nbsp;\u003c/em\u003e= 53.124, \u003cem\u003eP \u0026lt;\u003c/em\u003e 0.001\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of this study indicated that nurses’ retention intention was at a moderate level, consistent with the findings of Liu et al. [4]. Following the significant economic impact of the global coronavirus pandemic, China has also experienced a general reduction in nurses’ compensation[28]. Moreover, some hospitals in China have cut expenses, increasing the risk of layoffs and bankruptcy, which has inadvertently heightened work pressure on nurses and influenced their retention intention[8]. With the intensification of global aging, the demand for medical care among the elderly in China has risen. Long-term high-intensity work, emotionally demanding labor, and relatively low salaries are likely key factors contributing to nurses’ reduced retention intention[29]. The decline in nurses’ retention intention not only exacerbates nurse turnover but also threatens the quality of nursing services and the stability of the healthcare system. Therefore, it is recommended that nursing managers enhance retention intention by improving salary and welfare benefits, offering career development and promotion opportunities, and ensuring rational allocation of human resources[30].\u003c/p\u003e\n\u003cp\u003eOur research findings indicate that the higher the compassion fatigue of nurses is, the lower their retention intention will be. This finding underscores the substantial impact of compassion fatigue, a specific manifestation of occupational fatigue, on nursing professionals. Research indicates that nurses experience high levels of emotional labor, particularly in high-pressure departments such as emergency and ICU units, leading to elevated levels of compassion fatigue[31]. Intense and close emotional interactions with critically ill or terminally ill patients can intensify emotional consumption, resulting in emotional exhaustion, job burnout, anxiety, depression, and other mental health issues, thereby diminishing career satisfaction and retention intention[32]. Therefore, hospital and nursing managers should be aware of the long-term effects of compassion fatigue and invite relevant psychotherapists to implement interventions such as cognitive behavioral therapy (CBT) and mindfulness-based stress reduction (MBSR) [33, 34]. Additionally, providing adequate organizational support, reasonable scheduling, and workload adjustments can help alleviate compassion fatigue and enhance nurses’ retention intention.\u003c/p\u003e\n\u003cp\u003eOur research findings indicate that the higher the medical narrative ability of nurses is, the stronger their retention intention in their positions will be. Specifically, as nurses’ medical narrative ability increases, so does their retention intention. This ability not only enhances emotional interaction with patients but also strengthens nurses’ identification with their professional roles[35]. Effective communication through storytelling allows nurses to build stronger trust relationships with patients, better understand patient emotions and needs, and thereby increase their sense of identity and engagement in nursing work[20]. This finding aligns with existing research that identifies medical narrative ability as a critical factor in enhancing nurses’ emotional support and professional value[20]. By improving this skill, nurses can achieve greater job satisfaction, harmonize nurse-patient relationships, and reduce work-related stress, ultimately boosting their retention intention. Therefore, it is recommended that hospitals and nursing managers regularly implement narrative medicine training programs while providing comprehensive emotional and psychological support to help nurses enhance their communication skills, empathize with patients, manage emotional demands, and improve overall job satisfaction and retention intention[36, 37].\u003c/p\u003e\n\u003cp\u003eThis study reveals that compared with nurses aged 18-25, those aged 31-60 show a stronger retention intention, while younger nurses have a lower retention intention. Research indicates that older nurses, having experienced multiple career stages, typically possess extensive work experience and a strong sense of professional identity, enabling them to maintain high retention intention despite work pressures[38]. In contrast, younger nurses in the early stages of their careers are more prone to job burnout within a relatively short period due to uncertainties in career development paths, excessive occupational pressure, unclear career prospects, and dissatisfaction with salary and benefits[39]. Additionally, young nurses often face instability in personal and family life, leading to higher career mobility and greater susceptibility to changes in the external environment and career opportunities, which further reduces their retention intention[40]. Therefore, it is recommended that hospital managers provide older nurses with more challenging positions, management opportunities, or academic research spaces to sustain their work motivation and loyalty[41]. For younger nurses, offering comprehensive vocational training, promotion opportunities, and career planning can effectively enhance their retention intention[42, 43].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur research reveals that compared with nurses working 40 hours or less per week, those working more than 40 hours per week have a lower retention intention. This finding highlights the adverse impact of frequent overtime on the mental health and retention intention of nurses, providing an important basis for improving working conditions in the nursing industry and increasing the retention intention[44]. In China, the shortage of nursing human resources has led to widespread overtime work among nurses. Research indicates that nurses working longer hours experience higher levels of occupational fatigue and emotional strain, which diminishes their enthusiasm for nursing and reduces their willingness to remain in the profession[45]. The excessive workload, particularly for frontline clinical nurses, not only compromises their quality of life and personal relationships but also poses significant health risks, ultimately affecting career development and retention intention[46]. Therefore, ensuring a reasonable distribution of working hours to promote work-life balance is essential for enhancing nurses’ retention intention[47].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study reveals that nurses who work more than eight night shifts per month have a lower retention intention compared to those who do not work night shifts. Prolonged nocturnal work disrupts circadian rhythms, leading to diminished sleep quality and compromised immune function, among other health issues[48]. Additionally, night shifts are typically characterized by heavy workloads and high psychological stress. Night shift nurses often bear greater responsibilities independently, which can negatively impact their family life and social interactions. This heightened emotional burden not only exacerbates psychological pressure but also diminishes job satisfaction and enthusiasm, thereby affecting retention intention[49]. Therefore, it is recommended that nursing managers optimize the scheduling of night shifts to prevent clustering of consecutive night shifts and ensure adequate rest periods between shifts[50, 51]. Furthermore, enhancing working conditions for night shift nurses, such as providing comfortable rest areas and appropriate financial incentives, can effectively alleviate the associated stress and fatigue[50, 51].\u003c/p\u003e\n\u003ch2\u003eLimitations\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis research explored the connections among compassion fatigue, medical narrative ability, and nurses’ retention intention. Utilizing a multi-center cross-sectional survey approach, this study bolstered the reliability and applicability of its outcomes, thereby offering a theoretical basis for formulating specific intervention strategies aimed at enhancing nurses’ retention intention. Despite its significant contributions, the study is not without limitations. Firstly, the limitations of the sampling method. This study adopted a convenience sampling method, which may lead to sample selection bias and thereby affect the representativeness and generalizability of the research results. Therefore, future studies should consider more representative sampling strategies (such as stratified sampling) to enhance the sample's reflection of the target population. Secondly, the limitations of the measurement tools. This study mainly relied on self-report questionnaires for data collection, which may be influenced by subjective factors such as social desirability bias and recall bias, potentially reducing the accuracy of variable measurement. Thus, it is recommended that future studies combine intervention studies or qualitative research methods to enhance the objectivity and depth of the data. Thirdly, the limitations of sample representativeness. The sample used in this study was only drawn from Chinese hospitals, and the research conclusions may be influenced by specific cultural backgrounds. To verify the universality of the research conclusions and explore the moderating role of cultural factors, conducting cross-cultural comparative studies in the future is of great significance. Finally, the limitations of not including key confounding factors. This study did not consider some known organizational and psychosocial factors that have significant impacts on nurses’ retention intention, such as leadership support, workload perception, and job satisfaction. The absence of these variables may weaken the explanatory power of the research model for the variation in retention intention and affect the completeness and external validity of the research conclusions. Therefore, it is suggested that future studies further include and explore the relationships between these variables and the retention intention. In addition, in the future, methods such as probability sampling, multilevel modeling, validated tools, and prospective data collection can be adopted to better highlight the value of the research.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis research indicated that nurses demonstrated a moderate retention intention. The study found that compassion fatigue had an inverse relationship with retention intention, whereas medical narrative ability showed a positive correlation. The findings of this study hold both theoretical innovation value and practical significance. On one hand, it integrates medical humanities and occupational psychology, providing a new framework for understanding nurses\u0026rsquo; professional experiences and their retention intention. On the other hand, it directly addresses the core issue of global nursing workforce shortages and high turnover rates, offering clear, evidence-based intervention directions and improvement strategies for healthcare institutions, educational institutions, and policymakers. These strategies aim to enhance nurses\u0026apos; well-being, strengthen their professional resilience, and ultimately stabilize the nursing workforce and ensure high-quality medical services.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the participants in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY L, L Z, X Z, Z H, P Y, J W, J L and Y H conducted the research design and collected data. Y L, J W, and L Z analysed the data and wrote the manuscript. Y L, J W, L Z, J Land Y H revised the manuscript. All authors approved the final version for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Sichuan Medical and Health Care Promotion Institute Scientific Research Project (No. KY2023QN0218; No.KY2024SJ0232), the research project of Sichuan Gerontology Society (No.24SCLN0124), the research project of Sichuan Applied Psychology Research Center (No. CSXL-24308), and the Primary Health Development Research Center of Sichuan Province Program (No.SWFZ23-Y-21), the 2023 Scientific Research Project of Mianyang City Health Commission (NO.202318)，and the Yaan Applied Technology Research and Development Project \u0026nbsp;in 202(NO.32).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data on which the results of this study are based can be obtained from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Ethics Committee of Sichuan Taikang Hospital (No. SCTK-IRB-2024-030). This research was conducted in strict accordance with the Helsinki Declaration. All the data collected were anonymized and strictly kept confidential. Informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMin D, et al. Factors associated with retention intention of Registered Nurses in Korean nursing homes. Int Nurs Rev. 2022;69(4):459.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCho EY, Wee H. 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J Clin Nurs. 2024;33(3):998.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang H, et al. Relationship between night shift and sleep problems, risk of metabolic abnormalities of nurses: a 2 years follow-up retrospective analysis in the National Nurse Health Study (NNHS). Int Arch Occup Environ Health. 2023;96(10):1361.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJ\u0026oslash;rgensen JT, et al. Shift work and incidence of psychiatric disorders: The Danish Nurse Cohort study. J Psychiatr Res. 2021;139:132.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShan G, et al. Correction: Authoritarian leadership and nurse presenteeism: the role of workload and leader identification. BMC Nurs. 2023;22(1):3.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Nurse, Compassion fatigue, Medical narrative ability, Retention intention","lastPublishedDoi":"10.21203/rs.3.rs-5870594/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5870594/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eIn recent years, due to the increase in care demands caused by population aging and the rise in nurse-patient conflicts, the retention intention of nurses has become an urgent global issue, as high turnover rates pose significant challenges to healthcare systems around the world. Therefore, this study will explore nurses\u0026rsquo; retention intention and the associated factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis multi-center cross-sectional study recruited 1,831 nurses from eight hospitals across China between January and February 2024 through convenience sampling. Data collection was conducted using online surveys. The questionnaire was divided into four sections: the sociodemographic questionnaire, the Chinese Questionnaire for Nurse Intention to Remain Employed (C-QNIRE), the Medical Narrative Ability Scale (MNAS), and the Chinese version of Compassion Fatigue Short Scale (C-CF-Short Scale). We utilized descriptive statistics, normality test, one-way ANOVA, t-tests, Pearson correlation analysis, and multiple linear regression analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe results of this study showed that the total score of nurses\u0026rsquo; retention intention was 22.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71. The Multiple stepwise linear regression results showed that compassion fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.334, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), medical narrative ability(\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.250, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age (46-60years) (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.143, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age (41-45years) (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.121, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age (36-40years) (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.107, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age (31-35years) (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.093, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), working week(\u0026gt;\u0026thinsp;50h) (\u003cem\u003eβ\u003c/em\u003e = -0.096, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05),working week(46-50h) (\u003cem\u003eβ\u003c/em\u003e = -0.071, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05),working week(40-45h) (\u003cem\u003eβ\u003c/em\u003e = -0.070, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05),how many night shifts a month(\u0026gt;8) (\u003cem\u003eβ\u003c/em\u003e = -0.062, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were the main associated factors of nurses\u0026rsquo; retention intention, explaining 27.0% of the total variation.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study indicated that nurses demonstrate a moderate retention intention. Nursing administrators and educators should address this issue by proactively introducing strategies to reduce compassion fatigue and improve narrative medicine ability among nursing staff. Such initiatives can positively impact nurses\u0026rsquo; retention intention, thereby reducing the turnover of skilled nursing personnel. This is essential for effective management of nursing human resources and enhancing the overall quality of nursing care.\u003c/p\u003e","manuscriptTitle":"Relationship between Compassion fatigue, Medical Narrative Ability, and Retention intention among Nurses: A Cross-Sectional Multi- center Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 09:02:25","doi":"10.21203/rs.3.rs-5870594/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"662c98c3-352c-4bb8-ae91-dac28a1b1ce4","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T08:57:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-04 09:02:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5870594","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5870594","identity":"rs-5870594","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}