The Role of Professional Grief in Moderating Job Stress and Turnover Intention Among Nurses

The Role of Professional Grief in Moderating Job Stress and Turnover Intention Among Nurses | 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 The Role of Professional Grief in Moderating Job Stress and Turnover Intention Among Nurses Xue Liang, Jue Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5713235/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in BMC Psychology → Version 1 posted 9 You are reading this latest preprint version Abstract Background Nurses, as the largest workforce in healthcare, play a crucial role in achieving universal health coverage. However, they continually face both physical and emotional burdens. Identifying key stressors that contribute to turnover intention and examining whether professional grief moderates the relationship between job stress and turnover intention is essential for reducing nurse attrition. Methods This study utilized linear regression models and the Extreme Gradient Boosting machine (XGBoost) learning algorithm to analyze the impact of the total score of job stress and their dimensions on turnover intention. XGBoost, known for enhancing sensitivity in detection and improving generalization performance, is particularly beneficial for high-dimensional problems and data heterogeneity. It integrates multiple variables and accommodates small sample sizes, making it a valuable supplement to conventional regression techniques. Through hierarchical regression, the moderating role of professional grief between job stress and turnover intention was explored. Additionally, an interactive tool was used to visually present the results. Results Among the dimensions of job stress, patient care issues exhibited the strongest association with turnover intention, followed by nursing profession and work problems, time allocation and workload, management and interpersonal issues, and working environment and equipment problems. Notably, professional grief significantly moderated the relationship between job stress and turnover intention. Specifically, for overall job stress and the dimensions of nursing profession and work-related problems, time allocation and workload, and patient care issues, higher levels of professional grief intensified their impact on turnover intention. However, this moderating effect was not observed for stressors related to management and interpersonal issues or working environment and equipment problems. Conclusion In emotionally labor-intensive work environments, professional grief tends to amplify turnover intention, while its impact on issues related to management and material resources is less pronounced.Healthcare policymakers should focus on job stress and professional grief to reduce turnover intention, ultimately benefiting patient care and treatment outcomes. Nursing Turnover intention Job stress Professional grief Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 13 Figure 14 Figure 15 Introduction Nurses are the largest workforce in the health-care system and play a important role in achieving the goals of universal health coverage and sustainable development [ 1 ]. With rapid socio-economic development and changes in demographic structures, nurse shortages have become a widespread issue globally [ 2 ]. According to “The State of the world’s nursing 2020 report” jointly published by the World Health Organization (WHO) and the International Council of Nurses (ICN), without intervention, the global nursing workforce shortage is projected to reach 5.7 million by 2030 [ 3 ]. High turnover rates are a key factor in the shortage of nurses [ 4 ] and can affect quality and safety of care, leading to decreased patient satisfaction, increased errors in care, and higher mortality risks [ 5 ]. Additionally, the departure of colleagues can influence the turnover intention of remaining nurses, thereby exacerbating workforce instability and creating a vicious cycle [ 6 ]. For organizations, nurse turnover and the associated costs of recruitment increase operational expenses, and if nurses leave the profession, it also results in the loss of educational investments [ 7 ]. Therefore, reducing nurse turnover is considered an effective strategy to address nursing shortages, enhance healthcare service quality, and improve patient safety, while also helping to reduce healthcare institution costs [ 8 ]. Consequently, the timely and accurate identification of high turnover intention, followed by appropriate interventions, has become a key concern for healthcare managers [ 9 ]. The occupational characteristics of nursing involve numerous stressors, such as heavy workloads, complex tasks, and the need for continued attention [ 10 ]. These factors render nursing a profession marked by high responsibility, elevated risk, and intense pressure, resulting in significantly higher levels of job stress compared to other professional groups [ 11 ]. Existing research generally agrees that job stress is a key factor influencing nurses' turnover intention. The greater the job stress, the stronger the turnover intention [ 12 , 13 ]. However, given that hospital administrative systems are often constrained by regulations and reimbursement policies, identifying the specific aspects of job stress that are most closely related to turnover intention can provide economically viable solutions to alleviate the problem. [ 14 ]. Beyond physical and cognitive demands, nursing also involves significant emotional labor, requiring professionals to regulate their emotions while providing compassionate care [ 17 ]. In this context, professional grief emerges as a crucial yet often overlooked factor influencing nurses’ well-being. Professional grief refers to the emotional distress experienced due to various losses encountered in one’s career, including patient deaths, moral distress, and ethical dilemmas [ 15 ]. While society expects nurses to provide end-of-life care, the emotional burden they bear in this process is frequently neglected, leading to unrecognized psychological strain that may impact mental health and career commitment [ 16 ]. According to the theory of emotional labor [ 23 ], managing emotions in a professional setting demands significant psychological effort. Persistent exposure to professional grief can exacerbate emotional exhaustion, which, in turn, amplifies job stress and contributes to turnover intention. Several studies have found that professional grief negatively impacts nurses' careers [ 18 , 19 ]. From the perspective of role conflict theory, professional grief can also be conceptualized as a source of role conflict and overload[ 20 ]. Nurses are often required to maintain emotional composure and professional conduct, even when facing emotionally traumatic events such as patient death. This discrepancy between emotional experience and role expectation increases perceived role stress[ 21 ]. Therefore, nurses experiencing higher levels of professional grief may perceive more intense job stress, and consequently, the impact of job stress on their turnover intention may become stronger. In this way, professional grief may act as a moderator in the relationship between job stress and turnover intention. However, existing research remains predominantly qualitative, providing limited empirical evidence on the mechanisms through which professional grief interacts with job stress and turnover intention. Moreover, current approaches to managing professional grief are largely confined to individual coping strategies, lacking structured institutional interventions or support systems [ 22 ]. This gap highlights the pressing need for further research, particularly quantitative investigations, to elucidate the role of professional grief in shaping nurses' occupational outcomes and inform targeted interventions. Based on the above theoretical framework, the following hypotheses were proposed: H1: Job stress and its dimensions are positively associated with turnover intention among nurses. H2: Professional grief moderates the relationship between job stress and turnover intention, such that the positive relationship is stronger when professional grief is high. 2.1 Study design and participants This study employed a cross-sectional design and utilized convenience sampling at a tertiary general hospital in Shandong Province, China. The inclusion criteria were: age ≥ 18 years and possession of a nursing qualification certificate. Exclusion criteria included nurses on leave or continuing education, as well as those with any physical or mental conditions that could potentially interfere with their participation in the study. From March to October 2024, data were collected via an online questionnaire survey. The research team contacted the hospital’s nursing department and provided training to the data collectors—most of whom were head nurses from various departments. These trained data collectors then distributed the questionnaire link within their respective departmental nursing WeChat groups. During the training sessions, the research team emphasized ethical considerations and provided detailed instructions on how to complete and disseminate the questionnaire. To verify participant eligibility, the first section of the questionnaire presented the inclusion and exclusion criteria. Only participants who self-identified as meeting all inclusion criteria were able to proceed to the main part of the survey. Although no license numbers were collected to protect privacy, limiting distribution to the internal nursing communication channels helped ensure sample authenticity. Each questionnaire began with a section outlining the study's purpose, procedures involved, potential risks, and benefits. The report emphasized that all data would be anonymized, participants could withdraw from the study without punishment, and if nurses chose not to participate and no data would be collected. To ensure response accuracy, each IP address was restricted to a single response. After data collection, the research team downloaded the data for analysis. A total of 431 questionnaires were initially collected. After excluding 11 questionnaires that did not meet the inclusion criteria, 410 valid responses remained, yielding a response rate of 95.13%. 2.2 Demographic and Work-Related Information Based on previous studies, the sociodemographic and work-related variables selected for this research are associated with turnover intention and job stress. The sociodemographic variables include age, gender, marital status, education, and monthly income. Work-related covariates include working years and the number of night shifts per month. 2.3 Turnover Intention Scale Turnover Intention Scale in this study was based on the characteristics of nursing workforce attrition in China and Simon's turnover intention scale[ 24 , 25 ]. The tool consists of 7 items, which evaluate turnover intention from three perspectives: the hospital, the nursing profession, and the clinical department. It uses a 5-point Likert scale, with higher scores indicating stronger turnover tendencies. The Cronbach's alpha value for this scale in the present study was 0.966. 2.4 Nursing job stressor inventory The Nursing Job Stressor Inventory is widely used to measure job-related stress among nurses, and its application to the Chinese population has demonstrated satisfactory reliability and validity[ 26 ]. The inventory consists of 35 items, utilizing a 4-point Likert scale, and can be employed to assess overall job stress, as well as specific stress dimensions, including: nursing profession and work-related issues, time allocation and workload, working environment and equipment problems, and patient care challenges. Higher scores indicate greater levels of stress[ 27 ]. The overall Cronbach's alpha for the scale was 0.964, while the Cronbach's alpha for the five dimensions ranged from 0.890 to 0.934. 2.5 Grief State Scale for Nurses The Grief State Scale for Nurses is widely used to assess the level of professional grief among nursing staff[ 28 ]. The scale consists of 17 items, evaluating professional grief across four dimensions: emotional fluctuations, discomfort related to death, sadness following patient death, and emotional exhaustion after caregiving. All items are scored using a 5-point Likert scale, with higher scores indicating stronger professional grief. In the present study, the Cronbach's alpha value for this scale was 0.958. 2.6 Statistical analysis After confirming the normality of residuals, we employed Pearson correlation analysis to examine the relationships among job stress, professional grief, and turnover intention. Furthermore, we applied a multivariate linear regression model to assess the relationship between job stress and its five dimensions with turnover intention. Given that reliance on regression coefficients alone may overlook important factors[ 29 ], we incorporated the Extreme Gradient Boosting (XGBoost) algorithm[ 30 ]. This method enhances detection sensitivity, improves generalizability, and is well-suited for relatively small sample sizes[ 31 ]. For details, using the “XGBoost” package, the data were divided into a 70% training set and a 30% validation set. Variable importance was evaluated through gain calculations to strengthen the model's robustness and mitigate the risk of overfitting[ 32 ]. This method reflects the importance of the independent variable on the dependent variable through the gain value. The larger the gain value, the stronger the importance. All three models employed hierarchical regression analysis with robust standard errors. In Model 1, the impact of job stress and professional grief on turnover intention was examined. Model 2 was identical to Model 1 but included an interaction term between job stress and professional grief. Building upon Model 2, Model 3 introduced covariates. To further explore the interaction effects, simple slope analysis was conducted, and slope plots were generated using an open-source interaction tool based on ordinary least squares regression[ 33 ]. Statistical significance was set at a two-tailed test ( P = 0.05). Results A total of 410 participants were involved in this study (Table 1). Among all participants, 51.95% were aged between 30 and 40 years, and over 80% were female. A majority of the participants (296) were married, and the educational level of most participants (90.73%) was equivalent to that of a junior college. Additionally, 298 participants reported a monthly income exceeding 6,000 yuan. Approximately half of the participants (50.24%) had been employed for over 10 years. The job stressors total score of the participants was 74.22 ± 19.75. Scores for various dimensions of stress included: nursing profession and work-related issues (16.85 ± 5.11), time allocation and workload (13.00 ± 4.12), working environment and equipment issues (6.04 ± 2.44), and patient care-related challenges (22.78 ± 6.04). The score for professional grief was 60.60 ± 22.71, while the turnover intention score was 14.84 ± 7.42. 3.1 The relationship Among job Stress, professional grief, and turnover intention As shown in table 2, We found that job stress and all its dimensions were significantly positively correlated with turnover intention (r=0.376, r=0.354, r=0.353, r=0.255, r=0.344, r=0.276, all P<0.001), indicating that higher levels of job stress are associated with a stronger intention to leave. Similarly, professional grief also showed a significant positive correlation with turnover intention (r=0.689, P<0.001), suggesting that greater experiences of professional grief are linked to higher turnover intention. After controlling for covariates, we found that job stressors total score, along with its various dimensions—nursing profession and work-related issues, time allocation and workload, working environment and equipment issues, and patient care challenges—were all significantly associated with turnover intention. Specifically, The higher work-related stress, the higher the turnover intention (Table 3). Furthermore, employing the XGBoost machine learning method revealed varying degrees of association between various dimensions and turnover intention. As illustrated in Figure 1, the gain value indicates the relative importance of each factor in predicting turnover intention. The top three dimensions with the strongest associations were: patient care issues (gain = 0.164), nursing profession and work-related problems (gain = 0.162), and time allocation and workload (gain = 0.137). In practical terms, this suggests that patient care issues have the greatest influence on turnover intention, followed closely by work-related problems within the nursing profession and time management challenges. 3.2 The interaction between professional grief and job stress on turnover intention As shown in table 4, using the job stressors total score and its various dimensions as independent variables, professional grief as a moderator, and turnover intention as the dependent variable, we observed significant associations between job stressors (total score and its dimensions), professional grief, and turnover intention in Model 1 (all p -values < 0.001). In Model 2, we incorporated interaction terms. The results revealed that significant interaction effects were observed for the following dimensions: job stressors total score (β = 0.001, p = 0.004), nursing profession and work-related issues (β = 0.007, p = 0.001), time allocation and workload (β = 0.010, p < 0.001), working environment and equipment issues (β = 0.009, p = 0.037), and patient care issues (β = 0.003, p = 0.042). In Model 3, after controlling for covariates, the interaction effect for working environment and equipment issues was no longer statistically significant, while the remaining dimensions continued to show significant effects. To examine the interaction effects, we utilized small multiples and plotted simple slopes for increments of 1 standard deviation (SD), ranging from -2SD to +2SD. As showed in Figure 2, with increasing levels of professional grief, the impact of the job stressors total score on turnover intention shifted from non-significant to significant. Moreover, the regression coefficients increased correspondingly (–2SD: b = 0.00, 95% CI = [-0.05, 0.06]; –1SD: b = 0.04, 95% CI = [0.00, 0.07]; 0SD: b = 0.07, 95% CI = [0.04, 0.09]; +1SD: b = 0.10, 95% CI = [0.07, 0.13]; +2SD: b = 0.13, 95% CI = [0.08, 0.18]), indicating that professional grief moderates the relationship between job stressors total score and turnover intention. These patterns were consistent across the dimensions of nursing profession and work-related problems, time allocation and workload, and patient care issues(Figure 3, Figure 4, Figure 5). In other words, for overall job stress and the dimensions of nursing profession and work-related problems, time allocation and workload, and patient care issues, higher levels of professional grief exacerbated the impact of these stressors on turnover intention. In other words, nurses experiencing greater professional grief were more likely to leave when facing high levels of stress in these domains. However, this moderating effect was not observed in the dimensions of management and interpersonal issues or working environment and equipment problems, indicating that professional grief has a less pronounced influence in these areas. Discussion This study explored the relationship between job stress and turnover intention among nurses using both traditional linear regression and the emerging XGBoost methodologies. The results indicated that among the various dimensions of job stress, patient care issues showed the strongest correlation with turnover intention, followed by nursing profession and work problems, time allocation and workload, management and interpersonal issues, and working environment and equipment problems. These findings support Hypothesis 1 (H1), which proposed that job stress and its dimensions are positively associated with turnover intention among nurses. Additionally, professional grief moderated the relationship between job stress (including job stress, patient care issues, nursing profession and work problems, and time allocation and workload) and turnover intention, which confirms Hypothesis 2 (H2). This study employs the XGBoost methodologies to explore the relationship between job stress and turnover intention. Due to its powerful explanatory capacity and flexibility, the application of XGBoost in the medical field has been increasingly common in recent years[ 34 ]. In this study, the results from XGBoost were consistent with the linear regression analysis, further enhancing the credibility. The relationship between job stress and turnover intention aligns with the negative correlation observed in previous studies[ 35 ]. Notably, we found that patient care issues showed the strongest association with turnover intention, followed by nursing profession and work problems, time allocation and workload, management and interpersonal issues, and working environment and equipment problems. This may be due to the fact that the core of nursing work is centered around patients[ 36 ], and issues related to patient care are often directly linked to nurses[ 37 ]. When nurses face problems such as poor patient care quality or excessive patient demands in clinical practice, the resulting emotional and psychological burden may lead to increase these turnover intention[ 38 ]. At the same time, nurses often derive professional satisfaction from helping patients get back to health. When nurses find that their ability to provide high-quality care is hindered by structural barriers—such as inadequate resources or excessive workload—they may experience a profound disconnect between their professional ideals and workplace realities. This misalignment can lead to frustration, diminished emotional engagement, and reduced job satisfaction, ultimately contributing to high turnover intention[ 39 ]. This emotional sense of frustration and disappointment may be a key factor contributing to high turnover intention. Moreover, nurses suffer from limited promotion opportunities and unclear career paths throughout their careers[ 40 ]. When nurses perceive a lack of upward mobility or potential for professional growth, they may experience career burnout, further exacerbating turnover intention[ 41 ]. Many nurses enter the profession with idealism and passion, but if they lack career development opportunities, their enthusiasm for their work is waning, leading to reduced interest in nursing and, eventually, turnover intention[ 42 ]. In the sample of this study, more than half of the nurses had over 10 years of work experience, which makes this issue particularly salient. This may also explain why nursing profession and work problems exhibited a strong association with turnover intention, second only to patient care issues. The moderating effect of professional grief further clarifies how emotional labor interacts with occupational stressors to influence nurses’ career decisions. This may be because professional grief exacerbates the emotional burden on nurses[ 43 ]. When nurses are consistently exposed to emotionally taxing environments, particularly facing nursing profession and work problems, they may begin to doubt their careers and feel unable to achieve professional success or effectively alleviate patient suffering[ 44 ]. This loss of professional identity exacerbates nurses' alienation from their work, thereby increasing turnover intention[ 45 ]. Regarding time allocation and workload, these factors inherently impose significant stress on nurses[ 46 ]. If professional grief leads to substantial depletion of emotional resources, nurses may feel powerless in the face of heavy workloads, especially when lacking adequate time and resources[ 47 , 48 ]. They may perceive a disproportionate relationship between work effort and rewards, or even feel unable to continue bearing the emotional strain, finally leading to an increase in turnover intention[ 49 ]. Patient care issues are among the most emotionally taxing aspects of nursing work[ 50 ], involving challenges related to patient health, emotional support, and care quality. Professional grief makes nurses more emotionally exhausted when confronted with these issues, particularly when they are unable to effectively improve patient conditions or meet patient needs[ 51 ]. The frustration associated with such situations intensifies emotional strain, negatively affecting professional identity and fostering turnover intention. From the perspective of role conflict theory, professional grief can be interpreted as a role-based emotional overload, which amplifies the tension between job demands and nurses’ perceived role capacity. When this tension exceeds a critical threshold, it leads to emotional exhaustion and reduced job commitment. Thus, professional grief not only reflects a personal emotional state, but also functions as a contextual amplifier of job stress—especially in emotionally salient dimensions like patient care. Moreover, professional grief can influence nurses' coping strategy, making them more prone to adopting avoidant and passive coping mechanisms[ 52 ]. These avoidant strategies reduce nurses' ability to deal with job stress, leading to an accumulation of pressure at work [ 53 ]. However, as for issues related to management and interpersonal relationships or work environment and equipment, these problems are more systemic and structural, making them difficult to resolve solely through emotional regulation [ 54 ]. Moreover, compared to challenges in patient care, management and equipment issues are often beyond the individual nurse’s control. As a result, professional grief has a weaker impact on these aspects, as nurses may perceive them as external challenges rather than personal emotional burdens. In contrast, emotionally intense situations related to patient care create a stronger sense of personal responsibility, making professional grief more influential in these contexts [ 55 ]. Given the significant role of professional grief in shaping nurses' turnover intention, targeted interventions are essential. Hospital administrators should implement structured emotional support programs, such as peer support groups[ 56 ] and develop an evidence-based compassion professional grief program[ 57 ], to help nurses cope with professional grief more effectively. Additionally, providing clear career development pathways and recognition programs can reinforce nurses' professional identity and mitigate feelings of career dissatisfaction[ 58 ]. From a workforce retention perspective, organizations should focus on improving working conditions, ensuring adequate staffing, and optimizing resource allocation to alleviate unnecessary stressors[ 59 , 60 ]. Moreover, promoting a healthy work-life balance through flexible scheduling and mental health initiatives can help retain nurses and reduce burnout[ 61 ]. By addressing both emotional and structural factors, healthcare institutions can create a more supportive work environment, ultimately reducing turnover rates and improving overall care quality. The strength of this study is the focus on the nursing population, which possesses unique occupational characteristics and often faces problems such as patient death. This distinctive feature allows for an in-depth exploration of the moderating role of professional grief between job stress and turnover intention, providing precious insights that differ from studies conducted on the general population. To enhance the credibility, we employed both traditional linear regression and the advanced XGBoost algorithm to find the relationship between job stress and turnover intention. By confirming that patient care issues are the dimension most strongly associated with turnover intention, this study provides a solid basis for developing interventions aimed at reducing nurses' turnover intention. Limitations This study has several limitations. First, the assessment of variables relied on self-reported measurements, which may be subject to recall bias. Second, the use of a cross-sectional design to assess job stress and turnover intention does not allow for the determination of whether job stress precedes turnover intention, thereby limiting causal inference. Future research should consider longitudinal approaches to better establish causal relationships and examine how professional grief influences the dynamic interplay between job stress and turnover intention over time. Third, cultural variations in professional grief among nurses were not explicitly examined in this study. In the Chinese cultural context, professional grief may be influenced by collectivist values, which encourage emotional restraint and discourage open expressions of distress. Additionally, Confucian ethics emphasize a strong sense of duty, leading nurses to internalize emotional burdens rather than seek support. The stigma surrounding mental health in China may further limit nurses' willingness to address professional grief, exacerbating stress and increasing turnover intention. Finally, while the study considered some sociodemographic variables and work-related factors, certain potential variables (such as psychological resilience, coping strategies, and social support) were not included in the analysis[ 62 – 64 ]. These factors may play an important role in moderating the relationship between job stress and turnover intention. Future studies could think over these potential variables to uncover their role in the complex interactions. Conclusion This study combined linear regression with emerging machine learning methods to explore the relationship between job stress and turnover intention among nurses. The findings suggest that professional grief amplifies turnover intention in relation to job stress associated with emotional labor, while its impact on stress related to management and material resources is relatively smaller. To reduce turnover intention, healthcare policymakers should implement targeted interventions, such as grief counseling programs, resilience training, and peer support groups. Strengthening mental health resources and stress management strategies can help create a healthier work environment, ultimately improving nurse retention and patient care quality. Abbreviations None Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University. All methods were performed in accordance with the relevant guidelines and regulations. All included subjects gave their informed consent forms to participate in the study. Consent for publication All subjects gave written consent for their accounts to be anonymously published. Availability of data and materials The datasets generated during the current study are not publicly available due to privacy concerns, but the code used for the analysis in this study is available upon reasonable request from the corresponding author. Competing Interests The authors declare none. Funding This work was supported by the authors themselves and did not receive any funding from external sources. 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A systematic review and meta-analysis of the effectiveness of social support on turnover intention in clinical nurses. Front Public Health. 2024;12:1393024. Tan Y, Zhao Q, Yang H, Song S, Xie X, Yu Z. Turnover intention and coping strategies among older nursing assistants in China: a qualitative study. Front Psychol. 2023;14:1269611. Troy AS, Willroth EC, Shallcross AJ, Giuliani NR, Gross JJ, Mauss IB. Psychological Resilience: An Affect-Regulation Framework. Annual Review of Psychology. 2023;74 Volume 74, 2023:547–76. Tables Table 1. Characteristics of Participants (N=410) Variables Mean±SD or N (%) Age (years) <30 142 (34.63%) 30-40 213 (51.95%) ≥40 55 (13.41%) Gender Female 70 (17.07%) Male 340 (82.93%) Marital status Married/ Cohabitation 296 (72.2%) Singlehood 114 (27.8%) Education Technical secondary school 21 (5.12%) Junior college 372 (90.73%) Bachelor degree or above 17 (4.15%) Monthly income(yuan) 6000 298 (72.68%) Working years 10 206 (50.24%) Number of night shifts per month 0 163 (39.76%) 1-4 194 (47.32%) 5-9 44 (10.73%) >10 9 (2.2%) Job stressors total score 74.22±19.75 Nursing profession and work problems 16.85±5.11 Time allocation and workload 13.00±4.12 Working environment and equipment problems 6.04±2.44 Patient care issues 22.78±6.04 Professional grief 60.60±22.71 Turnover intention 14.84±7.42 Table 2. The Relationship Among Job Stress, Professional grief, and Turnover Intention 1 2 3 4 5 6 7 8 1.Job stressors total score 1 0.886 ** 0.826 ** 0.697 ** 0.914 ** 0.761 ** 0.291 ** 0.376 ** 2.Nursing profession and work problems 0.886 ** 1 0.801 ** 0.603 ** 0.745 ** 0.567 ** 0.278 ** 0.354 ** 3.Time allocation and workload 0.826 ** 0.801 ** 1 0.593 ** 0.686 ** 0.450 ** 0.296 ** 0.353 ** 4.Working environment and equipment problems 0.697 ** 0.603 ** 0.593 ** 1 0.629 ** 0.340 ** 0.191 ** 0.255 ** 5.Patient care issues 0.914 ** 0.745 ** 0.686 ** 0.629 ** 1 0.656 ** 0.269 ** 0.334 ** 6.Management and interpersonal problems 0.761 ** 0.567 ** 0.450 ** 0.340 ** 0.656 ** 1 0.174 ** 0.276 ** 7.Professional grief 0.291 ** 0.278 ** 0.296 ** 0.191 ** 0.269 ** 0.174 ** 1 0.689 ** 8.Turnover intention 0.376 ** 0.354 ** 0.353 ** 0.255 ** 0.334 ** 0.276 ** 0.689 ** 1 * :P<0.05, ** :P<0.001 Table 3. Regression models depicting the effects of job stress on turnover intention β 95%CI p -value Job stressors total score 0.078 0.015-5.376 <0.001 Nursing profession and work problems 0.274 0.056-4.857 <0.001 Time allocation and workload 0.314 0.069- 4.531 <0.001 Working environment and equipment problems 0.386 0.116- 3.322 0.001 Patient care issues 0.210 0.047- 4.430 <0.001 Management and interpersonal problems 0.216 0.048- 4.512 <0.001 Covariates: education, monthly income, marital status, gender, working years, age, number of night shifts per month. Table4. The interaction between professional grief and job stress on turnover intention Model1 Model2 Model3 R 2 β p -value β p -value β p -value Job stressors total score 0.509 0.072 <0.001 -0.019 0.581 -0.013 0.712 professional grief 0.519 0.207 <0.001 0.097 0.016 0.098 0.016 Job stressors total score * professional grief 0.532 0.001 0.004 0.001 0.005 Nursing profession and work problems 0.504 0.255 <0.001 -0.181 0.182 -0.158 0.255 professional grief 0.518 0.209 <0.001 0.082 0.033 0.083 0.034 Nursing profession and work problems * professional grief 0.530 0.007 0.001 0.007 0.001 Time allocation and workload 0.500 0.295 <0.001 -0.292 0.091 -0.284 0.107 professional grief 0.516 0.209 <0.001 0.076 0.047 0.074 0.055 Time allocation and workload * professional grief 0.529 0.010 <0.001 0.010 <0.001 Working environment and equipment problems 0.491 0.390 <0.001 -0.191 0.522 -0.139 0.651 professional grief 0.496 0.217 <0.001 0.159 <0.001 0.167 <0.001 Working environment and equipment problems * professional grief 0.505 0.009 0.037 0.008 0.066 Patient care issues Patient care issues 0.499 0.198 <0.001 -0.019 0.866 -0.008 0.949 professional grief 0.504 0.211 <0.001 0.133 0.001 0.134 0.001 Patient care issues * professional grief 0.516 0.003 0.042 0.003 0.045 Management and interpersonal problems 0.500 0.209 <0.001 0.031 0.803 0.017 0.893 professional grief 0.503 0.216 <0.001 0.174 <0.001 0.170 <0.001 Management and interpersonal problems * professional grief 0.516 0.003 0.127 0.003 0.092 Model3 included covariates (education, monthly income, marital status, gender, working years, age, number of night shifts per month). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2025 Read the published version in BMC Psychology → Version 1 posted Editorial decision: Revision requested 22 May, 2025 Reviews received at journal 20 May, 2025 Reviews received at journal 15 May, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers invited by journal 16 Apr, 2025 Submission checks completed at journal 16 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5713235","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":443957949,"identity":"617edde5-236f-48e2-95a7-330b6dbad0e6","order_by":0,"name":"Xue Liang","email":"","orcid":"","institution":"Department of Anesthesiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xue","middleName":"","lastName":"Liang","suffix":""},{"id":443957950,"identity":"446da4ba-3d41-4417-af9b-c4cbfed36c5e","order_by":1,"name":"Jue Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYJCCA4wNDAlgxocfNjz8/A34lfNAtBiAtDAenNmTJiM54wBhLQxQLcyHedgO2xg0JODXYs/ee/Dg1x1/8vjZuxMO8PCc5zEA2vrhYw4eW3jOJRyWPWNQLNlzdsMBCYvbPObMDcySM7fh0SKRY3BYss0gccON3A0HDHhu81g2HGBj5iVaSwLbOR4DIElQy8GPMC0H2A4QoeXMGYPDjG3GYL8cbOxJ5pGccbAZr1/Y23uMP/5skwOGWO/mz39+2Nnz8zcf/PARjxYQYOZB5QMTAyHA+IOgklEwCkbBKBjRAAAmgFuxrDDT+gAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Opthmology,Shandong Second Provincial General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jue","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-12-26 02:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5713235/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5713235/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40359-025-03000-8","type":"published","date":"2025-07-01T15:57:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80998100,"identity":"bb904321-7d34-4fd1-89d0-154a03346673","added_by":"auto","created_at":"2025-04-21 05:40:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21403,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe ranking of the association strength between different dimensions of job stress and turnover intention.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX-axis indicates the contribution (gain) of each variable to turnover intention, Y-axis indicates the variables.\u003c/p\u003e\n\u003cp\u003eAbbreviations: JStime: time allocation and workload, JSmajor: nursing profession and work problems, JSenvir: working environment and equipment problems, JSpatient: patient care issues,JSmanage: management and interpersonal problems.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/d2a540d51aa83c23495ab5b3.png"},{"id":80998110,"identity":"16bc796b-ac5a-4a1a-9364-64093ecf8580","added_by":"auto","created_at":"2025-04-21 05:40:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":170587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and job stressors total score\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and job stressors total score.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/81050bb0345c87919a97ee0f.png"},{"id":80999717,"identity":"9c04d3b7-8e74-4bdb-8a91-43c7bdd88cb9","added_by":"auto","created_at":"2025-04-21 06:05:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":179861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and nursing profession and work problems on turnover intention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and nursing profession and work problems.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/bf84045a5d24c6074e4ad51c.png"},{"id":80998112,"identity":"4f6c8b69-13a4-4e81-b7bf-1539c814fcd9","added_by":"auto","created_at":"2025-04-21 05:40:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":165144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and time allocation and workload on turnover intention.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and time allocation and workload.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/60990493554ad02c6b657b39.png"},{"id":80998127,"identity":"0b106e89-13b6-44fc-a929-44fce6be65d7","added_by":"auto","created_at":"2025-04-21 05:40:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":165640,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and patient care issues on turnover intention.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and patient care issues.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/f366a15dda0ff1edc35a7689.png"},{"id":80999739,"identity":"226cf9f6-9dcd-4ca5-a24f-e5ceee1befe4","added_by":"auto","created_at":"2025-04-21 06:05:28","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":170587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and job stressors total score\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and job stressors total score.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/09045e6012c71b53e892c2ee.png"},{"id":80998128,"identity":"389479a4-a4e5-4e31-a7ef-3cc941137a7c","added_by":"auto","created_at":"2025-04-21 05:40:38","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":179861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and nursing profession and work problems on turnover intention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and nursing profession and work problems.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/10d0c1e08a2cd88e7da62c5b.png"},{"id":80998115,"identity":"c747f3e8-9c0a-4c39-ab89-20163e52a63a","added_by":"auto","created_at":"2025-04-21 05:40:37","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":165144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe simple slope plot: the interaction between professional grief and time allocation and workload on turnover intention.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD:standard deviation, PTCL:percentiles, CI:confidence intervals. Each point represents a different data point. The left side represents lower levels of professional grief (-2 SD), while the right side represents higher levels of professional grief (+2 SD). The blue (bold) slopes indicate a significant interaction between professional grief and time allocation and workload.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/16aa7018214cd23bb9de904a.png"},{"id":86178989,"identity":"5d25c099-3279-4338-a215-501786027319","added_by":"auto","created_at":"2025-07-07 16:14:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2478063,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5713235/v1/496c0c75-0bfa-49aa-a76a-c1a5c1f989a4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of Professional Grief in Moderating Job Stress and Turnover Intention Among Nurses","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNurses are the largest workforce in the health-care system and play a important role in achieving the goals of universal health coverage and sustainable development [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. With rapid socio-economic development and changes in demographic structures, nurse shortages have become a widespread issue globally [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to \u0026ldquo;The State of the world\u0026rsquo;s nursing 2020 report\u0026rdquo; jointly published by the World Health Organization (WHO) and the International Council of Nurses (ICN), without intervention, the global nursing workforce shortage is projected to reach 5.7\u0026nbsp;million by 2030 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. High turnover rates are a key factor in the shortage of nurses [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and can affect quality and safety of care, leading to decreased patient satisfaction, increased errors in care, and higher mortality risks [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, the departure of colleagues can influence the turnover intention of remaining nurses, thereby exacerbating workforce instability and creating a vicious cycle [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For organizations, nurse turnover and the associated costs of recruitment increase operational expenses, and if nurses leave the profession, it also results in the loss of educational investments [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, reducing nurse turnover is considered an effective strategy to address nursing shortages, enhance healthcare service quality, and improve patient safety, while also helping to reduce healthcare institution costs [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Consequently, the timely and accurate identification of high turnover intention, followed by appropriate interventions, has become a key concern for healthcare managers [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe occupational characteristics of nursing involve numerous stressors, such as heavy workloads, complex tasks, and the need for continued attention [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These factors render nursing a profession marked by high responsibility, elevated risk, and intense pressure, resulting in significantly higher levels of job stress compared to other professional groups [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Existing research generally agrees that job stress is a key factor influencing nurses' turnover intention. The greater the job stress, the stronger the turnover intention [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, given that hospital administrative systems are often constrained by regulations and reimbursement policies, identifying the specific aspects of job stress that are most closely related to turnover intention can provide economically viable solutions to alleviate the problem. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond physical and cognitive demands, nursing also involves significant emotional labor, requiring professionals to regulate their emotions while providing compassionate care [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In this context, professional grief emerges as a crucial yet often overlooked factor influencing nurses\u0026rsquo; well-being. Professional grief refers to the emotional distress experienced due to various losses encountered in one\u0026rsquo;s career, including patient deaths, moral distress, and ethical dilemmas [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. While society expects nurses to provide end-of-life care, the emotional burden they bear in this process is frequently neglected, leading to unrecognized psychological strain that may impact mental health and career commitment [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. According to the theory of emotional labor [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], managing emotions in a professional setting demands significant psychological effort. Persistent exposure to professional grief can exacerbate emotional exhaustion, which, in turn, amplifies job stress and contributes to turnover intention. Several studies have found that professional grief negatively impacts nurses' careers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. From the perspective of role conflict theory, professional grief can also be conceptualized as a source of role conflict and overload[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Nurses are often required to maintain emotional composure and professional conduct, even when facing emotionally traumatic events such as patient death. This discrepancy between emotional experience and role expectation increases perceived role stress[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Therefore, nurses experiencing higher levels of professional grief may perceive more intense job stress, and consequently, the impact of job stress on their turnover intention may become stronger. In this way, professional grief may act as a moderator in the relationship between job stress and turnover intention. However, existing research remains predominantly qualitative, providing limited empirical evidence on the mechanisms through which professional grief interacts with job stress and turnover intention. Moreover, current approaches to managing professional grief are largely confined to individual coping strategies, lacking structured institutional interventions or support systems [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This gap highlights the pressing need for further research, particularly quantitative investigations, to elucidate the role of professional grief in shaping nurses' occupational outcomes and inform targeted interventions.\u003c/p\u003e \u003cp\u003eBased on the above theoretical framework, the following hypotheses were proposed:\u003c/p\u003e \u003cp\u003eH1: Job stress and its dimensions are positively associated with turnover intention among nurses.\u003c/p\u003e \u003cp\u003eH2: Professional grief moderates the relationship between job stress and turnover intention, such that the positive relationship is stronger when professional grief is high.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and participants\u003c/h2\u003e \u003cp\u003eThis study employed a cross-sectional design and utilized convenience sampling at a tertiary general hospital in Shandong Province, China. The inclusion criteria were: age\u0026thinsp;\u0026ge;\u0026thinsp;18 years and possession of a nursing qualification certificate. Exclusion criteria included nurses on leave or continuing education, as well as those with any physical or mental conditions that could potentially interfere with their participation in the study. From March to October 2024, data were collected via an online questionnaire survey. The research team contacted the hospital\u0026rsquo;s nursing department and provided training to the data collectors\u0026mdash;most of whom were head nurses from various departments. These trained data collectors then distributed the questionnaire link within their respective departmental nursing WeChat groups. During the training sessions, the research team emphasized ethical considerations and provided detailed instructions on how to complete and disseminate the questionnaire. To verify participant eligibility, the first section of the questionnaire presented the inclusion and exclusion criteria. Only participants who self-identified as meeting all inclusion criteria were able to proceed to the main part of the survey. Although no license numbers were collected to protect privacy, limiting distribution to the internal nursing communication channels helped ensure sample authenticity. Each questionnaire began with a section outlining the study's purpose, procedures involved, potential risks, and benefits. The report emphasized that all data would be anonymized, participants could withdraw from the study without punishment, and if nurses chose not to participate and no data would be collected. To ensure response accuracy, each IP address was restricted to a single response. After data collection, the research team downloaded the data for analysis. A total of 431 questionnaires were initially collected. After excluding 11 questionnaires that did not meet the inclusion criteria, 410 valid responses remained, yielding a response rate of 95.13%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Demographic and Work-Related Information\u003c/h2\u003e \u003cp\u003eBased on previous studies, the sociodemographic and work-related variables selected for this research are associated with turnover intention and job stress. The sociodemographic variables include age, gender, marital status, education, and monthly income. Work-related covariates include working years and the number of night shifts per month.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Turnover Intention Scale\u003c/h2\u003e \u003cp\u003eTurnover Intention Scale in this study was based on the characteristics of nursing workforce attrition in China and Simon's turnover intention scale[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The tool consists of 7 items, which evaluate turnover intention from three perspectives: the hospital, the nursing profession, and the clinical department. It uses a 5-point Likert scale, with higher scores indicating stronger turnover tendencies. The Cronbach's alpha value for this scale in the present study was 0.966.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Nursing job stressor inventory\u003c/h2\u003e \u003cp\u003eThe Nursing Job Stressor Inventory is widely used to measure job-related stress among nurses, and its application to the Chinese population has demonstrated satisfactory reliability and validity[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The inventory consists of 35 items, utilizing a 4-point Likert scale, and can be employed to assess overall job stress, as well as specific stress dimensions, including: nursing profession and work-related issues, time allocation and workload, working environment and equipment problems, and patient care challenges. Higher scores indicate greater levels of stress[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The overall Cronbach's alpha for the scale was 0.964, while the Cronbach's alpha for the five dimensions ranged from 0.890 to 0.934.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Grief State Scale for Nurses\u003c/h2\u003e \u003cp\u003eThe Grief State Scale for Nurses is widely used to assess the level of professional grief among nursing staff[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The scale consists of 17 items, evaluating professional grief across four dimensions: emotional fluctuations, discomfort related to death, sadness following patient death, and emotional exhaustion after caregiving. All items are scored using a 5-point Likert scale, with higher scores indicating stronger professional grief. In the present study, the Cronbach's alpha value for this scale was 0.958.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003eAfter confirming the normality of residuals, we employed Pearson correlation analysis to examine the relationships among job stress, professional grief, and turnover intention. Furthermore, we applied a multivariate linear regression model to assess the relationship between job stress and its five dimensions with turnover intention. Given that reliance on regression coefficients alone may overlook important factors[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], we incorporated the Extreme Gradient Boosting (XGBoost) algorithm[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This method enhances detection sensitivity, improves generalizability, and is well-suited for relatively small sample sizes[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. For details, using the \u0026ldquo;XGBoost\u0026rdquo; package, the data were divided into a 70% training set and a 30% validation set. Variable importance was evaluated through gain calculations to strengthen the model's robustness and mitigate the risk of overfitting[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This method reflects the importance of the independent variable on the dependent variable through the gain value. The larger the gain value, the stronger the importance.\u003c/p\u003e \u003cp\u003eAll three models employed hierarchical regression analysis with robust standard errors. In Model 1, the impact of job stress and professional grief on turnover intention was examined. Model 2 was identical to Model 1 but included an interaction term between job stress and professional grief. Building upon Model 2, Model 3 introduced covariates. To further explore the interaction effects, simple slope analysis was conducted, and slope plots were generated using an open-source interaction tool based on ordinary least squares regression[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Statistical significance was set at a two-tailed test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 410 participants were involved in this study (Table 1). Among all participants, 51.95% were aged between 30 and 40 years, and over 80% were female. A majority of the participants (296) were married, and the educational level of most participants (90.73%) was equivalent to that of a junior college. Additionally, 298 participants reported a monthly income exceeding 6,000 yuan. Approximately half of the participants (50.24%) had been employed for over 10 years. The job stressors total score of the participants was 74.22 \u0026plusmn; 19.75. Scores for various dimensions of stress included: nursing profession and work-related issues (16.85 \u0026plusmn; 5.11), time allocation and workload (13.00 \u0026plusmn; 4.12), working environment and equipment issues (6.04 \u0026plusmn; 2.44), and patient care-related challenges (22.78 \u0026plusmn; 6.04). The score for professional grief was 60.60 \u0026plusmn; 22.71, while the turnover intention score was 14.84 \u0026plusmn; 7.42.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 The relationship Among job Stress, professional grief, and turnover intention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in table 2, We found that job stress and all its dimensions were significantly positively correlated with turnover intention (r=0.376, r=0.354, r=0.353, r=0.255, r=0.344, r=0.276, all P\u0026lt;0.001), indicating that higher levels of job stress are associated with a stronger intention to leave. Similarly, professional grief also showed a significant positive correlation with turnover intention (r=0.689, P\u0026lt;0.001), suggesting that greater experiences of professional grief are linked to higher turnover intention.\u003c/p\u003e\n\u003cp\u003eAfter controlling for covariates, we found that job stressors total score, along with its various dimensions\u0026mdash;nursing profession and work-related issues, time allocation and workload, working environment and equipment issues, and patient care challenges\u0026mdash;were all significantly associated with turnover intention. Specifically, The higher work-related stress, the higher the turnover intention (Table 3). Furthermore, employing the XGBoost machine learning method revealed varying degrees of association between various dimensions and turnover intention. As illustrated in Figure 1, the gain value indicates the relative importance of each factor in predicting turnover intention. The top three dimensions with the strongest associations were: patient care issues (gain = 0.164), nursing profession and work-related problems (gain = 0.162), and time allocation and workload (gain = 0.137). In practical terms, this suggests that patient care issues have the greatest influence on turnover intention, followed closely by work-related problems within the nursing profession and time management challenges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe interaction between professional grief and job stress on turnover intention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in table 4, using the job stressors total score and its various dimensions as independent variables, professional grief as a moderator, and turnover intention as the dependent variable, we observed significant associations between job stressors (total score and its dimensions), professional grief, and turnover intention in Model 1 (all \u003cem\u003ep\u003c/em\u003e-values \u0026lt; 0.001). In Model 2, we incorporated interaction terms. The results revealed that significant interaction effects were observed for the following dimensions: job stressors total score (\u0026beta; = 0.001, \u003cem\u003ep\u003c/em\u003e = 0.004), nursing profession and work-related issues (\u0026beta; = 0.007, \u003cem\u003ep\u003c/em\u003e = 0.001), time allocation and workload (\u0026beta; = 0.010, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), working environment and equipment issues (\u0026beta; = 0.009, \u003cem\u003ep\u003c/em\u003e = 0.037), and patient care issues (\u0026beta; = 0.003, \u003cem\u003ep\u003c/em\u003e = 0.042). In Model 3, after controlling for covariates, the interaction effect for working environment and equipment issues was no longer statistically significant, while the remaining dimensions continued to show significant effects.\u003c/p\u003e\n\u003cp\u003eTo examine the interaction effects, we utilized small multiples and plotted simple slopes for increments of 1 standard deviation (SD), ranging from -2SD to +2SD. As showed in Figure 2, with increasing levels of professional grief, the impact of the job stressors total score on turnover intention shifted from non-significant to significant. Moreover, the regression coefficients increased correspondingly (\u0026ndash;2SD: b = 0.00, 95% CI = [-0.05, 0.06]; \u0026ndash;1SD: b = 0.04, 95% CI = [0.00, 0.07]; 0SD: b = 0.07, 95% CI = [0.04, 0.09]; +1SD: b = 0.10, 95% CI = [0.07, 0.13]; +2SD: b = 0.13, 95% CI = [0.08, 0.18]), indicating that professional grief moderates the relationship between job stressors total score and turnover intention. These patterns were consistent across the dimensions of nursing profession and work-related problems, time allocation and workload, and patient care issues(Figure 3, Figure 4, Figure 5). In other words, for overall job stress and the dimensions of nursing profession and work-related problems, time allocation and workload, and patient care issues, higher levels of professional grief exacerbated the impact of these stressors on turnover intention. In other words, nurses experiencing greater professional grief were more likely to leave when facing high levels of stress in these domains. However, this moderating effect was not observed in the dimensions of management and interpersonal issues or working environment and equipment problems, indicating that professional grief has a less pronounced influence in these areas.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study explored the relationship between job stress and turnover intention among nurses using both traditional linear regression and the emerging XGBoost methodologies. The results indicated that among the various dimensions of job stress, patient care issues showed the strongest correlation with turnover intention, followed by nursing profession and work problems, time allocation and workload, management and interpersonal issues, and working environment and equipment problems. These findings support Hypothesis 1 (H1), which proposed that job stress and its dimensions are positively associated with turnover intention among nurses. Additionally, professional grief moderated the relationship between job stress (including job stress, patient care issues, nursing profession and work problems, and time allocation and workload) and turnover intention, which confirms Hypothesis 2 (H2).\u003c/p\u003e \u003cp\u003eThis study employs the XGBoost methodologies to explore the relationship between job stress and turnover intention. Due to its powerful explanatory capacity and flexibility, the application of XGBoost in the medical field has been increasingly common in recent years[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In this study, the results from XGBoost were consistent with the linear regression analysis, further enhancing the credibility. The relationship between job stress and turnover intention aligns with the negative correlation observed in previous studies[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Notably, we found that patient care issues showed the strongest association with turnover intention, followed by nursing profession and work problems, time allocation and workload, management and interpersonal issues, and working environment and equipment problems. This may be due to the fact that the core of nursing work is centered around patients[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and issues related to patient care are often directly linked to nurses[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. When nurses face problems such as poor patient care quality or excessive patient demands in clinical practice, the resulting emotional and psychological burden may lead to increase these turnover intention[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. At the same time, nurses often derive professional satisfaction from helping patients get back to health. When nurses find that their ability to provide high-quality care is hindered by structural barriers\u0026mdash;such as inadequate resources or excessive workload\u0026mdash;they may experience a profound disconnect between their professional ideals and workplace realities. This misalignment can lead to frustration, diminished emotional engagement, and reduced job satisfaction, ultimately contributing to high turnover intention[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This emotional sense of frustration and disappointment may be a key factor contributing to high turnover intention. Moreover, nurses suffer from limited promotion opportunities and unclear career paths throughout their careers[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. When nurses perceive a lack of upward mobility or potential for professional growth, they may experience career burnout, further exacerbating turnover intention[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Many nurses enter the profession with idealism and passion, but if they lack career development opportunities, their enthusiasm for their work is waning, leading to reduced interest in nursing and, eventually, turnover intention[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In the sample of this study, more than half of the nurses had over 10 years of work experience, which makes this issue particularly salient. This may also explain why nursing profession and work problems exhibited a strong association with turnover intention, second only to patient care issues.\u003c/p\u003e \u003cp\u003eThe moderating effect of professional grief further clarifies how emotional labor interacts with occupational stressors to influence nurses\u0026rsquo; career decisions. This may be because professional grief exacerbates the emotional burden on nurses[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. When nurses are consistently exposed to emotionally taxing environments, particularly facing nursing profession and work problems, they may begin to doubt their careers and feel unable to achieve professional success or effectively alleviate patient suffering[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This loss of professional identity exacerbates nurses' alienation from their work, thereby increasing turnover intention[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Regarding time allocation and workload, these factors inherently impose significant stress on nurses[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. If professional grief leads to substantial depletion of emotional resources, nurses may feel powerless in the face of heavy workloads, especially when lacking adequate time and resources[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. They may perceive a disproportionate relationship between work effort and rewards, or even feel unable to continue bearing the emotional strain, finally leading to an increase in turnover intention[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Patient care issues are among the most emotionally taxing aspects of nursing work[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], involving challenges related to patient health, emotional support, and care quality. Professional grief makes nurses more emotionally exhausted when confronted with these issues, particularly when they are unable to effectively improve patient conditions or meet patient needs[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The frustration associated with such situations intensifies emotional strain, negatively affecting professional identity and fostering turnover intention. From the perspective of role conflict theory, professional grief can be interpreted as a role-based emotional overload, which amplifies the tension between job demands and nurses\u0026rsquo; perceived role capacity. When this tension exceeds a critical threshold, it leads to emotional exhaustion and reduced job commitment. Thus, professional grief not only reflects a personal emotional state, but also functions as a contextual amplifier of job stress\u0026mdash;especially in emotionally salient dimensions like patient care. Moreover, professional grief can influence nurses' coping strategy, making them more prone to adopting avoidant and passive coping mechanisms[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. These avoidant strategies reduce nurses' ability to deal with job stress, leading to an accumulation of pressure at work [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. However, as for issues related to management and interpersonal relationships or work environment and equipment, these problems are more systemic and structural, making them difficult to resolve solely through emotional regulation [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Moreover, compared to challenges in patient care, management and equipment issues are often beyond the individual nurse\u0026rsquo;s control. As a result, professional grief has a weaker impact on these aspects, as nurses may perceive them as external challenges rather than personal emotional burdens. In contrast, emotionally intense situations related to patient care create a stronger sense of personal responsibility, making professional grief more influential in these contexts [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the significant role of professional grief in shaping nurses' turnover intention, targeted interventions are essential. Hospital administrators should implement structured emotional support programs, such as peer support groups[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and develop an evidence-based compassion professional grief program[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], to help nurses cope with professional grief more effectively. Additionally, providing clear career development pathways and recognition programs can reinforce nurses' professional identity and mitigate feelings of career dissatisfaction[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. From a workforce retention perspective, organizations should focus on improving working conditions, ensuring adequate staffing, and optimizing resource allocation to alleviate unnecessary stressors[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Moreover, promoting a healthy work-life balance through flexible scheduling and mental health initiatives can help retain nurses and reduce burnout[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. By addressing both emotional and structural factors, healthcare institutions can create a more supportive work environment, ultimately reducing turnover rates and improving overall care quality.\u003c/p\u003e \u003cp\u003eThe strength of this study is the focus on the nursing population, which possesses unique occupational characteristics and often faces problems such as patient death. This distinctive feature allows for an in-depth exploration of the moderating role of professional grief between job stress and turnover intention, providing precious insights that differ from studies conducted on the general population. To enhance the credibility, we employed both traditional linear regression and the advanced XGBoost algorithm to find the relationship between job stress and turnover intention. By confirming that patient care issues are the dimension most strongly associated with turnover intention, this study provides a solid basis for developing interventions aimed at reducing nurses' turnover intention.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThis study has several limitations. First, the assessment of variables relied on self-reported measurements, which may be subject to recall bias. Second, the use of a cross-sectional design to assess job stress and turnover intention does not allow for the determination of whether job stress precedes turnover intention, thereby limiting causal inference. Future research should consider longitudinal approaches to better establish causal relationships and examine how professional grief influences the dynamic interplay between job stress and turnover intention over time. Third, cultural variations in professional grief among nurses were not explicitly examined in this study. In the Chinese cultural context, professional grief may be influenced by collectivist values, which encourage emotional restraint and discourage open expressions of distress. Additionally, Confucian ethics emphasize a strong sense of duty, leading nurses to internalize emotional burdens rather than seek support. The stigma surrounding mental health in China may further limit nurses' willingness to address professional grief, exacerbating stress and increasing turnover intention. Finally, while the study considered some sociodemographic variables and work-related factors, certain potential variables (such as psychological resilience, coping strategies, and social support) were not included in the analysis[\u003cspan additionalcitationids=\"CR63\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. These factors may play an important role in moderating the relationship between job stress and turnover intention. Future studies could think over these potential variables to uncover their role in the complex interactions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study combined linear regression with emerging machine learning methods to explore the relationship between job stress and turnover intention among nurses. The findings suggest that professional grief amplifies turnover intention in relation to job stress associated with emotional labor, while its impact on stress related to management and material resources is relatively smaller. To reduce turnover intention, healthcare policymakers should implement targeted interventions, such as grief counseling programs, resilience training, and peer support groups. Strengthening mental health resources and stress management strategies can help create a healthier work environment, ultimately improving nurse retention and patient care quality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNone\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University. All methods were performed in accordance with the relevant guidelines and regulations. All included subjects gave their informed consent forms to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll subjects gave written consent for their accounts to be anonymously published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are not publicly available due to privacy concerns, but the code used for the analysis in this study is available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare none.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the authors themselves and did not receive any funding from external sources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXue Liang: writing - original draft, methodology, formal analysis; Jue Wang: conceptualization, writing - review \u0026amp; editing. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank all the nurses for their participation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThe Lancet. 2020: unleashing the full potential of nursing. The Lancet. 2019;394:1879.\u003c/li\u003e\n\u003cli\u003eTamata AT, Mohammadnezhad M. A systematic review study on the factors affecting shortage of nursing workforce in the hospitals. Nurs Open. 2022;10:1247\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003eState of the world\u0026rsquo;s nursing 2020: investing in education, jobs and leadership. https://www.who.int/publications/i/item/9789240003279. Accessed 22 Dec 2024.\u003c/li\u003e\n\u003cli\u003eAmmari N, Gantare A. Ethical climate and turnover intention among nurses: A scoping review. 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Organizational Health Literacy: Opportunities for Patient-Centered Care in the Wake of COVID-19. Quality Management in Healthcare. 2021;30:49.\u003c/li\u003e\n\u003cli\u003eJun J, Ojemeni MM, Kalamani R, Tong J, Crecelius ML. Relationship between nurse burnout, patient and organizational outcomes: Systematic review. International Journal of Nursing Studies. 2021;119:103933.\u003c/li\u003e\n\u003cli\u003eKim H, Kim EG. A meta‐analysis on predictors of turnover intention of hospital nurses in South Korea (2000\u0026ndash;2020). Nurs Open. 2021;8:2406\u0026ndash;18.\u003c/li\u003e\n\u003cli\u003eWood E, King R, Robertson S, Senek M, Tod A, Ryan T. Sources of satisfaction, dissatisfaction and well-being for UK advanced practice nurses: A qualitative study. Journal of Nursing Management. 2021;29:1073\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eJones S, Bradbury A, Shortland S, Hewett F, Storey K. Clinical academic careers for general practice nurses: a qualitative exploration of associated barriers and enablers. J Res Nurs. 2021;26:704\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eAl-Qathmi A, Zedan H. The Effect of Incentive Management System on Turnover Rate, Job Satisfaction and Motivation of Medical Laboratory Technologists. Health Serv Res Manag Epidemiol. 2021;8:2333392820988404.\u003c/li\u003e\n\u003cli\u003eHe R, Liu J, Zhang W-H, Zhu B, Zhang N, Mao Y. Turnover intention among primary health workers in China: a systematic review and meta-analysis. BMJ Open. 2020;10:e037117.\u003c/li\u003e\n\u003cli\u003eFahey DM, Rumaker K, Ordille J. Grieving while you work, working while you grieve: Three strategies to reconnect the mind, body, and spirit after loss. 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Cureus. 15:e38834.\u003c/li\u003e\n\u003cli\u003eHan X, Pittman P, Barnow B. Alternative approaches to ensuring adequate nurse staffing. Med Care. 2021;59 10 Suppl 5:S463\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eGriffiths P, Saville C, Ball J, Jones J, Pattison N, Monks T. Nursing workload, nurse staffing methodologies and tools: a systematic scoping review and discussion. Int J Nurs Stud. 2020;103:103487.\u003c/li\u003e\n\u003cli\u003eRazai MS, Kooner P, Majeed A. Strategies and interventions to improve healthcare professionals\u0026rsquo; well-being and reduce burnout. J Prim Care Community Health. 2023;14:21501319231178641.\u003c/li\u003e\n\u003cli\u003eChen Y, Zhou X, Bai X, Liu B, Chen F, Chang L, et al. A systematic review and meta-analysis of the effectiveness of social support on turnover intention in clinical nurses. Front Public Health. 2024;12:1393024.\u003c/li\u003e\n\u003cli\u003eTan Y, Zhao Q, Yang H, Song S, Xie X, Yu Z. Turnover intention and coping strategies among older nursing assistants in China: a qualitative study. Front Psychol. 2023;14:1269611.\u003c/li\u003e\n\u003cli\u003eTroy AS, Willroth EC, Shallcross AJ, Giuliani NR, Gross JJ, Mauss IB. Psychological Resilience: An Affect-Regulation Framework. Annual Review of Psychology. 2023;74 Volume 74, 2023:547\u0026ndash;76.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Characteristics of Participants (N=410)\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"473\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMean\u0026plusmn;SD or N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003e\u0026lt;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e142 (34.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e30-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e213 (51.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026ge;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e55 (13.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e70 (17.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e340 (82.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003eMarried/ Cohabitation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e296 (72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eSinglehood\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e114 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003eTechnical secondary school\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e21 (5.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eJunior college\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e372 (90.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eBachelor degree or above\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e17 (4.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eMonthly income(yuan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003e\u0026lt;4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e31 (7.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;4000~6000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e81 (19.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026gt;6000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e298 (72.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eWorking years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003e\u0026lt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e102 (24.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e5-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e102 (24.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026gt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e206 (50.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eNumber of night shifts per month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\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: 321px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e163 (39.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e194 (47.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e5-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e44 (10.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026gt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e9 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eJob stressors total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e74.22\u0026plusmn;19.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eNursing profession and work problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e16.85\u0026plusmn;5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eTime allocation and workload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e13.00\u0026plusmn;4.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eWorking environment and equipment problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e6.04\u0026plusmn;2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003ePatient care issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e22.78\u0026plusmn;6.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eProfessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e60.60\u0026plusmn;22.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eTurnover intention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e14.84\u0026plusmn;7.42\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\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 2.\u0026nbsp;The Relationship Among Job Stress, Professional grief, and Turnover Intention\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"747\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e1.Job stressors total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.886\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.826\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.697\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.914\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.761\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.291\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.376\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e2.Nursing profession and work problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.886\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.801\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.603\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.745\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.567\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.278\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.354\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e3.Time allocation and workload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.826\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.801\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.593\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.686\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.450\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.296\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.353\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e4.Working environment and equipment problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.697\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.603\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.593\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.629\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.340\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.191\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.255\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e5.Patient care issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.914\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.745\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.686\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.629\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.656\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.269\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.334\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e6.Management and interpersonal problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.761\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.567\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.450\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.340\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.656\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.174\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.276\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e7.Professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.291\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.278\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.296\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.191\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.269\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.174\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.689\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 304px;\"\u003e\n \u003cp\u003e8.Turnover intention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.376\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.354\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.353\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.255\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.334\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.276\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.689\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1\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\u003csup\u003e*\u003c/sup\u003e:P\u0026lt;0.05,\u003csup\u003e\u0026nbsp;**\u003c/sup\u003e:P\u0026lt;0.001\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Regression models depicting the effects of job stress on turnover\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eintention\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 310px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 310px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob stressors total score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.015-5.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\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: 310px;\"\u003e\n \u003cp\u003eNursing profession and work problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.056-4.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\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: 310px;\"\u003e\n \u003cp\u003eTime allocation and workload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.069- 4.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\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: 310px;\"\u003e\n \u003cp\u003eWorking environment and equipment problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.116- 3.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 310px;\"\u003e\n \u003cp\u003ePatient care issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.047- 4.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\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: 310px;\"\u003e\n \u003cp\u003eManagement and interpersonal problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.048- 4.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\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\u003eCovariates: education, monthly income, marital status, gender, working years, age, number of night shifts per month.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable4. The interaction between professional grief and job stress on turnover intention\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"738\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eModel1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eModel2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eModel3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eJob stressors total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.072\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.019\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.581\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.013\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.712\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eprofessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.207\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.097\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.016\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.098\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.016\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eJob stressors total score * professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.004\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eNursing profession and work problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.255\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.181\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.182\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.158\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.255\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eprofessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.209\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.082\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.033\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.083\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.034\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eNursing profession and work problems * professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.007\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.007\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eTime allocation and workload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.295\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.292\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.091\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.284\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.107\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eprofessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.209\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.076\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.047\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.074\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.055\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eTime allocation and workload * professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.010\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\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: 325px;\"\u003e\n \u003cp\u003eWorking environment and equipment problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.390\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.191\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.522\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.139\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.651\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eprofessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.217\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.159\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.167\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\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: 325px;\"\u003e\n \u003cp\u003eWorking environment and equipment problems * professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.009\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.037\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.008\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.066\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003ePatient care issues Patient care issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.198\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.019\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.866\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.008\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.949\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eprofessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.211\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.133\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.134\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003ePatient care issues * professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.042\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.045\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eManagement and interpersonal problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.209\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.031\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.803\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.017\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.893\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 325px;\"\u003e\n \u003cp\u003eprofessional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.216\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.174\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.170\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\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: 325px;\"\u003e\n \u003cp\u003eManagement and interpersonal problems * professional grief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.127\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.092\u0026nbsp;\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\u003eModel3 included covariates (education, monthly income, marital status, gender, working years, age, number of night shifts per month).\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nursing, Turnover intention, Job stress, Professional grief","lastPublishedDoi":"10.21203/rs.3.rs-5713235/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5713235/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNurses, as the largest workforce in healthcare, play a crucial role in achieving universal health coverage. However, they continually face both physical and emotional burdens. Identifying key stressors that contribute to turnover intention and examining whether professional grief moderates the relationship between job stress and turnover intention is essential for reducing nurse attrition.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study utilized linear regression models and the Extreme Gradient Boosting machine (XGBoost) learning algorithm to analyze the impact of the total score of job stress and their dimensions on turnover intention. XGBoost, known for enhancing sensitivity in detection and improving generalization performance, is particularly beneficial for high-dimensional problems and data heterogeneity. It integrates multiple variables and accommodates small sample sizes, making it a valuable supplement to conventional regression techniques. Through hierarchical regression, the moderating role of professional grief between job stress and turnover intention was explored. Additionally, an interactive tool was used to visually present the results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the dimensions of job stress, patient care issues exhibited the strongest association with turnover intention, followed by nursing profession and work problems, time allocation and workload, management and interpersonal issues, and working environment and equipment problems. Notably, professional grief significantly moderated the relationship between job stress and turnover intention. Specifically, for overall job stress and the dimensions of nursing profession and work-related problems, time allocation and workload, and patient care issues, higher levels of professional grief intensified their impact on turnover intention. However, this moderating effect was not observed for stressors related to management and interpersonal issues or working environment and equipment problems.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn emotionally labor-intensive work environments, professional grief tends to amplify turnover intention, while its impact on issues related to management and material resources is less pronounced.Healthcare policymakers should focus on job stress and professional grief to reduce turnover intention, ultimately benefiting patient care and treatment outcomes.\u003c/p\u003e","manuscriptTitle":"The Role of Professional Grief in Moderating Job Stress and Turnover Intention Among Nurses","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 05:40:32","doi":"10.21203/rs.3.rs-5713235/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-22T11:46:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-20T13:52:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-15T15:33:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"85449924114684460214193222360803892993","date":"2025-04-16T16:05:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3516084567095963746980852284900660760","date":"2025-04-16T08:52:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138041286611969408388398977547671972059","date":"2025-04-16T07:45:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-16T07:41:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-16T06:40:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-04-15T11:54:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ceb55896-f1fc-4532-ba14-aa919b46c151","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-07T16:01:55+00:00","versionOfRecord":{"articleIdentity":"rs-5713235","link":"https://doi.org/10.1186/s40359-025-03000-8","journal":{"identity":"bmc-psychology","isVorOnly":false,"title":"BMC Psychology"},"publishedOn":"2025-07-01 15:57:24","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2025-04-21 05:40:32","video":"","vorDoi":"10.1186/s40359-025-03000-8","vorDoiUrl":"https://doi.org/10.1186/s40359-025-03000-8","workflowStages":[]},"version":"v1","identity":"rs-5713235","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5713235","identity":"rs-5713235","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}